- Last 7 days
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Reviewer #1 (Public review):
Summary:
In a heroic effort, Ozanna Burnicka-Turek et al. have made and investigated conduction system-specific Tbx3-Tbx5 deficient mice and investigated their cardiac phenotype. Perhaps according to expectations, given the body of literature on the function of the two T-box transcription factors in the heart/conduction system, the cardiomyocytes of the ventricular conduction system seemed to convert to "ordinary" ventricular working myocytes. As a consequence, loss of VCS-specific conduction system propagation was observed in the compound KO mice, associated with PR and QRS prolongation and elevated susceptibility to ventricular tachycardia.
Strengths:
Great genetic model. Phenotypic consequences at the organ and organismal levels are well investigated. The requirement of both Tbx3 and Tbx5 for maintaining VCS cell state has been demonstrated.
Weaknesses:
The actual cell state of the Tbx3/Tbx5 deficient conducting cells was not investigated in detail, and therefore, these cells could well only partially convert to working cardiomyocytes, and may, in reality, acquire a unique state.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This paper developed a model of chromosome mosaicism by using a new aneuploidy-inducing drug (AZ3146), and compared this to their previous work where they used reversine, to demonstrate the fate of aneuploid cells during murine preimplantation embryo development. They found that AZ3146 acts similarly to reversine in inducing aneuploidy in embryos, but interestingly showed that the developmental potential of embryos is higher in AZ3146-treated vs. reversine-treated embryos. This difference was associated with changes in HIF1A, p53 gene regulation, DNA damage, and fate of euploid and aneuploid cells when embryos were cultured in a hypoxic environment.
Strengths:
In the current study, the authors investigate the fate of aneuploid cells in the preimplantation murine embryo using a specific aneuploidy-inducing compound to generate embryos that were chimeras of euploid and aneuploid cells. The strength of the work is that they investigate the developmental potential and changes in gene expression profiles under normoxic and hypoxic culture conditions. Further, they also assessed how levels of DNA damage and DNA repair are altered in these culture conditions. They also assessed the allocation of aneuploid cells to the divergent cell lineages of the blastocyst stage embryo.
Weaknesses:
Inconsistent/missing description for sample size, biological/technical replicates, label orientation, the appropriate number of * for each figure panel, and statistical tests used.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Dopamine neurons contribute to motivated and motor behaviors in many ways, and ample recent evidence has suggested that distinct dopamine neuron subclasses support discrete behavioral and circuit functions. Prior studies have subdivided dopamine neurons by spatial localization, gene expression patterns, and physiological properties. However, many of these studies were bound by previous technical limitations that made comprehensive subclassification efforts difficult or impossible. The main goal of this manuscript was to characterize and further define dopamine neuron heterogeneity in the ventral midbrain. The study uses cutting-edge single nucleus RNA-seq (on the 10X Genomics platform) and spatial transcriptomics (on the MERFISH platform) to define dopamine neuron heterogeneity with unprecedented resolution. The result is a convincing and comprehensive subclassification of dopamine neurons into three main families, each with major branches and subtypes. In addition, the study reports comparisons between wild-type mice and mice that harbor a G2019S mutation in the Lrrk2 gene, which models a common cause of autosomally dominant Parkinson's Disease in humans. These results, while less robust due to the nature of the group comparisons, nevertheless identify vulnerability within specific dopamine neuron subpopulations. This vulnerability may contribute unique risk of dopamine neuron loss in the context of Parkinson's disease. Overall, the study is careful and rigorous and provides a critical resource for the rapidly evolving knowledge of dopamine neuron subtypes.
Strengths:
(1) The creation of a public-facing app where the snRNA-seq data can be investigated by anyone is a major strength.
(2) The manuscript includes careful comparisons to prior datasets that have sought to explore dopamine neuron heterogeneity. The result is a useful synthesis of new findings with previously published work, which is helpful for moving the field forward in this area.
(3) The integration of snRNA-seq with MERFISH results is particularly strong and enables insight not only into subclassification but also into how this relates to spatial localization. The careful neuroanatomy reveals important distinctions between Sox6, Calb1, and Gad2 positive dopamine neuron families, with some degree of spatial overlap.
Weaknesses:
(1) Important details about the nature of DEG comparisons between the wild type and the Lrrk2 G2019S model are missing.
(2) Some aspects of the integration between snRNA-seq and MERFISH data are not clear, and many MERFISH-identified cells do not appear to have a high-confidence cluster transfer into the snRNA-seq data space. Imputation is used to overcome some issues with the MERFISH dataset, but it is not clear that this is appropriate.
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Reviewer #1 (Public review):
Mutations in CDHR1, the human gene encoding an atypical cadherin-related protein expressed in photoreceptors, are thought to cause cone-rod dystrophy (CRD). However, the pathogenesis leading to this disease is unknown. Previous work has led to the hypothesis that CDHR1 is part of a cadherin-based junction that facilitates the development of new membranous discs at the base of the photoreceptor outer segments, without which photoreceptors malfunction and ultimately degenerate. CDHR1 is hypothesized to bind to a transmembrane partner to accomplish this function, but the putative partner protein has yet to be identified.
The manuscript by Patel et al. makes an important contribution toward improving our understanding of the cellular and molecular basis of CDHR1-associated CRD. Using gene editing, they generate a loss of function mutation in the zebrafish cdhr1a gene, an ortholog of human CDHR1, and show that this novel mutant model has a retinal dystrophy phenotype, specifically related to defective growth and organization of photoreceptor outer segments (OS) and calyceal processes (CP). This phenotype seems to be progressive with age. Importantly, Patel et al, present intriguing evidence that pcdh15b, also known for causing retinal dystrophy in previous Xenopus and zebrafish loss of function studies, is the putative cdhr1a partner protein mediating the function of the junctional complex that regulates photoreceptor OS growth and stability.
This research is significant in that it:
(1) provides evidence for a progressive, dystrophic photoreceptor phenotype in the cdhr1a mutant and, therefore, effectively models human CRD; and
(2) identifies pcdh15b as the putative, and long sought after, binding partner for cdhr1a, further supporting the theory of a cadherin-based junction complex that facilitates OS disc biogenesis.
Nonetheless, the study has several shortcomings in methodology, analysis, and conceptual insight, which limits its overall impact.
Below I outline several issues that the authors should address to strengthen their findings.
Major comments:
(1) Co-localization of cdhr1a and pcdh15b proteins
The model proposed by the authors is that the interaction of cdhr1a and pcdh15b occurs in trans as a heterodimer. In cochlear hair cells, PCDH15 and CDHR23 are proposed to interact first as dimers in cis and then as heteromeric complexes in trans. This was not shown here for cdhr1a and pcdh15b, but it is a plausible configuration, as are single heteromeric dimers or homodimers. Regardless, this model depends on the differential compartmental expression of the cdhr1a and pcdh15b proteins. Data in Figure 1 show convincing evidence that these two proteins can, at least in some cases, be distributed along the length of photoreceptor membranes that are juxtaposed, as would be the case for OS and CP. If pcdh15b is predominantly expressed in CPs, whereas cdhr1a is predominantly expressed in OS, then this should be confirmed with actin double labeling with cdhr1a and pcdh15b since the apicobasal oriented (vertical) CPs would express actin in this same orientation but not in the OS. This would help to clarify whether cdhr1a and pcdh15b can be trafficked to both OS and CP compartments or whether they are mutually exclusive.
Photoreceptor heterogeneity goes beyond the cone versus rod subtypes discussed here and it is known that in zebrafish, CP morphology is distinct in different cone subtypes as well as cone versus rod. It would be important to know which specific photoreceptor subtypes are shown in zebrafish (Figures 1A-C) and the non-fish species depicted in Figures 1E-L. Also, a larger field of view of the staining patterns for Figures 1E-L would be a helpful comparison (could be added as a supplementary figure).
(2) Cdhr1a function in cell culture
The authors should explain the multiple bands in the anti-FLAG blots. Also, it would be interesting to confirm that the cdhr1a D173 mutant prevents the IP interaction with pcdh15b as well as the additive effects in aggregate assays of Figure 2.
Is it possible that the cultured cells undergo proliferation in the aggregation assays shown in Figure 2? Cells might differentially proliferate as clusters form in rotating cultures. A simple assay for cell proliferation under the different transfection conditions showing no differences would address this issue and lend further support to the proposed specific changes to cell adhesion as a readout of this assay.
Also, the authors report that the number of clusters was normalized to the field of view, but this was not defined. Were the n values different fields of view from one transfection experiment, or were they different fields of view from separate transfection experiments? More details and clarification are needed.
(3) Methodological issues in quantification and statistical analyses
Were all the OS and CP lengths counted in the observation region or just a sample within the region? If the latter, what were the sampling criteria? For CPs, it seems that the length was an average estimate based on all CPs observed surrounding one cone or one-rod cell. Is this correct? Again, if sampled, how was this implemented? In Fig 4M', the cdhr1a-/- ROS mostly looks curvilinear. Did the measurements account for this, or were they straight linear dimension measurements from base to tip of the OS as depicted in Fig 5A-E? A clearer explanation of the OS and CP length quantification methodology is required.
How were cone and rod photoreceptor cell counts performed? The legend in Figure 4 states that they again counted cells in the observation region, but no details were provided. For example, were cones and rods counted as an absolute number of cells in the observation region (e.g., number of cones per defined area) or relative to total (DAPI+) cell nuclei in the region? Changes in cell density in the mutant (smaller eye or thinner ONL) might affect this quantification so it would be important to know how cell quantification was normalized.
In Figure 6I, K, measuring the length of the signal seems problematic. The dimension of staining is not always in the apicobasal (vertical) orientation. It might be more accurate to measure the cdhr1a expression domain relative to the OS (since the length of the OS is already reduced in the mutants). Another possible approach could be to measure the intensity of cdhr1 staining relative to the intensity within a Prph2 expression domain in each group. The authors should provide complementary evidence to support their conclusion.
A better description of the statistical methodology is required. For example, the authors state that "each of the data points has an n of 5+ individuals." This is confusing and could indicate that in Figure 4F alone there were ~5000 individuals assayed (~100 data points per treatment group x n=5 individuals per data point x 10 treatment groups). I don't think that is what the authors intended. It would be clearer if the authors stated how many OS, CP, or cells were counted in their observation region averaged per individual, and then provided the n value of individuals used per treatment group (controls and mutants), on which the statistical analyses should be based.
There are hundreds of data points in the separate treatment groups shown in several of the graphs. It would not be correct to perform the ANOVA on the separate OS or CP length measurements alone as this will bias the estimates since they are not all independent samples. For example, in Figure 6H, 5dpf pcdh15b+/- have shorter CPs compared to WT but pcdh15b-/- have longer compared to WT. This could be an artifact of the analysis. Moreover, the authors should clarify in the Methods section which ANOVA post hoc tests were used to control for multiple pairwise comparisons.
(4) Cdhr1a function in photoreceptors
The cdhr1a IHC staining in 5dpf WT larvae in Figure 3E appears different from the cdhr1a IHC staining in 5dpf WT larvae in Figure 1A or Figure 6I. Perhaps this is just the choice of image. Can the authors comment or provide a more representative image?
The authors show that pcdh15b localization after 5dpf mirrored the disorganization of the CP observed with actin staining. They also show in Figure 5O that at 180dpf, very little pcdh15b signal remains. They suggest based on this data that total degradation of CPs has occurred in the cdhr1a-/- photoreceptors by this time. However, although reduced in length, COS and cone CPs are still present at 180dpf (Figure 5E, E'). Thus, contrary to the authors' general conclusion, it is possible that the localization, trafficking, and/or turnover of pcdh15b is maintained through a cdhr1a-dependent mechanism, irrespective of the degree to which CPs are maintained. The experiments presented here do not clearly distinguish between a requirement for maintenance of localization versus a secondary loss of localization due to defective CPs.
(5) Conceptual insights
The authors claim that cdhr1a and pcdh15b double mutants have synergistic OS and CP phenotypes. I think this interpretation should be revisited.
First, assuming the model of cdhr1a-pcdh15b interaction in trans is correct, the authors have not adequately explained the logic of why disrupting one side of this interaction in a single mutant would not give the same severity of phenotype as disrupting both sides of this interaction in a double mutant.
Second, and perhaps more critically, at 10dpf the OS and CP lengths in cdhr1a-/- mutants (Figure 7J, T) are significantly increased compared to WT. In contrast, there are no significant differences in these measurements in the pcdh15b-/- mutants. Yet in double homozygous mutants, there is a significant reduction of ~50% in these measurements compared to WT. A synergistic phenotype would imply that each mutant causes a change in the same direction and that the magnitude of this change is beyond additive in the double mutants (but still in the same direction). Instead, I would argue that the data presented in Figure 7 suggest that there might be a functionally antagonistic interaction between cdhr1a and pcdh15b with respect to OS and CP growth at 10dpf.
If these proteins physically interacted in vivo, it would appear that the interaction is complex and that this interaction underlies both OS growth-promoting and growth-restraining (stabilizing) mechanisms working in concert. Perhaps separate homodimers or heterodimers subserve distinct CP-OS functional interactions. This might explain the age-dependent differences in mutant CP and OS length phenotypes if these mechanisms are temporally dynamic or exhibit distinct OS growth versus maintenance phases. Regardless of my speculations, the model presented by the authors appears to be too simplistic to explain the data.
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Reviewer #1 (Public review):
Gray and colleagues describe the identification of Integrator complex subunit 12 (INTS12) as a contributor to HIV latency in two different cell lines and in cells isolated from the blood of people living with HIV. The authors employed a high-throughput CRISPR screening strategy to knock down genes and assess their relevance in maintaining HIV latency. They had used a similar approach in two previous studies, finding genes required for latency reactivation or genes preventing it and whose knockdown could enhance the latency-reactivating effect of the NFκB activator AZD5582. This work builds on the latter approach by testing the ability of gene knockdowns to complement the latency-reactivating effects of AZD5582 in combination with the BET inhibitor I-BET151. This drug combination was selected because it has been previously shown to display synergistic effects on latency reactivation.
The finding that INTS12 may play a role in HIV latency is novel, and the effect of its knockdown in inducing HIV transcription in primary cells, albeit in only a subset of donors, is intriguing. However, there are some data and clarifications that would be important to include to complement the information provided in the current version of the manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors were attempting to identify the molecular and cellular basis for why modulators of the HR pathway, specifically PARPi, are not effective in CDK12 deleted or mutant prostate cancers and they seek to identify new therapeutic agents to treat this subset of metastatic prostate cancer patients. Overall, this is an outstanding manuscript with a number of strengths and in my opinion represents a significant advance in the field of prostate cancer biology and experimental therapeutics.
Strengths:
The patient data cohort size and clinical annotation from Figure 1 are compelling and comprehensive in scope. The associations between tandem duplications and amplifications of oncogenes that have been well-credentialed to be drivers of cancer development and progression are fascinating and the authors identify that in those that have AR amplification for example, there is evidence for AR pathway activation. The association between CDK12 inactivation and various specific gene/pathway perturbations is fascinating and is consistent with previously published studies - it would be interesting to correlate these changes with cell line-based studies in which CDK12 is specifically deleted or inhibited with small molecules to see how many pathways/gene perturbations are shared between the clinical samples and cell and mouse models with CDK12 perturbation. The short-term inhibitor studies related to changes in HRD genes and protein expression with CDK12/13 inhibition are fascinating and suggest differential pathway effects between short inhibition of CDK12/13 and long-term loss of CDK12. The in vivo studies with the inhibitor of CDK12/13 are intriguing but not definitive
Weaknesses:
Given that there are different mutations identified at different CDK12 sites as illustrated in Figure 1B it would be nice to know which ones have been functionally classified as pathogenic and for which ones that the pathogenicity has not been determined. This would be especially interesting to perform in light of the differences in the LOH scores and WES data presented - specifically, are the pathogenic mutations vs the mutations for which true pathogenicity is unknown more likely to display LOH or TD? For the cell inhibition studies with the CDK12/13 inhibitor, more details characterizing the specificity of this molecule to these targets would be useful. Additionally, could the authors perform short-term depletion studies with a PROTAC to the target or short shRNA or non-selected pool CRISPR deletion studies of CDK12 in these same cell lines to complement their pharmacological studies with genetic depletion studies? Also perhaps performing these same inhibitor studies in CDK12/13 deleted cells to test the specificity of the molecule would be useful. Additionally, expanding these studies to additional prostate cancer cell lines or organdies models would strengthen the conclusions being made. More information should be provided about the dose and schedule chosen and the rationale for choosing those doses and schedules for the in vivo studies proposed should be presented and discussed. Was there evidence for maximal evidence of inhibition of the target CDK12/13 at the dose tested given the very modest tumor growth inhibition noted in these studies?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:<br /> In this study by Fang et al., the authors show how STAMBPL1 promotes TNBC angiogenesis via a feed-forward GRHL3/HIF1a/VEGFA axis. They demonstrate that STAMBPL1 interacts with FOXO1, define the required domains in each protein, and illustrate that this interaction facilitates FOXO1 transcriptional factor activity, which then activating GRHL3/HIF1a/VEGFA signaling. Lastly, they show that the combination of VEGFR and FOXO1 inhibitors can synergistically suppress STAMBPL1-overexpressing TNBC.
Strengths:
The manuscript is clearly written, and the results are well explained. The observation that STAMBPL1 mediates GRHL3 transcription through its interaction with FOXO1 is novel. The findings also have important translational potential.
Weaknesses:<br /> The mechanism by which STAMBPL1 mediates GRHL3 transcription through its interaction with FOXO1 is not sufficiently discussed, especially in relation to how STAMBPL1 regulates FOXO1. Some reported effects are modest.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
This is a well-done clinical study which provides new information on the effects of metabolic disturbances in the human skeleton. 63 postmenopausal women undergoing hip arthroplasty, consisting of T2D with obesity; obesity alone; and neither T2D nor obesity were studied. Most of the findings relate to T2D. Increased serum TNF-α was found in T2D, as well as increased bone gene expression of TNF- α, which was associated with reduced expression of Wnt pathway genes. mRNA levels of certain of the cytokines correlated with Wnt signaling components. In addition, the increased serum TNF- α in T2D was associated with reduced Young's modulus, a measure of bone strength. A strength of this paper is that it provides information in an area that is not well-understood. However, there are a number of concerns that warrant direct addressing.
(1) Can the authors speculate why the changes in cytokines and Wnt expression do not impact bone microarchitecture?
(2) The authors state that they are showing an association between inflammation and bone strength via the regulation of Wnt signaling. However they have only shown here that serum cytokines correlate with bone strength. It is true that the authors have previously shown that Wnt signaling correlated with bone strength. But here it would be useful to show if bone strength is also correlated with inflammatory genes.
(3) AGEs increase inflammation (by binding to RAGE which triggers an inflammatory cascade). AGEs might also increase SOST. From their previous work, it seems that the authors have bone AGE measures on these patients and they have shown their relationship with SOST. Do the increased AGEs relate to inflammation as measured by serum and bone expression?
(4) Were bone turnover markers done to show how the inflammation and Wnt findings relate to bone resorption and formation?
(5) RNA integrity values should be reported to confirm that the RNA has not degraded.
(6) The discussion of adiponectin could be clearer (studies are cited that show both positive and negative effects). Please clarify that adiponectin effects on bone are complex and what they are.
(7) Were patients excluded for prior as well as current antiresorptive medication use?
(8) Fig 4A. correlation between SOST mRNA and TNF-a mRNA seems to be driven by 1 outlier. Does the relationship persist if it is removed?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
This article deals with the chemotactic behavior of E coli bacteria in thin channels (a situation close to 2D). It combines experiments and simulations.
The authors show experimentally that, in 2D, bacteria swim up a chemotactic gradient much more effectively when they are in the presence of lateral walls. Systematic experiments identify an optimum for chemotaxis for a channel width of ~8µm, close to the average radius of the circle trajectories of the unconfined bacteria in 2D. It is known that these circles are chiral and impose that the bacteria swim preferentially along the right-side wall when there is no chemotactic gradient. In the presence of a chemotactic gradient, this larger proportion of bacteria swimming on the right wall yields chemotaxis. This effect is backed by numerical simulations and a geometrical analysis.
If the conclusions drawn from the experiments presented in this article seem clear and interesting, I find that the key elements of the mechanism of this wall-directed chemotaxis are not sufficiently emphasized. Moreover, the paper would be clearer with more details on the hypotheses and the essential ingredients of the analyses.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors present a modelling study to test the hypothesis that horizontal gene transfer (HGT) can modulate the outcome of interspecies competition in microbiomes, and in particular promote bistability in systems across scales. The premise is a model developed by the same authors in a previous paper where bistability happens because of a balance between growth rates and competition for a mutual resource pool (common carrying capacity). They show that introducing a transferrable element that gives a "growth rate bonus" expands the region of parameter space where bistability happens. The authors then investigate how often (in terms of parameter space) this bistability occurs across different scales of complexity, and finally under selection for the mobile element (framed as ABR selection).
Strengths:
The authors tackle an important, yet complex, question: how do different evolutionary processes impact the ecology of microbial ecosystems? They do a nice job at increasing the scales of heterogeneity and asking how these impact their main observable: bistability.
Weaknesses:
The author's starting point is their interaction LV model and the manuscript then explores how this model behaves under different scenarios. Because the structure of the model and the underlying assumptions essentially dictate these outcomes, I would expect to see much more focus on how these two aspects relate to the specific scenarios that are discussed. For example:
A key assumption is that the mobile element conveys a multiplicative growth rate benefit (1+lambda). However, the competition between the species is modelled as a factor gamma that modulates the competition for overall resource and thus appears in the saturation term (1+ S1/Nm + gamma2*S2/Nm). This means that gamma changes the perceived abundance of the other species (if gamma > 1, then from the point of view of S1 it looks like there are more S2 than there really are). Most importantly, the relationship between these parameters dictates whether or not there will be bistability (as the authors state).
This decoupling between the transferred benefit and the competition can have different consequences. One of them is that - from the point of view of the mobile element - the mobile element competes at different strengths within the same population compared to between. To what degree introducing such a mobile element modifies the baseline bistability expectation thus strongly depends on how it modifies gamma and lambda.
Thus, this structural aspect needs to be much more carefully presented to help the reader follow how much of the results are just trivial given the model assumptions and which have more of an emergent flavour. From my point of view, this has an important impact on helping the reader understand how the model that the authors present can contribute to the understanding of the question "how microbes competing for a limited number of resources stably coexist". I do appreciate that this changes the focus of the manuscript from a presentation of simulation results to more of a discussion of mathematical modelling.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Weiler, Teichert, and Margrie systematically analyzed long-range cortical connectivity, using a retrograde viral tracing strategy to identify layer and region-specific cortical projections onto the primary visual, primary somatosensory, and primary motor cortices. Their analysis revealed several hundred thousand inputs into each region, with inputs originating from almost all cortical regions but dominated in number by connections within cortical sub-networks (e.g. anatomical modules). Generally, the relative areal distribution of contralateral inputs followed the distribution of corresponding ipsilateral inputs. The largest proportion of inputs originated from layer 6a cells, and this layer 6 dominance was more pronounced for contralateral than ipsilateral inputs, which suggests that these connections provide predominantly feedback inputs. The hierarchical organization of input regions was similar between ipsi- and contralateral regions, except for within-module connections, where ipsilateral connections were much more feed-forward than contralateral. These results contrast earlier studies which suggested that contralateral inputs only come from the same region (e.g. V1 to V1) and from L2/3 neurons. Thus, these results provide valuable data supporting a view of interhemispheric connectivity in which layer 6 neurons play an important role in providing modulatory feedback.
The conclusions of this paper are mostly well-supported by the data and analysis, but additional consideration of possible experimental biases is needed.
Further discussion or analysis is needed about possible biases in uptake efficiency for different cell types. Is it possible that the nuclear retro-AAV has a tropism for layer 6 axons? Quantitative comparisons with results obtained with alternative methods such as rabies virus (Yao et al., 2023) or anterograde tracing (Harris et al., 2019) may be helpful for this.
Quantitative analysis of the injection sites should be included to account for possible biases. For example, L6 neurons are known to be the main target of contralateral inputs into the visual cortex (Yao et al., 2023). Thus, if the injections are biased towards or against layer 6 neurons, this may change the layer distribution of retrogradely labeled input cells. Comparison across biological replicates may help reveal sensitivity to particular characteristics of the injections.
The possibility of labeling axons of passage within the white matter should be addressed. This could potentially lead to false positive connections, contributing to the broad connectivity from most cortical regions that were observed.
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www.uqac.ca www.uqac.caMoodle1
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Organisation générale de Moodle et aussi comment naviguer facilement à l’intérieur de celui-ci.
effacer cette phrase
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Reviewer #1 (Public review):
D'Oliviera et al. have demonstrated cleavage of human TRMT1 by the SARS-CoV-2 main protease in vitro. Following, they solved the structure of Mpro (Nsp5)-C145A bound to TRMT1 substrate peptide, revealing binding conformation distinct from most viral substrates. Overall, this work enhances our understanding of substrate specificity for a key drug target of CoV2. The paper is well-written and the data is clearly presented. It complements the companion article by demonstrating interaction between Mpro and TRMT1, as well as TRMT1 cleavage under isolated conditions in vitro. They show that cleaved TRMT1 has reduced tRNA binding affinity, linking a functional consequence to TRMT1 cleavage by MPro. Importantly, the revelation for flexible substrate binding of Nsp5 is fundamental for understanding Nsp5 as a drug target. Trmt1 cleavage assays by Mpro revealed similar kinetics for TRMT1 cleavage as compared to nsp8/9 viral polyprotein cleavage site. They purify TRMT1-Q350K, in which there is a mutation in the predicted cleavage consensus sequence, and confirm that it is resistant to cleavage by recombinant Mpro. I am unable to comment critically on the structural analyses as it is outside of my expertise. Overall, I think that these findings are important for confirming TRMT1 as a substrate of Mpro, defining substrate binding and cleavage parameters for an important drug target of SARS-CoV-2, and may be of interest to researchers studying RNA modifications.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public review):
A high fraction of cells in early embryos carry aneuploid karyotypes, yet even chromosomally mosaic human blastocysts can implant and lead to healthy newborns with diploid karyotypes. Previous studies in other models have shown that genotoxic and proteotoxic stresses arising from aneuploidy lead to the activation of the p53 pathway and autophagy, which helps eliminate cells with aberrant karyotypes. These observations have been here evaluated and confirmed in human blastocysts. The study also demonstrates that the second lineage and formation of primitive endoderm are particularly impaired by aneuploidy.
Comments on revisions:
The authors have addressed the critical issues sufficiently. In particular, they improved the data analysis and added additional data from embryonal samples.
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public review):
Summary:
In this manuscript, Yan and colleagues introduce a modification to the previously published PETRI-seq bacterial single cell protocol to include a ribosomal depletion step based on a DNA probe set that selectively hybridizes with ribosome-derived (rRNA) cDNA fragments. They show that their modification of the PETRI-seq protocol increases the fraction of informative non-rRNA reads from ~4-10% to 54-92%. The authors apply their protocol to investigating heterogeneity in a biofilm model of E. coli, and convincingly show how their technology can detect minority subpopulations within a complex community.
Strengths:
The method the authors propose is a straightforward and inexpensive modification of an established split-pool single cell RNA-seq protocol that greatly increases its utility, and should be of interest to a wide community working in the field of bacterial single cell RNA-seq.
Comments on revised version:
The reviewers have responded thoughtfully and comprehensively to all of my comments. I believe the details of the protocol are now much easier to understand, and the text and methods have been significantly clarified. I have no further comments.
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Reviewer #1 (Public review):
Summary:
This work investigated the role of CXXC-finger protein 1 (CXXC1) in regulatory T cells. CXXC1-bound genomic regions largely overlap with Foxp3-bound regions and regions with H3K4me3 histone modifications in Treg cells. CXXC1 and Foxp3 interact with each other, as shown by co-immunoprecipitation. Mice with Treg-specific CXXC1 knockout (KO) succumb to lymphoproliferative diseases between 3 to 4 weeks of age, similar to Foxp3 KO mice. Although the immune suppression function of CXXC1 KO Treg is comparable to WT Treg in an in vitro assay, these KO Tregs failed to suppress autoimmune diseases such as EAE and colitis in Treg transfer models in vivo. This is partly due to the diminished survival of the KO Tregs after transfer. CXXC1 KO Tregs do not have an altered DNA methylation pattern; instead, they display weakened H3K4me3 modifications within the broad H3K4me3 domains, which contain a set of Treg signature genes. These results suggest that CXXC1 and Foxp3 collaborate to regulate Treg homeostasis and function by promoting Treg signature gene expression through maintaining H3K4me3 modification.
Strengths:
Epigenetic regulation of Treg cells has been a constantly evolving area of research. The current study revealed CXXC1 as a previously unidentified epigenetic regulator of Tregs. The strong phenotype of the knockout mouse supports the critical role CXXC1 plays in Treg cells. Mechanistically, the link between CXXC1 and the maintenance of broad H3K4me3 domains is also a novel finding.
Weaknesses:
(1) It is not clear why the authors chose to compare H3K4me3 and H3K27me3 enriched genomic regions. There are other histone modifications associated with transcription activation or repression. Please provide justification.
(2) It is not clear what separates Clusters 1 and 3 in Figure 1C. It seems they share the same features.
(3) The claim, "These observations support the hypothesis that FOXP3 primarily functions as an activator by promoting H3K4me3 deposition in Treg cells." (line 344), seems to be a bit of an overstatement. Foxp3 certainly can promote transcription in ways other than promoting H3K3me3 deposition, and it also can repress gene transcription without affecting H3K27me3 deposition. Therefore, it is not justified to claim that promoting H3K4me3 deposition is Foxp3's primary function.
(4) For the in vitro suppression assay in Figure S4C, and the Treg transfer EAE and colitis experiments in Figure 4, the Tregs should be isolated from Cxxc1 fl/fl x Foxp3 cre/wt female heterozygous mice instead of Cxxc1 fl/fl x Foxp3 cre/cre (or cre/Y) mice. Tregs from the homozygous KO mice are already activated by the lymphoproliferative environment and could have vastly different gene expression patterns and homeostatic features compared to resting Tregs. Therefore, it's not a fair comparison between these activated KO Tregs and resting WT Tregs.
(5) The manuscript didn't provide a potential mechanism for how CXXC1 strengthens broad H3K4me3-modified genomic regions. The authors should perform Foxp3 ChIP-seq or Cut-n-Taq with WT and Cxxc1 cKO Tregs to determine whether CXXC1 deletion changes Foxp3's binding pattern in Treg cells.
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Reviewer #1 (Public review):
Summary:
The manuscript by Rowell et al aims to identify differences in TCR recombination and selection between foetal and adult thymus in mice. Authors sequenced the unpaired bulk TCR repertoire in foetal and adult mice thymi and studied both TCRB and TCRa characteristics in the double negative (DN, CD4-CD8-) and single positive (SP4 CD4+CD8- and SP8 CD4-CD8+) populations. They identified age-related differences in TCRa and TCRB segment usage, including a preferential bias toward 3'TRAV and 5' TRAJ rearrangements in foetal cells compared to adults who had a larger perveance for 5'TRAV segments. By depleting the thymocyte population in adult thymi using hydrocortisone, the authors demonstrated that the repertoire became more foetal like, they, therefore, argue that the preferential 5'TRAV rearrangements in adults may be resulting from prolonged/progressive TCRa rearrangements in the adult thymocytes. In line with previous studies, Authors demonstrate that the foetal TCR repertoire was less diverse, less evenly distributed and had fewer non-template insertions while containing more clonal expansions. In addition, the authors claim that changes in V-J usage and CDR1 and CDR2 in the DN vs SP repertoires indicated that positive selection of foetal thymocytes are less dependent on interactions with the MHC.
Strengths:
Overall, the manuscript provides an extensive analysis of the foetal and adult TCR repertoire in the thymus, resulting in new insights in T cell development in foetal and adult thymi.
Weaknesses:
Three major concerns arise:<br /> (1) the authors have analysed TCR repertoires of only 4 foetal and 4 adult mice, considering the high spread the study may have been underpowered.
- The sample size was increased in the revised version
(2) Gating strategies are missing and
- These have now been provided in the revised version
(3) The manuscript is very technical and clearly aimed for a highly specialised audience with expertise in both thymocyte development and TCR analysis. Considering eLife is a scientific journal with a broader readership, Authors are recommended to provide schematics of the TCR rearrangements/their findings and include a summary of conclusions/implications of their findings at the end of each results section rather than waiting till the discussion. This will help the reader to interpret their findings while reading the results.
- These have now been included in the revised version
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Reviewer #1 (Public Review):
The authors report compound heterozygous deleterious variants in the kinase domains of the non-receptor tyrosine kinases (NRTK) TNK2/ACK1 in familial SLE. They suggest that ACK1 and BRK deficiencies are associated with human SLE and impair efferocytosis.
The experiments in this revision showing that a weekly injection of ACK1 or BRK inhibitors induced various kinds of lupus-related autoantibodies in BALB/c supported the pivotal role of ACK1/BRK in systemic autoimmunity, although treated mice failed to demonstrate the full picture of lupus.
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Reviewer #1 (Public Review):
This article is interesting because the phenotype of the virus with mutations that alter the affinity of HS has been associated with how the viral particle interacts with HS and, thus, with binding and entry. However, the data in this manuscript is compelling and strongly suggests that the mutation that increases the affinity of HS alters capsid stability. To my knowledge, this is the first evidence that such mutation causes capsid destabilization. Furthermore, the idea that this mutation increases infectivity in cell lines by also using a pH-independent route and that, in vivo, this mutation attenuates the virus is very novel. Last year Wa-Chu's lab proposed that encephalopathic Alphaviruses produce capsids with different sizes and that this helps to attenuate highly pathogenic viruses (which might not be the case for non encepahlopatic Alphavirsues). However, they did not demonstrate whether these alterations attenuate the virus and if the altered morphology affects capsid stability. Therefore, this manuscript is fundamental as it contributes to understanding how the assembly/disassembly mechanism can be used to attenuate a virus. Furthermore, it is possible this mechanism could not be restricted to viruses that belong to the Picornaviridae family and opens a new door to understanding viral attenuation in other icosahedral viruses.
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Reviewer #1 (Public Review):
This manuscript was previously reviewed and this earlier evaluation resulted in two conflicting assessments. I fully endorse the favourable opinion of former Reviewer 1 and find most negative comments of former Reviewer 2 inappropriate.
This work is absolutely necessary. Even though the authors find it difficult to be fully assertive in the end, their ground work in trying to demonstrate the existence of bias in PPI data is undeniably valuable. Other authors have tried before to show the limitation of unequivocally assigning the degree distribution to a power law but these doubts have had a weak impact. This new study is a great opportunity to discuss further a concern for a simplistic view of PPI network topology. The recent contribution of Broido & Clauset was definitely one to bounce on. The approach of this new manuscript is compelling. Dividing the study in several parts, each reflecting an attempt to bring out commonly used shortcuts in PPI network analyses, makes sense.
Surprisingly, the authors do not refer to the endless controversy of labeling hubs as party or date, which is another manifestation of the interpretative bias of PPI data.
The only worthy point prompted by former Reviewer 2 is the effect of spoke expansion. In their response, the authors suggest that it would probably extend questioning and even if it is considered as future work, it could be mentioned in the main manuscript.
In the end, this submission is an invitation to constructively rethink the analysis of PPI networks and it feeds the discussion on modelling degree distributions that should not be considered as a solved issue.
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Reviewer #1 (Public review):
This is a very relevant study, with the potential of having high impact on future research on the evolution of chemical defense mechanisms in animals. The authors present a substantial number of new and surprising experimental results, i.e., the presence in low quantities of alkaloids in amphibians previously deemed to lack these toxins. These data are then combined with literature data to weave the importance of passive accumulation mechanisms into a 4-phases scenario of the evolution of chemical defense in alkaloid-containing poison frogs.
In general, the new data presented in the manuscript are of high quality and high scientific interest, the suggested scenario compelling, and the discussion thorough. Also, the revised version of the manuscript has been carefully prepared with a high quality of illustrations. UI did not detect typos in the text
Understanding that the majority of dendrobatid frogs, including species considered undefended, can contain low quantities of alkaloids in their skin provides an entirely new perspective to our understanding of how the amazing specializations of poison frogs evolved. Although only few non-dendrobatids were included in the alkaloid screening, some of these also included minor quantities of alkaloids, and the capacity of passive alkaloid accumulation may therefore characterize numerous other frog clades, or even amphibians in general.
The overall quality of the work is exceptional. The authors also have done a fantastic job restructuring the manuscript in response to my initial comments, and it is now very clear which new hypotheses are presented and which testable predictions for future studies derive from these hypotheses. This study will be highly influential in informing and guiding future research on toxicity, alkaloid sequestration and resistance, and evolution of aposematism.
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Reviewer #1 (Public review):
Summary:
Utilizing transgenic lineage tracing techniques and tissue clearing-based advanced imaging and three-dimensional slices reconstruction, the authors comprehensively mapped the distribution atlas of NFATc1+ and PDGFR-α+ cells in dental and periodontal mesenchyme and tracked their in vivo trajectories. This important work expands our understanding of both single and double positive NFATc1 and PDGFR-α cells in maintaining dental and periodontal mesenchyme homeostasis, and will provide impact on clinical application and investigation. The strength of this work is convincing, as it employed CRISPR/Cas9-mediated gene editing to generate two dual recombination systems, and mapped gNFATc1+ and PDGFR-α+ cells residing in dental and periodontal mesenchyme, their capacity for progeny cell generation, and their inclusive, exclusive and hierarchical relations in homeostasis, generating a spatiotemporal atlas of these skeletal stem cell population.
This work has theoretical or practical implications in the periodontal field. The methods, data and analyses support the claims.
Comments on revised version:
The authors have addressed my main concerns.
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Reviewer #1 (Public review):
In this work, Veseli et al. present a computational framework to infer the functional diversity of microbiomes in relation to microbial diversity directly from metagenomic data. The framework reconstructs metabolic modules form metagenomes and calculates the per-population copy number of each module, resulting in the proportion of microbes in the sample carrying certain genes. They applied this framework to a dataset of gut microbiomes from 109 inflammatory bowel disease (IBD) patients, 78 patients with other gastrointestinal conditions, and 229 healthy controls. The found that the microbiomes of IBD patients were enriched in a high fraction of metabolic pathways, including biosynthesis pathways such as those for amino acids, vitamins, nucleotides, and lipids. Hence, they had higher metabolic independence compared with healthy controls. To an extent, the authors also found a pathway enrichment suggesting higher metabolic independence in patients with gastrointestinal conditions other than IBD indicating this could be a signal for a general loss in host health. Finally, a machine learning classifier using high metabolic independence in microbiomes could predict IBD with good accuracy. Overall, this is an interesting and well-written article and presents a novel workflow that enables a comprehensive characterization of microbiome cohorts.
Comments on revisions:
I believe that after the second round of revisions, the Reviewers sufficiently addressed the comments and improved the manuscript. Open questions have been answered. I have no further comments.
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Joint Public Review:
The subject area will have general appeal to those interested in the study of Pavlovian conditioning. The paper is important, showcasing a rigorous experimental design, several different approaches to data analysis, careful consideration of prior literature, and a thorough introduction. The results indicate that the rate of Pavlovian learning is determined by the ratio of reward rate during cue to the overall reward rate, and that the asymptotic response rate is determined by the reward rate during cue. These findings provide context to many conflicting recent results on this topic and are supported by strong/convincing evidence.
It is additionally claimed that the parameter that governs the acquisition and asymptote of responding in rats is exactly the same as that which governs the acquisition and asymptote of responding in the Gibbon and Balsam (1981) study that used pigeons as experimental subjects; and that the rates of responding during the inter-trial interval and the cue are proportional to the corresponding reward rates with the same proportionality constant. In both of these respects, there are several points that stand in need of clarification - at present, the strength of the evidence in support of these claims is solid. More generally, there are some points that could clarify aspects of rate estimation theory and, thereby, increase the rating of the paper from important to fundamental. These points range from analytical to conceptual and are presented below.
ANALYTICAL
(1) A key claim made here is that the same relationship (including the same parameter) describes data from pigeons by Gibbon and Balsam (1981; Figure 1) and the rats in this study (Figure 3). The evidence for this claim, as presented here, is not as strong as it could be. This is because the measure used for identifying trials to criterion in Figure 1 appears to differ from any of the criteria used in Figure 3, and the exact measure used for identifying trials to criterion influences the interpretation of Figure 3***. To make the claim that the quantitative relationship is one and the same in the Gibbon-Balsam and present datasets, one would need to use the same measure of learning on both datasets and show that the resultant plots are statistically indistinguishable, rather than simply plotting the dots from both data sets and spotlighting their visual similarity. In terms of their visual characteristics, it is worth noting that the plots are in log-log axis and, as such, slight visual changes can mean a big difference in actual numbers. For instance, between Figure 3B and 3C, the highest information group moves up only "slightly" on the y-axis but the difference is a factor of 5 in the real numbers. Thus, in order to support the strong claim that the quantitative relationships obtained in the Gibbon-Balsam and present datasets are identical, a more rigorous approach is needed for the comparisons.
***The measure of acquisition in Figure 3A is based on a previously established metric, whereas the measure in Figure 3B employs the relatively novel nDKL measure that is argued to be a better and theoretically based metric. Surprisingly, when r and r2 values are converted to the same metric across analyses, it appears that this new metric (Figure 3B) does well but not as well as the approach in Figure 3A. This raises questions about why a theoretically derived measure might not be performing as well on this analysis, and whether the more effective measure is either more reliable or tapping into some aspect of the processes that underlie acquisition that is not accounted for by the nDKL metric.
(2) Another interesting claim here is that the rates of responding during ITI and the cue are proportional to the corresponding reward rates with the same proportionality constant. This too requires more quantification and conceptual explanation. For quantification, it would be more convincing to calculate the regression slope for the ITI data and the cue data separately and then show that the corresponding slopes are not statistically distinguishable from each other. Conceptually, it is not clear why the data used to test the ITI proportionality came from the last 5 conditioning sessions. What were the decision criteria used to decide on averaging the final 5 sessions as terminal responses for the analyses in Figure 5? Was this based on consistency with previous work, or based on the greatest number of sessions where stable data for all animals could be extracted?
If the model is that animals produce response rates during the ITI (a period with no possible rewards) based on the overall rate of rewards in the context, wouldn't it be better to test this before the cue learning has occurred? Before cue learning, the animals would presumably only have attributed rewards in the context to the context and thus, produce overall response rates in proportion to the contextual reward rate. After cue learning, the animals could technically know that the rate of rewards during ITI is zero. Why wouldn't it be better to test the plotted relationship for ITI before cue learning has occurred? Further, based on Figure 1, it seems that the overall ITI response rate reduces considerably with cue learning. What is the expected ITI response rate prior to learning based on the authors' conceptual model? Why does this rate differ from pre and post-cue learning? Finally, if the authors' conceptual framework predicts that ITI response rate after cue learning should be proportional to contextual reward rate, why should the cue response rate be proportional to the cue reward rate instead of the cue reward rate plus the contextual reward rate?
(3) There is a disconnect between the gradual nature of learning shown in Figures 7 and 8 and the information-theoretic model proposed by the authors. To the extent that we understand the model, the animals should simply learn the association once the evidence crosses a threshold (nDKL > threshold) and then produce behavior in proportion to the expected reward rate. If so, why should there be a gradual component of learning as shown in these figures? In terms of the proportional response rule to the rate of rewards, why is it changing as animals go from 10% to 90% of peak response? The manuscript would be greatly strengthened if these results were explained within the authors' conceptual framework. If these results are not anticipated by the authors' conceptual framework, this should be explicitly stated in the manuscript.
(4) Page 27, Procedure, final sentence: The magazine responding during the ITI is defined as the 20 s period immediately before CS onset. The range of ITI values (Table 1) always starts as low as 15 s in all 14 groups. Even in the case of an ITI on a trial that was exactly 20 s, this would also mean that the start of this period overlaps with the termination of the CS from the previous trial and delivery (and presumably consumption) of a pellet. It should be indicated whether the definition of the ITI period was modified on trials where the preceding ITI was < 20 s, and if any other criteria were used to define the ITI. Were the rats exposed to the reinforcers/pellets in their home cage prior to acquisition?
(5) For all the analyses, the exact models that were fit and the software used should be provided. For example, it is not necessarily clear to the reader (particularly in the absence of degrees of freedom) that the model discussed in Figure 3 fits on the individual subject data points or the group medians. Similarly, in Figure 6 there is no indication of whether a single regression model was fit to all the plotted data or whether tests of different slopes for each of the conditions were compared. With regards to the statistics in Figure 6, depending on how this was run, it is also a potential problem that the analyses do not correct for the potentially highly correlated multiple measurements from the same subjects, i.e. each rat provides 4 data points which are very unlikely to be independent observations.
CONCEPTUAL
(1) We take the point that where traditional theories (e.g., Rescorla-Wagner) and rate estimation theory (RET) both explain some phenomenon, the explanation in terms of RET may be preferred as it will be grounded in aspects of an animal's experience rather than a hypothetical construct. However, like traditional theories, RET does not explain a range of phenomena - notably, those that require some sort of expectancy/representation as part of their explanation. This being said, traditional theories have been incorporated within models that have the representational power to explain a broader array of phenomena, which makes me wonder: Can rate estimation be incorporated in models that have representational power; and, if so, what might this look like? Alternatively, do the authors intend to claim that expectancy and/or representation - which follow from probabilistic theories in the RW mould - are unnecessary for explanations of animal behaviour?***
***If the authors choose to reply to these points, they should consider taking advantage of an "Ideas and Speculation" subsection within the Discussion that is supported by eLife [ https://elifesciences.org/inside-elife/e3e52a93/elife-latest-including-ideas-and-speculation-in-elife-papers ].
(2) The discussion of Rescorla's (1967) and Kamin's (1968) findings needs some elaboration. These findings are already taken to mean that the target CS in each design is not informative about the occurrence of the US - hence, learning about this CS fails. In the case of blocking, we also know that changes in the rate of reinforcement across the shift from stage 1 to stage 2 of the protocol can produce unblocking. Perhaps more interesting from a rate estimation perspective, unblocking can also be achieved in a protocol that maintains the rate of reinforcement while varying the sensory properties of the US (Wagner). How does rate estimation theory account for these findings and/or the demonstrations of trans-reinforcer blocking (Pearce-Ganesan)? Are there other ways that the rate estimation account can be distinguished from traditional explanations of blocking and contingency effects? If so, these would be worth citing in the discussion. More generally, if one is going to highlight seminal findings (such as those by Rescorla and Kamin) that can be explained by rate estimation, it would be appropriate to acknowledge findings that challenge the theory - even if only to note that the theory, in its present form, is not all-encompassing. For example, it appears to me that the theory should not predict one-trial overshadowing or the overtraining reversal effect - both of which are amenable to discussion in terms of rates. I assume that the signature characteristics of latent inhibition and extinction would also pose a challenge to rate estimation theory, just as they pose a challenge to Rescorla-Wagner and other probability-based theories. Is this correct?
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Reviewer #1 (Public Review):
Summary:
A key challenge at the second chemical step of splicing is the identification of the 3' splice site of an intron. This requires recruitment of factors dedicated to the second chemical step of splicing and exclusion of factors dedicated to the first chemical step of splicing. Through the highest resolution cyroEM structure of the spliceosome to-date, the authors show the binding site for Fyv6, a factor dedicated to the second chemical step of splicing, is mutually exclusive with the binding site for a distinct factor dedicated to the first chemical step of splicing, highlighting that splicing factors bind to the spliceosome at a specific stage not only by recognizing features specific to that stage but also by competing with factors that bind at other stages. The authors further reveal that Fyv6 functions at the second chemical step to promote selection of 3' splice sites distal to a branch point and thereby discriminate against proximal, suboptimal 3' splice site. Lastly, the authors show by cyroEM that Fyv6 physically interacts with the RNA helicase Prp22 and by genetics Fyv6 functionally interacts with this factor, implicating Fyv6 in 3'SS proofreading and mRNA release from the spliceosome. The evidence for this study is robust, with the inclusion of genomics, reporter assays, genetics, and cyroEM. Further, the data overall justify the conclusions, which will be of broad interest.
Strengths:
(1) The resolution of the cryoEM structure of Fyv6-bound spliceosomes at the second chemical step of splicing is exceptional (2.3 Angstroms at the catalytic core; 3.0-3.7 Angstroms at the periphery), providing the best view of this spliceosomal intermediate in particular and the core of the spliceosome in general.<br /> (2) The authors observe by cryoEM three distinct states of this spliceosome, each distinguished from the next by progressive loss of protein factors and/or RNA residues. The authors appropriately refrain from overinterpreting these states as reflecting distinct states in the splicing cycle, as too many cyroEM studies are prone to do, and instead interpret these observations to suggest interdependencies of binding. For example, when Fyv6, Slu7, and Prp18 are not observed, neither are the first and second residues of the intron, which otherwise interact, suggesting an interdependence between 3' splice site docking on the 5' splice site and binding of these second step factors to the spliceosome.<br /> (3) Conclusions are supported from multiple angles.<br /> (4) The interaction between Fyv6 and Syf1, revealed by the cyroEM structure, was shown to account for the temperature-sensitive phenotypes of a fyv6 deletion, through a truncation analysis.<br /> (5) Splicing changes were observed in vivo both by indirect copper reporter assays and directly by RT-PCR.<br /> (6) Changes observed by RNA-seq are validated by RT-PCR.<br /> (7) The authors go beyond simply observing a general shift to proximal 3'SS usage in the fyv6 deletion by RNA-seq by experimentally varying branch point to 3' splice site distance experimentally in a reporter and demonstrating in a controlled system that Fyv6 promotes distal 3' splice sites.<br /> (8) The importance of the Fyv6-Syf1 interaction for 3'SS recognition is demonstrated by truncations of both Fyv6 and of Syf1.<br /> (9) In general, the study was executed thoroughly and presented clearly.
Comments on revisions:
The authors have satisfactorily addressed the comments.
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Reviewer #1 (Public review):
Summary:
This study reports single-cell RNA sequencing results of lung adenocarcinoma, comparing 4 treatment-naive and 5 post-neoadjuvant chemotherapy tumor samples.<br /> The authors claim that there are metabolic reprogramming in tumor cells as well as stromal and immune cells after chemotherapy.<br /> The most significant findings are in the macrophages that there are more pro-tumorigenic cells after chemotherapy, i.e. CD45+CD11b+ARG+ cells. In the treatment-naive samples, more anti-tumorigenic CD45+CD11b+CD86+ macrophages are found. They sorted each population and performed functional analyses.
Strengths:
Comparison of the treatment-naive and post-chemotherapy samples of lung adenocarcinoma.
Weaknesses:
After the revision, issues remain with lengthy descriptive clustering type analysis, insufficient statistical support, and inefficient figure presentation.
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Reviewer #1 (Public review):
Summary:
This study examined the associations of healthy lifestyles with comprehensive and organ-specific biological ages. It emphasized the importance of lifestyle factors in determining biological ages, which were using common blood biomarkers and body measures.
Strengths:
The data were from a large cohort study and defined comprehensive and six-specified BA.
Weaknesses highlighted previously:
(1) Since only 8.5% of participants from the CMEC were included in the study, has any section bias happened?
(2) The author should specify the efficiency of FFQ. How FFQ can genuinely reflect the actual intake? Moreover, how was the aMED calculated in your study?
(3) HLI (range) and HLI (category) should be clearly defined.
(4) The rationale of comprehensive and specific BA construction should be clearly defined and discussed. For example, can cardiopulmonary BA be reflected only by using cardiopulmonary status? I do not think so.
(5) The lifestyle index is defined based on an equal-weight approach, but this does not reflect reality and can not fully answer the research questions it raises.
Comments on the revised version:
The author answered most of the questions raised. However, since wine is the most important component of aMED, removing wine or alcohol may result in biased estimates. In addition, The authors acknowledge the limitations of this approach, namely that some biomarkers may not fully capture the complete aging process of the system; this weakness is particularly remarkable in organ-specific BA. The authors emphasize that it is cost-effective and easy to implement. However, the results associated with organ-specific BA may not be credible because they do not fully reflect the state of a particular organ. It is recommended that these shortcomings and the applicability of the results should be discussed in the text.
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Reviewer #1 (Public review):
The authors sought to determine the impact of early antiretroviral treatment on the size, composition, and decay of the HIV latent reservoir. This reservoir represents the source of viral rebound upon treatment interruption and therefore constitutes the greatest challenge to achieving an HIV cure. A particular strength of this study is that it reports on reservoir characteristics in African women, a significantly understudied population, of whom some have initiated treatment within days of acute HIV diagnosis. With the use of highly sensitive and current technologies, including digital droplet PCR and near full-length genome next-generation sequencing, the authors generated a valuable dataset for investigation of proviral dynamics in women initiating early treatment compared to those initiating treatment in chronic infection. The authors confirm previous reports that early antiretroviral treatment restricts reservoir size, but further show that this restriction extends to defective viral genomes, where late treatment initiation was associated with a greater frequency of defective genomes. Furthermore, an additional strength of this study is the longitudinal comparison of viral dynamics post-treatment, wherein early treatment was shown to be associated with a more rapid rate of decay in proviral genomes, regardless of intactness, over a period of one year post-treatment. While it is indicated that intact genomes were not detected after one year following early treatment initiation, sampling depth is noted as a limitation of the study by the authors, and caution should thus be taken with interpretation where sequence numbers are low. Defective genomes are more abundant than intact genomes and are therefore more likely to be sampled. Early treatment was also associated with reduced proviral diversity and fewer instances of polymorphisms associated with cytotoxic T-lymphocyte immune selection. This is expected given that rapid evolution and extensive immune selection are synonymous with HIV infection in the absence of treatment, yet points to an additional benefit of early treatment in the context of immune therapies to restrict the reservoir.
This is one of the first studies to report the mapping of longitudinal intactness of proviral genomes in the globally dominant subtype C. The data and findings from this study therefore represent a much-needed resource in furthering our understanding of HIV persistence and informing broadly impactful cure strategies. The analysis on clonal expansion of proviral genomes may be limited by higher sequence homogeneity in hyperacute infection i.e., cells with different proviral integration sites may have a higher likelihood of containing identical genomes compared to chronic infection.
Overall, these data demonstrate the distinct benefits of early treatment initiation at reducing the barrier to a functional cure for HIV, not only by restricting viral abundance and diversity but also potentially through the preservation of immune function and limiting immune escape. It therefore provides clues to curative strategies even in settings where early diagnosis and treatment may be unlikely.
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Reviewer #1 (Public review):
Previous studies have highlighted some of these paracrine activities of Toxoplasma - and Rasogi et al (mBio, 2020) used a single cell sequencing approach of cells infected in vitro with the WT or MYR KO parasites - and one of their conclusions was that MYR-1 dependent paracrine activities counteract ROP-dependent processes. Similarly, Chen et al (JEM 2020) highlighted that a particular rhoptry protein (ROP16) could be injected into uninfected macrophages and move them to an anti-inflammatory state that might benefit the parasite.
Caveats around immunity and as yet no insight into how this works. In Fig 2 there is a marked defect in the ability of the parasites to expand at day 2 and day 5. Together, these data sets suggest that this paracrine effect mediated by MYR-1 works early - well before the development of adaptive responses.
Comments on revisions:
The authors have provided their perspective on the original review. There were some previous comments that revolved around whether some of the early changes were masked by pooling data sets where they have reiterated that it is not statistically different. Would have been nice to have seen out addressed by having experiments that were appropriately powered. But it's their call.
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Reviewer #1 (Public review):
In their manuscript, authors Isotani et al used in vivo and ex vivo models to show that nicotine could promote stemness and tumorigenicity in murine model. The authors further provided data supporting that the effects of nicotine on stem cell proliferation and tumor initiation were mediated by the Hippo-YAP/TAZ and Notch signal pathway.
The major strength of this study is the using a set of tools, including Lgr5 reporter mice (Lgr5-EGFP-IRES-CreERT2 mice), stem cell-specific Apc knockout mice (Lgr5CreER Apcfl/fl mice), organoids derived from these mice and chemical compounds (agonists and antagonists) to demonstrate nicotine affects stem cells rather than Paneth cells, leading to increased intestinal stemness and tumorigenicity. Whereas, all models are restricted to mice, lacking analysis of human samples or human intestinal organoids to prove the human relevance of these findings.
Overall, the presented results support their conclusions. A previous study reported that nicotine acts through the α2β4 nAChR to enhance Wnt production by Paneth cells, which subsequently affects ISCs. In contrast, this manuscript demonstrated that nicotine directly promotes ISCs through α7-nAChR, independent of Paneth cells. Therefore, this manuscript offers novel insights into the mechanism of nicotine's effects on the mouse intestine.
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Reviewer #2 (Public review):
In this manuscript, Tiedje and colleagues longitudinally track changes in parasite numbers across four time points as a way of assessing the effect of malaria control interventions in Ghana. Some of the study results have been reported previously, and in this publication, the authors focus on age-stratification of the results. Malaria prevalence was lower in all age groups after IRS. Follow-up with SMC, however, maintained lower parasite prevalence in the targeted age group but not the population as a whole. Additionally, they observe that diversity measures rebound more slowly than prevalence measures. This adds to a growing literature that demonstrates the relevance of asymptomatic reservoirs.
Strengths:
Overall, I found these results clear, convincing, and well-presented. There is growing interest in developing an expanded toolkit for genomic epidemiology in malaria, and detecting changes in transmission intensity is one major application. As the authors summarize, there is no one-size-fits-all approach, and the Bayesian MOIvar estimate developed here has the potential to complement currently used methods, particularly in regions with high diversity/transmission. I find its extension to a calculation of absolute parasite numbers appealing as this could serve as both a conceptually straightforward and biologically meaningful metric.
Weaknesses:
While I understand the conceptual importance of distinguishing among parasite prevalence, mean MOI, and absolute parasite number, I am not fully convinced by this manuscript's implementation of "census population size". The authors reference the population genetic literature, but within the context of that field, "census population size" refers to the total population size (which, if not formally counted, can be extrapolated) as opposed to "effective population" size, which accounts for a multitude of demographic factors. There is often interesting biology to be gleaned from the magnitude of difference between N and Ne. In this manuscript, however, "census population size" is used to describe the number of distinct parasites detected within a sample, not a population. As a result, the counts do not have an immediate population genetic interpretation and cannot be directly compared to Ne. This doesn't negate their usefulness but does complicate the use of a standard population genetic term. In contrast, I think that sample parasite count will be most useful in an epidemiological context, where the total number of sampled parasites can be contrasted with other metrics to help us better understand how parasites are divided across hosts, space and time. However, for this use, I find it problematic that the metric does not appear to correct for variations in participant number. For instance, in this study, participant numbers especially varied across time for 1-5 year-olds (N=356, 216, 405, and 354 in 2012, 2014, 2015, and 2017 respectively). This sample size variability is accounted for with other metrics like mean MOI. In sum, while the manuscript opens up an interesting discussion, I'm left with an incomplete understanding of the robustness and interpretability of the new proposed metric.
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Reviewer #1 (Public review):
Previous experimental studies demonstrated that membrane association drives avidity for several potent broadly HIV-neutralizing antibodies and its loss dramatically reduces neutralization. In this study, the authors present a tour de force analysis of molecular dynamics (MD) simulations that demonstrate how several HIV-neutralizing membrane-proximal external region (MPER)-targeting antibodies associate with a model lipid bilayer.
First, the authors compared how three MPER antibodies, 4E10, PGZL1, and 10E8, associated with model membranes, constructed with two lipid compositions similar to native viral membranes. They found that the related antibodies 4E10 and PGZL1 strongly associate with a phospholipid near heavy chain loop 1, consistent with prior crystallographic studies. They also discovered that a previously unappreciated framework region between loops 2-3 in the 4E10/PGZL1 heavy chain contributes to membrane association. Simulations of 10E8, an antibody from a different lineage, revealed several differences from published X-ray structures. Namely, a phosphatidylcholine binding site was offset and includes significant interaction with a nearby framework region. The revised manuscript demonstrates that these lipid interactions are robust to alterations in membrane composition and rigidity. However, it does not address the reverse-that phospholipids known experimentally not to associate with these antibodies (if any such lipids exist) also fail to interact in MD simulations.
Next, the authors simulate another MPER-targeting antibody, LN01, with a model HIV membrane either containing or missing an MPER antigen fragment within. Of note, LN01 inserts more deeply into the membrane when the MPER antigen is present, supporting an energy balance between the lowest energy conformations of LN01, MPER, and the complex. These simulations recapitulate lipid binding interactions solved in published crystallographic studies but also lead to the discovery of a novel lipid binding site the authors term the "Loading Site", which could guide future experiments with this antibody.
The authors next established course-grained (CG) MD simulations of the various antibodies with model membranes to study membrane embedding. These simulations facilitated greater sampling of different initial antibody geometries relative to membrane. These CG simulations , which cannot resolve atomistic interactions, are nonetheless compelling because negative controls (ab 13h11, BSA) that should not associate with membrane indeed sample significantly less membrane.
Distinct geometries derived from CG simulations were then used to initialize all-atom MD simulations to study insertion in finer detail (e.g., phospholipid association), which largely recapitulate their earlier results, albeit with more unbiased sampling. The multiscale model of an initial CG study with broad geometric sampling, followed by all-atom MD, provides a generalized framework for such simulations.
Finally, the authors construct velocity pulling simulations to estimate the energetics of antibody membrane embedding. Using the multiscale modelling workflow to achieve greater geometric sampling, they demonstrate that their model reliably predicts lower association energetics for known mutations in 4E10 that disrupt lipid binding. However, the model does have limitations: namely, its ability to predict more subtle changes along a lineage-intermediate mutations that reduce lipid binding are indistinguishable from mutations that completely ablate lipid association. Thus, while large/binary differences in lipid affinity might be predictable, the use of this method as a generative model are likely more limited.
The MD simulations conducted throughout are rigorous and the analysis are extensive, creative, and biologically inspired. Overall, these analyses provide an important mechanistic characterization of how broadly neutralizing antibodies associate with lipids proximal to membrane-associated epitopes to drive neutralization.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In their manuscript, Gomez-Frittelli and colleagues characterize the expression of cadherin6 (and -8) in colonic IPANs of mice. Moreover, they found that these cdh6-expressing IPANs are capable of initiating colonic motor complexes in the distal colon, but not proximal and midcolon. They support their claim by morphological, electrophysiological, optogenetic, and pharmacological experiments.
Strengths:
The work is very impressive and involves several genetic models and state-of-the-art physiological setups including respective controls. It is a very well-written manuscript that truly contributes to our understanding of GI-motility and its anatomical and physiological basis. The authors were able to convincingly answer their research questions with a wide range of methods without overselling their results.
Weaknesses:
The authors put quite some emphasis on stating that cdh6 is a synaptic protein (in the title and throughout the text), which interacts in a homophilic fashion. They deduct that cdh6 might be involved in IPAN-IPAN synapses (line 247ff.). However, Cdh6 does not only interact in synapses and is expressed by non-neuronal cells as well (see e.g., expression in the proximal tubuli of the kidney). Moreover, cdh6 does not only build homodimers, but also heterodimers with Chd9 as well as Cdh7, -10, and -14 (see e.g., Shimoyama et al. 2000, DOI: 10.1042/0264-6021:3490159). It would therefore be interesting to assess the expression pattern of cdh6-proteins using immunostainings in combination with synaptic markers to substantiate the authors' claim or at least add the possibility of cell-cell-interactions other than synapses to the discussion. Additionally, an immunostaining of cdh6 would confirm if the expression of tdTomato in smooth muscle cells of the cdh6-creERT model is valid or a leaky expression (false positive).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this manuscript the Treisman and colleagues address the question of how protein phosphatase 1 (PP1) regulatory subunits (or PP1-interacting protein (PIPs)) confer specificity on the PP1 catalytic subunit which by itself possesses little substrate specificity. In prior work the authors showed that the PIP Phactrs confers specificity by remodelling a hydrophobic groove immediately adjacent to the PP1 catalytic site through residues within the RVxF- ø ø -R-W string of Phactrs. Specifically, the residues proximal and including the 'W' of the RVxF- ø ø -R-W string remodel the hydrophobic groove. Other residues of the RVxF- ø ø -R-W string (i.e. the RVxF- ø ø -R) are not involved in this remodelling.
The authors suggest that the RVxF- ø ø -R-W string is a conserved feature of many PIPs including PNUTS, Neurabin/spinophilin and R15A. However, from a sequence and structural perspective, only the RVxF- ø ø -R- is conserved. The W is not conserved in most and in the R15A structure (PDB:7NZM) the Trp side chain points away from the hydrophobic channel - this could be a questionable interpretation due to model-building into the low-resolution cryo-EM map (4 A).
In this paper, the authors convincingly show that Neurabin confers substrate specificity through interactions of its PDZ domain with the PDZ domain-binding motif (PBM) of 4E-BP. They show the PBM motif is required for Neurabin to increase PP1 activity towards 4E-BP and a synthetic peptide modelled on 4E-BP and also a synthetic peptide based on IRSp53 with a PBM added. The PBM of 4E-BP1 confers high affinity binding to the Neurabin PDZ domain. A crystal structure of a PP1-4E-BP1 fusion with Neurabin shows that the PBM of 4E-BP interacts with the PDZ domain of Neurabin. No interactions of 4E-BP and the catalytic site of PP1 are observed. Cell biology work showed that Neurabin-PP1 regulates the TOR signalling pathway by dephosphorylating 4E-BPs.
Strengths:
This work demonstrates convincingly using a variety of cell biology, proteomics, biophysics and structural biology that the PP1 interacting protein Neurabin confers specificity on PP1 through an interaction of its PDZ domain with a PDZ-binding motif of 4E-BP1 proteins. Remodelling of the hydrophobic groove of the PP1 catalytic subunit is not involved in Neurabin-dependent substrate specificity, in contrast to how Phactrs confers specificity on PP1. The active site of the Neurabin/PP1 complex does not recognise residues in the vicinity of the phospho-residue, thus allowing for multiple phospho-sites on 4E-BP to be dephosphorylated by Neurabin/PP1. This contrasts with substrate specificity conferred by the Phactrs PIP that confers specificity of Phactrs/PP1 towards its substrates in a sequence-specific context by remodelling the hydrophobic groove immediately adjacent to the catalytic. The structural and biochemical insights are used to explore the role of Neurabin/PP1 in dephosphorylation 4E-BPs in vivo, showing that Neurabin/PP1 regulates the TOR signalling pathway, specifically mTORC1-dependent translational control.
Weaknesses:
The only weakness is the suggestion that a conserved RVxF- ø ø -R-W string exists in PIPs. The 'W' is not conserved in sequence and 3 dimensions in most of the PIPs discussed in this manuscript. The lack of conservation of the W would be consistent with the finding based on multiple PP1-PIP structures that apart from Phactrs, no other PIP appears to remodel the PP1 hydrophobic channel.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public review):
The authors of this study developed a method to quantify calvarial bone marrow from MRI head scans, enabling the study of its composition in large datasets of adults, usually collected to study the brain. Bone marrow intensity can be semi-quantitatively measured in T1-weighted MRI scans due to the greater signal intensity of fat than watery red marrow. This is an ingenious use of the MRI-produced information for other important phenotypes, such as bone structure and marrow content. Different head types were tested for complying with the model, which is notable.
The model was also successfully validated using several publicly available MRI resources - real data - in (1) a dataset consisting of 30 individuals that were scanned 10 times each at 3-day intervals, and (2) the monozygotic (MZ) twin data from the Human Connectome Project cohort. Then the authors applied this validated method to head-MRI scans from the UK Biobank (n=33,042) to extract information on the spatial distribution of bone marrow adiposity (BMA) in the calvaria, allowing a GWAS to identify associated genes.
The authors revealed high heritability and identified 41 genetic loci significantly associated with the BMA trait, including six sex-specific loci. Of note, statistics estimate that 99% of BMA trait-influencing variants are shared with BMD (497 of 500 variants), which may mean these results demonstrate the biological relevance to bone health. Some of the BMA genes were found related to the Wnt pathway, including WNT16, WNT4, NXN; this is a "positive control", since the Wnt/β-catenin signaling pathway was suggested as an important determinant of BMA. Also, associations in genes (BMP4, DLX5, LGR4, LRP4, SFRP4) that are known to specifically influence adiposity, are encouraging. Integrating mapped genes with bone marrow single-cell RNA-seq data revealed patterns of adipogenic lineage differentiation and lipid loading.
The study also investigated the genetic overlap between BMA and twelve (or 13) "brain and body" traits and identified significant genetic correlations with BMI, cognitive ability, and Parkinson's disease.
In sum, since MRI head scans present a hitherto unexplored opportunity to address unresolved aspects of bone marrow biology, this study is both timely and innovative.
There are, however, some assumptions, findings, and their interpretation, which require more critical focus.
Sex-specificity is well described and studied here. Men have higher BMA than women, but post-menopausal women catch up in the BMA values. The authors believe that calvarial marrow has a number of features that make it particularly well-suited to the study of BMA process - which is clinically important in other bone sites. It has a simple "sandwiched" structure that they are able to model. This is true only to some extent: a condition called "Hyperostosis frontalis interna", of unknown etiology (described by Smith & Hemphill in 1956) - is characterized by irregular overgrowth of the inner table of the frontal bone (symmetric/bilateral). Although not of clinical significance, typically benign, studies report a prevalence of 12%; However, it's most common in postmenopausal women - where prevalences up to 49% in women over the age of 65 - have been reported. Thus, sexual dimorphism is obvious and the effect of estrogen is likely shared with whichever bone - and marrow - age-related pathology. So, for women not using HRT, this new layer of the bone might interfere with the calvarial BMA readings and in turn, affect the BMA-related analyses. The authors suspect that the effect of BMA on BMD may be biased in women; they should comment on those "with low BMD and high BMA" given that hyperostosis frontalis might be an issue. A strong effect of SNPs in the ESR1 chromosomal region might be akin to the above concern.
Then, there is a perfect overlap of the BMA SNPs that are shared with BMD (497 of 500 variants), which may prove a "face validity" of the MRI-derived BMA. However, the BMD in the study was heel-derived eBMD - which is a good proxy for osteoporosis and is mostly driven by trabecular bone. Thus, there might be a concern that the BMA metrics capture some trabecular BMD.
Next, integrating mapped genes with existing bone marrow single-cell RNA-sequencing data revealed patterns of adipogenic lineage differentiation and lipid loading. The problem here is that the scRNAseq studies of the Bone Marrow niche are overwhelmingly mouse. The authors might wish to justify why they are relevant to humans (in the absence of the human-specific scRNAseq).
For genetic correlation analysis, the authors selected 7 body and 6 brain traits. The latter traits reflect cognition (general cognitive ability and educational attainment) and brain-related disorders. This selection might seem arbitrary. The interpretation of genetic correlation with cognitive ability, education, and Parkinson's disease was attributed to the recently discovered vascular channels that link calvarial bone marrow to the meninges. This is a fascinating hypothesis, which requires functional proof. However, there might be simpler explanations. Thus, the diploe and the inner table of the calvarium are drained by the same veins as the dura. From the anatomy textbook, we know that diploic veins connect the pericranial and endocranial venous system through the skull.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Ma, Yang et al. report a new investigation aimed at elucidating one of the key nutrients S. Typhimurium (STM) utilizes with the nutrient-poor intracellular niche within the macrophage, focusing on the amino acid beta-alanine. From these data, the authors report that beta-alanine plays an important role in mediating STM infection and virulence. The authors employ a multidisciplinary approach that includes some mouse studies and ultimately propose a mechanism by which panD, involved in B-Ala synthesis, mediates the regulation of zinc homeostasis in Salmonella. The impact of this work is questionable. There are already many studies reporting Salmonella-effector interactions, and while this adds to that knowledge it is not a significant advance over previous studies. While the authors are investigating an interesting question, the work has two important weaknesses; if addressed, the conclusions of this work and broader relevance to bacterial pathogenesis would be enhanced.
Strengths:
This reviewer appreciates the multidisciplinary nature of the work. The overall presentation of the figure graphics are clear and organized.
Weaknesses:
First, this study is very light on mechanistic investigations, even though a mechanism is proposed. Zinc homeostasis in cells, and roles in bacteria infections, are complex processes with many players. The authors have not thoroughly investigated the mechanisms underlying the roles of B-Ala and panD in impacting STM infection such that other factors cannot be ruled out. Defining the cellular content of Zn2+ STM in vivo would be one such route. With further mechanistic studies, the possibility cannot be ruled out that the authors have simply deleted two important genes and seen an infection defect - this may not relate directly to Zn2+ acquisition.
Second, the authors hint at their newly described mechanism/pathway being important for disease and possibly a target for therapeutics. This claim is not justified given that they have employed a single STM strain, which was isolated from chickens and is not even a clinical isolate. The authors could enhance the impact of their findings and relevance to human disease by demonstrating it occurs in human clinical isolates and possibly other serovars. Further, the use of mouse macrophage as a model, and mice, have limited translatability to human STM infections.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The paper by Tolossa et al. presents classification studies that aim to predict the anatomical location of a neuron from the statistics of its in-vivo firing pattern. They study two types of statistics (ISI distribution, PSTH) and try to predict the location at different resolutions (region, subregion, cortical layer).
Strengths:
This paper provides a systematic quantification of the single-neuron firing vs location relationship.
The quality of the classification setup seems high.
The paper uncovers that, at the single neuron level, the firing pattern of a neuron carries some information on the neuron's anatomical location, although the predictive accuracy is not high enough to rely on this relationship in most cases.
Weaknesses:
As the authors mention in the Discussion, it is not clear whether the observed differences in firing are epiphenomenal. If the anatomical location information is useful to the neuron, to what extent can this be inferred from the vicinity of the synaptic site, based on the neurotransmitter and neuromodulator identities? Why would the neuron need to dynamically update its prediction of the anatomical location of its pre-synaptic partner based on activity when that location is static, and if that information is genetically encoded in synaptic proteins, etc (e.g., the type of the synaptic site)? Note that the neuron does not need to classify all possible locations to guess the location of its pre-synaptic partner because it may only receive input from a subset of locations. If an argument on activity-based estimation being more advantageous to the neuron than synaptic site-based estimation cannot be made, I believe limiting the scope of the paper (e.g., in the Introduction) to an epiphenomenal observation and its quantification will improve the scientific quality.Life Assessment
This article reports a useful set of findings on how electrophysiological response properties of neurons correlate with their position in the brain. The evidence currently remains incomplete, with reviewers making specific suggestions for how clustering needs to be redone. The manuscript would also benefit from a more focused presentation of results and the removal of incorrect claims about recording biases.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Mitotic kinesins carry out crucial roles in intracellular motility and mitotic spindle organization. Although many mitotic kinesins have been extensively studied, a few conserved mitotic motors remain poorly explored, including chromosome-associated kinesins. Here, Furusaki et al reconstitute recombinant chromosome-associated kinesin or chromokinesin (Kid) and reveal processive plus-end motility along microtubules. The authors purify multiple versions of Kid, revealing dimeric organization and their processive microtubule plus-ended motility which depends on their conserved motor domains, neck linkers, and coiled-coil regions. The study reveals for the first time that KID can recruit and transport duplex DNA along microtubules using its conserved C-terminal DNA binding domain. The work provides crucial revised thinking about the mechanisms of Chromokinesins mitosis as physical processive motors that mobilize chromosomes towards the microtubule plus ends in early metaphase.
Strengths:
The authors reconstitute multiple chromosome-associated kinesin (KID) orthologs from Xenopus and humans with microtubules and determine their oligomerization. The study shows how coiled-coil and neck linker regions of KID are essential for its function as its deletion leads to non-processive motility. CHimeras placing the KID coiled-coil and neck linker on the KIF1A motor domain led to the production of a processive recombinant motor supporting the compatibility of their motility mechanisms. The KID c-terminal tail binds and transports only double-stranded DNA and its deletion or single-stranded DNA leads to defects in this activity.
Weaknesses:
A minor weakness in the studies is that they do not resolve the mechanisms of KID in binding large duplex DNA molecules or condensed chromatin. The authors suggest a model in which KID forms multimers along large chromosomes that lead to their transport, but this model was not directly tested.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The study by McKim et al seeks to provide a comprehensive description of the connectivity of neurosecretory cells (NSCs) using a high-resolution electron microscopy dataset of the fly brain and several single-cell RNA seq transcriptomic datasets from the brain and peripheral tissues of the fly. They use connectomic analyses to identify discrete functional subgroups of NSCs and describe both the broad architecture of the synaptic inputs to these subgroups as well as some of the specific inputs including from chemosensory pathways. They then demonstrate that NSCs have very few traditional presynapses consistent with their known function as providing paracrine release of neuropeptides. Acknowledging that EM datasets can't account for paracrine release, the authors use several scRNAseq datasets to explore signaling between NSCs and characterize widespread patterns of neuropeptide receptor expression across the brain and several body tissues. The thoroughness of this study allows it to largely achieve it's goal and provides a useful resource for anyone studying neurohormonal signaling.
Strengths:
The strengths of this study are the thorough nature of the approach and the integration of several large-scale datasets to address short-comings of individual datasets. The study also acknowledges the limitations that are inherent to studying hormonal signaling and provides interpretations within the the context of these limitations.
Weaknesses:
Overall, the framing of this paper needs to be shifted from statements of what was done to what was found. Each subsection, and the narrative within each, is framed on topics such as "synaptic output pathways from NSC" when there are clear and impactful findings such as "NSCs have sparse synaptic output". Framing the manuscript in this way allows the reader to identify broad takeaways that are applicable to other model system. Otherwise, the manuscript risks being encyclopedic in nature. An overall synthesis of the results would help provide the larger context within which this study falls.
The cartoon schematic in Figure 5A (which is adapted from a 2020 review) has an error. This schematic depicts uniglomerular projection neurons of the antennal lobe projecting directly to the lateral horn (without synapsing in the mushroom bodies) and multiglomerular projection neurons projecting to the mushroom bodies and then lateral horn. This should be reversed (uniglomerular PNs synapse in the calyx and then further project to the LH and multiglomerular PNs project along the mlACT directly to the LH) and is nicely depicted in a Strutz et al 2014 publication in eLife.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
PROTACs are heterobifunctional molecules that utilize the Ubiquitin Proteasome System to selectively degrade target proteins within cells. Upon introduction to the cells, PROTACs capture the activity of the E3 ubiquitin ligases for ubiquitination of the targeted protein, leading to its subsequent degradation by the proteasome. The main benefit of PROTAC technology is that it expands the "druggable proteome" and provides numerous possibilities for therapeutic use. However, there are also some difficulties, including the one addressed in this manuscript: identifying suitable target-E3 ligase pairs for successful degradation. Currently, only a few out of about 600 E3 ligases are used to develop PROTAC compounds, which creates the need to identify other E3 ligases that could be used in PROTAC synthesis. Testing the efficacy of PROTAC compounds has been limited to empirical tests, leading to lengthy and often failure-prone processes. This manuscript addressed the need for faster and more reliable assays to identify the compatible pairs of E3 ligases-target proteins. The authors propose using the RiPA assay, which depends on rapamycin-induced dimerization of FKBP12 protein with FRB domain. The PROTAC technology is advancing rapidly, making this manuscript both timely and essential. The RiPA assay might be useful in identifying novel E3 ligases that could be utilized in PROTAC technology. Additionally, it could be used at the initial stages of PROTAC development, looking for the best E3 ligase for the specific target.
The authors described an elegant assay that is scalable, easy-to-use and applicable to a wide range of cellular models. This method allows for the quantitative validation of the degradation efficacy of a given pair of E3 ligase-target protein, using luciferase activity as a measure. Importantly, the assay also enables the measurement of kinetics in living cells, enhancing its practicality.
Strengths:
(1) The authors have addressed the crucial needs that arise during PROTAC development. In the introduction, they nicely describe the advantages and disadvantages of the PROTAC technology and explain why such an assay is needed.
(2) The study includes essential controls in experiments (important for generating new assay), such as using the FRB vector without E3 ligase as a negative control, testing different linkers (which may influence the efficacy of the degradation), and creating and testing K-less vectors to exclude the possibility of luciferase or FKBP12 ubiquitination instead of WDR5 (the target protein). Additionally, the position of the luc in the FKBP12 vector and the position of VHL in the FRB vector are tested. Different E3 ligases are tested using previously identified target proteins, confirming the assay's utility and accuracy.
(3) The study identified a "new" E3 ligase that is suitable for PROTAC technology (FBXL).
Weaknesses:
It is not clear how feasible it would be to adapt the assay for high-throughput screens.
Comments on revisions:
The authors have addressed my previous concerns and made changes to the manuscript, resulting in a well-written paper.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
The study investigates light chains (LCs) using three distinct approaches, with a focus on identifying a conformational fingerprint to differentiate amyloidogenic light chains from multiple myeloma light chains. The study's major contribution is the identification of a low-populated "H state," which the authors propose as a unique marker for AL-LCs. While this finding is promising, the review highlights several strengths and weaknesses. Strengths include the valuable contribution of identifying the H state and the use of multiple approaches, which provide a comprehensive understanding of LC structural dynamics. However, the study suffers from weaknesses, particularly in the interpretation of SAXS data, lack of clarity in presentation, and methodological inconsistencies. Critical concerns include high error margins between SAXS profiles and MD fits, unclear validation of oligomeric species in SAXS measurements, and insufficient quantitative cross-validation between experimental (HDX) and computational data (MD). This reviewer calls for major revisions including clearer definitions, improved methodology, and additional validation, to strengthen the conclusions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This study investigated the heterogeneous responses to Mycobacterium tuberculosis (Mtb) in 19 wild-derived inbred mouse strains collected from various geographic locations. The goal of this study is to identify novel mechanisms that regulate host susceptibility to Mtb infection. Using the genetically resistant C57BL/6 mouse strain as the control, they successfully identified a few mouse strains that revealed higher bacterial burdens in the lung, implicating increased susceptibility in those mouse strains. Furthermore, using flow cytometry analysis, they discovered strong correlations between CFU and various immune cell types, including T cells and B cells. The higher neutrophil numbers correlated with significantly higher CFU in some of the newly identified susceptible mouse strains. Interestingly, MANB and MANC mice exhibited comparable numbers of neutrophils but showed drastically different bacterial burdens. The authors then focused on the neutrophil heterogeneity and utilized a single-cell RNA-seq approach, which led to identifying distinct neutrophil subsets in various mouse strains, including C57BL/6, MANA, MANB, and MANC. Pathway analysis on neutrophils in susceptible MANC strain revealed a highly activated and glycolytic phenotype, implicating a possible mechanism that may contribute to the susceptible phenotype. Lastly, the authors found that a small group of neutrophil-specific genes are expressed across many other cell types in the MANC strain.
Strengths:
This manuscript has many strengths.
(1) Utilizing and characterizing novel mouse strains that complement the current widely used mouse models in the field of TB. Many of those mouse strains will be novel tools for studying host responses to Mtb infection.
(2) The study revealed very unique biology of neutrophils during Mtb infection. It has been well-established that high numbers of neutrophils correlate with high bacterial burden in mice. However, this work uncovered that some mouse strains could be resistant to infection even with high numbers of neutrophils in the lung, indicating the diverse functions of neutrophils. This information is important.
Weaknesses:
The weaknesses of the manuscript are that the work is relatively descriptive. It is unclear whether the neutrophil subsets are indeed functionally different. While single-cell RNA seq did provide some clues at transcription levels, functional and mechanistic investigations are lacking. Similarly, it is unclear how highly activated and glycolytic neutrophils in MANC strain contribute to its susceptibility.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this manuscript, Guo and colleagues used a cell rounding assay to screen a library of compounds for inhibition of TcdB, an important toxin produced by Clostridioides difficile. Caffeic acid and derivatives were identified as promising leads, and caffeic acid phenethyl ester (CAPE) was further investigated.
Strengths:
Considering the high morbidity rate associated with C. difficile infections (CDI), this manuscript presents valuable research in the investigation of novel therapeutics to combat this pressing issue. Given the rising antibiotic resistance in CDI, the significance of this work is particularly noteworthy. The authors employed a robust set of methods and confirmatory tests, which strengthened the validity of the findings. The explanations provided are clear, and the scientific rationale behind the results is well-articulated. The manuscript is extremely well-written and organized. There is a clear flow in the description of the experiments performed. Also, the authors have investigated the effects of CAPE on TcdB in careful detail and reported compelling evidence that this is a meaningful and potentially useful metabolite for further studies.
Weaknesses:
This is really a manuscript about CAPE, not caffeic acid, and the title should reflect that. Also, a few details are missing from the description of the experiments. The authors should carefully revise the manuscript to ascertain that all details that could affect the interpretation of their results are presented clearly. Just as an example, the authors state in the results section that TcdB was incubated with compounds and then added to cells. Was there a wash step in between? Could compound carryover affect how the cells reacted independently from TcdB? This is just an example of how the authors should be careful with descriptions of their experimental procedures. Lastly, authors should be careful when drawing conclusions from the analysis of microbiota composition data. Ascribing causality to correlational relationships is a recurring issue in the microbiome field. Therefore, I suggest authors carefully revise the manuscript and tone down some statements about the impact of CAPE treatment on the gut microbiota.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public review):
Summary:
The present study aims to associate reproduction with age-related disease as support of the antagonistic pleiotorpy hypothesis of ageing, predominantly using Mendelian Randomization. The authors found evidence that early-life reproductive success is associated with advanced ageing.
Strengths:
Large sample size. Many analyses.
Weaknesses:
There are some errors in the methodology, that require revisions.
In particular, the main conclusions drawn by the authors refer to the Mendelian Randomization analyses. However, the authors made a few errors here that need to be reconsidered:
(1) Many of the outcomes investigated by the authors are continuous outcomes, while the authors report odds ratios. This is not correct and should be revised.
(2) Some of the odds ratios (for example the one for osteoporosis) are really small, while still reaching the level of statistical significance. After some checking, I found the GWAS data used to generate these MR estimates were processed by the program BOLT-LLM. This program is a linear mixed model program, which requires the transformation of the beta estimates to be useful for dichotomous outcomes. The authors should check the manual of BOLT-LLM and recalculate the beta estimates of the SNP-outcome associations prior to the Mendelian Randomization analyses. This should be checked for all outcomes as it doesn't apply to all.
(3) The authors should follow the MR-Strobe guidelines for presentation.
(4) The authors should report data in the text with a 95% confidence interval.
(5) The authors should consider correction for multiple testing.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public review):
Summary:
The characteristics of endometrium health are an increasing topic in women's health issues, especially in the context of endometriosis. In this respect, having access to information is hampered by the inaccessibility of the uterine tissue. The authors propose here using the menstrual fluid (easily accessible by non-invasive methods) as an access door towards getting relevant information.
Overall, the paper is divided into two parts:<br /> (1) The comparison between menstrual fluid samples and biopsies of the endometrium.<br /> 2) As a proof of concept, the authors then compared 11 controls and 7 endometriosis cases in this way, from different severity stages.
Strengths:
In Figure 1, general features of the 15 samples are presented (volume/number of cells/hematopoietic cells - cd45 labeling). The authors then used single-cell RNA-seq to characterize the different samples. Through having access to endometrium biopsies, they were able to compare the profiles obtained.
In the MF samples from the second part of the paper - aiming at comparing endometriosis and controls - one question is raised about the effect of culture. The authors compared freshly isolated and cultured tissues (ex vivo vs in vitro) by bulk RNA seq. Biases induced by the culture procedure were identified. Deconvolution was applied to strengthen this observation, with an important increase of seemingly stromal and unknown cells, especially in the unsorted cells and the CD45+ cells.
Interestingly, since the authors got successive samples from the same donor, they could evaluate the consistency of the samples and reveal indeed an overall stability of the molecular profile of the samples in a given patient.
The authors then attempted - quite originally - to characterize biomarkers in two major cell compartments that they studied - CD45- (stromal-like) and CD45+ (immune cells).
Weaknesses:
A potential problem is the justification of the a priori mix of cell types of three different phenotypes (CD45+, CD45- EPCAM+, and CD45- EPCAM-) from each patient before moving to the scRNAseq. It is not clear to me why this has been done, I guess that using directly the samples would supposedly bias the result. But in this case, why is it supposed that three categories are enough (immune cells, epithelial cells, and stromal cells)? I suppose that other markers could characterize other subtypes of the cells, and take into account the possibility of other cell types, for instance, connected to pain sensitivity, such as neuron precursor. Hence, the justification of the organized mixes should be much more detailed in my opinion.
It is a bit unclear to me when the biopsies were collected in the cycle of the donor patients.
The description of these markers that are deregulated is presented as a list, and connected with existing publications, which could rather be presented in discussion than in the results. The authors do tend to demonstrate that the Menstrual Fluid is a good proxy to analyse the endometrium health status of the women affected with endometriosis.
The identification of MTRNR2L1 seems to be a major discovery of the paper, as well as in a lesser measure HBG2, and it is a bit strange why these putative markers were not emphasized in the abstract. HBG2 was certainly identified previously in endometriosis endothelial cells but seems extremely variable from one sample to another - Geo profile (GDS3060, GDS3060 / 213515_x_at (inist.fr)).
Overall, the transcriptome analysis is a bit shallow, with no effort made to try to find potential transcription factors or miRNA that could activate/inhibit a series of modified genes; it could be relevant to identify such master genes or master regulators through bioinformatics analyses and wet-lab validations, to understand better the cascade of events.
Another issue that was overlooked is the presence of 'stem-cells' in the MF obtained. Since endometriosis is supposed to occur from the implantation of uterine stem cells, this category could be a major topic of scrutiny, in terms of quantity in the MF, as well as in terms of their specific molecular properties.
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Reviewer #1 (Public review):
The authors attempted to replicate previous work showing that counterconditioning leads to more persistent reduction of threat responses, relative to extinction. They also aimed to examine the neural mechanisms underlying counterconditioning and extinction. They achieved both of these aims and were able to provide some additional information, such as how counterconditioning impacts memory consolidation. Having a better understanding of which neural networks are engaged during counterconditioning may provide novel pharmacological targets to aid in therapies for traumatic memories. It will be interesting to follow up by examining the impact of varying amounts of time between acquisition and counterconditioning phases, to enhance replicability to real-world therapeutic settings.
Major strengths
• This paper is very well written and attempts to comprehensively assess multiple aspects of counterconditioning and extinction processes. For instance, the addition of memory retrieval tests is not core to the primary hypotheses but provides additional mechanistic information on how episodic memory is impacted by counterconditioning. This methodical approach is commonly seen in animal literature, but less so in human studies.
• The Group x Cs-type x Phase repeated measure statistical tests with 'differentials' as outcome variables are quite complex, however, the authors have generally done a good job of teasing out significant F test findings with post hoc tests and presenting the data well visually. It is reassuring that there is a convergence between self-report data on arousal and valence and the pupil dilation response. Skin conductance is a notoriously challenging modality, so it is not too concerning that this was placed in the supplementary materials. Neural responses also occurred in logical regions with regard to reward learning.
• Strong methodology with regards to neuroimaging analysis, and physiological measures.
• The authors are very clear on documenting where there were discrepancies from their pre-registration and providing valid rationales for why.
Major Weaknesses
• The statistics showing that counterconditioning prevents differential spontaneous recovery are the weakest p values of the paper (and using one-tailed tests, although this is valid due to directions being pre-hypothesised). This may be due to a relatively small number of participants and some variability in responses. It is difficult to see how many people were included in the final PDR and neuroimaging analyses, with exclusions not clearly documented. Based on Figure 3, there are relatively small numbers in the PDR analyses (n=14 and n=12 in counterconditioning and extinction, respectively). Of these, each group had 4 people with differential PDR results in the opposing direction to the group mean. This perhaps warrants mention as the reported effects may not hold in a subgroup of individuals, which could have clinical implications.
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Reviewer #1 (Public review):
Summary:
In this work, the authors examine the activity and function of D1 and D2 MSNs in dorsomedial striatum (DMS) during an interval timing task. In this task, animals must first nosepoke into a cued port on the left or right; if not rewarded after 6 seconds, they must switch to the other port. Thus, this task requires animals to estimate if at least 6 seconds have passed after the first nosepoke. After verifying that animals estimate the passage of 6 seconds, the authors examine striatal activity during this interval. They report that D1-MSNs tend to decrease activity, while D2-MSNs increase activity, throughout this interval. They suggest that this activity follows a drift-diffusion model, in which activity increases (or decreases) to a threshold after which a decision is made. The authors next report that optogenetically inhibiting D1 or D2 MSNs, or pharmacologically blocking D1 and D2 receptors, increased the average wait time. This suggests that both D1 and D2 neurons contribute to the estimate of time, with a decrease in their activity corresponding to a decrease in the rate of 'drift' in their drift-diffusion model. Lastly, the authors examine MSN activity while pharmacologically inhibiting D1 or D2 receptors. The authors observe most recorded MSNs neurons decrease their activity over the interval, with the rate decreasing with D1/D2 receptor inhibition.
Major strengths:
The study employs a wide range of techniques - including animal behavioral training, electrophysiology, optogenetic manipulation, pharmacological manipulations, and computational modeling. The question posed by the authors - how striatal activity contributes to interval timing - is of importance to the field and has been the focus of many studies and labs. This paper contributes to that line of work by investigating whether D1 and D2 neurons have similar activity patterns during the timed interval, as might be expected based on prior work based on striatal manipulations. However, the authors find that D1 and D2 neurons have distinct activity patterns. They then provide a decision-making model that is consistent with all results. The data within the paper is presented very clearly, and the authors have done a nice job presenting the data in a transparent manner (e.g., showing individual cells and animals). Overall, the manuscript is relatively easy to read and clear, with sufficient detail given in most places regarding the experimental paradigm or analyses used.
Major weaknesses:
The results are based on a relatively small dataset (tens of cells).
Impact:
The task and data presented by the authors are very intriguing, and there are many groups interested in how striatal activity contributes to the neural perception of time. The authors perform a wide variety of experiments and analysis to examine how DMS activity influences time perception during an interval-timing task, allowing for insight into this process.
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Reviewer #1 (Public review):
Mitochondria are essential organelles consisting in mammalian cells of about 1500 different proteins. Most of those are synthesized in the cytosol as precursor proteins, imported into mitochondria, and sorted into one of the four sub-mitochondrial compartments. The TIM23 complex, which is embedded in the mitochondrial inner membrane, facilitates the import of proteins that harbor Mitochondrial Targeting Sequence (MTS) at their N-terminus. Such proteins are sorted mainly to the mitochondrial matrix while some sub-groups are destined also to the inner membrane or the intermembrane space. TIMM50 (Tim50 in yeast) is an essential component of the TIM23 complex and mutations in this protein were reported to cause several diseases.
Summary:
In the current study, the authors analyzed the impact of TIMM50 mutations on the mitochondrial proteome in both patients' cells and mouse neurons. They provide compelling evidence for several surprising and highly interesting observations: (i) TIMM50 mutations affect the steady-state levels of only a portion of the putative TIMM50 substrates, (ii) such mutations result in increased electrical activity in mice neurons and in reduced levels of some potassium ion channels in the plasma membrane. These findings shed new light on mitochondrial biogenesis in mammalian cells and hint at an unexpected link between mitochondria and ion channels at the plasma membrane.
Strengths:
The authors used both cells from patients and neurons from mice to investigate the impact of mutations in TIMM50 on mitochondrial proteome and function.
Comments on revisions:
The authors addressed all my concerns regarding the original submission.
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Reviewer #2 (Public review):
Summary
The authors address three primary questions:<br /> (1) how FGF13 variants confer seizure susceptibility,<br /> (2) the specific cell types involved, and<br /> (3) the underlying mechanisms, particularly regarding Nav dysfunction.
They use different Cre drivers to generate cell type-specific knockouts (KOs). First, using Nestin-Cre to create a whole-brain Fgf13 KO, they observed spontaneous seizures and premature death. While KO of Fgf13 in excitatory neurons does not lead to spontaneous seizures, KO in inhibitory neurons recapitulates the seizures and premature death observed in the Nestin-Cre KO. They further narrow down the critical cell type to MGE-derived interneurons (INs), demonstrating that MGE-neuron-specific KO partially reproduces the observed phenotypes. "All interneuron" KOs exhibit deficits in synaptic transmission and interneuron excitability, not seen in excitatory neuron-specific KOs. Finally, they rescue the defects in the interneuron-specific KO by expressing specific Fgf13 isoforms. This is an elegant and important study adding to our knowledge of mechanisms that contribute to seizures.
Strengths<br /> • The study provides much-needed cell type-specific KO models.<br /> • The authors use appropriate Cre lines and characterize the phenotypes of the different KOs.<br /> • The metabolomic analysis complements the rest of the data effectively.<br /> • The study confirms and extends previous research using improved approaches (KO lines vs. in vitro KD or antibody infusion).<br /> • The methods and analyses are robust and well-executed.
Weaknesses
• One weakness lies in the use of the Nkx2.1 line (instead of Nkx2.1CreER) in the paper. As a result, some answers to key questions are incomplete. For instance, it remains unclear whether the observed effects are due to Chandelier cells or NGFCs, potentially both MGE and CGE derived, explaining why Nkx2.1 alone does not fully replicate the overall inhibitory KO. Using Nkx2.1CreER could have helped address the cell specificity. With the Nkx2.1 line used in the paper, the answer is partial.<br /> • While the mechanism behind the reduced inhibitory drive in the IN-specific KO is suggested to be presynaptic, the chosen method does not allow them to exactly identify the mechanisms (spontaneous vs mEPSC/mIPSC), and whether it is a loss of inhibitory synapses (potentially axo-axonic) or release probability.
General Assessment
The general conclusions of this paper are supported by data. As it is, the claim that "these results enhance our understanding of the molecular mechanisms that drive the pathogenesis of Fgf13-related seizures" is partially supported. A more cautious term may be more appropriate, as the study shows the mechanism is not Nav-mediated and suggests alternative mechanisms without unambiguously identifying them. The conclusion that the findings "expand our understanding of FGF13 functions in different neuron subsets" is supported, although somewhat overstated, as the work is not conclusive about the exact neuron subtypes. However, it does indeed show differential functions for specific neuronal classes, which is a significant result.
Impact and Utility
This paper is undoubtedly valuable. Understanding that excitatory neurons are not the primary contributors to the observed phenotypes is crucial. The finding that the effects are not MGE-unique is also important. This work provides a solid foundation for further research and will be a useful resource for future studies.
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Reviewer #1 (Public review):
Summary:
This paper investigates the neural population activity patterns of the medial frontal cortex in rats performing a nose poking timing task using in vivo calcium imaging. The results showed neurons that were active at the beginning and end of the nose poking and neurons that formed sequential patterns of activation that covaried with the timed interval during nose poking on a trial-by-trial basis. The former were not stable across sessions, while the latter tended to remain stable over weeks. The analysis of incorrect trials suggests the shorter non-rewarded intervals were due to errors in the scaling of the sequential pattern of activity.
Strengths:
This study measured stable signals using in vivo calcium imaging during experimental sessions that were separated by many days in animals performing a nose poking timing task. The correlation analysis on the activation profile to separate the cells in the three groups was effective and the functional dissociation between beginning and end, and duration cells was revealing. The analysis on the stability of decoding of both the nose poking state and poking time was very informative. Hence, this study dissected a neural population that formed sequential patterns of activation that encoded timed intervals.
Weaknesses:
It is not clear whether animals had enough simultaneously recorded cells to perform the analyzes of Figures 2-4. In fact, rat 3 had 18 responsive neurons which probably is not enough to get robust neural sequences for the trial-by-trial analysis and the correct and incorrect trial analysis. In addition, the analysis of behavioral errors could be improved. The analysis in Figure 4A could be replaced by a detailed analysis on the speed, and the geometry of neural population trajectories for correct and incorrect trials. In the case of Figure 4G is not clear why the density of errors formed two clusters instead of having a linear relation with the produce duration. I would be recommendable to compute the scaling factor on neuronal population trajectories and single cell activity or the computation of the center of mass to test the type III errors.
Due to the slow time resolution of calcium imaging, it is difficult to perform robust analysis on ramping activity. Therefore, I recommend downplaying the conclusion that: "Together, our data suggest that sequential activity might be a more relevant coding regime than the ramping activity in representing time under physiological conditions."
Comments on revisions:
The authors responded properly to my initial comments. However, I have three additional recommendations for the reviewed manuscript.
First, the paper urgently needs proofreading by a professional English editor. Second, Figure 4 must be divided in 2, it has too many panels and the resolution of the figure is low. Finally, please consider that what is called scaling factor in Figure 4G should be called something like neural sequence position index. A scaling factor in the timing literature implies that the pattern of activation of a cell contracts or expands according to the timed interval.
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Reviewer #2 (Public review):
Summary
Lines et al investigate the integration of sensory-evoked calcium signals in astrocytes of the primary somatosensory cortex in anesthetized mice. More precisely, their goal is to better characterize the mechanisms that govern the emergence of whole-cell events in astrocytes, here referred to as calcium surges. As a single astrocyte communicates with hundreds of thousands of synapses simultaneously, understanding the spatial and temporal integration of calcium signals in astrocytes and the mechanisms governing these phenomena is of tremendous importance to deepen our understanding of signal processing in the central nervous system. In line with previous reports in the field, the authors find that most signals originate in the arborization of astrocytes, occasionally leading to somatic and whole-cell events. On average, the latter occur following domain activity closer to the soma, suggesting a centripetal propagation of signals leading to somatic events. Moreover, they observe that the distance from the soma to active domains increases with time after somatic events, suggesting a potential centrifugal propagation of signals post-somatic activity. The results suggest that most calcium surges depend on the expression of IP3R2, the main calcium channel in astrocytes, located at the membrane of the endoplasmic reticulum. Finally, they report a correlation between the percentage of active domains in the astrocyte "arbor", the emergence of a somatic event, and the frequency of slow inward currents from neighboring neurons. The main claim of this manuscript is that there would be a spatial threshold inherent to astrocytes of ~23% of domain activation above which a calcium surge is observed. Although the study provides data and concepts that are important for the glia field, the conclusions seem a little too assertive and general with respect to what can be deduced from the data and methods used.
Strengths
The major strength of this study is the experimental approach that allowed the authors to obtain numerous and informative calcium recordings in vivo in the somatosensory cortex in mice in response to sensory stimuli as well as in situ. Notably, they developed an interesting approach to modulate the percentage of active domains in the astrocyte arborization by varying the intensity of peripheral stimulation (its amplitude, frequency, or duration). The question investigated is important as the mechanisms governing signal integration in astrocytes and its effect on neighboring cells are poorly understood.
Weaknesses
The major weakness of the manuscript is the method used to analyze and quantify calcium activity, which mostly relies on the analysis of averaged data and overlooks the variability of the signals measured. As a result, the main claims from the manuscript seem to be incompletely supported by the data.
Although the revised version includes more discussion on the experiments that could be done to extend the results from this study, more discussion would be needed to clarify the limitations on what can be deduced from the proposed experimental and analytical design. Notably, the analysis pipeline seems biased by the assumption of the existence of a spatial threshold dictating the emergence of global calcium events in astrocytes. Although there is a clear linear correlation between the percentage of active somas and the percentage of active domains in the arborization (Figure 2 panel F), concluding on the existence of an inherent threshold of domain activity is not completely supported by the data (see e.g. Figure 2 panel F or Figure 4 panel E). It would probably be more accurate to report that most somatic events occur when the percentage of arbor domains being active is above 21-24% (95% confidence interval of the reported threshold). Thus, some of the conclusions from the manuscript, such as p.14 l.34-35 " spatial threshold of domains that needs to be reached in order to lead to soma activation", seem a bit too assertive as some astrocytes did display soma activation with a much smaller percentage of active domains or on the contrary, no somatic event despite domain activity way above the threshold. Similarly, as Figure 6 demonstrates a strong effect of IP3R2 knock-out on somatic activation but reports a non-zero probability of soma activity in IP3R2 -/- mice (panel F), the conclusion that IP3R2 are necessary to trigger an astrocytic calcium surge seems a bit too strong. Finally, the results reported in Figure 7 demonstrate the existence of a strong correlation between SICs, the percentage of active astrocyte domains on, and somatic activation, so that the conclusion "These results indicate that spatial threshold of the astrocyte calcium surge has a functional impact on gliotransmission" (l.4&-48 page 13) also seems a bit too assertive.
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Reviewer #1 (Public review):
Summary:
There is a long-standing idea that choices influence evaluation: options we choose are re-evaluated to be better than they were before the choice. There has been some debate about this finding, and the authors developed several novel methods for detecting these re-evaluations in task designs where options are repeatedly presented against several alternatives. Using these novel methods the authors clearly demonstrate this re-evaluation phenomenon in several existing datasets and show that estimations of dynamic valuation correlate with neural activity in prefrontal cortex.
Strengths:
The paper is well-written and figures are clear. The authors provided evidence for the behaviour effect using several techniques and generated surrogate data (where the ground truth is known) to demonstrate the robustness of their methods. The author avoid over-selling the work, with a lucid description of limitations, and potential for further exploration of the work, in the discussion.
Comments on revisions:
The authors did a good job responding to the comments.
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Reviewer #1 (Public review):
Summary:
The authors investigated if/how distractor suppression derived from statistical learning may be implemented in early visual cortex. While in a scanner, participants conducted a standard additional singleton task in which one location more frequently contained a salient distractor. The results showed that activity in EVC was suppressed for the location of the salient distractor as well as for neighbouring neutral locations. This suppression was not stimulus specific - meaning it occurred equally for distractors, targets and neutral items - and it was even present in trials in which the search display was omitted. Generally, the paper was clear, the experiment was well-designed, and the data are interesting. Nevertheless, I do have several concerns mostly regarding the interpretation of the results.
(1) My biggest concern with the study is regarding the interpretation of some of the results. Specifically, regarding the dynamics of the suppression. I appreciate that there are some limitations with what you might be able to say here given the method but I do feel as if you have committed to a single interpretation where others might still be at play. Below I've listed a few alternatives to consider.
(a) Sustained Suppression. I was wondering if there is anything in your results that would speak for or against the suppression being task specific. That is, is it possible that people are just suppressing the HPDL throughout the entire experiment (i.e., also through ITI, breaks, etc., rather than just before and during the search). Since the suppression does not seem volitional, I wonder if participants might apply a blanket suppression to HPDL until they learn otherwise. Since your localiser comes after the task you might be able to see hints of sustained suppression in the HPDL during these trials.
(b) Enhancement followed by suppression. Another alternative that wasn't discussed would be an initial transient enhancement of the HPDL which might be brought on by the placeholders followed by more sustained suppression through the search task. Of course, on the whole this would look like suppression, but this still seems like it would hold different implications compared to simply "proactive suppression". This would be something like search and destroy however could be on the location level before the actual onset of the search display.
(2) I was also considering whether your effects might be at least partially attributable to priming type effects. This would be on the spatial (not feature) level as it is clear that the distractors are switching colours. Basically, is it possible that on trial n participants see the HPDL with the distractor in it and then on trial n+1 they suppress that location. This would be something distinct from the statistical learning framework and from the repetition suppression discussion you have already included. To test for this, you could look at the trials that follow omission or trials. If there is no suppression or less suppression on these trials it would seem fair to conclude that the suppression is at least in part due to the previous trial.
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Joint Public Review:
In the microglia research community, it is accepted that microglia change their shape both gradually and acutely along a continuum that is influenced by external factors both in their microenvironments and in circulation. Ideally, a given morphological state reflects a functional state that provides insight into a microglia's role in physiological and pathological conditions. The current manuscript introduces MorphoCellSorter, an open-source tool designed for automated morphometric analysis of microglia. This method adds to the many programs and platforms available to assess the characteristics of microglial morphology; however, MorphoCellSorter is unique in that it uses Andrew's plotting to rank populations of cells together (in control and experimental groups) and presents "big picture" views of how entire populations of microglia alter under different conditions. Notably, MorphoCellSorter is versatile, as it can be used across a wide array of imaging techniques and equipment. For example, the authors use MorphoCellSorter on images of fixed and live tissues representing different biological contexts such as embryonic stages, Alzheimer's disease models, stroke, and primary cell cultures.
This manuscript outlines a strategy for efficiently ranking microglia beyond the classical homeostatic vs. active morphological states. The outcome offers only a minor improvement over the already available strategies that have the same challenge: how to interpret the ranking functionally.
Strengths and Weaknesses:
(1) The authors offer an alternative perspective on microglia morphology, exploring the option to rank microglia instead of categorizing them with means of clusterings like k-means, which should better reflect the concept of a microglia morphology continuum. They demonstrate that these ranked representations of morphology can be illustrated using histograms across the entire population, allowing the identification of potential shifts between experimental groups. Although the idea of using Andrews curves is innovative, the distance between ranked morphologies is challenging to measure, raising the question of whether the authors oversimplify the problem. Also, the discussion about the pipeline's uniqueness does not go into the details of alternative models. The introduction remains weak in outlining the limitations of current methods (L90). Acknowledging this limitation will be necessary.
(2) The manuscript suffers from several overstatements and simplifications, which need to be resolved. For example:
a) L40: The authors talk about "accurately ranked cells". Based on their results, the term "accuracy" is still unclear in this context.
b) L50: Microglial processes are not necessarily evenly distributed in the healthy brain. Depending on their embedded environment, they can have longer process extensions (e.g., frontal cortex versus cerebellum).
c) L69: The term "metabolic challenge" is very broad, ranging from glycolysis/FAO switches to ATP-mediated morphological adaptations, and it needs further clarification about the author's intended meaning.
d) L75: Is morphology truly "easy" to obtain?
e) L80: The sentence structure implies that clustering or artificial intelligence (AI) are parameters, which is incorrect. Furthermore, the authors should clarify the term "AI" in their intended context of morphological analysis.
f) L390f: An assumption is made that the contralateral hemisphere is a non-pathological condition. How confident are the authors about this statement? The brain is still exposed to a pathological condition, which does not stop at one brain hemisphere.
(3) Methodological questions:
a) L299: An inversion operation was applied to specific parameters. The description needs to clarify the necessity of this since the PCA does not require it.
b) Different biological samples have been collected across different species (rat, mouse) and disease conditions (stroke, Alzheimer's disease).<br /> Sex is a relevant component in microglia morphology. At first glance, information on sex is missing for several of the samples. The authors should always refer to Table 1 in their manuscript to avoid this confusion. Furthermore, how many biological animals have been analyzed? It would be beneficial for the study to compare different sexes and see how accurate Andrew's ranking would be in ranking differences between males and females. If they have a rationale for choosing one sex, this should be explained.<br /> In the methodology, the slice thickness has been given in a range. Is there a particular reason for this variability? Also, the slice thickness is inadequate to cover the entire microglia morphology. How do the authors include this limitation of their strategy? Did the authors define a cut-off for incomplete microglia?
c) The manuscript outlines that the authors have used different preprocessing pipelines, which is great for being transparent about this process. Yet, it would be relevant to provide a rationale for the different imaging processing and segmentation pipelines and platform usages (Supplementary Figure 7). For example, it is not clear why the Z maximum projection is performed at the end for the Alzheimer's Disease model, while it's done at the beginning of the others. The same holds through for cropping, filter values, etc. Would it be possible to analyze the images with the same pipelines and compare whether a specific pipeline should be preferable to others? On a note, Matlab is not open-access.<br /> This also includes combining the different animals to see which insights could be gained using the proposed pipelines.
d) L227: Performing manual thresholding isn't ideal because it implies the preprocessing could be improved. Additionally, it is important to consider that morphology may vary depending on the thresholding parameters. Comparing different acquisitions that have been binarized using different criteria could introduce biases.
e) Parameter choices:
L375: When using k-means clustering, it is good practice to determine the number of clusters (k) using silhouette or elbow scores. Simply selecting a value of k based on its previous usage in the literature is not rigorous, as the optimal number of clusters depends on the specific data structure. If they are seeking a more objective clustering approach, they could also consider employing other unsupervised techniques, (e.g. HDBSCAN) (L403f).
L373: A rationale for the choice of the 20 non-dimensional parameters as well as a detailed explanation of their computation such as the skeleton process ratio is missing. Also, how strongly correlated are those parameters, and how might this correlation bias the data outcomes? Differences between circularity and roundness factors are not coming across and require further clarification. One is applied to the soma and the other to the cell, but why is neither circularity nor loudness factor applied to both?
f) PCA analysis:
The authors spend a lot of text to describe the basic principles of PCA. PCA is mathematically well-described and does not require such depth in the description and would be sufficient with references. Furthermore, there are the following points that require attention:
L321: PC1 is the most important part of the data could be an incorrect statement because the highest dispersion could be noise, which would not be the most relevant part of the data. Therefore, the term "important" has to be clarified.
L323: As before, it's not given that the first two components hold all the information.
L327 and L331 contain mistakes in the nomenclature: Mix up of "wi" should be "wn" because "i" does not refer to anything. The same for "phi i = arctan(yn/wn)" should be "phi n".
L348: Spearman's correlation measures monotonic correlation, not linear correlation. Either the authors used Pearson Correlation for linearity or Spearman correlation for monotonic. This needs to be clarified to avoid misunderstandings.
g) If the authors find no morphological alteration, how can they ensure that the algorithm is sensitive enough to detect them? When morphologies are similar, it's harder to spot differences. In cases where morphological differences are more apparent, like stroke, classification is more straightforward.
h) Minor aspects:
{section sign} % notation requires to include (weight/volume) annotation.
{section sign} Citation/source of the different mouse lines should be included in the method sections (e.g. L117).
{section sign} L125: The length of the single housing should be specified to ensure no variability in this context.
{section sign} L673: Typo to the reference to the figure.
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Reviewer #1 (Public review):
Summary:
The manuscript presents a significant and rigorous investigation into the role of CHMP5 in regulating bone formation and cellular senescence. The study provides compelling evidence that CHMP5 is essential for maintaining endolysosomal function and controlling mitochondrial ROS levels, thereby preventing the senescence of skeletal progenitor cells.
Strengths:
The authors demonstrate that the deletion of Chmp5 results in endolysosomal dysfunction, elevated mitochondrial ROS, and ultimately enhanced bone formation through both autonomous and paracrine mechanisms. The innovative use of senolytic drugs to ameliorate musculoskeletal abnormalities in Chmp5-deficient mice is a novel and critical finding, suggesting potential therapeutic strategies for musculoskeletal disorders linked to endolysosomal dysfunction.
Weaknesses:
The manuscript requires a deeper discussion or exploration of CHMP5's roles and a more refined analysis of senolytic drug specificity and effects. This would greatly enhance the comprehensiveness and clarity of the manuscript.
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Reviewer #1 (Public review):
Summary:
This manuscript explores the role of the Evening Complex (EC), specifically focusing on ELF3, a disordered protein component of the EC, and its temperature-dependent phase behavior. The study highlights the role of polyQ tracts in modulating temperature-sensitive condensate formation and provides a combination of computational approaches, including REST2 simulations and coarse-grained Martini simulations, to investigate how polyQ tract length and sequence context influence this behavior.
Strengths:
The study addresses a key question in plant biology - how temperature influences circadian clock-mediated growth regulation through protein phase behavior. The manuscript introduces the novel finding that polyQ tract length modulates the temperature-dependent formation of helices and condensates.
Weaknesses:
(1) Coarse-Grained Simulation Results Not Supported by Data:<br /> The results presented in Figure 6A of the manuscript do not seem to show a clear trend in the number of clusters formed as a function of polyQ tract length. This is particularly evident in the comparison between 0Q and 7Q polyQ lengths, which display statistically similar values in terms of the number of clusters. The lack of distinction between these values raises questions about the sensitivity of the coarse-grained simulations to polyQ tract length, which the authors claim as a key modulator of condensate formation. This discrepancy weakens the argument that polyQ length directly impacts the clustering behavior in the simulations.<br /> Suggested Analysis:<br /> - A more detailed statistical analysis should be performed to assess whether the observed differences between polyQ lengths are significant. This could involve hypothesis testing or the use of error bars in the graphs to better communicate the variability in the data.<br /> - Additionally, the authors should examine whether there are other features, such as cluster shape or internal structure, that might differentiate between different polyQ lengths, even if the total number of clusters is similar.
(2) Inconsistency in Cluster Size Across Temperatures (Figure 6B):<br /> The results in Figure 6B show a striking difference in the size of the largest cluster between temperatures of 290K and 300K. This abrupt shift in behavior lacks a clear mechanistic explanation. Typically, phase transitions driven by temperature are more gradual, unless there is some underlying structural or chemical shift that the authors have not accounted for. Without a clear explanation, this sudden change in behavior reduces confidence in the simulation results.<br /> Suggested Analysis:<br /> - The authors should explore possible explanations for the dramatic difference in cluster size between 290K and 300K. For example, they could investigate whether specific interactions (such as the breaking or formation of hydrogen bonds or hydrophobic contacts) might explain the behavior at higher temperatures.<br /> - It is important to check whether the coarse-grained simulation model has been adequately parameterized and scaled for accurate temperature dependence. Atomistic simulations of monomers and dimers with varying polyQ tract lengths could be used to fine-tune the coarse-grained model, ensuring it accurately reflects molecular behavior. The gross estimate of a 10% scaling factor might be insufficient and could lead to inaccurate representations of cluster formation.
(3) Scaling of Coarse-Grained Model with Atomistic Simulations:<br /> As mentioned, the coarse-grained model used in the study may not have been properly scaled against atomistic data. A simple scaling factor of 10% may not be appropriate for accurately capturing the behavior of polyQ tracts across different lengths, especially considering their sensitivity to subtle changes in temperature. Without rigorous validation against atomistic simulations, the coarse-grained model's predictions could be skewed.<br /> Suggested Analysis:
(4) To address this, the authors should compare the coarse-grained model with atomistic simulations of monomeric and dimeric forms of ELF3 with different polyQ tract lengths. By comparing key structural parameters (e.g., radius of gyration, contact maps, and clustering propensity), the authors could adjust the coarse-grained model to more accurately reflect the atomistic behavior. The authors have wealth of atomistic simulation data that could afford such benchmarking and identification of scaling factor<br /> o Additionally, the authors should investigate whether the assumed scaling factor of 10% is appropriate for each polyQ length or whether it needs to be refined based on specific properties, such as the number of hydrophobic interactions or secondary structure stability.
(5) Lack of Analysis for Liquid-Like Behavior in Phase Separation:<br /> The simulations presented in the manuscript do not analyze the liquid-like behavior of ELF3 condensates, which is a key characteristic of liquid-liquid phase separation (LLPS). In LLPS systems, condensates are often dynamic, with chains exchanging between clusters, indicating liquid-like rather than solid-like behavior. The authors fail to probe this crucial aspect, which is necessary to support the claim that ELF3 undergoes phase separation.<br /> Suggested Analysis:<br /> - The authors should conduct additional analyses to probe the liquid-like nature of the clusters formed by ELF3. One approach would be to analyze the dynamics of chain exchange between clusters, measuring how frequently chains leave one cluster and join another over time. This analysis would reveal whether the condensates behave as liquid-like, dynamic structures or more static, solid-like aggregates.<br /> - Additionally, the temperature dependence of these exchange dynamics should be investigated. In true liquid-liquid phase separation, the rate of chain exchange is often sensitive to temperature. Observing how this rate changes between 290K and 300K, for instance, could help explain the abrupt shift in cluster size seen in Figure 6B.<br /> - The authors should also analyze whether the internal structures of the condensates are consistent with a liquid-like phase. For example, radial distribution functions and contact lifetimes could be calculated to reveal whether the clusters exhibit liquid-like organization.
(6) Lack of justification of polydispersity of polyQ:<br /> The authors don't provide any rationale for choice of different copies of polyQ used in the manuscript for their chain-growth simulation studies. It will be more apt if it can be motivated via some precedent experimental observations.
(7) Lack of initiative to connect to Experiments:<br /> While the computational models and simulations provide robust theoretical insights, the absence of direct experimental validation weakens the overall impact of the manuscript. For example, experimental data on how specific mutations in the polyQ tract influence ELF3 behavior in vivo would significantly bolster the authors' claims. The manuscript would benefit from either citing existing experimental studies that corroborate these findings or from suggesting future experimental directions.
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Reviewer #1 (Public review):
(1) Summary of the Paper:
This paper by Chen et al. examines the cellular composition and gene expression of the hypothalamic medial preoptic area (MPOA) in two closely related deer mouse species (P. maniculatus and P. polionotus) that exhibit distinct social behaviors. Through single-nucleus RNA sequencing (snRNA-seq), Chen et al., identify sex- and species-specific neuronal cell types that likely contribute to differences in mating and parental care. By comparing monogamous and promiscuous species, the study provides insights into how neuronal diversity and gene expression changes in the MPOA might underlie the evolution of social behaviors.
(2) Strengths of the Paper:
The paper excels in several areas. First, the data presentation is clear and well-organized, making the complex findings easy to follow. The writing is straightforward and highly accessible, which enhances the overall readability. The experimental design is innovative, particularly in how they combined samples from different species into the same dataset and then used post-hoc identification to distinguish cell types by species. This dramatically controls for potential batch effects in my opinion. Additionally, the authors contextualize their findings within the framework of previously published studies on Mus musculus, providing a strong comparative analysis that enhances the significance of their work.
3) Weaknesses of the Paper:
The major limitation of the study is the absence of causal experiments linking the observed changes in MPOA cell types to species-specific social behaviors. While the study provides valuable correlational data, it lacks functional experiments that would demonstrate a direct relationship between the neuronal differences and behavior. For instance, manipulating these cell types or gene expressions in vivo and observing their effects on behavior would have strengthened the conclusions, although I certainly appreciate the difficulty in this, especially in non-musculus mice. Without such experiments, the study remains speculative about how these neuronal differences contribute to the evolution of social behaviors.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The researchers examined how individuals who were born blind or lost their vision early in life process information, specifically focusing on the decoding of Braille characters. They explored the transition of Braille character information from tactile sensory inputs, based on which hand was used for reading, to perceptual representations that are not dependent on the reading hand.
They identified tactile sensory representations in areas responsible for touch processing and perceptual representations in brain regions typically involved in visual reading, with the lateral occipital complex serving as a pivotal "hinge" region between them.
In terms of temporal information processing, they discovered that tactile sensory representations occur prior to cognitive perceptual representations. The researchers suggest that this pattern indicates that even in situations of significant brain adaptability, there is a consistent chronological progression from sensory to cognitive processing.
Strengths:
By combining fMRI and EEG, and focusing on the diagnostic case of Braille reading, the paper provides an integrated view of the transformation processing from sensation to perception in the visually deprived brain. Such a multimodal approach is still rare in the study of human brain plasticity and allows to discern the nature of information processing in blind people early visual cortex, as well as the timecourse of information processing in a situation of significant brain adaptability.
Weaknesses:
ROI and searchlight analyses are not completely overlapping, although this might be due to the specific limits and strengths of each approach. Moreover, the conclusions regarding the behavioral relevance of the sensory and perceptual representations in the putatively reorganized brain, although important, are limited due to the behavioral measurements adopted.
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Reviewer #1 (Public review):
Summary:
Triple-negative breast cancer (TNBC) accounts for approximately 15-20% of all breast cancers. Compared to other types of breast cancer, TNBC exhibits highly aggressive clinical characteristics, a greater likelihood of metastasis, poorer clinical outcomes, and lower survival rates. Immunotherapy is an important treatment option for TNBC, but there is significant heterogeneity in treatment response. Therefore, it is crucial to accurately identify immunosuppressive patients before treatment and actively seek more effective therapeutic approaches for TNBC patients.
Strengths:
In this work, the authors collected and integrated data from single cells and large volumes of RNA sequencing and RNA-SEQ to analyze the TME landscape mediated by genes associated with iron death. On this basis, the prediction model of prognosis and treatment response of 131 patients was constructed using a machine learning algorithm, which is beneficial to provide individualized and precise treatment guidance for breast cancer patients.
Weaknesses:
However, there are still some issues that need to be clarified:
(1) The description of the research background is too brief and concise, and it is necessary to add some information about the limitations of existing methods and the differences and advantages of this study compared with other published relevant studies, so as to better highlight the necessity and research value of this study.
(2) This study is a retrospective analysis of a public data set and lacks experimental validation and prospective experiments to support the results of bioinformatics analysis. This should be added to the acknowledgment of limitations in the study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public review):
Summary:
Juan Liu et al. investigated the interplay between habitat fragmentation and climate-driven thermophilization in birds in an island system in China. They used extensive bird monitoring data (9 surveys per year per island) across 36 islands of varying size and isolation from the mainland covering 10 years. The authors use extensive modeling frameworks to test a general increase of the occurrence and abundance of warm-dwelling species and vice versa for cold-dwelling species using the widely used Community Temperature Index (CTI), as well the relationship between island fragmentation in terms of island area and isolation from the mainland on extinction and colonization rates of cold- and warm-adapted species. They found that indeed there was thermophilization happening during the last 10 years, which was more pronounced for the CTI based on abundances and less clearly for the occurrence based metric. Generally, the authors show that this is driven by an increased colonization rate of warm-dwelling and an increased extinction rate of cold-dwelling species. Interestingly, they unravel some of the mechanisms behind this dynamic by showing that warm-adapted species increased while cold-dwelling decreased more strongly on smaller islands, which is - according to the authors - due to lowered thermal buffering on smaller islands (which was supported by air temperature monitoring done during the study period on small and large islands). They argue, that the increased extinction rate of cold-adapted species could also be due to lowered habitat heterogeneity on smaller islands. With regards to island isolation, they show that also both thermophilization processes (increase of warm and decrease of cold-adapted species) was stronger on islands closer to the mainland, due to closer sources to species populations of either group on the mainland as compared to limited dispersal (i.e. range shift potential) in more isolated islands.
The conclusions drawn in this study are sound, and mostly well supported by the results. Only few aspects leave open questions and could quite likely be further supported by the authors themselves thanks to their apparent extensive understanding of the study system.
Strengths:
The study questions and hypotheses are very well aligned with the methods used, ranging from field surveys to extensive modeling frameworks, as well as with the conclusions drawn from the results. The study addresses a complex question on the interplay between habitat fragmentation and climate-driven thermophilization which can naturally be affected by a multitude of additional factors than the ones included here. Nevertheless, the authors use a well balanced method of simplifying this to the most important factors in question (CTI change, extinction, colonization, together with habitat fragmentation metrics of isolation and island area). The interpretation of the results presents interesting mechanisms without being too bold on their findings and by providing important links to the existing literature as well as to additional data and analyses presented in the appendix.
Weaknesses:
The metric of island isolation based on distance to the mainland seems a bit too oversimplified as in real-life the study system rather represents an island network where the islands of different sizes are in varying distances to each other, such that smaller islands can potentially draw from the species pools from near-by larger islands too - rather than just from the mainland. Although the authors do explain the reason for this metric, backed up by earlier research, a network approach could be worthwhile exploring in future research done in this system. The fact, that the authors did find a signal of island isolation does support their method, but the variation in responses to this metric could hint on a more complex pattern going on in real-life than was assumed for this study.
Comments on revisions:
I'm happy with the revisions made by the authors.
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Reviewer #1 (Public review):
Summary:
The Avrillon et al. explore the neural control of muscle by decomposing the firing activity of constituent motor units from the grid of surface electromyography (EMG) in the Tibialis (TA) Anterior and Vastus Lateralis (VL) during isometric contractions. The study involves extensive samples of motor units across the broadest range of voluntary contraction intensities up to 80% of MVC. The authors examine rate coding of the population of motor units, which describes the instantaneous firing rate of each motor unit as a function of muscle force. This relationship is characterized by a natural logarithm function that delineates two distinct phases: an initial phase with a steep acceleration in firing rate, particularly pronounced in low-threshold motor units, and a subsequent modest linear increase in firing rate, more significant in high-threshold motor units.
Strengths:
The study makes a significant contribution to the field of neuromuscular physiology by providing a detailed analysis of motor unit behavior during muscle contractions in a few ways.
(1) The significance lies in its comprehensive framework of motor unit activity during isometric contractions in the broad range of intensities, providing insights into the non-linear relationship between the firing rate and the muscle force. The extensive sample of motor units across the pool confirms the observation in animal studies in which the the spinal motoneuron exhibits a discharge consists of the distinct phases in response to synaptic currents, under the influence of persistent inward currents. As such, it is now reasonable to state the human motor units across the pool are also under control of gain modulation via some neuromodulatory effects in addition to synaptic inputs arising from ionotropic effects.<br /> (2) The firing scheme across in the entire motoneuron pool revealed in this study reconciles the discrepancy in firing organization under debate; i.e., whether it is 'onion skin' like or not (Heckman and Enoka 2012). The onion skin like model states that the low threshold motor units discharge higher than high threshold motor units and has been held for long time because the firing behaviors were examined in a partial range of contraction force range due to technical limitations. This reconciliation is crucial because it is fundamental to modelling the organization of motor unit recruitment and rate coding to achieve a desired force generation to advance our understanding of motor control.<br /> (3) The extensive data collection with a novel blind source separation algorithm on the expanded number of channel of surface EMG signal provides a robust dataset that enhances the reliability and validity of findings, setting a new standard for empirical studies in the field. \par<br /> Collectively, this study fills several knowledge gaps in the field and advances our understanding the mechanism underlying the isometric force generation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public review):
Summary:
In this manuscript, Otero-Coronel and colleagues use a combination of acoustic stimuli and electrical stimulation of the tectum to study MSI in the M-cells of adult goldfish. They first perform a necessary piece of groundwork in calibrating tectal stimulation for maximal M-cell MSI, and then characterize this MSI with slightly varying tectal and acoustic inputs. Next, they quantify the magnitude and timing of FFI that each type of input has on the M-cell, finding that both the tectum and the auditory system drive FFI, but that FFI decays more slowly for auditory signals. These are novel results that would be of interest to a broader sensory neuroscience community. By then providing pairs of stimuli separated by 50ms, they assess the ability of the first stimulus to suppress responses to the second, finding that acoustic stimuli strongly suppress subsequent acoustic responses in the M-cell, that they weakly suppress subsequent tectal stimulation, and that tectal stimulation does not appreciably inhibit subsequent stimuli of either type. Finally, they show that M-cell physiology mirrors previously reported behavioural data in which stronger stimuli underwent less integration.
The manuscript is generally well written and clear. The discussion of results is appropriately broad and open-ended. It's a good document. Our major concerns regarding the study's validity are captured in the individual comments below. In terms of impact, the most compelling new observation is the quantification of the FFI from the two sources and the logical extension of these FFI dynamics to M-cell physiology during MSI. It is also nice, but unsurprising, to see that the relationship between stimulus strength that MSI is similar for M-cell physiology to what has previously been shown for behavior. While we find the results interesting, we think that they will be of greatest interest to those specifically interested in M-cell physiology and function.
Strengths:
The methods applied are challenging and appropriate and appear to be well executed. Open questions about the physiological underpinnings of M-cell function are addressed using sound experimental design and methodology, and convincing results are provided that advance our understanding of how two streams of sensory information can interact to control behavior.
Weaknesses:
Our concerns about the manuscript are captured in the following specific comments, which we hope will provide a useful perspective for readers and actionable suggestions for the authors.
Comments relevant to the revised manuscript:
Our general assessment (above) stands unchanged from the original version. All of our comments and concerns about the original manuscript have been addressed except for two, one very minor and one quite important:
Original Comment 1 (Minor):<br /> "Line 124. Direct stimulation of the tectum to drive M-cell-projecting tectal neurons not only bypasses the retina, it also bypasses intra-tectal processing and inputs to the tectum from other sources (notably the thalamus). This is not an issue with the interpretation of the results, but this description gives the (false) impression that bypassing the retina is sufficient to prevent adaptation. Adding a sentence or two to accurately reflect the complexity of the upstream circuitry (beyond the retina) would be welcome."
The authors have replied:<br /> "The reviewer is right in that direct tectal stimulation bypasses all neural processing upstream, not only that produced in the retina and that the tectum does not exclusively process visual information. The revised version now acknowledges (lines 245-252, revised manuscript) the complexity of the system."
We think that this is sufficient to address our concern. Some citations may be in order to underpin the new text.
Original Comment 5 (Major):<br /> Figure 4C and lines 398-410.<br /> "These are beautiful examples of M-cell firing, but the text suggests that they occurred rarely and nowhere close to significantly above events observed from single modalities. We do not see this a valid result to report because there is insufficient evidence that the phenomenon shown is consistent or representative of your data."
The authors have replied:<br /> "Our experimental conditions required anesthesia and paralysis, conditions designed to reduce neuronal firing and suppress motor output. We think it is valuable to report that we still see that simultaneous presentation subthreshold unisensory stimuli can add up to become suprathreshold, paralleling behavioral observations. We do not claim and acknowledge that those examples are representative of our recording conditions, but are likely to be more representative of the multisensory integration process taking place in freely moving fish. The revised manuscript adds context to these example traces to justify their inclusion (lines 420-426)."
We do not feel that this important concern has been addressed. The stats are definitively negative. There is no statistical evidence from these data that multisensory integration is occurring in this assay. The aesthesia, paralysis, and low n may provide explanations for this negative result, but it is still a negative result (p=0.5269). To show two examples of multisensory integration for subthreshold stimuli fits the narrative, but this result is not supported. Examples where individual stimuli caused APs (and combined stimuli did not) also occurred, presumably, and at a rate that is statistically indistinguishable to the examples shown in Figure 5. As such, if results from this assay are going to be in the manuscript, acoustic-only and tectum-only examples should be shown as well, although they would not fit the narrative. To be meaningful, this experiment would have to show that multisensory integration is happening in this circuit. Frustrating though it must be, the experiment has given a negative result to that question.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary
A novel statistical model of neural population activity called the Random Projection model has been recently proposed. Not only is this model accurate, efficient, and scalable, but also is naturally implemented as a shallow neural network. This work proposes a new class of RP model called the reshaped RP model. Inheriting the virtue of the original RP model, the proposed model is more accurate in terms of data fitting and efficient in terms of lower firing rate than the original, as well as compatible with various biological constraints. In particular, the authors have demonstrated that normalizing the total synaptic input in the reshaped model has a homeostatic effect on the firing rates of the neurons, resulting in even more efficient representations with equivalent accuracy. These results suggest that synaptic normalization contributes to synaptic homeostasis as well as efficiency in neural encoding.
Strength
This paper demonstrates that the accuracy and efficiency of the random projection models can be improved by extending the model with reshaped projections. Furthermore, it broadens the applicability of the model under biological constraints of synaptic regularization. It also suggests the advantage of the sparse connectivity structure over the fully connected model for modeling spiking statistics. In summary, this work successfully integrates two different elements, statistical modeling of the spikes and synaptic homeostasis in a single biologically plausible neural network model. The authors logically demonstrate their arguments with clear visual presentations and well-structured text, facilitating an unambiguous understanding for readers.
Discussions
The authors have clearly responded to most of our questions in the revised manuscript and we are happy to recommend publishing the final version of the article as it is. Below, we would like to present some alternative interpretations of the results. These comments are not exclusive with the claims made in the articles; it is rather intended to enhance the understanding of readers by providing additional perspectives.
As summarized above, the main contribution of the work consists of two parts; (1) the reshaped RP model achieved higher performance in explaining the statistics of the spiking activity of cortical neurons with more efficient representations (=lower firing rate), (2) synaptic homeostatic normalization in the reshaped RP model yields even more efficient representations without impairing the fitting performance.
For part (1),<br /> Suppl. Fig. 1B compares reshaped RP models with RP and RP with pruning and replacement (R&P). The better performance of RP with P&R might imply the advantage of pruning over gradient descent in this setting, reflecting the non-convexities of the problem. Alternatively, it might suggest the benefit of the increased number of parameters, since pruning allows the network to explore the broader parameter space during the learning process. This latter view might partially explain the superiority of the reshaped RP model over the original RP model.<br /> It is interesting that the backprop model has higher firing rate than the reshaped model (Fig. 1D). This trend is unchanged when optimization of the neural threshold is also allowed (Supp. Fig. 2A). Since backprop model overperforms reshaped model slightly but robustly, high firing rates in the backprop model might be a genuine feature of the spike statistics.
For part (2),<br /> We note that λ regulates the average firing rate, since maximizing the entropy <-ln p(x)> with a regularization term -λ <\sum _i f(x_i)> results in λ_i = λ for all i in the Boltzmann distribution of eq. 2. Suppl. Fig. 2B could be understood as demonstrating this "homeostatic" effect of λ.<br /> Suppl. Fig. 3 could be interpreted as demonstrating the interaction of two different homeostatic mechanisms: one at the firing-rate level (as regulated by λ) and the other at the synaptic level (as regulated by φ). It shows that the range of synaptic constraints where the fitting performance is not impaired differs by the value of λ. For example, if lambda is small (\lambda = 0.25), synaptic constraint can easily deteriorate the performance; on the other hand, if lambda is large (\lambda = 4), performance remains unchanged under strict synaptic constraint. Considering that practically we are most interested in the regime where the model performs best (λ = 2.0), an advantageous feature of the homeostatic model is that homeostatic constraint is harmless at λ=2.0 for the wide range of constraints.
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Reviewer #1 (Public review):
Summary:
The manuscript presents a short report investigating mismatch responses in the auditory cortex, following previous studies focused on visual cortex. By correlating mouse locomotion speed with acoustic feedback levels, the authors demonstrate excitatory responses in a subset of neurons to halts in expected acoustic feedback. They show a lack of responses to mismatch in he visual modality. A subset of neurons show enhanced mismatch responses when both auditory and visual modalities are coupled to the animal's locomotion.
While the study is well-designed and addresses a timely question, several concerns exist regarding the quantification of animal behavior, potential alternative explanations for recorded signals, correlation between excitatory responses and animal velocity, discrepancies in reported values, and clarity regarding the identity of certain neurons.
Strengths:
(1) Well-designed study addressing a timely question in the field.<br /> (2) Successful transition from previous work focused on visual cortex to auditory cortex, demonstrating generic principles in mismatch responses.<br /> (3) Correlation between mouse locomotion speed and acoustic feedback levels provides evidence for prediction signal in the auditory cortex.<br /> (4) Coupling of visual and auditory feedback show putative multimodal integration in auditory cortex.
Weaknesses:
(1) Lack of quantification of animal behavior upon mismatches, potentially leading to alternative interpretations of recorded signals.<br /> (2) Unclear correlation between excitatory responses and animal velocity during halts, particularly in closed-loop versus playback conditions.<br /> (3) Discrepancies in reported values in a few figure panels raise questions about data consistency and interpretation.<br /> (4) Ambiguity regarding the identity of the [AM+VM] MM neurons.
Comments on revisions:
I am satisfied with all clarifications and additional analyses performed by the authors.<br /> The only concern I have is about changes in running after [AM+VM] mismatches.<br /> The authors reported that they "found no evidence of a change in running speed or pupil diameter following [AM + VM] mismatch (Figures S5A)" (line 197).<br /> Nevertheless, it seems that there is a clear increase in running speed for the [AM+VM] condition (S5A). Could this be more specifically quantified? I am concerned that part of the [AM+VM] could stem from this change in running behavior. Could one factor out the running contribution?
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Reviewer #1 (Public review):
Summary:
This paper is focused on the role of Cadherin Flamingo (Fmi) in cell competition in developing Drosophila tissues. A primary genetic tool is monitoring tissue overgrowths caused by making clones in the eye disc that expression activated Ras (RasV12) and that are depleted for the polarity gene scribble (scrib). The main system that they use is ey-flp, which make continuous clones in the developing eye-antennal disc beginning at the earliest stages of disc development. It should be noted that RasV12, scrib-i (or lgl-i) clones only lead to tumors/overgrowths when generated by continuous clones, which presumably creates a privileged environment that insulates them from competition. Discrete (hs-flp) RasV12, lgl-i clones are in fact out-competed (PMID: 20679206), which is something to bear in mind. They assess the role of fmi in several kinds of winners, and their data support the conclusion that fmi is required for winner status. However, they make the claim that loss of fmi from Myc winners converts them to losers, and the data supporting this conclusion is not compelling.
Strengths:
Fmi has been studied for its role in planar cell polarity, and its potential role in competition is interesting.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Tobón and Moser reveal a remarkable amount of presynaptic diversity in the fundamental Ca dependent exocytosis of synaptic vesicles at the afferent fiber bouton synapse onto the pilar or mediolar sides of single inner hair cells of mice. These are landmark findings with profound implications for understanding acoustic signal encoding and presynaptic mechanisms of synaptic diversity at inner hair cell ribbon synapses. The paper will have an immediate and long-lasting impact in the field of auditory neuroscience.
Main findings: 1) Synaptic delays and jitter of masker responses are significantly shorter (synaptic delay: 1.19 ms) at high SR fibers (pilar) than at low SR fibers (mediolar; 2.57 ms). 2) Masked evoked EPSC are significantly larger in high SR than in low SR. 3) Quantal content and RRP size are 14 vesicles in both high and low SR fibers. 4) Depression is faster in high SR synapses suggesting they have a higher release probability and tighter Ca nanodomain coupling to docked vesicles. 5) Recovery of master-EPSCs from depletion is similar for high and low SR synapses, although there is a slightly faster rate for low SR synapses that have bigger synaptic ribbons, which is very interesting. 6) High SR synapses had larger and more compact (monophasic) sEPSCs, well suited to trigger rapidly and faithfully spikes. 7) High SR synapses exhibit lower voltage (~sound pressure in vivo) dependent thresholds of exocytosis.
Great care was taken to use physiological external pH buffers and physiological external Ca concentrations. Paired recordings were also performed at higher temperatures with IHCs at physiological resting membrane potentials and in more mature animals than previously done for paired recordings. This is extremely challenging because it becomes increasingly difficult to visualize bouton terminals when myelination becomes more prominent in the cochlear afferents. In addition, perforated patch recordings were used in the IHC to preserve its intracellular milieu intact and thus extend the viability of the IHCs. The experiments are tour-de-force and reveal several novel aspects of IHC ribbon synapses. The data set is rich and extensive. The analysis is detailed and compelling.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The study investigates protein-protein interactions (PPIs) within the nuage, a germline-specific organelle essential for piRNA biogenesis in Drosophila melanogaster, using AlphaFold2 to predict interactions among 20 nuage-localizing proteins. The authors identify five novel interaction candidates and experimentally validate three of them, including Spindle-E and Squash, through co-immunoprecipitation assays. They confirm the functional significance of these interactions by disrupting salt bridges at the Spn-E_Squ interface. The study further expands its scope to analyze approximately 430 oogenesis-related proteins, validating three additional interaction pairs. A comprehensive screen of around 12,000 Drosophila proteins for interactions with the key piRNA pathway player, Piwi, identifies 164 potential binding partners. Overall, the research demonstrates that in silico approaches using AlphaFold2 can link bioinformatics predictions with experimental validation, streamlining the identification of novel protein interactions and reducing the reliance on extensive experimental efforts. The manuscript is commendably clear and easy to follow; however, areas for improvement should be addressed to enhance its clarity and rigor.
Major Concerns:
(1) While AlphaFold2 was developed and trained primarily for predicting protein structures and their interactions, applying it to predict protein-protein interactions is an extrapolation of its intended use. This introduces several important considerations and risks. First, it assumes that AlphaFold's accuracy in structure prediction extends to interactions, despite not being explicitly trained for this task. Additionally, the assumption that high-scoring models with structural complementarity imply biologically relevant interactions is not always valid. Experimental validation is essential to address these uncertainties, as over-reliance on computational predictions without such validation can lead to false positives and inaccurate conclusions. The authors should expand on the assumptions, limitations, and risks associated with using AlphaFold2 for predicting protein-protein interactions.
(2) The authors experimentally validated three interactions, out of five predicted interactions, using co-immunoprecipitation (co-IP). They attributed the lack of validation for the other two predictions to the limitations of the co-IP method. However, further clarification on the potential limitations of the co-immunoprecipitation behind the negative results would strengthen the conclusions. While co-IP is a widely used technique, it may not detect weak or transient interactions, which could explain the failure to validate some predictions. Suggesting alternative validation methods such as FRET or mass spectrometry could further substantiate the results. On the other hand, AlphaFold2 predictions are not infallible and may generate false positives, particularly when dealing with structurally plausible but biologically irrelevant interactions. By acknowledging both the potential limitations of co-IP and the possibility of false positives from AlphaFold2, the authors can provide a more balanced interpretation of their findings.
(3) In line 143, the authors state that "This approach identified 13 pairs; seven of these were already known to form complexes, confirming the effectiveness of AlphaFold2 in predicting complex formations (Table 2). The highest pcScore pair was the Zuc homodimer, possibly because AlphaFold2 had learned from Zuc homodimer's crystal structure registered in the database." While the authors mentioned the presence of the Zuc homodimer's crystal structure, they do not provide a systematic bioinformatics analysis to evaluate pairwise sequence identity or check for the presence of existing structures for all the proteins or protein pairs (or their homologs) in databases such as the Protein Data Bank (PDB) or Swiss-Model. Conducting such an analysis is critical, as it significantly impacts the novelty and reliability of AlphaFold2 predictions. For instance, high sequence identity between the query proteins could lead to high-scoring models for biologically irrelevant interactions. Including this information would strengthen the conclusions regarding the accuracy and utility of the predictions.
(4) While the manuscript successfully identifies novel protein interactions, the broader biological significance of these interactions remains underexplored. The manuscript could benefit from elaborating on how these findings may contribute to understanding the piRNA pathway and its implications on germline development, transposon repression, and oogenesis.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Through a series of CRISPR-Cas9 screens, the GPX4 antioxidant pathway was identified as a critical suppressor of cold-induced cell death in hibernator-derived cells. Hamster BHK-21 cells exposed to repeated cold and rewarming cycles revealed five genes (Gpx4, Eefsec, Pstk, Secisbp2, and Sepsecs) as critical components of the GPX4 pathway, which protects against cold-induced ferroptosis. A second screen with continuous cold exposure confirmed the essential role of GPX4 in prolonged cold tolerance. GPX4 knockout lines exhibited complete cell death within four days of cold exposure, and pharmacological inhibition of GPX4 further increased cell death, underscoring the necessity of GPX4's catalytic activity in cold conditions.
An additional CRISPR screen in human cold-sensitive K562 cells identified 176 genes for cold survival. The GPX4 pathway was found to confer significant resistance to cold in hibernators and human cells, with GPX4 loss significantly increasing cold-induced cell death.
Comparing hamster and human GPX4, overexpression of GPX4 in human K562 cells, whether hamster or human GPX4, dramatically improved cold tolerance, while catalytically dead mutants showed no such effect. These findings suggest that GPX4 abundance is a key limiting factor for cold tolerance in human cells, and primary cell types show strong sensitivity to GPX4 loss, highlighting that differences in cold tolerance across species may be due to varying GPX4-mediated protection.
Strengths:
(1) Innovative Approach: The study employs a series of unbiased genome-wide CRISPR-Cas9 screens in both hibernator- and non-hibernator-derived cells to investigate the mechanisms controlling cellular cold tolerance. Notably, this is the first genome-scale CRISPR-Cas9 screen conducted in cells derived from a hibernator, the Syrian hamster.
(2) Identification of the GPX4 Pathway: Identifying glutathione peroxidase 4 (GPX4) as a critical suppressor of cold-induced cell death significantly contributes to the field. Recently, GPX4 was also reported as a potent regulator of cold tolerance through overexpression screening (Sone et al.) in hamsters, which further supports this finding.
(3) Improved Cold Viability Assessment: The study identifies an important technical artifact in using trypan blue to assess cell viability following cold exposure. It reveals that cells stained immediately after cold exposure retain the dye, inaccurately indicating cell death. By introducing a brief rewarming period before viability assessment, the authors significantly improve the accuracy of detecting cold-induced cell death. This refinement in methodology ensures more reliable results and sets a new standard for future research on cold stress in cells.
Weaknesses:
(1) Mechanisms Regulating GPX4 Levels: While the study highlights GPX4 levels as a major determinant of cellular cold tolerance, it does not discuss how these levels are regulated or why they differ between hibernators and non-hibernators. This omission leaves an important aspect of GPX4's role in cold tolerance unexplored.
(2) Generalizability Across Species: Although the study demonstrates the role of GPX4 in several mammalian species, it does not investigate whether this mechanism extends to other vertebrates (e.g., fish and amphibians) that also face cold challenges. This limitation could restrict the broader evolutionary claims made by the study.
(3) Variability in Cold Sensitivity Across Human Cell Lines: The study observes significant variability in cold tolerance among different human cell lines but does not explain these differences clearly. This leaves a key aspect of human cell cold sensitivity insufficiently addressed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This is an important and very well-presented set of experiments following up on prior work from the lab investigating knock-down (KD) of EMC10 in the restoration of neuronal and cognitive deficits in 22q11.2 Del models, including now both human iPSCs and a mouse model in vivo now with ASOs.
The valuable progress in this current manuscript is the development of ASOs, and the proof of efficacy in vivo in mice of the ASO in knock-down of EMC10 and amelioration of in vivo behavioral phenotypes.
The experiments include iPSC studies demonstrating elevations of EMC10 in a solid collection of paired iPSC lines. These studies also provide evidence of manipulation of EMC10 by overexpression and inhibition of miRNAs that exist in the 22q11 interval. The iPSC studies also nicely demonstrate the rescue of impairments with KD of EMC10 in neuronal arborization as well as KCl-induced neuronal activity. The major in vivo contributions reflect an impressive demonstration of the efficacy of two ASOs in vivo on both KD of EMC10 in vivo and through improvement in behavioral abnormalities in the 22q11 mouse in a range of different behaviors, including social behavior and learning behaviors.
Overall, there are many strengths reflected in this study, including in particular the synergy between in vitro studies in human cell models and in vivo studies in the well-characterized mouse model. The experiments are generally rigorously performed, well-powered, and nicely presented. The claims with regard to the mechanisms of EMC10 elevations and the importance of restoration of EMC10 expression to neuronal morphology and behavior are well supported by the data. The work may be further supported in future studies, by investigation of rescue by ASOs of circuit dysfunction in vivo or ex vivo through electrophysiology in the mouse model. Also, in future studies, investigation of the mechanism by which EMC10, an ER protein involved in protein processing, may function in the observed neuronal abnormalities; however, these studies are clearly for future investigations.
The potential impact of the work is found in the potential value of the ASO approach to the treatment of 22q11, or the pre-clinical evidence that knock-down of this protein may lead to some amelioration of cognitive symptoms. Overall, a very convincing and complementary set of experiments to support EMC10 KD as a therapeutic strategy.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Chang and colleagues used tetrode recordings in behaving rats to study how learning an audiovisual discrimination task shapes multisensory interactions in the auditory cortex. They found that a significant fraction of neurons in the auditory cortex responded to visual (crossmodal) and audiovisual stimuli. Both auditory-responsive and visually-responsive neurons preferentially responded to the cue signaling the contralateral choice in the two-alternative forced choice task. Importantly, multisensory interactions were similarly specific for the congruent audiovisual pairing for the contralateral side.
Strengths:
The experiments were conducted in a rigorous manner. Particularly thorough are the comparisons across cohorts of rats trained in a control task, in a unisensory auditory discrimination task, and the multisensory task, while also varying the recording hemisphere and behavioral state (engaged vs. anesthesia). The resulting contrasts strengthen the authors' findings and rule out important alternative explanations. Through the comparisons, they show that the enhancements of multisensory responses in the auditory cortex are specific to the paired audiovisual stimulus and specific to contralateral choices in correct trials and thus dependent on learned associations in a task-engaged state.
Weaknesses:
The main result is that multisensory interactions are specific for contralateral paired audiovisual stimuli, which is consistent across experiments and interpretable as a learned task-dependent effect. However, the alternative interpretation of behavioral signals is crucial to rule out, which would also be specific to contralateral, correct trials in trained animals. Although the authors focus on the first 150 ms after cue onset, some of the temporal profiles of activity suggest that choice-related activity could confound some of the results.
The auditory stimuli appear to be encoded by short transient activity (in line with much of what we know about the auditory system), likely with onset latencies (not reported) of 15-30 ms. Stimulus identity can be decoded (Figure 2j) apparently with an onset latency around 50-75 ms (only the difference between A and AV groups is reported) and can be decoded near perfectly for an extended time window, without a dip in decoding performance that is observed in the mean activity Figure 2e. The dynamics of the response of the example neurons presented in Figures 2c and d and the average in 2e therefore do not entirely match the population decoding profile in 2j. Population decoding uses the population activity distribution, rather than the mean, so this is not inherently problematic. It suggests however that the stimulus identity can be decoded from later (choice-related?) activity. The dynamics of the population decoding accuracy are in line with the dynamics one could expect based on choice-related activity. Also the results in Figures S2e,f suggest differences between the two learned stimuli can be in the late phase of the response, not in the early phase.
First, it would help to have the same time axis across panels 2,c,d,e,j,k. Second, a careful temporal dissociation of when the central result of multisensory enhancements occurs in time would discriminate better early sensory processing-related effects versus later decision-related modulations.
In the abstract, the authors mention "a unique integration model", "selective multisensory enhancement for specific auditory-visual pairings", and "using this distinct integrative mechanisms". I would strongly recommend that the authors try to phrase their results more concretely, which I believe would benefit many readers, i.e. selective how (which neurons) and specific for which pairings?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors investigate the role of chirping in a species of weakly electric fish. They subject the fish to various scenarios and correlate the production of chirps with many different factors. They find major correlations between the background beat signals (continuously present during any social interactions) or some aspects of social and environmental conditions with the propensity to produce different types of chirps. By analyzing more specifically different aspects of these correlations they conclude that chirping patterns are related to navigation purposes and the need to localize the source of the beat signal (i.e. the location of the conspecific).
The study provides a wealth of interesting observations of behavior and much of this data constitutes a useful dataset to document the patterns of social interactions in these fish. Some data, in particular the high propensity to chirp in cluttered environments, raises interesting questions. Their main hypothesis is a useful addition to the debate on the function of these chirps and is worth being considered and explored further.
After the initial reviewers' comments, the authors performed a welcome revision of the way the results are presented. Overall the study has been improved by the revisions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The manuscript the authors have tried to dissect the functions of Proteasome activator 28γ (PA28γ) which is known to activate proteosomal function in an ATP independent manner. Although there are multiple works that have highlighted the role of this protein in tumour, this study specifically tried to develop a correlate with Complement C1q binding protein (C1QBp) that is associated with immune response and energy homeostasis.
Strengths:
The observations of the authors hint that beyond PA28y association with proteasome, it might also stabilize certain proteins such as C1QBP which influences the energy metabolism.
Weaknesses:
The strength of the work also becomes its main drawback. That is, how PA28y stabilizes C1QBP or how C1QBP elicits its pro-tumourigenic role under PA28y OE.
In most of the experiments the authors have been dependent on the parallel changes in the expression of both the proteins to justify their stabilizing interaction. However, this approach is indirect at best and does not confirm the direct stabilizing effect of this interaction. IP experiments do not indicate direct interaction and have some quality issues. The upregulation of C1QBP might be indirect at best. It is quite possible that PA28y might be degrading some secondary protein/complex which is responsible for C1QBP expression. Since the core idea of the work is PA28y direct interaction with C1QBP stabilizing it, the same should be demonstrated in more convincing manner.
In all of the assays C1QBP has been detected as doublet. However, the expression pattern of the two bands vary depending on the experiment. In some cases the upper band is intensely stained and in some the lower bands. Does C1QBP isoforms exist and whether they are differentially regulated depending on experiment conditions/tissue types?
Problems with the background of the work: Line 76. This statement is far-fetched. There are presently a number of literatures that have dealt with metabolic programming of OSCC including identification of specific metabolites. Moreover, beyond estimation of OCR, the authors have not conducted any experiments related to metabolism. In the Introduction, significance of this study and how it will extend our understanding of OSCC needs to be elaborated.
Review of Revised Version:
Although the authors have partly corrected the manuscript by removing the mislabeling in their Co-IP experiments, my primary concern on the actual functional connotations and direct interaction between PA28y and C1QBP still remains unaddressed. As already mentioned in my previous review, since the core idea of the work is PA28y's direct interaction with C1QBP, stabilizing it, the same should be demonstrated in a more convincing manner.
My other observation on the detection of C1QBP as a doublet has been addressed by usage of anti-C1QBP Monoclonal antibody against the polyclonal one used before. C1QBP doublets have not been observed in the present case.
The authors have also worked on the presentation of the background by suitably modifying the statements and incorporating appropriate citations.
However, the authors are requested to follow the recommendations provided to them by the reviewers to address the major concerns.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript by Poltavski and colleagues describes the discovery of previously unreported enteric neural crest-derived cells (ENCDC) which are marked by Pax2 and originating from the Placodes. By creating multiple conditional mouse mutants, the authors demonstrate these cells are a distinct population from the previously reported ENCDCs which originate from the Vagal neural crest cells and express Wnt1.
These Pax2-positive ENCDCs are affected due to the loss of both Ret and Ednrb highlighting that these cells are also ultimately part of the canonical processes governing ENCDC and enteric nervous system (ENS) development. The authors also make explant cultures from the mouse GI tract to detect how Ednrb signaling is important for Ret signaling pathways in these cells and rediscovers the interactions between these 2 pathways. One important observation the authors make is that CGRP-positive neurons in the adult distal colon seem to be primarily derived from these Pax2-positive ENCDCs, which are significantly reduced in the Ednrb mutants, thus highlighting the role of Ednrb in maintaining this neuronal type.
Comments on latest version:
Author response: We disagree that the datasets from previous studies provide additional insights that are relevant to the current study. It must be appreciated that Wnt1Cre and Pax2Cre are genetic lineage tracers and that migratory ENS progenitor cells labeled with these reagents do not maintain expression of Wnt1 and Pax2 mRNA or protein. The Wnt1 and Pax2 genes are only transiently expressed within their distinct regions of the ectoderm, and their expression turns off as cells delaminate and begin migration. Thus, Pax2Cre-labeled ENS progenitor cells are not Pax2-positive thereafter. The single cell RNA-Seq studies suggested by the reviewer were collected from older embryos and postnatal mice, and do not represent the E10.5-E11.5 period that accounts for genesis of Ret-mediated and Ednrb-mediated Hirschsprung disease pathology. Even with the most recent work by Zhou et al (Dev Cell, 2024) that included E10.5 cells, this analysis only evaluated neural crest-derived Sox10Cre lineage cells, which does not include the placode-derived Pax2Cre lineage (as we show explicitly in Fig. 2-figure supplement 2). Consequently, it would not be possible to find the "Pax2-positive cells" in these datasets. Performing a new transcriptomic analysis by isolating Pax2Cre-lineage and Wnt1Cre-lineage cells at the appropriate developmental time points could be the basis of future studies, but we think these are beyond the scope of the present paper.
Reviewer comment: Since these cells are a completely new discovery, additional validation would be beneficial. Whole early GI tract datasets are available, such as human 6-week fetal gut data (PMID: 29802404) and whole mouse embryo studies spanning development that include ENS (PMID: 38355799). If the authors believe that none of these existing datasets can detect these cells in their developmental state and that targeted cell studies with specific Cre drivers would be required, they should make this explicitly clear.
A key advantage of discovering a new cell type, particularly in the relatively understudied field of ENS, is the opportunity for the broader community to leverage this finding to inform their own research. If these cells are absent from current datasets, even those covering the whole GI tract, this should be clearly communicated.
I aim to support the authors here. New discoveries in science require robust validation to enhance their impact. The authors have generated an important reagent with great potential for broader use, and addressing these straightforward requests would strengthen the study and make it more valuable to the scientific community.
Author response: The observation that human mutations in RET and EDNRB both cause Hirschsprung disease is decades old, and of course numerous studies in human, mouse, and cells have addressed the relation between the two signaling pathways. We did not mean to imply that we were the first to discover that Ret and Ednrb signaling pathways interact. The reviewer cites a number of papers all from the Chakravarti lab that address this phenomenon; while these are a valuable contribution to the field, there is still more to be learned. The model elaborated in PMID: 31313802, in which Ret and Ednrb are both enmeshed in a common gene regulatory network, does not readily explain why each has a different phenotypic manifestation and doesn't take into account the importance of the placodal lineage. The main new contributions of our paper are the existence of a new cell lineage that contributes to the ENS, and that the placodal and neural crest lineages utilize Ret and Ednrb signaling differently. The clarification of how these elements are differentially used by the two lineages explains long-segment and short-segment Hirschsprung disease (Ret and Ednrb mutants, respectively) far better than in past studies. The reviewer unfortunately dismisses these insights and seems to feel that a biochemical exploration of one specific component of the signaling interaction (Y1015 phosphorylation) would be more relevant. This should be the basis of future studies and are beyond the scope of the new findings reported in the present paper
Reviewer comment: The authors completely miss the point. There is no association between phenotypic severity (L-HSCR, S-HSCR, or TCA) and mutations in a given gene in HSCR. EDNRB, for example, has a syndromic association with Waardenburg-Shah syndrome (WS4-A), which includes pigmentation anomalies due to EDNRB expression in neural crest cells that give rise to pigment cells.
The authors' discovery reinforces the current paradigm that nearly all HSCR is mediated by mutations in genes within the GRN, accounting for 72% of the population attributable risk. This is valuable; reinforcing established paradigms with new data is crucial, and the authors should appreciate the significance of this contribution.
The discovery of the signaling interaction is particularly important, as it offers a potential explanation for disease severity and provides a basis for classifying patients in future sequencing studies. It is surprising that the authors seem reluctant to highlight this novel finding, as it could greatly benefit future research, including the development of specific mouse mutants and advancing human genetics studies.
Author response: The reviewer overlooked that one of the review articles that we cited (Chen, Hsu, & Hung, 2020) has a dedicated paragraph for RET (section 3.14), which summarizes the work by Barheri-Yarmand et al (PMID: 25795775) which is the very paper noted by the reviewer in the comment above. The reviewer also somewhat misstated the results of the Barheri-Yarmand et al study. By immunostaining, this paper showed nuclear localization of endogenous Ret, albeit a version of Ret with a disease-associated mutation that makes it constitutively active by constitutive autophosphorylation. Nonetheless, this was endogenous Ret. The paper also used overexpression of GFP-tagged RET in HEK293 cells to show that wildtype RET can behave in a similar manner, at least under these circumstances. Our point is simply that Ret (and other receptor tyrosine kinases) can be found in the nucleus in certain biological contexts, and our observations are consistent with this precedent. The reviewer also suggests a biochemical follow-up analysis related to this observation, which we agree would be of interest. Such an investigation however is beyond the scope of the present study.
Reviewer comment: As the authors themselves now highlight from the cited paper that any evidence of RET entering the nucleus is of a mutant RET protein, How does this align with their discovery for wildtype protein?
This finding of nuclear localization of RET is both intriguing and unprecedented. Despite extensive biochemical studies on RET, given its role as an oncogene, this feature has not been identified before. If validated, this discovery could significantly advance the field and improve interpretation of future studies. I reiterate my previous point: a novel finding that challenges the current paradigm requires additional evidence.
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Reviewer #1 (Public review):
The manuscript describes comprehensive structure-function studies combining structural studies, Alphafold2-based modelling, and extensive structural validation by mutagenesis and biochemical experiments. Consequently, a sophisticated activation mechanism of Mical1 as a representative of the MICAL family is elucidated at the molecular level. Since MICAL proteins are important regulators of membrane trafficking and cytoskeleton dynamics, the study is of high relevance for many groups. Structural data are of high quality, the modelling data appear to be sound, and the subsequent biochemical analyses are carried out in great detail, yielding a complete story. I have little to criticize on this beautiful work.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
The manuscript "Osterix Facilitates Osteocytic Communication by Targeting Connexin43" investigates the role of Osterix (Osx) in osteocytes using a Col1α1-CreER;Osxfl/fl mouse model and cultured cells. The study reveals that Osx is expressed in osteocytes, and its deletion in vitro leads to a significant reduction in osteocyte dendrite formation, highlighting its critical role in maintaining cellular communication. Through ChIP-seq analysis, the authors identified Connexin43 (Cx43) as a direct downstream target of Osx. Moreover, treatment with all-trans retinoic acid (ATRA), a known agonist of Cx43, was able to rescue the dendritic network in osteocytes, restoring their communication capabilities in vitro.
This research provides valuable insights into the molecular mechanisms by which Osx influences osteocyte function, particularly through its regulation of Cx43. However, despite these findings, the study does not fully elucidate all the mechanisms involved in Osx-mediated osteocytic communication. Several conclusions, particularly those related to the broader signaling pathways, require additional experimental evidence and further investigation to be fully substantiated. This study provides a new aspect in understanding the complex role of Osx in bone biology but leaves open questions regarding the intricacies of its regulatory network.
Major Comments:
(1) In the Col1a1-CreER;tdTomato mice, the number of tdTomato+ cells in the cortical bone appears lower compared to Osx+ cells. The overlap between tdTomato+ and Osx+ cells in Figure 1 is limited. Could this affect the knockout efficiency? Can the authors provide data on Osx knockout efficiency in vivo? While immunostaining of Osx is shown in both control and mutant mice in Figure 2A, the Osx expression pattern differs from Figure 1A. Osx expression is relatively low in the bone marrow in Figure 1A, but much stronger in Figure 2A.
Additionally, Osx+ cells in Figure 1A seem confined to the bone surface, whereas Figure 2A shows a broader distribution. What developmental stage of mice was used in Figure 1? Could the authors also provide co-staining with other osteocyte markers alongside Osx?
(2) The authors mentioned using both siRNA and Lenti-Osx to modulate Osx expression. What was the specific purpose of these experiments? If the authors aim to demonstrate that Osx plays a critical role in osteocytes, they should provide data on downstream targets or markers relevant to osteocyte function. Additionally, did these treatments affect processes like differentiation or cell viability in osteocytes? The current results only demonstrate that siRNA and Lenti-Osx can successfully modulate Osx expression in vitro, but further evidence is needed to support broader functional conclusions.
(3) Osx knockout mice exhibited a decreased osteocyte dendritic network both in vivo and in vitro. To better understand how this affects overall bone health, could the authors provide additional parameters, such as bone thickness, bone strength, and other relevant metrics? Furthermore, to determine whether these phenotypes are primarily due to defects in the osteocyte dendritic network or a reduction in osteocyte numbers, the authors should also assess the number of osteocytes in the knockout mice Figure 2.
(4) Regarding the Lucifer Yellow Dye Transfer Assay in Figure 3, the authors should provide data on cell density and cell viability for both control and mutant groups. Additionally, although less dye is observed in the mutant group, the migration distance appears comparable to the control group. Could the authors explain this result? Furthermore, how was transmission speed between the groups evaluated in Figure 3D? More details on the method used to assess transmission speed would be helpful.
(5) For a more comprehensive and unbiased analysis of Osx function in osteocytes, the authors should present a full analysis of differentially expressed genes, rather than focusing solely on integrins. Additionally, it would be beneficial to include an analysis of the knockdown group alongside the other groups, considering the animal model used in this study involves knockout mice.
(6) In the immunofluorescence staining of integrin αvβ1 in the si-Osx and Lenti-Osx groups, the cellular localization of integrin αvβ1 appears altered. Unlike the control group, where it is mainly localized in the cytoplasm, positive signals are observed in the nucleus of the si-Osx and Lenti-Osx groups. Additionally, since integrin αvβ1 is a membrane protein, shouldn't it primarily be observed on the cell membrane rather than in the cytoplasm? Could the authors clarify this observation?
(7) The results regarding Cx43 expression after Lenti-Osx treatment are questionable. It appears that the images for the Lenti-GFP and Lenti-Osx groups have been misrepresented. The merged images for the Lenti-GFP control group seem to belong to the Lenti-Osx group, and vice versa. If the images were presented in their correct order, the conclusions would contradict the authors' claims. This issue needs to be addressed to ensure an accurate interpretation of the data.
(8) The authors demonstrated that ATRA treatment elevates Cx43 protein levels in the control group, where Osx function is normal. However, can ATRA also restore Cx43 protein levels in the si-Osx treated group, where Osx transcriptional function is impaired? Theoretically, Cx43 protein levels should not be restored in the si-Osx group. Could the observed rescue phenotype be due to effects downstream of Cx43? This possibility should be considered and clarified.
(9) Does the Cx43 mutation of knockout cause similar phenotypes in the animal model? Can restoration of Cx43 rescue the bone phenotype?
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public review):
Summary:
In this manuscript, Yan and colleagues introduce a modification to the previously published PETRI-seq bacterial single cell protocol to include a ribosomal depletion step based on a DNA probe set that selectively hybridizes with ribosome-derived (rRNA) cDNA fragments. They show that their modification of the PETRI-seq protocol increases the fraction of informative non-rRNA reads from ~4-10% to 54-92%. The authors apply their protocol to investigating heterogeneity in a biofilm model of E. coli, and convincingly show how their technology can detect minority subpopulations within a complex community.
Strengths:
The method the authors propose is a straightforward and inexpensive modification of an established split-pool single cell RNA-seq protocol that greatly increases its utility, and should be of interest to a wide community working in the field of bacterial single cell RNA-seq.
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Reviewer #1 (Public review):
The revision by Wang et al is a much more clear and readable manuscript than the original version, which I think was a bit too terse and hard to parse. In this version, I think I basically understand all the analyses that the authors undertake and how they argue that those analyses support their conclusions.
The fundamental claim of the manuscript is that rRNA genes experience substitutions much too quickly, given that they are a multi-copy gene system. As clarified by the authors in their response, and as I think is relatively clear in the manuscript, they are collapsing all copies of the rRNA array down. They first quantify polymorphism (in this expanded definition, where polymorphism means variable at a given site across any copy). The authors find elevated levels of heterozygosity in rRNA genes compared to single copy genes, which isn't surprising, given that there is a substantially higher target size; that being said, the increase in polymorphism is smaller than the increase in target size. They then look at substitutions between mouse species and also between human and chimp, and argue that the substitution rate is too fast compared to single copy genes in many cases.
I think that this is an interesting problem and one that obviously occupies some space in the literature. As the authors point out, one possibility for explaining the elevated fixation rate is that there is some kind of positive selection in these putatively non-functional regions. The authors, instead, argue that the elevated rate of evolution is due to neutral homogenizing processes. I'm sympathetic to this argument, I'm a neutralist myself :)
That being said, I find the whole analysis and the connection with the WFH model very strange. As I stated in my previous review, it feels very odd to chalk everything up to variance in reproductive success, rather than explicitly modeling the molecular processes that may lead to the homogenization. For example, the authors bring up gene conversion, and even do a small test of gene conversion. But a force like biased gene conversion is perhaps better modeled as a deterministic force, rather than a stochastic force. Indeed, I think that explicit modeling of mutation dynamics has been very helpful in understanding the role of replicative vs damage-related mutation in humans, as seen in Gao et al (2016) and Spisak et al (2024). I realize, as the authors say in their cover letter, that this is hard! But a major concern with this manuscript is that it's about whether drift can plausibly explain the pattern, but then it's basically impossible to know if it really can, because we have no way to compare the estimated parameters with biophysical or biochemical measurements of the rates of homogenizing forces, because the homogenizing forces are just wrapped up under "variance in reproductive success". I think a much more interesting manuscript would have a more explicit model of homogenizing forces.
I also have some concerns about the data analysis, echoing some concerns of the other reviewer. The biggest issue is that traditional read mapping and SNP calling pipelines for highly duplicated loci don't really make sense. I don't fully understand the variant calling pipeline. The authors state that "All mapping and analysis are performed among individual copies of rRNA genes." which makes it sound like the reads mapping to different copies were somehow deconvolved, which is what you'd need to do to use "normal" variant calling approaches that call look for homozygotes and heterozygotes. But I don't know enough about this literature to understand how they did that and if it makes any sense. If, instead, they called variants against collapsed rRNA copies, then using a standard variant calling approach does not make sense. If you have a variant in 2 out of 100 copies, a standard variant calling algorithm would very likely call that a homozygous ancestral site. Conditional on the variant calls being reasonable, however, I'm basically okay with their use of read counts to estimate "allele frequencies" within individuals.
I have some more minor comments:
(1) In the paragraph starting line 61, the authors say that WF models are unable to handle things like viral epidemics and transposons. I don't think that's really fair: the issue here isn't WF dynamics or not, it's that there is fundamentally evolution on two levels (which is also the case in the rRNA case considered in this manuscript). I certainly agree with the authors that you can't just naively apply standard pop gen theory in these systems, but I think the arrow at the WF model is misaimed, as the real issue is drift and selection on multiple levels.
(2) Line 268-269: The authors argue that the long term rate of evolution in rRNA genes is roughly similar to single copy genes, suggesting not a big influence of increased mutation rate. I'm not sure I understand where this number comes from, as opposed to the divergence numbers they look at in Table 3. These seem to be two different conclusions from roughly the same measurement? Surely I am misunderstanding something.
References:
Gao, Z., Wyman, M. J., Sella, G., & Przeworski, M. (2016). Interpreting the dependence of mutation rates on age and time. PLoS biology, 14(1), e1002355.
Spisak, N., de Manuel, M., Milligan, W., Sella, G., & Przeworski, M. (2024). The clock-like accumulation of germline and somatic mutations can arise from the interplay of DNA damage and repair. PLoS biology, 22(6), e3002678.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors set out to measure the diffusion of small drug molecules inside live cells. To do this, they selected a range of fluorescent drugs, as well as some commonly used dyes, and used FRAP to quantify their diffusion. The authors find that drugs diffuse and localize within the cell in a way that is weakly correlated with their charge, with positively charged molecules displaying dramatically slower diffusion and a high degree of subcellular localization.
The study is important because it points to an important issue related to the way drugs behave inside cells beyond the simple "IC50" metric (a decidedly mesoscopic/systemic value). The authors conclude, and I agree, that their results point to nuanced effects that are governed by drug chemistry that could be optimized to make them more effective.
Strengths:
(1) The work examines an understudied aspect of drug delivery.
(2) The work uses well-established methodologies to measure diffusion in cells
(3) The work provides an extensive dataset, covering a range of chemistries that are common in small molecule drug design
(4) The authors consider several explanations as to the origin of changes in cellular diffusion
Comments on revised version:
In general, my comments were addressed, new discussions were added, and the paper has been improved significantly, which is great.
However, despite providing very clear instructions, a lot of my comments re statistical treatment were disregarded. Bar charts still do not show the repeats as individual points. Errors bars still represent SEM, which gives a wrong idea about the spread of the data. FRAP lines are still averages, and still do not show the spread of the data.
Significance assignments are done based on average and SEMs, as opposed to the full dataset. There is nothing technically wrong with this, but it generally creates an impression that things are more reproducible/rigorous/significant than they would be if the data was shown completely.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This manuscript by Shan, Guo, Zhang, Chen et al., shows a raft of interesting data including the first cryo-EM structures of human PIEZO1. Clearly the molecular basis of PIEZO channel inactivation is of great interest and as such this manuscript provides some valuable extra information that may help to ultimately build a molecular picture of PIEZO channel inactivation. However, the current manuscript though does not provide any compelling evidence for a detailed mechanism of PIEZO inactivation.
Strengths:
This manuscript documents the first cryo-EM structures of human PIEZO1 and gain of function mutants associated with hereditary anaemia. It is also the first evidence showing that PIEZO1 gain of function mutants are also regulated by the auxiliary subunit MDFIC.
Weaknesses:
While the structures are interesting and clear differences can be seen in the presence of the auxiliary subunit MDFIC the major conclusions and central tenets of the paper, especially a role for pore lipids in inactivation, lack data to support them. The post translational modification of PIEZOs auxiliary subunit MDFIC is not modelled as a covalent interaction.
Comments on revisions:
The revisions do absolutely nothing to allay any of the major concerns documented in my initial review of this manuscript.
(1) Mouse vs Human inactivation<br /> Not only is a quantification not provided the literature on this point is still not at all referenced or discussed.<br /> (2) MDFIC -lipidation<br /> Even if they are not assigned in the PDB for illustration they can at least be modelled correctly as covalently bound acyl chains.<br /> (3) Pore lipids and inactivation<br /> None of the explanations are consistent with the data shown.<br /> (4) Cytosolic plug<br /> There is not even any extra discussion provided on this point.<br /> (5) Reduced sensitivity of PIEZO1 in the presence of MDFIC and its regulatory mechanism<br /> No quantification is provided.<br /> (6) Both referencing of the PIEZO1 literature and prose could be improved.<br /> There is little to no attempt to improve the referencing.
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Reviewer #1 (Public review):
Summary:
Mehmet Mahsum Kaplan et al. demonstrate that Meis2 expression in neural crest-derived mesenchymal cells is crucial for whisker follicle (WF) development, as WF fails to develop in wnt1-Cre;Meis2 cKO mice. Advanced imaging techniques effectively support the idea that Meis2 is essential for proper WF development and that nerves, while affected in Meis2 cKO, are dispensable for WF development and not the primary cause of WF developmental failure. The study also reveals that although Meis2 significantly downregulates Foxd1 in the mesenchyme, this is not the main reason for WF development failure. The paper presents valuable data on the role of mesenchymal Meis2 in WF development. However, further quantification and analysis of the WF developmental phenotype would be beneficial in strengthening the claim that Meis2 controls early WF development rather than causing a delay or arrest in development. A deeper sequencing data analysis could also help link Meis2 to its downstream targets that directly impact the epithelial compartment.
Strengths:
(1) The authors describe a novel molecular mechanism involving Mesenchymal Meis2 expression, which plays a crucial role in early WF development.
(2) They employ multiple advanced imaging techniques to illustrate their findings beautifully.
(3) The study clearly shows that nerves are not essential for WF development.
Weaknesses:
(1) The authors claim that Meis2 acts very early during development, as evidenced by a significant reduction in EDAR expression, one of the earliest markers of placode development. While EDAR is indeed absent from the lower panel in Figure 3C of the Meis2 cKO, multiple placodes still express EDAR in the upper two panels of the Meis2 cKO. The authors also present subsequent analysis at E13.3, showing one escaped follicle positive for SHH and Sox9 in Figures 1 and 3. Does this suggest that follicles are specified but fail to develop? Alternatively, could there be a delay in follicle formation? The increase in Foxd1 expression between E12.5 and E13.5 might also indicate delayed follicle development, or as the authors suggest, follicles that have escaped the phenotype. The paper would significantly benefit from robust quantification to accompany their visual data, specifically quantifying EDAR, Sox9, and Foxd1 at different developmental stages. Additionally, analyzing later developmental stages could help distinguish between a delay or arrest in WF development and a complete failure to specify placodes.
(2) The authors show that single-cell sequencing reveals a reduction in the pre-DC population, reduced proliferation, and changes in cell adhesion and ECM. However, these changes appear to affect most mesenchymal cells, not just pre-DCs. Moreover, since E12.5 already contains WFs at different stages of development, as well as pre-DCs and DCs, it becomes challenging to connect these mesenchymal changes directly to WF development. Did the authors attempt to re-cluster only Cluster 2 to determine if a specific subpopulation is missing in Meis2 cKO? Alternatively, focusing on additional secreted molecules whose expression is disrupted across different clusters in Meis2 cKO could provide insights, especially since mesenchymal-epithelial communication is often mediated through secreted molecules. Did the authors include epithelial cells in the single-cell sequencing, can they look for changes in mesenchyme-epithelial cell interactions (Cell Chat) to indicate a possible mechanism?
(3) The authors aim to link Meis2 expression in the mesenchyme with epithelial Wnt signaling by analyzing Lef1, bat-gal, Axin1, and Wnt10b expression. However, the changes described in the figures are unclear, and the phenotype appears highly variable, making it difficult to establish a connection between Meis2 and Wnt signaling. For instance, some follicles and pre-condensates are Lef1 positive in Meis2 cKO. Including quantification or providing a clearer explanation could help clarify the relationship between mesenchymal Meis2 and Wnt signaling in both epidermal and mesenchymal cells. Did the authors include epithelial cells in the sequencing? Could they use single-cell analysis to demonstrate changes in Wnt signaling?
(4) Existing literature, including studies on Neurog KO and NGF KO, as well as the references cited by the authors, suggest that nerves are unlikely to mediate WF development. While the authors conduct a thorough analysis of WF development in Neurog KO, further supporting this notion, this point may not be central to the current work. Additionally, the claim that Meis2 influences trigeminal nerve patterning requires further analysis and quantification for validation.
(5) Meis2 expression seems reduced but has not entirely disappeared from the mesenchyme. Can the authors provide quantification?
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Yan and colleagues introduce a modification to the previously published PETRI-seq bacterial single-cell protocol to include a ribosomal depletion step based on a DNA probe set that selectively hybridizes with ribosome-derived (rRNA) cDNA fragments. They show that their modification of the PETRI-seq protocol increases the fraction of informative non-rRNA reads from ~4-10% to 54-92%. The authors apply their protocol to investigating heterogeneity in a biofilm model of E. coli, and convincingly show how their technology can detect minority subpopulations within a complex community.
Strengths:
The method the authors propose is a straightforward and inexpensive modification of an established split-pool single-cell RNA-seq protocol that greatly increases its utility, and should be of interest to a wide community working in the field of bacterial single-cell RNA-seq.
Weaknesses:
The manuscript is written in a very compressed style and many technical details of the evaluations conducted are unclear and processed data has not been made available for evaluation, limiting the ability of the reader to independently judge the merits of the method.
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Reviewer #1 (Public review):
Summary:
In this study, the authors address whether the dorsal nucleus of the inferior colliculus (DCIC) in mice encodes sound source location within the front horizontal plane (i.e., azimuth). They do this using volumetric two-photon Ca2+ imaging and high-density silicon probes (Neuropixels) to collect single-unit data. Such recordings are beneficial because they allow large populations of simultaneous neural data to be collected. Their main results and the claims about those results are the following:
(1) DCIC single-unit responses have high trial-to-trial variability (i.e., neural noise);<br /> (2) approximately 32% to 40% of DCIC single units have responses that are sensitive to sound source azimuth;<br /> (3) single-trial population responses (i.e., the joint response across all sampled single units in an animal) encode sound source azimuth "effectively" (as stated in the title) in that localization decoding error matches average mouse discrimination thresholds;<br /> (4) DCIC can encode sound source azimuth in a similar format to that in the central nucleus of the inferior colliculus (as stated in the Abstract);<br /> (5) evidence of noise correlation between pairs of neurons exists;<br /> and 6) noise correlations between responses of neurons help reduce population decoding error.<br /> While simultaneous recordings are not necessary to demonstrate results #1, #2, and #4, they are necessary to demonstrate results #3, #5, and #6.
Strengths:
- Important research question to all researchers interested in sensory coding in the nervous system.<br /> - State-of-the-art data collection: volumetric two-photon Ca2+ imaging and extracellular recording using high-density probes. Large neuronal data sets.<br /> - Confirmation of imaging results (lower temporal resolution) with more traditional microelectrode results (higher temporal resolution).<br /> - Clear and appropriate explanation of surgical and electrophysiological methods. I cannot comment on the appropriateness of the imaging methods.
Strength of evidence for the claims of the study:
(1) DCIC single-unit responses have high trial-to-trial variability -<br /> The authors' data clearly shows this.
(2) Approximately 32% to 40% of DCIC single units have responses that are sensitive to sound source azimuth -<br /> The sensitivity of each neuron's response to sound source azimuth was tested with a Kruskal-Wallis test, which is appropriate since response distributions were not normal. Using this statistical test, only 8% of neurons (median for imaging data) were found to be sensitive to azimuth, and the authors noted this was not significantly different than the false positive rate. The Kruskal-Wallis test was not reported for electrophysiological data. The authors suggested that low numbers of azimuth-sensitive units resulting from the statistical analysis may be due to the combination of high neural noise and a relatively low number of trials, which would reduce the statistical power of the test. This is likely true and highlights a weakness in the experimental design (i.e., a relatively small number of trials). The authors went on to perform a second test of azimuth sensitivity-a chi-squared test-and found 32% (imaging) and 40% (e-phys) of single units to have statistically significant sensitivity. However, the use of a chi-squared test is questionable because it is meant to be used between two categorical variables, and neural response had to be binned before applying the test.
(3) Single-trial population responses encode sound source azimuth "effectively" in that localization decoding error matches average mouse discrimination thresholds -<br /> If only one neuron in a population had responses that were sensitive to azimuth, we would expect that decoding azimuth from observation of that one neuron's response would perform better than chance. By observing the responses of more than one neuron (if more than one were sensitive to azimuth), we would expect performance to increase. The authors found that decoding from the whole population response was no better than chance. They argue (reasonably) that this is because of overfitting of the decoder model-too few trials were used to fit too many parameters-and provide evidence from decoding combined with principal components analysis which suggests that overfitting is occurring. What is troubling is the performance of the decoder when using only a handful of "top-ranked" neurons (in terms of azimuth sensitivity) (Fig. 4F and G). Decoder performance seems to increase when going from one to two neurons, then decreases when going from two to three neurons, and doesn't get much better for more neurons than for one neuron alone. It seems likely there is more information about azimuth in the population response, but decoder performance is not able to capture it because spike count distributions in the decoder model are not being accurately estimated due to too few stimulus trials (14, on average). In other words, it seems likely that decoder performance is underestimating the ability of the DCIC population to encode sound source azimuth.
To get a sense of how effective a neural population is at coding a particular stimulus parameter, it is useful to compare population decoder performance to psychophysical performance. Unfortunately, mouse behavioral localization data do not exist. Instead, the authors compare decoder error to mouse left-right discrimination thresholds published previously by a different lab. However, this comparison is inappropriate because the decoder and the mice were performing different perceptual tasks. The decoder is classifying sound sources to 1 of 13 locations from left to right, whereas the mice were discriminating between left or right sources centered around zero degrees. The errors in these two tasks represent different things. The two data sets may potentially be more accurately compared by extracting information from the confusion matrices of population decoder performance. For example, when the stimulus was at -30 deg, how often did the decoder classify the stimulus to a lefthand azimuth? Likewise, when the stimulus was +30 deg, how often did the decoder classify the stimulus to a righthand azimuth?
(4) DCIC can encode sound source azimuth in a similar format to that in the central nucleus of the inferior colliculus -<br /> It is unclear what exactly the authors mean by this statement in the Abstract. There are major differences in the encoding of azimuth between the two neighboring brain areas: a large majority of neurons in the CNIC are sensitive to azimuth (and strongly so), whereas the present study shows a minority of azimuth-sensitive neurons in the DCIC. Furthermore, CNIC neurons fire reliably to sound stimuli (low neural noise), whereas the present study shows that DCIC neurons fire more erratically (high neural noise).
(5) Evidence of noise correlation between pairs of neurons exists -<br /> The authors' data and analyses seem appropriate and sufficient to justify this claim.
(6) Noise correlations between responses of neurons help reduce population decoding error -<br /> The authors show convincing analysis that performance of their decoder increased when simultaneously measured responses were tested (which include noise correlation) than when scrambled-trial responses were tested (eliminating noise correlation). This makes it seem likely that noise correlation in the responses improved decoder performance. The authors mention that the naïve Bayesian classifier was used as their decoder for computational efficiency, presumably because it assumes no noise correlation and, therefore, assumes responses of individual neurons are independent of each other across trials to the same stimulus. The use of a decoder that assumes independence seems key here in testing the hypothesis that noise correlation contains information about sound source azimuth. The logic of using this decoder could be more clearly spelled out to the reader. For example, if the null hypothesis is that noise correlations do not carry azimuth information, then a decoder that assumes independence should perform the same whether population responses are simultaneous or scrambled. The authors' analysis showing a difference in performance between these two cases provides evidence against this null hypothesis.
Minor weakness:<br /> - Most studies of neural encoding of sound source azimuth are done in a noise-free environment, but the experimental setup in the present study had substantial background noise. This complicates comparison of the azimuth tuning results in this study to those of other studies. One is left wondering if azimuth sensitivity would have been greater in the absence of background noise, particularly for the imaging data where the signal was only about 12 dB above the noise.
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- Nov 2024
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Reviewer #1 (Public review):
This study by Alejandro Rosell et al. reveals the immunoregulatory role of the RAS-p110α pathway in macrophages, specifically in regulating monocyte extravasation and lysosomal digestion during inflammation. Disrupting this pathway, through genetic tools or pharmacological intervention in mice, impairs the inflammatory response, leading to delayed resolution and more severe acute inflammation. The authors suggest that activating p110α with small molecules could be a potential therapeutic strategy for treating chronic inflammation. These findings provide important insights into the mechanisms by which p110α regulates macrophage function and the overall inflammatory response.
The updates made by the authors in the revised version have addressed the main points raised in the initial review, further improving the strength of their findings.
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Reviewer #1 (Public review):
Summary:
Tian et al. describes how TIPE regulates melanoma progression, stemness, and glycolysis. The authors link high TIPE expression to increased melanoma cell proliferation and tumor growth. TIPE causes dimerization of PKM2, as well as translocation of PKM2 to the nucleus, thereby activating HIF-1alpha. TIPE promotes the phosphorylation of S37 on PKM2 in an ERK-dependent manner. TIPE is shown to increase stem-like phenotype markers. The expression of TIPE is positively correlated with the levels of PKM2 Ser37 phosphorylation in murine and clinical tissue samples. Taken together, the authors demonstrate how TIPE impacts melanoma progression, stemness, and glycolysis through dimeric PKM2 and HIF-1alpha crosstalk.
The authors manipulated TIPE expression using both shRNA and overexpression approaches throughout the manuscript. Using these models, they provide strong evidence of the involvement of TIPE in mediating PKM2 Ser37 phosphorylation and dimerization. The authors also used mutants of PKM2 at S37A to block its interaction with TIPE and HIF-1alpha. In addition, an ERK inhibitor (U0126) was used to block the phosphorylation of Ser37 on PKM2. The authors show how dimerization of PKM2 by TIPE causes nuclear import of PKM2 and activation of HIF-1alpha and target genes. Pyridoxine was used to induce PKM2 dimer formation, while TEPP-46 was used to suppress PKM2 dimer formation. TIPE maintains stem cell phenotypes by increasing expression of stem-like markers. Furthermore, the relationship between TIPE and Ser37 PKM2 was demonstrated in murine and clinical tissue samples.
The evaluation of how TIPE causes metabolic reprogramming can be further assessed using isotope tracing experiments.
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Reviewer #1 (Public Review):
Summary:
The work by Joseph et al "Impact of the clinically approved BTK inhibitors on the conformation of full-length BTK and analysis of the development of BTK resistance mutations in chronic lymphocytic leukemia" seeks to comparatively analyze the effect of a range of covalent and noncovalent clinical BTK inhibitors upon BTK conformation. The novel aspect of this manuscript is that it seeks to evaluate the differential resistance mutations that arise distinctly from each of the inhibitors.
Strengths:
This is an exciting study that builds upon the fundamental notion of ensemble behavior in solutions for enzymes such as BTK. The HDX-MS and NMR experiments are adequately and comprehensively presented.
Comments on the revised version:
I am satisfied with the revisions and the clear explanations.
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Reviewer #1 (Public Review):
Summary:
The authors want to understand fundamental steps in ligand binding to muscle nicotinic receptors using computational methods. Overall, although the work provides new information and support for existing models of ligand activation of this receptor type, some limitations in the methods and approach mean that the findings are not as conclusive as hoped.
Strengths:
The strengths include the number of ligands tried, and the comparison to the existing mature analysis of receptor function from the senior author's lab.
Weaknesses:
The weakness are the brevity of the simulations, the concomitant lack of scope of the simulations, the lack of depth in the analysis and the incomplete relation to other relevant work. The free energy methods used seem to lack accuracy - they are only correct for 2 out of 4 ligands.
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Reviewer #1 (Public review):
Summary:
Zhang et al. describe a delicate relationship between Tet2 and FBP1 in the regulation of hepatic gluconeogenesis.
Strengths:
The studies are very mechanistic, indicating that this interaction occurs via demethylation of HNF4a. Phosphorylation of HNF4a at ser 313 induced by metformin also controls the interaction between Tet2 and FBP1.
Weaknesses:
The results are briefly described, and oftentimes, the necessary information is not provided to interpret the data. Similarly, the methods section is not well developed to inform the reader about how these experiments were performed. While the findings are interesting, the results section needs to be better developed to increase confidence in the interpretation of the results.
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Reviewer #1 (Public review):
The authors presented a new MNase-based proximity ligation method called MChIP-C, allowing for the measurement of protein-mediated chromatin interactions at single-nucleosome resolution on a genome-wide scale. With improved resolution and sensitivity, they explored the spatial connectivity of active promoters and identified the potential candidates for establishing/maintaining E-P interactions. Finally, with published CRISPRi screens, they found that most functionally-verified enhancers do physically interact with their cognate promoters, supporting the enhancer-promoter looping model.
While the study's experimental approach and findings are interesting. However, several issues need to be addressed:
(1) The authors described that "the lack of interaction between experimentally-validated enhancers and their cognate promoters in some studies employing C-methods has raised doubts regarding the classical promoter-enhancer looping model", so it's intriguing to see whether the MChIP-C could indeed detect the E-P interactions which were not identified by C-methods as they mentioned (Benabdallah et al., 2019; Gupta et al., 2017). I agree that they identified more E-P interactions using MChIP-C, but specifically, they should show at least 2-3 cases. It's important since this is the main conclusion the authors want to draw.
(2) The authors compared their data to those of Chen et al. (Chen et al., 2022), who used PLAC-seq with anti-H3K4me3 antibodies in K562 cells and standard Micro-C data previously reported for K562, concluding that "MChIP-C achieves superior sensitivity and resolution compared to C-methods based on standard restriction enzymes.". This is not convincing since they only compared their data to one dataset. More datasets from other cell lines should be included.
(3) The reasons to choose Chen's data (Chen et al., 2022) and CRISPRi screens (Fulco et al., 2019; Gasperini et al., 2019) should be provided since there are so many out there.
(4) The authors identify EP300 histone acetyltransferase and the SWI/SNF remodeling complex as potential candidates for establishing and/or maintaining enhancer-promoter interactions, but not RNA polymerase II, mediator complex, YY1 and BRD4. More explanation is needed for this point since they're previously suggested to be associated with E-P interactions.
(5) The limitations of the method should be discussed.
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Reviewer #1 (Public review):
Summary:
The manuscript proposes that 5mC modifications to DNA, despite being ancient and widespread throughout life, represent a vulnerability, making cells more susceptible to both chemical alkylation and, of more general importance, reactive oxygen species. Sarkies et al take the innovative approach of introducing enzymatic genome-wide cytosine methylation system (DNA methyltransferases, DNMTs) into E. coli, which normally lacks such a system. They provide compelling evidence that the introduction of DNMTs increases the sensitivity of E. coli to chemical alkylation damage. Surprisingly they also show DNMTs increase the sensitivity to reactive oxygen species and propose that the DNMT generated 5mC presents a target for the reactive oxygen species that is especially damaging to cells. Evidence is presented that DNMT activity directly or indirectly produces reactive oxygen species in vivo, which is an important discovery if correct, though the mechanism for this remains obscure.
Strengths:
This work is based on an interesting initial premise, it is well-motivated in the introduction and the manuscript is clearly written. The results themselves are compelling.
Weaknesses:
I am not currently convinced by the principal interpretations and think that other explanations based on known phenomena could account for key results. Specific points below.
(1) As noted in the manuscript, AlkB repairs alkylation damage by direct reversal (DNA strands are not cut). In the absence of AlkB, repair of alklylation damage/modification is likely through BER or other processes involving strand excision and resulting in single stranded DNA. It has previously been shown that 3mC modification from MMS exposure is highly specific to single stranded DNA (PMID:20663718) occurring at ~20,000 times the rate as double stranded DNA. Consequently, the introduction of DNMTs is expected to introduce many methylation adducts genome-wide that will generate single stranded DNA tracts when repaired in an AlkB deficient background (but not in an AlkB WT background), which are then hyper-susceptible to attack by MMS. Such ssDNA tracts are also vulnerable to generating double strand breaks, especially when they contain DNA polymerase stalling adducts such as 3mC. The generation of ssDNA during repair is similarly expected follow the H2O2 or TET based conversion of 5mC to 5hmC or 5fC neither of which can be directly repaired and depend on single strand excision for their removal. The potential importance of ssDNA generation in the experiments has not been considered.
(2) The authors emphasise the non-additivity of the MMS + DNMT + alkB experiment but the interpretation of the result is essentially an additive one: that both MMS and DNMT are introducing similar/same damage and AlkB acts to remove it. The non-additivity noted would seem to be more consistent with the ssDNA model proposed in #1. More generally non-additivity would also be seen if the survival to DNA methylation rate is non-linear over the range of the experiment, for example if there is a threshold effect where some repair process is overwhelmed. The linearity of MMS (and H2O2) exposure to survival could be directly tested with a dilution series of MMS (H2O2).
(3) The substantial transcriptional changes induced by DNMT expression (Supplemental Figure 4) are a cause for concern and highlight that the ectopic introduction of methylation into a complex system is potentially more confounded than it may at first seem. Though the expression analysis shows bulk transcription properties, my concern is that the disruptive influence of methylation in a system not evolved with it adds not just consistent transcriptional changes but transcriptional heterogeneity between cells which could influence net survival in a stressed environment. In practice I don't think this can be controlled for, possibly quantified by single-cell RNA-seq but that is beyond the reasonable scope of this paper.
(4) Figure 4 represents a striking result. From its current presentation it could be inferred that DNMTs are actively promoting ROS generation from H2O2 and also to a lesser extent in the absence of exogenous H2O2. That would be very surprising and a major finding with far-reaching implications. It would need to be further validated, for example by in vitro reconstitution of the reaction and monitoring ROS production. Rather, I think the authors are proposing that some currently undefined, indirect consequence of DNMT activity promotes ROS generation, especially when exogenous H2O2 is available. It would help if this were clarified.
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Reviewer #1 (Public review):
In the current manuscript, the authors use theoretical and analytical tools to examine the possibility of neural projections to engage ensembles of synaptic clusters in active dendrites. The analysis is divided into multiple models that differ in the connectivity parameters, speed of interactions and identity of the signal (electric vs. second messenger). They first show that random connectivity almost ensures the representation of presynaptic ensembles. As expected, this convergence is much more likely for small group sizes and slow processes, such as calcium dynamics. Conversely, fast signals (spikes and postsynaptic potentials) and large groups are much less likely to recruit spatially clustered inputs. Dendritic nonlinearity in the postsynaptic cells was found to play a highly important role in distinguishing these clustered activation patterns, both when activated simultaneously and in sequence. The authors tackled the difficult issue of noise, showing a beneficiary effect when noise 'happen' to fill in gaps in a sequential pattern but degraded performance at higher background activity levels. Last, the authors simulated selectivity to chemical and electrical signals. While they find that longer sequences are less perturbed by noise, in more realistic activation conditions, the signals are not well resolved in the soma.
While I think the premise of the manuscript is worth exploring, I have a number of reservations regarding the results.
(1) In the analysis, the authors made a simplifying assumption that the chemical and electrical processes are independent. However, this is not the case; excitatory inputs to spines often trigger depolarization combined with pronounced calcium influx; this mixed signaling could have dramatic implications on the analysis, particularly if the dendrites are nonlinear (see below)<br /> (2) Sequence detection in active dendrites is often simplified to investigating activation in a part of or the entirety of individual branches. However, the authors did not do that for most of their analysis. Instead, they treat the entire dendritic tree as one long branch and count how many inputs form clusters. I fail to see why the simplification is required and suspect it can lead to wrong results. For example, two inputs that are mapped to different dendrites in the 'original' morphology but then happen to fall next to each other when the branches are staggered to form the long dendrites would be counted as neighbors.<br /> (3) The simulations were poorly executed. Figures 5 and 6 show examples but no summary statistics. The authors emphasize the importance of nonlinear dendritic interactions, but they do not include them in their analysis of the ectopic signals! I find it to be wholly expected that the effects of dendritic ensembles are not pronounced when the dendrites are linear.
To provide a comprehensive analysis of dendritic integration, the authors could simulate more realistic synaptic conductances and voltage-gated channels. They would find much more complicated interactions between inputs on a single site, a sliding temporal and spatial window of nonlinear integration that depends on dendritic morphology, active and passive parameters and synaptic properties. At different activation levels, the rules of synaptic integration shift to cooperativity between different dendrites and cellular compartments, further complicated by nonlinear interactions between somatic spikes and dendritic events.
While it is tempting to extend back-of-the-napkin calculations of how many inputs can recruit nonlinear integration in active dendrites, the biological implementation is very different from this hypothetical. It is important to consider these questions, but I am not convinced that this manuscript adequately addressed the questions it set out to probe, nor does it provide information that was unknown beforehand.
Update after the first revision:
In this revision, the authors significantly improved the manuscript. They now address some of my concerns. Specifically, they show the contribution of end-effects on spreading the inputs between dendrites. This analysis reveals greater applicability of their findings to cortical cells, with long, unbranching dendrites than other neuronal types, such as Purkinje cells in the cerebellum.
They now explain better the interactions between calcium and voltage signals, which I believe improve the take-away message of their manuscript. They modified and added new figures that helped to provide more information about their simulations.<br /> However, some of my points remain valid. Figure 6 shows depolarization of ~5mV from -75. This weak depolarization would not effectively recruit nonlinear activation of NMDARs. In their paper, Branco and Hausser (2010) showed depolarizations of ~10-15mV. More importantly, the signature of NMDAR activation is the prolonged plateau potential and activation at more depolarized resting membrane potentials (their Figure 4). Thus, despite including NMDARs in the simulation, the authors do not model functional recruitment of these channels. Their simulation is thus equivalent to AMPA only drive, which can indeed summate somewhat nonlinearly.
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Reviewer #1 (Public review):
Summary:
The authors introduced neutron crystallography coupled with room temperature X-ray crystallography to exam the redox properties of the BtFt [4Fe-4S] cluster expressed in E. coli. Neutron structure allowed the authors to exam the influence of Asp64 on the redox properties of the [4Fe-4S] cluster. The neutron structure also allowed for the identification of the hydrogen network around the [4Fe-4S] structure. This work was followed by density functional theory calculation to examine different redox states which also pointed to the role of Asp64 in affecting or dictating redox function of the [4Fe-4S] cluster. Based on the DFT work the authors examine the redox properties under oxic and anoxic conditions in wild type enzymes and in a D64N mutant again showing the role of Asp64 on the redox kinetics and redox potential of the [4Fe-4S] cluster. Lastly, the authors examined similar [4Fe-4S] ferredoxins from several organisms and with a Asp64 or Glu64 observed a similar role of Asp64 on the low potential state of the [4Fe-4S] cluster. The major conclusion of the study was to identify the role of specific amino acids, in this case Asp64, in controlling the redox state and kinetics of [4Fe-4S] clusters. The authors also demonstrate the strength of neutron crystallography when combined with classical X-ray crystallography and classical spectral/redox studies.
Strengths:
In general, the experimental design is logical and the results are convincing demonstrating the role of Asp64 on the redox properties of [4Fe-4S] clusters in ferredoxins.
Weaknesses:
The role(s) of coordinating amino acids on the redox properties of a functional group is not surprising, this reviewer believes this is a novel result in ferredoxins and does make a nice contribution to the field.
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Reviewer #1 (Public review):
Summary:
A description of small phosphatised fossils from the Kuanchuanpu, formations that are claimed to represent unequivocal early segmented bilaterians with limbs, ie annelids or panarthropods. All material from the Kuanchuanpu is of interest, and the mode of preservation is certainly striking.
However, few details apart from bilateral symmetry and paired protrusions are present. In addition, fragments of potential progenitors such as anabaritiids cannot be entirely ruled out. In addition, the broader claims about the nature of the Cambrian explosion, the gap between the fossil record and molecular clocks, and what various authors have said about them are either inadequate or incorrect. For example, Budd and Jackson did not at all make the claim that the earliest bilaterians were soft-bodied and tiny. Glaessner (1958) is a very out-of-date reference to use. We know that bilaterians certainly existed by the time of Kuanchuanpo.
Even so, it is possible that these fragments do represent internal moulds of taxa such as lobopod-like organisms, even if the evidence is not totally persuasive.
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Reviewer #1 (Public review):
Summary:
In this manuscript, Corso-Diaz et al, focus on the NRL transcription factor (TF), which is critical for retinal rod photoreceptor development and function. The authors profile NRL's protein interactome, revealing several RNA-binding proteins (RBPs) among its components. Notably, many of these RBPs are associated with R-loop biology, including DHX9 helicase, which is the primary focus of this study. R-loops are three-stranded nucleic acid structures that frequently form during transcription. The authors demonstrate that R-loop levels increase during photoreceptor maturation and establish an interaction between NRL TF and DHX9 helicase. The association between NRL and RBPs like DHX9 suggests a cooperative regulation of gene expression in a cell-type-specific manner, an intriguing discovery relevant to photoreceptor health. Since DHX9 is a key regulator of R-loop homeostasis, the study proposes a potential mechanism where a cell-type-specific TF controls the expression of certain genes by modulating R-loop homeostasis. This study also presents the first data on R-loop mapping in mammalian retinas and shows the enrichment of R-loops over intergenic regions as well as genes encoding neuronal function factors. While the research topic is very important, there is some concern regarding the data presented: there are substantial data supporting the interaction between NRL and DHX9, including pull-down experiments and proximity labeling assay (PLA), however, the data showing an interaction between NRL and DDX5, another R-loop-associated helicase, are inadequate. Importantly, the data supporting the claim that NRL interacts with R-loops are absolutely insufficient and at best, correlative. The next concerns are regarding the R-loop mapping data analysis and visualization.
Strengths:
There is compelling evidence that the NRL transcription factor interacts with several RNA binding proteins, and specifically, sufficient data supporting the interaction of NRL with DHX9 helicase.<br /> A major strength is the use of the single-stranded R-loop mapping method in the mouse retina.
Weaknesses:
(1) Figure S1A: There is a strong band in GST-IP (control IP) for either HNRNPUI1 or HNRNPU, although the authors state in their results that there is a strong interaction of these two RBPs with NRL. Both DHX9 and DDX5 samples have a faint band in the GST-IP. There is an extremely faint band for HNRNPA2B1 in the GST-NRL IP lane. Given this is a pull-down with added benzonase treatment to remove all nucleic acids, these data suggest, that previously observed NRL interactions with these particular RBPs are mediated via nucleic acids. Similarly, there is a loss of band signal for HNRNM in this assay, although it was identified as an NRL-interacting protein in three assays, which again suggests that nucleic acids mediate the interaction.
(2) The data supporting NRL-DDX5 interaction in rod photoreceptor nuclei is very weak. In Figure 2D, the PLA signal for DDX5-NRL is very weak in the adult mouse retina and is absent in the human retina, as shown in Figure 2H. Given that there is no NRL-KO available for the human PLA assay, the control experiments using single-protein antibodies should be included in the assay. Similarly, the single-protein antibody control PLA experiments should be included in the experimental data presented in Figure 2J.
(3) The EMSA experiment using a probe containing NRL binding motif within the DHX9 promoter should include incubation with retina nuclear extracts depleted for NRL as a control.
(4) There is a reduced amount of DHX9 pulled down in NRL-IP in HEK293 cells, but there is no statistically significant difference in the reciprocal IP (DHX9-IP and blotting for NRL) (Figure 4C).
(5) The only data supporting the claim that NRL interacts with R-loops are presented in Figure 5A. This is a co-IP of R-loops and then blotting for NRL, DHX9, and DDX5. Here, there is no signal for DDX5, quantification of DHX9 signal shows no statistically significant difference between RNase H treated and untreated samples, while NRL shows a signal in RNase H treated sample. These data are not sufficient to make the statement regarding the interaction of NRL with R-loops.
(6) Regarding R-loop mapping, the data analysis is quite confusing. The authors perform two different types of analyses: either overall narrow and broad peak analysis or strand-specific analysis. Given that the authors used ssDRIP-seq, which is a method designed to map R-loops strand specifically, it is confusing to perform different types of analyses. Next, the peak analysis is usually performed based on the RNase H treated R-loop mapping; what does it mean then to have a pool of "Not R-loops", see Figure 6B? In that regard, what does the term "unstranded" R-loops mean? Based on the authors' definition, these are R-loops that do not fall within the group of strand-specific R-loops. The authors should explain the reasons behind these types of analyses and explain, what the biological relevance of these different types of R-loops is.
(7) It would be more useful to show the percent distribution of R-loops over the different genomic regions, instead of showing p-value enrichment, see Figure 6C.
(8) Based on the model presented, NRL regulates R-loop biology via interaction with RBPs, such as DHX9, a known R-loop resolution helicase. Given that the gene targets of NRL TF are known, it would be useful to then analyze the R-loop mapping data across this gene set.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this preprint, Madrigal et al present "Tom1p ubiquitin ligase structure, interaction with Spt6p, and function in maintaining normal transcript levels and the stability of chromatin in promoters" which describes the identification of Tom1p, a conserved ubiquitin ligase, as a potential binding partner for the transcription elongation/histone chaperone Spt6p, and reveal the Tom1p structure as determined by CryoEM. Tom1p is a homolog of human HUWE1, which has been implicated in decay for a variety of basic protein substrates such as ribosomal proteins and histones. Structure-function analyses identify regions required for Spt6p interaction, suggesting that the interaction with Spt6p is phosphorylation dependent, and for interactions with histones, the latter of which confers phenotypes in vivo when mutated, suggesting that the Tom1p acidic region is important for its function. What is less clear is the function or interaction with Spt6p. The manuscript speculates that Spt6p-Tom1p interactions may tune Tom1p localization, and it is shown that Tom1p is recruited to transcribed genes by chromatin IP. In addition, the Tom1p structure will be valuable to those trying to understand the mechanisms of this very large ubiquitin ligase. Here, structures of homologs from other organisms have already been described elsewhere, however, the authors here indicate some details potentially not previously visualized in other structures.
Strengths:
It has not previously been known that the Spt6p tSH2 had any additional targets. Interaction with a ubiquitin ligase already implicated in histone turnover given Spt6p's role as histone chaperone is interesting. A structure of Tom1p also provides insight into this very large, conserved protein and structure-function analysis in a model system is a good start towards mechanistic dissection.
Weaknesses:
Some aspects of the manuscript seem less cohesive in that there are two halves of the manuscript and both don't quite solidify insights into the Spt6p relationship to Tom1p or deepen our understanding of Tom1p mechanism extensively, though results are a great start on both sides of the paper. There are several points that are less clear in that it is not known if Spt6p interacts with Tom1p and in what context. The interaction surface of Spt6p able to interact with Tom1p is the identical tSH2 that would be predicted to be occupied by phosphorylated RNAPII when Spt6p is incorporated into the RNAPII elongation complex. This means how and when Spt6p might be available to interact with Tom1p is not clear. Previous work from the Hill and Formosa groups on the tSH2 domain and its RNAPII linker target have suggested that phenotypes of mutants in the two are similar, suggesting that their main function is to interact with each other. A simple test of examining Tom1p interaction with genes in the tSH2 mutant was not done. Additionally, the Spt6p interacting surface on Tom1p is not narrowed to a specific putatively phosphorylated residue that it might target. It remains possible that mutations in other regions of Tom1p affect potential phosphorylation of this target, and therefore it is possible that some mutations that alter Spt6p interaction could do so indirectly. Finally, the authors might consider additional models for their discussion where Spt6p potentially could function to deliver histones to Tom1p.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This impressive study presents a comprehensive scRNAseq atlas of the cranial region during neural induction, patterning, and morphogenesis. The authors collected a robust scRNAseq dataset covering six distinct developmental stages. The analysis focused on the neural tissue, resulting in a highly detailed temporal map of neural plate development. The findings demonstrate how different cell fates are organized in specific spatial patterns along the anterior-posterior and medial-lateral axes within the developing neural tissue. Additionally, the research utilized high-density single-cell RNA sequencing (scRNAseq) to reveal intricate spatial and temporal patterns independent of traditional spatial techniques.
The investigation utilized diffusion component analysis to spatially order cells based on their positioning along the anterior-posterior axis, corresponding to the forebrain, midbrain, hindbrain, and medial-lateral axis. By cross-referencing with MGI expression data, the identification of cell types was validated, affirming the expression patterns of numerous known genes and implicating others as differentially expressed along these axes. These findings significantly advance our understanding of the spatially regulated genes in neural tissues during early developmental stages. The emphasis on transcription factors, cell surface, and secreted proteins provides valuable insights into the intricate gene regulatory networks underpinning neural tissue patterning. Analysis of a second scRNAseq dataset where Shh signaling was inhibited by culturing embryos in SAG identified known and previously unknown transcripts regulated by Shh, including the Wnt pathway.
The data includes the neural plate and captures all major cell types in the head, including the mesoderm, endoderm, non-neural ectoderm, neural crest, notochord, and blood. With further analyses, this high-quality data promises to significantly advance our understanding of how these tissues develop in conjunction with the neural tissue, paving the way for future breakthroughs in developmental biology and genomics.
Strengths:
The data is well presented in the figures and thoroughly described in the text. The quality of the scRNAseq data and bioinformatic analysis is exceptional.
Weaknesses:
No weaknesses were identified by this reviewer.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this manuscript, Javid and colleagues worked to understand the molecular mechanisms involved in mistranslation in mycobacteria. They had previously discovered that mistranslation is an important mechanism underlying antibiotic tolerance in mycobacteria. Using a clever genetic screen they identify that deletion of gidB, a 16S ribosomal RNA methyltransferase, leads to lowered mistranslation (i.e. higher translational fidelity), but only in genetic backgrounds or environmental conditions that increase mistranslation rates.
Strengths:
The strengths of this manuscript are the clever genetic screen, the powerful mistranslation assays, and the clear writing and figures explaining a complex biological problem. Their identification of gidB as a factor important for mistranslation deepens our knowledge about this interesting phenomenon.
Weaknesses:
The structural work at the end feels like both an afterthought in terms of the science and the writing. I would suggest re-writing that section to be clearer about what the figure says and does not say. For example, the caption of Figure 6 appears to be more informative than the text and refers to concepts not present in the main text. In general, I found this section to be the most difficult to understand.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
This paper focuses on secondary structure and homodimers in the HIV genome. The authors introduce a new method called HiCapR which reveals secondary structure, homodimer, and long-range interactions in the HIV genome. The experimental design and data analysis are well-documented and statistically sound. However, the manuscript could be further improved in the following aspects.
Major comments:
(1) Please give the full name of an abbreviation the first time it appears in the paper, for example, in L37, "5' UTR" "RRE".
(2) The introduction could be strengthened by discussing the limitations of existing methods for studying HIV RNA structures and interactions and highlighting the specific advantages of the HiCapR method.
(3) Please reorganize Results Part 1.
(4) Is there any reason that the authors mention "genome structure of SARS-CoV-2" in L95?
(5) L102: Please clarify the purpose of comparing "NL4-3" and "GX2005002." Additionally, could you explain what NL4-3 and GX2005002 are? The connection between NL4-3, GX2005002, and HIV appears to be missing.
(6) Figure 1A is not able to clearly present the innovation point of HiCapR.
(7) Please compare the contact metrics detected by HiCapR and current techniques like SHAPE on the local interactions to assess the accuracy of HiCapR in capturing local RNA interactions relative to established methods.
(8) The paper needs further language editing.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This study seeks to identify a molecular mechanism whereby the small molecule RY785 selectively inhibits Kv2.1 channels. Specifically, it sought to explain some of the functional differences that RY785 exhibits in experimental electrophysiology experiments as compared to other Kv inhibitors, namely the charged and non-specific inhibitor tetraethylammonium (TEA). This study used a recently published cryo-EM Kv2.1 channel structure in the open activated state and performed a series of multi-microsecond-long all-atom molecular dynamics simulations to study Kv2.1 channel conduction under the applied membrane voltage with and without RY785 or TEA present. While TEA directly blocks K+ permeation by occluding ion permeation pathway, RY785 binds to multiple non-polar residues near the hydrophobic gate of the channel driving it to a semi-closed non-conductive state. This mechanism was confirmed using an additional set of simulations and used to explain experimental electrophysiology data,
Strengths:
The total length of simulation time is impressive, totaling many tens of microseconds. The study develops forcefield parameters for the RY785 molecule based on extensive QM-based parameterization. The computed permeation rate of K+ ions through the channel observed under applied voltage conditions is in reasonable agreement with experimental estimates of the single-channel conductance. The study performed extensive simulations with the apo channel as well as both TEA and RY785. The simulations with TEA reasonably demonstrate that TEA directly blocks K+ permeation by binding in the center of the Kv2.1 channel cavity, preventing K+ ions from reaching the SCav site. The conclusion is that RY785 likely stabilizes a partially closed conformation of the Kv2.1 channel and thereby inhibits the K+ current. This conclusion is plausible given that RY785 makes stable contact with multiple hydrophobic residues in the S6 helix. This further provides a possible mechanism for the experimental observations that RY785 speeds up the deactivation kinetics of Kv2 channels from a previous experimental electrophysiology study.
Weaknesses:
The study, however, did not produce this semi-closed channel conformation and acknowledges that more direct simulation evidence would require extensive enhanced-sampling simulations. The study has not estimated the effect of RY785 binding on the protein-based hydrophobic pore constriction, which may further substantiate their proposed mechanism. And while the study quantified K+ permeation, it does not make any estimates of the ligand binding affinities or rates, which could have been potentially compared to the experiment and used to validate the models.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this paper, the authors have leveraged Single-cell RNA sequencing of the various stages of the evolution of lung adenocarcinoma to identify the population of macrophages that contribute to tumor progression. They show that S100a4+ alveolar macrophages, active in fatty acid metabolic activity, such as palmitic acid metabolism, seem to drive the atypical adenomatous hyperplasia (AAH) stage. These macrophages also seem to induce angiogenesis promoting tumor growth. Similar types of macrophage infiltration were demonstrated in the progression of the human lung adenocarcinomas.
Strengths:
Identification of the metabolic pathways that promote angiogenesis-dependent progression of lung adenocarcinomas from early atypical changes to aggressive invasive phenotype could lead to the development of strategies to abort tumor progression.
Weaknesses:
(1) Can the authors demonstrate what are the functional specialization of the S100a4+ alveolar macrophages that promote the progression of the AAH to the more aggressive phenotype? What are the factors produced by these unique macrophages that induce tumor progression and invasiveness?
(2) Angiogenic factors are not only produced by the S100a4+ cells but also by pericytes and potentially by the tumor cells themselves. Then, how do these factors aberrantly trigger tumor angiogenesis that drives tumor growth?
(3) It is not clear how abnormal fatty acid uptake by the macrophages drives the progression of tumors.
(4) Does infusion or introduction of S100a4+ polarized macrophages promote the progression of AAH to a more aggressive phenotype?
(5) How does Anxa and Ramp1 induction in inflammatory cells induce angiogenesis and tumor progression?
(6) For the in vitro studies the authors might consider using primary tumor cells and not cell lines.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public review):
Summary:
In this manuscript, the authors consider the effects of eugenol (EUG), a plant-produced substance known to reduce oxidative stress in various cellular contexts via Nrf2, in alleviating the effects of streptozotocin (STZ), a known rodent beta cell toxin. They claim that EUG treatment would be useful for T1D therapy.
Strengths:
The experiments shown are sufficiently clear and rather convincing in documenting that eugenol can revert the effects of streptozotocin on animal physiology as well as beta cell oxidative stress and cell death via activation of Nrf2.
In the revised manuscript the authors corrected/explained most of the specific inconsistencies/mistakes pointed out.
However, they did not address the opening paragraph that points out major concerns. I summarize them below, together with some that were dealt with in their response but still remain unaddressed or not commented upon.
- STZ treatment cannot be used as a T1D model for the reasons I outlined in my previous letter. I would have been happy to see a response on that but they did not provide any. The manuscript is misleading in this important respect.
- Mechanistically, the manuscript remains at a rather superficial level. I highlighted some possibilities to enrich the manuscript but none was addressed even in the discussion.<br /> (a) How is eugenol penetrating the cell, is there a receptor that could be potentially targeted?<br /> (b) Are there intermediary proteins that convey the effect to the Nrf2/Keap1 complex or is eugenol directly disrupting their interaction?<br /> (c) What are direct downstream Nrf2 effectors?<br /> (d) Besides, streptozotocin is also a powerful DNA alkylating agent, are such effects relieved by eugenol?
- It is puzzling that all molecular analyses show a gradual reversion effect with increasing doses of eugenol but this gradual effect is apparently missing in many of the physiological parameters assessed in Figure 1, including the all-important OGTT assays. Can the authors interpret this? In the high eugenol group in the OGTT assays there is a group of mice that are clearly outliers. Most likely the STZ treatment for these mice was not efficient and their inclusion skews the results. Besides, it is important to assess differences among eugenol groups (one way ANOVA). The statistical tests provided are incomplete and sometimes not done correctly.
- Given that medical research is still heavily biased in favor of analyses in males and given that the authors have analyzed in Figure 1 a very large number of animals what are the results stratified by sex?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
It is evident that studying leukocyte extravasation in vitro is a challenge. One needs to include physiological flow, culture cells and isolate primary immune cells. Timing is of utmost importance and a reproducible setup essential. Extra challenges are met when extravasation kinetics in different vascular beds is required, e.g., across the blood-brain barrier. In this study, the authors describe a reliable and reproducible method to analyze leukocyte TEM under physiological flow conditions, including this analysis. That the software can also detect reverse TEM is a plus.
Strengths:
It is quite a challenge to get this assay reproducible and stable, in particular as there is flow included. Also for the analysis, there is currently no clear software analysis program, and many labs have their own methods. This paper gives the opportunity to unify the data and results obtained with this assay under label-free conditions. This should eventually lead to more solid and reproducible results.
Also, the comparison between manual and software analysis is appreciated.
Weaknesses:
The authors stress that it can be done in BBB models, but I would argue that it is much more broadly applicable. This is not necessarily a weakness of the study but more an opportunity to strengthen the method. So I would encourage the authors to rewrite some parts and make it more broadly applicable.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this manuscript, the authors employed direct RNA sequencing with nanopores, enhanced by 5' end adaptor ligation, to comprehensively interrogate the human transcriptome at single-molecule and nucleotide resolution. They conclude that cellular stress induces prevalent 5' end RNA decay that is coupled to translation and ribosome occupancy. Contrary to the literature, they found that, unlike typical RNA decay models in normal conditions, stress-induced RNA decay is dependent on XRN1 but does not depend on the removal of the poly(A) tail. The findings presented are interesting and the authors fully established these paradigm-shifting findings using cutting-edge technologies.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors report an fMRI investigation of the neural mechanisms by which selective attention allows capacity-limited perceptual systems to preferentially represent task-relevant visual stimuli. Specifically, they examine competitive interactions between two simultaneously-presented items from different categories, to reveal how task-directed attention to one of them modulates the activity of brain regions that respond to both. The specific hypothesis is that attention will bias responses to be more like those elicited by the relevant object presented on its own, and further that this modulation will be stronger for more dissimilar stimulus pairs. This pattern was confirmed in univariate analyses that measured the mass response of a priori regions of interest, as well as multivariate analyses that considered the patterns of evoked activity within the same regions. The authors follow these neuroimaging results with a simulation study that favours a "tuning" mechanism of attention (enhanced responses to highly effective stimuli, and suppression for ineffective stimuli) to explain this pattern.
Strengths:
The manuscript clearly articulates a core issue in the cognitive neuroscience of attention, namely the need to understand how limited perceptual systems cope with complex environments in the service of the observer's goals. The use of a priori regions of interest (and a control region), and the inclusion of both univariate and multivariate analyses as well as a simple model, are further strengths. The authors carefully derive clear indices of attentional effects (for both univariate and multivariate analyses) which makes explication of their findings easy to follow.
Weaknesses:
Direct estimation of baseline responses may have improved the validity of the modelling. The presentation of transparently overlapping items has some methodological advantages, but somewhat limits the ecological validity of connections to real-world visual "clutter".
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This article investigated the relationship between different intensities of exercise training and intestinal barrier dysfunction, and further explores the possible mechanisms, including the contribution of stress response, inflammatory response, gut microbiota alterations, and derived metabolites.
Strengths:
This article mainly focused on different aspects of the phenotypes and the morphology of intestinal barrier dysfunction induced by exercise training.
Weaknesses:
This article lacks the verification of the association of causality among various phenotypes and lacks a comprehensive understanding of the underlying mechanisms of how exercise contributes to intestinal barrier dysfunction.
(1) For example, the author claimed that heat shock and ischemia are the causes of intestinal epithelial damage caused by exercise, and it is not only evidenced by detecting the expression of a few regulators, such as HSF and HSP70 after exercise; and by Immunohistochemical analysis of intestinal morphology and inflammation.
(2) Many kinds of intestinal bacteria could produce short-chain fatty acids, such as Faecalibacterium Prausnitzii, did the authors check their abundance in the intestine after exercise training?
(3) How to define exercise intensity? Was VO2 Max testing used in this study?
(4) As the strict control, it is recommended to set 4 groups of exercise training groups: daily vigorous exercise training, daily moderate exercise training, daily vigorous exercise training with intermittent rest days, and daily moderate exercise training with intermittent rest days.
(5) Are there any differences in diet and metabolism between different groups of mice, which may affect the phenotypes, especially the composition and the the diverstiy of gut microbiota?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
In this study, Sarver and colleagues carried out an exhaustive analysis of the functioning of various components (Complex I/II/IV) of the mitochondrial electron transport chain (ETC) using a real-time cell metabolic analysis technique (commonly referred as Seahorse oxygen consumption rate (OCR) assay). The authors aimed to generate an atlas of ETC function in about 3 dozen tissue types isolated from all major mammalian organ systems. They used a recently published improvised method by which ETC function can be quantified in freshly frozen tissues. This method enabled them to collect data from almost all organ systems from the same mouse and use many biological replicates (10 mice/experiment) required for an unbiased and statistically robust analysis. Moreover, they studied the influence of sex (male and female) and aging (young adult and old age) on ETC function in these organ systems. The main findings of this study are (1) cells in the heart and kidneys have very active ETC complexes compared to other organ systems, (2) the sex of the mice has little influence on the ETC function, and (3) aging undermined the mitochondrial function in most tissue, but surprisingly in some tissue aging promoted the activity of ETC complexes (e.g., Quadriceps, plantaris muscle, and Diaphragm).
Comments on the second revision:
My previous concern remains unaddressed in the new revision. As I mentioned earlier, it is crucial for the authors to include a detailed discussion on the limitations of their method, specifically how maximal respiration does not accurately reflect the actual ATP production rate. Additionally, the authors should highlight the fact that data provided in the manuscript should be interpreted with caution.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this study, the authors used both the commonly used neonatal hyperoxia model as well as cell-type-specific genetic inactivation of Tgfbr2 models to study the basis of BPD. The bulk of the analyses focus on the mesenchymal cells. Results indicate impaired myofibroblast proliferation, resulting in decreased cell number. Inactivation of Etc2 in Pdgfra-lineaged cells, preventing cytokinesis of myofibroblasts, led to alveolar simplification. Together, the findings demonstrate that disrupted myofibroblast proliferation is a key contributor to BPD pathogenesis.
Strengths:
Overall, this comprehensive study of BPD models advances our understanding of the disease. The data are of high quality.
Comments on latest version:
In the revision, the authors addressed all critiques.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Malaria parasites detoxify free heme molecules released from digested host hemoglobins by biomineralizing them into inert hemozoin. Thus, why malaria parasites retain PfHO, a dead enzyme that loses the capacity of catabolizing heme, is an outstanding question that has puzzled researchers for more than a decade. In the current manuscript, the authors addressed this question by first solving the crystal structure of PfHO and aligning it with structures of other heme oxygenase (HO) proteins. They found that the N-terminal 95 residues of PfHO, which failed to crystalize due to its disordered nature, may serve as signal and transit peptides for PfHO subcellular localization. This was confirmed by subsequent microscopic analysis with episomally expressed PfHO-GFP and a GFP reporter fused to the first 83 residues of PfHO (PfHO N-term-GFP). To investigate the functional importance of PfHO, the authors generated an anhydrotetracycline (aTC) controlled PfHO knockdown strain. Strikingly, the parasites lacking PfHO failed to grow and lost their apicoplast. Finally, by chromatin immunoprecipitation (ChIP), quantitative PCR/RT-PCR and growth assays, the authors showed that both the cognate N-terminus and HO-like domain were required for PfHO function as an apicoplast DNA interacting protein.
The authors systemically performed multidisciplinary approaches to address this difficult question: what is the function of this enzymatically dead PfHO? I enjoyed reading this manuscript and its thoughtful discussion. This study is not only of clinical importance for antimalarial treatments but also deepens our understanding of protein function evolution.
The authors proposed that PfHO interacts with apicoplast genome DNA via the electropositive N-terminus. Interestingly, these positively charged residues are not conserved between Plasmodium, Theileria and Babesia. I will be curious to follow the authors' future work to investigate the function of this electropositive N-terminus, possibly by comparative and mutagenesis analysis?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Mohseni and Elhaik have critically examined the widespread use of principal component analysis (PCA) in phylogenetic inferences within the discipline of physical anthropology. The authors present compelling evidence that PCA underperforms compared to machine learning (ML) classifiers. This excellent work not only challenges the reliability of PCA-based taxonomic inferences, but also adds to a growing body of literature questioning the application of PCA in physical anthropology, thereby initiating a fruitful discussion in our field. Moreover, it underscores the crucial need of external validation methods in such studies.
The authors have addressed nearly all of my comments, and my questions have been fully answered. The revised manuscript represents a significant improvement.
The new title more effectively conveys the central message emerging from this research; The revised introduction more precisely addresses the methodological challenges currently facing the discipline.<br /> I am equally amazed by the profound susceptibility of the PCA results, as demonstrated by the alterations introduced by the authors, and by the contrasting robustness of the ML classifiers. I trust that this contrast will spark a fruitful discussion about the application of both methods in our field. It should also inspire further research conducted by physical anthropologists to study the role of ML in this discipline.<br /> Lastly, and importantly, I believe the authors should be commended for addressing the broader implications of their work, particularly in relation to public perceptions of science (pp. 20-21).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors examine CD8 T cell selective pressure in early HCV infection using. They propose that after initial CD8-T mediated loss of virus fitness, in some participants around 3 months after infection, HCV acquires compensatory mutations and improved fitness leading to virus progression.
Strengths:
Throughout the paper, the authors apply well-established approaches in studies of acute to chronic HIV infection for studies of HCV infection. This lends rigor the to the authors' work.
Weaknesses:
(1) The Discussion could be strengthened by a direct discussion of the parallels/differences in results between HIV and HCV infections in terms of T cell selection, entropy, and fitness.
(2) In the Results, please describe the Barton model functionality and why the fitness landscape model was most applicable for studies of HCV viral diversity.
(3) Recognize the caveats of the HCV mapping data presented.
(4) The authors should provide more data or cite publications to support the authors' statement that HCV-specific CD8 T cell responses decline following infection.
(5) Similarly, as the authors' measurements of HCV T and humoral responses were not exhaustive, the text describing the decline of T cells with the onset of humoral immunity needs caveats or more rigorous discussion with citations (Discussion lines 319-321).
(6) What role does antigen drive play in these data -for both T can and antibody induction?
(7) Figure 3 - are the X and Y axes wrongly labelled? The Divergent ranges of population fitness do not make sense.
(8) Figure S3 - is the green line, average virus fitness?
(9) Use the term antibody epitopes, not B cell epitopes.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this manuscript, De La Forest Divonne et al. build a repertory of hemocytes from adult Pacific oysters combining scRNAseq data with cytologic and biochemical analyses. Three categories of hemocytes were described previously in this species (i.e. blast, hyalinocyte, and granulocytes). Based on scRNAseq data, the authors identified 7 hemocyte clusters presenting distinct transcriptional signatures. Using Kegg pathway enrichment and RBGOA, the authors determined the main molecular features of the clusters. In parallel, using cytologic markers, the authors classified 7 populations of hemocytes (i.e. ML, H, BBL, ABL, SGC, BGC, and VC) presenting distinct sizes, nucleus sizes, acidophilic/basophilic, presence of pseudopods, cytoplasm/nucleus ratio and presence of granules. Then, the authors compared the phenotypic features with potential transcriptional signatures seen in the scRNAseq. The hemocytes were separated in a density gradient to enrich for specific subpopulations. The cell composition of each cell fraction was determined using cytologic markers and the cell fractions were analysed by quantitative PCR targeting major cluster markers (two per cluster). With this approach, the authors could assign cluster 7 to VC, cluster 2 to H, and cluster 3 to SGC. The other clusters did not show a clear association with this experimental approach. Using phagocytic assays, ROS, and copper monitoring, the authors showed that ML and SGC are phagocytic, ML produces ROS, and SGC and BGC accumulate copper. Then with the density gradient/qPCR approach, the authors identified the populations expressing anti-microbial peptides (ABL, BBL, and H). At last, the authors used Monocle to predict differentiation trajectories for each subgroup of hemocytes using cluster 4 as the progenitor subpopulation.
The manuscript provides a comprehensive characterisation of the diversity of circulating immune cells found in Pacific oysters.
Strengths:
The combination of the two approaches offers a more integrative view.
Hemocytes represent a very plastic cell population that has key roles in homeostatic and challenged conditions. Grasping the molecular features of these cells at the single-cell level will help understand their biology.
This type of study may help elucidate the diversification of immune cells in comparative studies and evolutionary immunology.
Weaknesses:
The study should be more cautious about the conclusions, include further analyses, and inscribe the work in a more general framework.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Chemotherapy-induced chronic kidney injury is a significant and growing concern, as it can lead to long-term renal damage and compromised kidney function. The authors have highlighted an important aspect of this issue by evaluating the potential protective effects of OPCs against cisplatin-induced kidney injury. They propose that OPCs may mitigate renal damage by reducing NET formation, which could improve kidney function.
Strengths:
The study addressed a significant issue in the field of chemotherapy-induced kidney injury. The use of multiple markers and experimental methods provided a comprehensive exploration of the impact of OPCs on kidney damage. This approach allowed for a nuanced understanding of how OPCs might mitigate renal injury by reducing NET formation and improving kidney function.
Weaknesses:
The hypothesis is intriguing and relevant. However, the study encounters challenges, such as incomplete evidence and discrepancies between the text and data. Addressing these issues is crucial to improving the overall study's conclusions. The paper can potentially advance the understanding of therapeutic strategies for chemotherapy-induced kidney injury. Nonetheless, a clearer presentation of the data is necessary for it to have a substantial impact.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Kainov et al investigated the prevalence of mutations in 3'UTR that affect gene expression in cancer to identify noncoding cancer drivers.
The authors used data from normal controls (1000 genome data) and compared it to cancer data (PCAWG). They found that in cancer 3'UTR mutations had a stronger effect on cleavage than the normal population. These mutations are negatively selected in the normal population and positively selected in cancers. The authors used PCAWG data set to identify such mutations and found that the mutations that lead to a reduction of gene expression are enriched in tumor suppressor genes and those that are increased in gene expression are enriched for oncogenes. 3'UTR mutations that reduce gene expression or occur in TSGs co-occur with non-synonymous mutations. The authors then validate the effect of 3'UTR mutations experimentally using a luciferase reporter assay. These data identify a novel class of noncoding driver genes with mutations in 3'UTR that impact polyadenylation and thus gene expression.
This is an elegant study with fundamental insight into identifying cancer driver genes. The conclusions of this paper are mostly well supported by data, but some aspects of data analysis need to be extended.
Comments on revisions:
The authors addressed most of my comments.
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Reviewer #1 (Public review):
Summary:
It is well known that autophagosomes/autolysosomes move along microtubules. However, because previous studies did not distinguish between autophagosomes and autolysosomes, it remains unknown whether autophagosomes begin to move after fusion with lysosomes or even before fusion. In this manuscript, the authors show, using fusion-deficient cells, that both pre-fusion autophagosomes and lysosomes can move along the MT toward the minus end. By screening motor proteins and Rabs, the authors found that autophagosomal traffic is primarily regulated by the dynein-dynactin system and can be counter-regulated by kinesins. They also show that Rab7-Epg5 and Rab39-ema interactions are important for autophagosome trafficking.
Strengths:
This study uses reliable Drosophila genetics and high-quality fluorescence microscopy. The data are properly quantified and statistically analyzed. It is a reasonable hypothesis that gathering pre-fusion autophagosomes and lysosomes in close proximity improves fusion efficiency.
Weaknesses:
(1) To distinguish autophagosomes from autolysosomes, the authors used vps16 RNAi cells, which are supposed to be fusion deficient. However, the extent to which fusion is actually inhibited by knockdown of Vps16A is not shown. The co-localization rate of Atg8 and Lamp1 should be shown (as in Figure 8). Then, after identifying pre-fusion autophagosomes and lysosomes, the localization of each should be analyzed. It is also possible that autophagosomes and lysosomes are tethered by factors other than HOPS (even if they are not fused). If this is the case, autophagosomal trafficking would be affected by the movement of lysosomes.
(2) The authors analyze autolysosomes in Figures 6 and 7. This is based on the assumption that autophagosome-lysosome fusion takes place in cells without vps16A RANi. However, even in the presence of Vps16A, both pre-fusion autophagosomes and autolysosomes should exist. This is also true in Figure 8H, where the fusion of autophagosomes and lysosomes is partially suppressed in knockdown cells of dynein, dynactin, Rab7, and Epg5. If the effect of fusion is to be examined, it is reasonable to distinguish between autophagosomes and autolysosomes and analyze only autolysosomes.
(3) In this study, only vps16a RNAi cells were used to inhibit autophagosome-lysosome fusion. However, since HOPS has many roles besides autophagosome-lysosome fusion, it would be better to confirm the conclusion by knockdown of other factors (e.g., Stx17 RNAi).
(4) Figure 8: Rab7 and Epg5 are also known to be directly involved in autophagosome-lysosome tethering/fusion. Even if the fusion rate is reduced in the absence of Rab7 and Epg5, it may not be the result of defective autophagosome movement, but may simply indicate that these molecules are required for fusion itself. How do the authors distinguish between the two possibilities?
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Reviewer #2 (Public review):
Summary:
In this manuscript, the authors investigated how partial loss of SynGap1 affects inhibitory neurons derived from the MGE in the auditory cortex, focusing on their synaptic inputs and excitability. While haplo-insufficiently of SynGap1 is known to lead to intellectual disabilities, the underlying mechanisms remain unclear.
Strengths:
The questions are novel
Weaknesses:
Despite the interesting and novel questions, there are significant issues regarding the experimental design and potential misinterpretations of key findings. Consequently, the manuscript contributes little to our understanding of SynGap1 loss mechanisms.
Major issues in the second version of the manuscript:<br /> In the review of the first version there were major issues and contradictions with the sEPSC and mEPSC data, and were not resolved after the revision, and the new control experiments rather confirmed the contradiction.<br /> In the original review I stated: "One major concern is the inconsistency and confusion in the intermediate conclusions drawn from the results. For instance, while the sEPSC data indicates decreased amplitude in PV+ and SOM+ cells in cHet animals, the frequency of events remains unchanged. In contrast, the mEPSC data shows no change in amplitudes in PV+ cells, but a significant decrease in event frequency. The authors conclude that the former observation implies decreased excitability. However, traditionally, such observations on mEPSC parameters are considered indicative of presynaptic mechanisms rather than changes of network activity. The subsequent synapse counting experiments align more closely with the traditional conclusions. This issue can be resolved by rephrasing the text. However, it would remain unexplained why the sEPSC frequency shows no significant difference. If the majority of sEPSC events were indeed mediated by spiking (which is blocked by TTX), the average amplitudes and frequency of mEPSCs should be substantially lower than those of sEPSCs. Yet, they fall within a very similar range, suggesting that most sEPSCs may actually be independent of action potentials. But if that was indeed the case, the changes of purported sEPSC and mEPSC results should have been similar."<br /> Contradictions remained after the revision of the manuscript. On one hand, the authors claimed in the revised version that "We found no difference in mEPSC amplitude between the two genotypes (Fig. 1g), indicating that the observed difference in sEPSC amplitude (Figure 1b) could arise from decreased network excitability". On the other hand, later they show "no significative difference in either amplitude or inter-event intervals between sEPSC and mEPSC, suggesting that in acute slices from adult A1, most sEPSCs may actually be AP independent." The latter means that sEPSCs and mEPSCs are the same type of events, which should have the same sensitivity to manipulations.
Concerns about the quality of the synapse counting experiments were addressed by showing additional images in a different and explaining quantification. However, the admitted restriction of the analysis of excitatory synapses to the somatic region represent a limitation, as they include only a small fraction of the total excitation - even if, the slightly larger amplitudes of their EPSPs are considered.
New experiments using pari-pulse stimulation provided an answer to issues 3 and 4. Note that the numbering of the Figures in the responses and manuscript are not consistent.
I agree that low sampling rate of the APs does not change the observed large differences in AP threshold, however, the phase plots are still inconsistent in a sense that there appears to be an offset, as all values are shifted to more depolarized membrane potentials, including threshold, AP peak, AHP peak. This consistent shift may be due to a non-biological differences in the two sets of recordings, and, importantly, it may negate the interpretation of the I/f curves results (Fig. 5e).
Additional issues:<br /> The first paragraph of the Results mentioned that the recorded cells were identified by immunolabelling and axonal localization. However, neither the Results nor the Methods mention the criteria and levels of measurements of axonal arborization.
The other issues of the first review were adequately addressed by the Authors and the manuscript improved by these changes.
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Reviewer #3 (Public review):
Summary:
The manuscript by Ma et al. describes a multi-model (pig, mouse, organoid) investigation into how fecal transplants protect against E. coli infection. The authors identify A. muciniphila and B. fragilis as two important strains and characterize how these organisms impact the epithelium by modulating host signaling pathways, namely the Wnt pathway in lgr5 intestinal stem cells.
Strengths:
The strengths of this manuscript include the use of multiple model systems and follow up mechanistic investigations to understand how A. muciniphila and B. fragilis interacted with the host to impact epithelial physiology.
Weaknesses:
As in previous revisions, there remains concerning ambiguity in the methodology used for microbiota sequence analysis and it would be difficult to replicate the analysis in any meaningful way. In this revision, concerns about the rigor and reproducibility of this component of the manuscript have been increased. Readers should be cautious with interpretation of this data.
(1) In previous versions of the manuscript it would appear the correct bioproject accession was listed but, the actual link went to an unrelated project. The updated accession link appears to contain raw data; however, the authors state they used an Illumina HiSeq 2500. This would be an unusual choice for V3-V4 as it would not have read lengths long enough to overlap. Inspection of the first sample (SRR19164796) demonstrates that this is absolutely not the raw data, as there is a ~400 nt forward read, and a 0 length reverse read. All quality scores are set to 30. There is no logical way to go from HiSeq 2500 raw data and read lengths to what was uploaded to the SRA and it was certainly not described in the manuscript.
(2) No multiple testing correction was applied to the microbiome data.
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Reviewer #1 (Public Review):
The authors analyse droplet size distributions of multiple protein condensates and fit to a scaling ansatz to highlight that they exhibit features of first-order and second-order phase transitions. While the experimental evidence is solid, the text lacks connection and contextualization to the well-understood expectations from the coupling of percolation and phase separation in protein condensates - a phenomenon that is increasingly gaining consensus amongst the community. The evidence supports the percolatoin+phase separation model rather than being close to a true critical point in the liquid-gas phase space. Overall, the work is useful to the community.
Strengths:<br /> The experimental analysis of distinct protein condensates is very well done and the reported exponents/scaling framework provides a clear framework to help the community help deconvolve signatures of percolation in condensates.
Weaknesses:
The principal concern this reviewer has is that the reviewers adopt a framing in this paper to present a discovery of second-order features and connections to criticality - however they ignore/miss the connections to percolation (a well-understood second-order transition that is expected to play a major role in protein condensates). I believe this needs to be addressed and the paper suitably revised to help connect with these expectations.
- Protein condensates have been increasingly understood to be described as fluids whose assembly is driven by a connection of density (phase separation, first-order) and connectivity (percolation, second-order) transitions. This has been long known in the polymer community (Flory, Stockmayer, Tanaka, Rubinstein, Semenov and others) and recently repopularized in the condensate community (by Pappu and Mittag, in particular, amongst others). The authors make no connections to any of this frameworks - which actually seem to be the essence of what they are describing.
- Percolation theory, which has been around for more than half-a-century, has clear-cut scaling laws that have essentially similar forms to the ansatz adopted by the authors and the commonalities/differences are not discussed by the authors - this is essential since this provides a physical basis for their ansatz rather than an arbitrary mathematical formulation. In particular, percolation models connect size distribution exponents to factors like dimensionality, valence, etc. and if these connections can be made with this data, that would be very powerful.
- The connections between spinodal decomposition and second-order phase transitions are very confusing. Spindal decomposition happens when the barriers for first-order phase transitions are zero and systems can phase separate without crossing nucleation barriers. Further, the "criticality" discussed in the paper is confusing since it more likely refers to a percolation threshold and much less likely to a "critical temperature" (Tc -where spinodal and binodals become identical). I would recommend reframing this argument.
It's unlikely, in this reviewer's opinion, that the authors are actually discussing a "first-order" liquid-gas critical point - because saturation concentrations of these proteins can be much higher with temperature and the critical point would thus likely be at much higher concentrations (and ofc temperature). Further the scaling exponents don't fall in that class naturally. However, if the authors disagree, I would appreciate clear quantitative reasons (including through the scaling exponents in that universality class) and be happy to be convinced to change my mind. As provided, the data does not support this model.
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Reviewer #1 (Public review):
Summary:
Bennion and colleagues present a careful examination of how an earlier set of memories can either interfere with or facilitate memories formed later. This impressive work is a companion piece to an earlier paper by Antony and colleagues (2022) in which a similar experimental design was used to examine how a later set of memories can either interfere with or facilitate memories formed earlier. This study makes contact with an experimental literature spanning 100 years, which is concerned with the nature of forgetting, and the ways in which memories for particular experiences can interact with other memories. These ideas are fundamental to modern theories of human memory, for example, paired-associates studies like this one are central to the theoretical idea that interference between memories is a much bigger contributor to forgetting than any sort of passive decay.
Strengths:
At the heart of the current investigation is a proposal made by Osgood in the 1940s regarding how paired associates are learned and remembered. In these experiments one learns a pair of items, A-B (cue-target), and then later learns another pair that is related in some way, either A'-B (changing the cue, delta-cue), or A-B' (changing the target, delta-target), or A'-B' (changing both, delta-both), where the prime indicates that item has been modified, and may be semantically related to the original item. The authors refer to the critical to-be-remembered pairs as base pairs. Osgood proposed that when the changed item is very different from the original item there will be interference, and when the changed item is similar to the original item there will be facilitation. Osgood proposed a graphical depiction of his theory in which performance was summarized as a surface, with one axis indicating changes to the cue item of a pair and the other indicating changes to the target item, and the surface itself necessary to visualize the consequences of changing both.
In the decades since Osgood's proposal, there have been many studies examining slivers of the proposal, e.g., just changing targets in one experiment, just changing cues in another experiment. Because any pair of experiments use different methods, this has made it difficult to draw clear conclusions about the effects of particular manipulations.
The current paper is a potential landmark, in that they manipulate multiple fundamental experimental characteristics using the same general experimental design. Importantly, they manipulate the semantic relatedness of the changed item to the original item, the delay between the study experience and the test, and which aspect of the pair is changed. Furthermore, they include both a positive control condition (where the exact same pair is studied twice), and a negative control condition (where a pair is only studied once, in the same phase as the critical base pairs). This allows them to determine when the prior learning exhibits an interfering effect relative to the negative control condition, and also allows them to determine how close any facilitative effects come to matching the positive control.
The results are interpreted in terms of a set of existing theories, most prominently the memory-for-change framework, which proposes a mechanism (recursive reminding) potentially responsible for the facilitative effects examined here. One of the central results is the finding that a stronger semantic relationship between a base pair and an earlier pair has a facilitative effect on both the rate of learning of the base pair and the durability of the memory for the base pair. This is consistent with the memory-for-change framework, which proposes that this semantic relationship prompts retrieval of the earlier pair, and the two pairs are integrated into a common memory structure that contains information about which pair was studied in which phase of the experiment. When semantic relatedness is lower, they more often show interference effects, with the idea being that competition between the stored memories makes it more difficult to remember the base pair.
This work represents a major methodological and empirical advance for our understanding of paired-associates learning, and it sets a laudably high bar for future work seeking to extend this knowledge further. By manipulating so many factors within one set of experiments, it fills a gap in the prior literature regarding the cognitive validity of an 80-year-old proposal by Osgood. The reader can see where the observed results match Osgood's theory and where they are inconclusive. This gives us insight, for example, into the necessity of including a long delay in one's experiment, to observe potential facilitative effects. This point is theoretically interesting, but it is also a boon for future methodological development, in that it establishes the experimental conditions necessary for examining one or another of these facilitation or interference effects more closely.
The authors were exceptionally responsive to the suggestions of the reviewers, and the revisions have improved the theoretical clarity of the paper. I think the value of this work will grow with time, as memory researchers and theorists use it as a benchmark for new theory development. For example, the data from these experiments will undoubtedly be used to develop and constrain a new generation of computational models of paired-associates learning.
Weaknesses:
One minor weakness of the work is that the overarching theoretical framing does not necessarily specify the expected result for each and every one of the many effects examined. For example, with a narrower set of semantic associations being considered (all of which are relatively high associations) and a long delay, varying the semantic relatedness of the target item did not reliably affect the memorability of that pair. However, the same analysis showed a significant effect when the wider set of semantic associations was used. The positive result is consistent with the memory-for-change framework, but the null result isn't clearly informative to the theory. However, research is never done; comparing the results with the two sets of semantic associations is informative from a methodological perspective, in that it establishes the degree to which semantic relatedness must be altered to affect behavioral performance in a paired-associates task.
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Reviewer #1 (Public review):
Somasundaram and colleagues explore the role of transcription factors in retinal ganglion cell (RGC) death and axonal regeneration after a disease relevant insult (mechanical axonal injury). The work significantly extends our knowledge of the role of MAPK and integrated stress response (ISR) in controlling RGC fate after injury. Specifically, the manuscript shows that after axonal injury PERK-activated ISR acts through Atf4 to drive a prodeath transcriptional response in RGCs, in part by crosstalk with the prodeath JUN transcriptional program. Also, and perhaps most interesting, the work shows that PERK-ATF4 pathway activation is pro-regenerative for RGC axons. A major plus of the manuscript is that many new RNA-seq datasets are generated that describe the major prodegenerative and proregenerative gene networks altered after axonal injury. A limitation of the study is that it does not directly compare the effect of inhibiting the PERK-ATF4 pathway with inhibiting JUN and/or JUN-CHOP double deficient animals. It would also be useful, for the cell survival experiments shown in Figure 1, to examine a longer time point than 14 days to understand the long-term consequence of manipulating the PERK-ATF4 pathway.
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Reviewer #1 (Public Review):
Summary:
The authors are interested in the developmental origin of the neurons of the cerebellar nuclei. They identify a population of neurons with a specific complement of markers originating in a distinct location from where cerebellar nuclear precursor cells have been thought to originate that show distinct developmental properties. The cerebellar nuclei have been well studied in recent years to understand their development through an evolutionary lens, which supports the importance of this study. The discovery of a new germinal zone giving rise to a new population of CN neurons is an exciting finding, and it enriches our understanding of cerebellar development, which has previously been quite straightforward, where cerebellar inhibitory cells arise from the ventricular zone and the excitatory cells arise from the rhombic lip.
Strengths:
One of the strengths of the manuscript is that the authors use a wide range of technical approaches, including transgenic mice that allow them to disentangle the influence of distinct developmental organizers such at ATOH.<br /> Their finding of a novel germinal zone and a novel population of CN neurons is important for developmental neuroscientists, cerebellar neuroscientists.
Weaknesses:
One important question raised by this work is what do these newly identified cells eventually become in the adult cerebellum. Are they excitatory or inhibitory? Do they correspond to a novel cell type or perhaps one of the cell classes that have been recently identified in the cerebellum (e.g. Fujita et al., eLife, 2020)? Understanding this would significantly bolster the impact of this manuscript.
The major weakness of the manuscript is that it is written for a very specialized reader who has a strong background in cerebellar development, making it hard to read for eLife's general audience. It's challenging to follow the logic of some of the experiments as well as to contextualize these findings in the field of cerebellar development.
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Reviewer #1 (Public review):
Summary:
Fats and lipids serve many important roles in cancers, including serving as important fuels for energy metabolism in cancer cells by being oxidized in the mitochondria. The process of fatty acid oxidation is initiated by the enzyme carnitine palmitoyltransferase 1A (CPT1A), and the function and targetability of CPT1A in cancer metabolism and biology has been heavily investigated. This includes studies that have found important roles for CPT1A in colorectal cancer growth and metastasis.
In this study, Chen and colleagues use analysis of patient samples and functional interrogation in animal models to examine the role CPT1A plays in colorectal cancer (CRC). The authors find that CPT1A expression is decreased in CRC compared to paired healthy tissue and that lower expression correlates with decreased patient survival over time, suggesting that CPT1A may suppress tumor progression. To functionally interrogate this hypothesis, the authors both use CRISPR to knockout CPT1A in a CRC cell line that expresses CPT1A, and overexpress CPT1A in a CRC cell line with low expression. In both systems, increased CPT1A expression decreased cell survival and DNA repair in response to radiation in culture. Further, in xenograft models CPT1A decreased tumor growth basally and radiotherapy could further decrease tumor growth in CPT1A expressing tumors. As CRC is often treated with radiotherapy, the authors argue this radiosensitization driven by CPT1A could explain why CPT1A expression correlates with increased patient survival.
Lastly, Chen and colleagues sought to understand why CPT1A suppresses CRC tumor growth and sensitizes the tumors to radiotherapy in culture. Antioxidant capacity of cells can increase cell survival, so the authors examine antioxidant gene expression and levels in CPT1A expressing and non-expressing cells. CPT1A expression suppresses expression of antioxidant metabolism genes and lowers levels of antioxidants. Antioxidant metabolism genes can be regulated by the FOXM1 transcription factor, and the authors find that CPT1A expression regulates FOXM1 levels and that antioxidant gene expression can be partially rescued in CPT1A expressing CRC cells. This leads the authors to propose the following model: CPT1A expression downregulates FOXM1 (via some yet undescribed mechanism) which then leads to decreased antioxidant capacity in CRC cells and thus suppressing tumor progression and increasing radiosensitivity. This is an interesting model that could explain suppression of CPT1A expression in CRC, but key tenets of the model are untested and speculative.
Strengths:
• Analysis of CPT1A in paired CRC tumors and non-tumor tissue using multiple modalities combined with analysis of independent datasets rigorously show that CPT1A is downregulated in CRC tumors at the RNA and protein level.<br /> • The authors use paired cell line model systems where CPT1A is both knocked out and overexpressed in cells lines that endogenously express or repress CPT1A respectively. These complementary model systems increase the rigor of the study.<br /> • The finding that a metabolic enzyme generally thought to support tumor energetics actually is a tumor suppressor in some settings is theoretically quite interesting.
Weaknesses:
• The authors propose that CPT1A expression modulates antioxidant capacity in cells by suppressing FOXM1 and that this pathway alters CRC growth and radiotherapy response. However, key aspects of this model are not tested. The authors do not show that FOXM1 contributes to regulation of antioxidant levels in CRC cells and tumors or if FOXM1 suppression is key to inhibition of CRC tumor growth and radiosensitization by CPT1A. Thus, the model the authors propose is speculative and not supported by the existing data.<br /> • The authors propose two mechanisms by which CPT1A expression triggers radiosensitization: decreasing DNA repair capacity (Fig. 3) and decreasing antioxidant capacity (Fig. 5). However, while CPT1A expression does alter these capacities in CRC cells, neither is functionally tested to determine if altered DNA repair or antioxidant capacity (or both) are the reason why CRC cells are more sensitive to radiotherapy or are delayed in causing tumors in vivo. Thus, this aspect of the proposed model is also speculative.<br /> • The authors find that CPT1A affects radiosensitization in cell culture and assess this in vivo. In vivo, CPT1A expression slows tumor growth even in the absence of radiotherapy, and radiotherapy only proportionally decreases tumor growth to the same extent as it does in CPT1A non-expressing CRC tumors. The authors propose from this data that CPT1A expression also sensitizes tumors to radiotherapy in vivo. However, it is unclear that CPT1A expression causes radiosensitization in vivo or if CPT1A expression acts as independent tumor suppressor to which radiotherapy has an additive effect. Additional experiments would be necessary to differentiate between these possibilities.<br /> • The authors propose in Figure 3 that DNA repair capacity is inhibited in CRC cells by CPT1A expression. However, the gH2AX immunoblots performed in Figure 3H-I that measure DNA repair kinetics are not convincing that CPT1A expression impairs DNA repair kinetics. Separate blots are shown for CPT1A expressing and non-expressing cell lines, not allowing for rigorous comparison of gH2AX levels and resolution as CPT1A expression is modulated.
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Reviewer #1 (Public review):
The paper by Chen et al describes the role of neuronal themo-TRPV3 channels in the firing of cortical neurons at a fever temperature range. The authors began by demonstrating that exposure to infrared light increasing ambient temperature causes body temperature to rise to a fever level above 38{degree sign}C. Subsequently, they showed that at the fever temperature of 39{degree sign}C, the spike threshold (ST) increased in both populations (P12-14 and P7-8) of cortical excitatory pyramidal neurons (PNs). However, the spike number only decreased in P7-8 PNs, while it remained stable in P12-14 PNs at 39 degrees centigrade. In addition, the fever temperature also reduced the late peak postsynaptic potential (PSP) in P12-14 PNs. The authors further characterized the firing properties of cortical P12-14 PNs, identifying two types: STAY PNs that retained spiking at 30{degree sign}C, 36{degree sign}C, and 39{degree sign}C, and STOP PNs that stopped spiking upon temperature change. They further extended their analysis and characterization to striatal medium spiny neurons (MSNs) and found that STAY MSNs and PNs shared the same ST temperature sensitivity. Using small molecule tools, they further identified that themo-TRPV3 currents in cortical PNs increased in response to temperature elevation, but not TRPV4 currents. The authors concluded that during fever, neuronal firing stability is largely maintained by sensory STAY PNs and MSNs that express functional TRPV3 channels. Overall, this study is well designed and executed with substantial controls, some interesting findings, and quality of data. Here are some specific comments:
(1) Could the authors discuss, or is there any evidence of, changes in TRPV3 expression levels in the brain during the postnatal 1-4 week age range in mice?
(2) Are there any differential differences in TRPV3 expression patterns that could explain the different firing properties in response to fever temperature between the STAY- and STOP neurons?
(3) TRPV3 and TRPV4 can co-assemble to form heterotetrameric channels with distinct functional properties. Do STOP neurons exhibit any firing behaviors that could be attributed to the variable TRPV3/4 assembly ratio?
(4) In Figure 7, have the authors observed an increase of TRPV3 currents in MSNs in response to temperature elevation?
(5) Is there any evidence of a relationship between TRPV3 expression levels in D2+ MSNs and degeneration of dopamine-producing neurons?
(6) Does fever range temperature alter the expressions of other neuronal Kv channels known to regulate the firing threshold?
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Reviewer #1 (Public review):
In this study, Ma et al. aimed to determine previously uncharacterized contributions of tissue autofluorescence, detector afterpulse, and background noise on fluorescence lifetime measurement interpretations. They introduce a computational framework they named "Fluorescence Lifetime Simulation for Biological Applications (FLiSimBA)" to model experimental limitations in Fluorescence Lifetime Imaging Microscopy (FLIM) and determine parameters for achieving multiplexed imaging of dynamic biosensors using lifetime and intensity. By quantitatively defining sensor photon effects on signal-to-noise in either fitting or averaging methods of determining lifetime, the authors contradict any claims of FLIM sensor expression insensitivity to fluorescence lifetime and highlight how these artifacts occur differently depending on the analysis method. Finally, the authors quantify how statistically meaningful experiments using multiplexed imaging could be achieved.
A major strength of the study is the effort to present results in a clear and understandable way given that most researchers do not think about these factors on a day-to-day basis. The model code is available and written in Matlab, which should make it readily accessible, although a version in other common languages such as Python might help with dissemination in the community. One potential weakness is that the model uses parameters that are determined in a specific way by the authors, and it is not clear how vastly other biological tissue and microscope setups may differ from the values used by the authors.
Overall, the authors achieved their aims of demonstrating how common factors (autofluorescence, background, and sensor expression) will affect lifetime measurements and they present a clear strategy for understanding how sensor expression may confound results if not properly considered. This work should bring to awareness an issue that new users of lifetime biosensors may not be aware of and that experts, while aware, have not quantitatively determined the conditions where these issues arise. This work will also point to future directions for improving experiments using fluorescence lifetime biosensors and the development of new sensors with more favorable properties.
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Reviewer #1 (Public review):
Summary:
Diarrheal diseases represent an important public health issue. Among the many pathogens that contribute to this problem, Salmonella enterica serovar Typhimurium is an important one. Due to the rise in antimicrobial resistance and the problems associated with widespread antibiotic use, the discovery and development of new strategies to combat bacterial infections is urgently needed. The microbiome field is constantly providing us with various health-related properties elicited by the commensals that inhabit their mammalian hosts. Harnessing the potential of these commensals for knowledge about host-microbe interactions as well as useful properties with therapeutic implications will likely remain a fruitful field for decades to come. In this manuscript, Wang et al use various methods, encompassing classic microbiology, genomics, chemical biology, and immunology, to identify a potent probiotic strain that protects nematode and murine hosts from S. enterica infection. Additionally, authors identify gut metabolites that are correlated with protection, and show that a single metabolite can recapitulate the effects of probiotic administration.
Strengths:
The utilization of varied methods by the authors, together with the impressive amount of data generated, to support the claims and conclusions made in the manuscript is a major strength of the work. Also, the ability to move beyond simple identification of the active probiotic, also identifying compounds that are at least partially responsible for the protective effects, is commendable.
Weaknesses:
Although there is a sizeable amount of data reported in the manuscript, there seems to be a chronic issue of lack of details of how some experiments were performed. This is particularly true in the figure legends, which for the most part lack enough details to allow comprehension without constant return to the text. Additionally, 2 figures are missing. Figure 6 is a repetition of Figure 5, and Figure S4 is an identical replicate of Figure S3.
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Reviewer #1 (Public review):
In this manuscript, the authors recorded cerebellar unipolar brush cells (UBCs) in acute brain slices. They confirmed that mossy fiber (MF) inputs generate a continuum of UBC responses. Using systematic and physiological trains of MF electrical stimulation, they demonstrated that MF inputs either increased or decreased UBC firing rates (UBC ON vs. OFF) or induced complex, long-lasting modulation of their discharges. The MF influence on UBC firing was directly associated with a specific combination of metabotropic glutamate receptors, mGluR2/3 (inhibitory) and mGluR1 (excitatory). Ultimately, the amount and ratio of these two receptors controlled the time course of the effect, yielding specific temporal transformations such as phase shifts.
Overall, the topic is compelling, as it broadens our understanding of temporal processing in the cerebellar cortex. The experiments are well-executed and properly analyzed.
Strengths:
(1) A wide range of MF stimulation patterns was explored, including burst duration and frequency dependency, which could serve as a valuable foundation for explicit modeling of temporal transformations in the granule cell layer.
(2) The pharmacological blockade of mGluR2/3, mGluR1, AMPA, and NMDA receptors helped identify the specific roles of these glutamate receptors.
(3) The experiments convincingly demonstrate the key role of mGluR1 receptors in temporal information processing by UBCs.
Weaknesses:
(1) This study is largely descriptive and represents only a modest incremental advance from the previous work (Guo et al., Nat. Commun., 2021).
(2) The MF activity used to mimic natural stimulation was previously collected in primates, while the recordings were conducted in mice.
(3) Inhibition was blocked throughout the study, reducing its physiological relevance.
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Reviewer #1 (Public review):
Summary:
The authors examined whether aberrantly projecting retinal ganglion cells in albino mice innervate a separate population of thalamocortical neurons, as would be predicted for Hebbian learning rules. The authors find support for this hypothesis in correlated light and electron microscopy (CLEM) reconstructions of retinal ganglion cell axons and thalamocortical neurons. In a second line of investigation, the authors ask the same question about retinal ganglion cell innervation of local inhibitory interneurons of the mouse LGN. The authors conclude that these connections are less specific.
Strengths:
The authors make good use of CLEM to test a circuit-level hypothesis, and they find an interesting difference in RGC synaptic innervation patterns for thalamocortical neurons vs. local interneurons.
Weaknesses:
The conclusions about the local interneuron innervation are a little more difficult to interpret. One would expect to only capture a small part of the local interneuron dendritic field, as compared to the smaller thalamocortical neurons, right? Doesn't that imply that finding some evidence of promiscuous connectivity means that other dendrites that were not observed probably connect to many different RGCs?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this study, the authors use ChEC-seq, an MNase based method to map yeast RNA pol II. Part of the reasoning for this study is that earlier biochemical work suggested pol II initiation and termination should involve slow steps at the UAS/promoter and termination regions that are not well visualized by formaldehyde-based ChIP methods. Here the authors find that pol II ChIP and ChEC give complementary patterns. Pol II ChIP signals are strongest in the coding region (where ChIP signal correlates well with transcription (rho = 0.62)). In contrast, pol II ChEC signals are strongest at promoters (rho = 0.52) and terminator regions. Weaker upstream ChEC signals are also observed at the STM class genes where biochemical studies have suggested a form of Pol (and maybe other general factors) is recruited to UAS sites. ChEC of TFIIA and TFIIE give promoter-specific ChEC signals as expected. Extending this work to elongation factors Ctk1 and Spt5 unexpectedly give strong signals near the PIC location and little signals over the coding region. This, and mapping CTD S2 and S5 phosphorylation by ChEC suggests to me that, for some reason, ChEC isn't optimal for detecting components of the elongation complex over coding regions.
Examples are also presented where perturbations of transcription can be measured by ChEC. Modeling studies are shown where adjustment of kinetic parameters agree well with ChEC data and that these models can be used to estimate which steps in transcription are affected by various perturbations. However, no tests were performed to see if the predictions could be validated by other means. Finally, the role of nuclear pore binding by Gcn4 is explored, although the effects are small and this proposal should be explored more completely in future studies. Overall, the authors show that pol II ChEC is a valuable and complementary method for investigating transcription mechanisms and slow steps at the initiation and termination regions.
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public review):
Summary:
In this manuscript, Yan and colleagues introduce a modification to the previously published PETRI-seq bacterial single cell protocol to include a ribosomal depletion step based on a DNA probe set that selectively hybridizes with ribosome-derived (rRNA) cDNA fragments. They show that their modification of the PETRI-seq protocol increases the fraction of informative non-rRNA reads from ~4-10% to 54-92%. The authors apply their protocol to investigating heterogeneity in a biofilm model of E. coli, and convincingly show how their technology can detect minority subpopulations within a complex community.
Strengths:
The method the authors propose is a straightforward and inexpensive modification of an established split-pool single cell RNA-seq protocol that greatly increases its utility, and should be of interest to a wide community working in the field of bacterial single cell RNA-seq.
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Annotators
URL
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The main goal of the paper was to identify signals that activate FLP-1 release from AIY neurons in response to H2O2, previously shown by the authors to be an important oxidative stress response in the worm.
Strengths:
This study builds upon the authors' previous work (Jia and Sieburth 2021) by further elucidating the gut-derived signaling mechanisms that coordinate the organism-wide antioxidant stress response in C. elegans.
By detailing how environmental cues like oxidative stress are transduced into gut-derived peptidergic signals, this study represents a valuable advancement in understanding the integrated physiological responses governed by the gut-brain axis.
This work provides valuable mechanistic insights into the gut-specific regulation of the FLP-2 peptide signal.
Weaknesses:
Although the authors identify intestinal FLP-2 as the endocrine signal important for regulating the secretion of the neuronal antioxidant neuropeptide, FLP-1, there is no effort made to identify how FLP-2 levels regulate FLP-1 secretion or identify whether this regulation is occurring directly through the AIY neuron or indirectly. This is brought up in the discussion, but identifying a target for FLP-2 in this pathway seems like a crucial missing piece of information in characterizing this pathway.
Comments on revised version:
In general I think the revision is improved and addresses my comments. It is unfortunate though that the authors did not address my main question (did they test the frpr-18 mutant, and if not, why?). The fact that there are other potentially relevant receptors which bind to some FLP-2 peptides with low affinity is not really a justification not to test the known high-affinity receptor (i.e. FRPR-18).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The manuscript by Choi and co-authors presents "P3 editing", which leverages dual-component guide RNAs (gRNA) to induce protein-protein proximity. They explore three strategies for leveraging prime-editing gRNA (pegRNA) as a dimerization module to create a molecular proximity sensor that drives genome editing, splitting a pegRNA into two parts (sgRNA and petRNA), inserting self-splicing ribozymes within pegRNA, and dividing pegRNA at the crRNA junction. Among these, splitting at the crRNA junction proved the most promising, achieving significant editing efficiency. They further demonstrated the ability to control genome editing via protein-protein interactions and small molecule inducers by designing RNA-based systems that form active gRNA complexes. This approach was also adaptable to other genome editing methods like base editing and ADAR-based RNA editing.
Strengths:
The study demonstrates significant advancements in leveraging guide RNA (gRNA) as a dimerization module for genome editing, showcasing its high specificity and versatility. By investigating three distinct strategies-splitting pegRNA into sgRNA and petRNA, inserting self-splicing ribozymes within the pegRNA, and dividing the pegRNA at the repeat junction-the researchers present a comprehensive approach to achieving molecular proximity and reconstituting function. Among these methods, splitting the pegRNA at the repeat junction emerged as the most promising, achieving editing efficiencies up to 76% of the control, highlighting its potential for further development in CRISPR-Cas9 systems. Additionally, the study extends genome editing control by linking protein-protein interactions to RNA-mediated editing, using specific protein-RNA interaction pairs to regulate editing through engineered protein proximity. This innovative approach expands the toolkit for precision genome editing, demonstrating the feasibility of controlling genome editing with enhanced specificity and efficiency.
Weaknesses:
The initial experiments with splitting the pegRNA into sgRNA and petRNA showed low editing efficiency, less than 2%. Similarly, inserting self-splicing ribozymes within pegRNA was inefficient, achieving under 2% editing efficiency in all constructs tested, possibly hindered by the prime editing enzyme. The editing efficiency of the crRNA and petracrRNA split at the repeat junction varied, with the most promising configurations only reaching 76% of the control efficiency. The RNA-RNA duplex formation's inefficiency might be due to the lack of additional protein binding, leading to potential degradation outside the Cas9-gRNA complex. Extending the approach to control genome editing via protein-protein interactions introduced complexity, with a significant trade-off between efficiency and specificity, necessitating further optimization. The strategy combining RADARS and P3 editing to control genome editing with specific RNA expression events exhibited high background levels of non-specific editing, indicating the need for improved specificity and reduced leaky expression. Moreover, P3 editing efficiencies are exclusively quantified after transfecting DNA into HEK cells, a strategy that has resulted in past reproducibility concerns for other technologies. Overall, the various methods and combinations require further optimization to enhance efficiency and specificity, especially when integrating multiple synthetic modules.
Comments on revisions:
I think the authors have successfully addressed the initial concerns. Their adaption of the main text and discussion makes the limitations of P3 editing much clearer.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
This study is part of an ongoing effort to clarify the effects of cochlear neural degeneration (CND) on auditory processing in listeners with normal audiograms. This effort is important because ~10% of people who seek help for hearing difficulties have normal audiograms and current hearing healthcare has nothing to offer them.
The authors identify two shortcomings in previous work that they intend to fix. The first is a lack of cross-species studies that make direct comparisons between animal models in which CND can be confirmed and humans for which CND must be inferred indirectly. The second is the low sensitivity of purely perceptual measures to subtle changes in auditory processing. To fix these shortcomings, the authors measure envelope following responses (EFRs) in gerbils and humans using the same sounds, while also performing histological analysis of the gerbil cochleae, and testing speech perception while measuring pupil size in the humans.
The study begins with a comprehensive assessment of the hearing status of the human listeners. The only differences found between the young adult (YA) and middle-aged (MA) groups are in thresholds at frequencies > 10 kHz and DPOAE amplitudes at frequencies > 5 kHz. The authors then present the EFR results, first for the humans and then for the gerbils, showing that amplitudes decrease more rapidly with increasing envelope frequency for MA than for YA in both species. The histological analysis of the gerbil cochleae shows that there were, on average, 20% fewer IHC-AN synapses at the 3 kHz place in MA relative to YA, and the number of synapses per IHC was correlated with the EFR amplitude at 1024 Hz.
The study then returns to the humans to report the results of the speech perception tests and pupillometry. The correct understanding of keywords decreased more rapidly with decreasing SNR in MA than in YA, with a noticeable difference at 0 dB, while pupillary slope (a proxy for listening effort) increased more rapidly with decreasing SNR for MA than for YA, with the largest differences at SNRs between 5 and 15 dB. Finally, the authors report that a linear combination of audiometric threshold, EFR amplitude at 1024 Hz, and a few measures of pupillary slope is predictive of speech perception at 0 dB SNR.
I only have two questions/concerns about the specific methodologies used:
(1) Synapse counts were made only at the 3 kHz place on the cochlea. However, the EFR sounds were presented at 85 dB SPL, which means that a rather large section of the cochlea will actually be excited. Do we know how much of the EFR actually reflects AN fibers coming from the 3 kHz place? And are we sure that this is the same for gerbils and humans given the differences in cochlear geometry, head size, etc.?
(2) Unless I misunderstood, the predictive power of the final model was not tested on held-out data. The standard way to fit and test such a model would be to split the data into two segments, one for training and hyperparameter optimization, and one for testing. But it seems that the only split was for training and hyperparameter optimization.
While I find the study to be generally well executed, I am left wondering what to make of it all. The purpose of the study with respect to fixing previous methodological shortcomings was clear, but exactly how fixing these shortcomings has allowed us to advance is not. I think we can be more confident than before that EFR amplitude is sensitive to CND, and we now know that measures of listening effort may also be sensitive to CND. But where is this leading us?
I think what this line of work is eventually aiming for is to develop a clinical tool that can be used to infer someone's CND profile. That seems like a worthwhile goal but getting there will require going beyond exploratory association studies. I think we're ready to start being explicit about what properties a CND inference tool would need to be practically useful. I have no idea whether the associations reported in this study are encouraging or not because I have no idea what level of inferential power is ultimately required.
That brings me to my final comment: there is an inappropriate emphasis on statistical significance. The sample size was chosen arbitrarily. What if the sample had been half the size? Then few, if any, of the observed effects would have been significant. What if the sample had been twice the size? Then many more of the observed effects would have been significant (particularly for the pupillometry). I hope that future studies will follow a more principled approach in which relevant effect sizes are pre-specified (ideally as the strength of association that would be practically useful) and sample sizes are determined accordingly.
So, in summary, I think this study is a valuable but limited advance. The results increase my confidence that non-invasive measures can be used to infer underlying CND, but I am unsure how much closer we are to anything that is practically useful.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors test the "OHC-fluid-pump" hypothesis by assaying the rates of kainic acid dispersal both in quiet and in cochleae stimulated by sounds of different levels and spectral content. The main result is that sound (and thus, presumably, OHC contractions and expansions) result in faster transport along the duct. OHC involvement is corroborated using salicylate, which yielded results similar to silence. Especially interesting is the fact that some stimuli (e.g., tones) seem to provide better/faster pumping than others (e.g., noise), ostensibly due to the phase profile of the resulting cochlear traveling-wave response.
Strengths:
The experiments appear well controlled and the results are novel and interesting. Some elegant cochlear modeling that includes coupling between the organ of Corti and the surrounding fluid as well as advective flow supports the proposed mechanism.
The current limitations and future directions of the study, including possible experimental tests, extensions of the modeling work, and practical applications to drug delivery, are thoughtfully discussed.
Weaknesses:
Although the authors provide compelling evidence that OHC motility can usefully pump fluid, their claim (last sentence of the Abstract) that wideband OHC motility (i.e., motility in the "tail" region of the traveling wave) evolved for the purposes of circulating fluid---rather then emerging, say, as a happy by-product of OHC motility that evolved for other reasons---seems too strong.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this paper, Thomas et al. set out to study seasonal brain gene expression changes in the Eurasian common shrew. This mammalian species is unusual in that it does not hibernate or migrate but instead stays active all winter while shrinking and then regrowing its brain and other organs. The authors previously examined gene expression changes in two brain regions and the liver. Here, they added data from the hypothalamus, a brain region involved in the regulation of metabolism and homeostasis. The specific goals were to identify genes and gene groups that change expression with the seasons and to identify genes with unusual expression compared to other mammalian species. The reason for this second goal is that genes that change with the season could be due to plastic gene regulation, where the organism simply reacts to environmental change using processes available to all mammals. Such changes are not necessarily indicative of adaptation in the shrew. However, if the same genes are also expression outliers compared to other species that do not show this overwintering strategy, it is more likely that they reflect adaptive changes that contribute to the shrew's unique traits.
The authors succeeded in implementing their experimental design and identified significant genes in each of their specific goals. There was an overlap between these gene lists. The authors provide extensive discussion of the genes they found.
The scope of this paper is quite narrow, as it adds gene expression data for only one additional tissue compared to the authors' previous work in a 2023 preprint. The two papers even use the same animals, which had been collected for that earlier work. As a consequence, the current paper is limited in the results it can present. This is somewhat compensated by an expansive interpretation of the results in the discussion section, but I felt that much of this was too speculative. More importantly, there are several limitations to the design, making it hard to draw stronger conclusions from the data. The main contribution of this work lies in the generated data and the formulation of hypotheses to be tested by future work.
Strengths:
The unique biological model system under study is fascinating. The data were collected in a technically sound manner, and the analyses were done well. The paper is overall very clear, well-written, and easy to follow. It does a thorough job of exploring patterns and enrichments in the various gene sets that are identified.
I specifically applaud the authors for doing a functional follow-up experiment on one of the differentially expressed genes (BCL2L1), even if the results did not support the hypothesis. It is important to report experiments like this and it is terrific to see it done here.
Weaknesses:
While the paper successfully identifies differentially expressed seasonal genes, the real question is (as explained by the authors) whether these are evolved adaptations in the shrews or whether they reflect plastic changes that also exist in other species. This question was the motivation for the inter-species analyses in the paper, but in my view, these cannot rigorously address this question. Presumably, the data from the other species were not collected in comparable environments as those experienced by the shrews studied here. Instead, they likely (it is not specified, and might not be knowable for the public data) reflect baseline gene expression. To see why this is problematic, consider this analogy: if we were to compare gene expression in the immune system of an individual undergoing an acute infection to other, uninfected individuals, we would see many, strong expression differences. However, it would not be appropriate to claim that the infected individual has unique features - the relevant physiological changes are simply not triggered in the other individuals. The same applies here: it is hard to draw conclusions from seasonal expression data in the shrews to non-seasonal data in the other species, as shrew outlier genes might still reflect physiological changes that weren't active in the other species.
There is no solution for this design flaw given the public data available to the authors except for creating matched data in the other species, which is of course not feasible. The authors should acknowledge and discuss this shortcoming in the paper.
Related to the point above: in the section "Evolutionary Divergence in Expression" it is not clear which of the shrew samples were used. Was it all of them, or only those from winter, fall, etc? One might expect different results depending on this. E.g., there could be fewer genes with inferred adaptive change when using only summer samples. The authors should specify which samples were included in these analyses, and, if all samples were used, conduct a robustness analysis to see which of their detected genes survive the exclusion of certain time points.
In the same section, were there also genes with lower shrew expression? None are mentioned in the text, so did the authors not test for this direction, or did they test and there were no significant hits?
The Discussion is too long and detailed, given that it can ultimately only speculate about what the various expression changes might mean. Many of the specific points made (e.g. about the blood-brain-barrier being more permissive to sensing metabolic state, about cross-organ communication, the paragraphs on single, specific genes) are a stretch based on the available data. Illustrating this point, the one follow-up experiment the authors did (on BCL2L1) did not give the expected result. I really applaud the authors for having done this experiment, which goes beyond typical studies in this space. At the same time, its result highlights the dangers of reading too much into differential expression analyses.
There is no test of whether the five genes observed in both analyses (seasonal change and inter-species) exceed the number expected by chance. When two gene sets are drawn at random, some overlap is expected randomly. The expected overlap can be computed by repeated draws of pairs of random sets of the same size as seen in real data and by noting the overlap between the random pairs. If this random distribution often includes sets of five genes, this weakens the conclusions that can be drawn from the genes observed in the real data.
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www.linkedin.com www.linkedin.com
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Prof. Smith lives in London and has a brother in Berlin, Dr. Smith. To visit him, balancing time, cost, and carbon emissions is a tough call to make. But there is another problem. Dr. Smith has no brother in London. How can that be?
for - BEing journey - example - demonstrates system 1 vs system 2 thinking - example - unconscious bias - example - symbolic incompleteness
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This paper reports an interesting and clever task that allows the joint measurement of both perceptual judgments and confidence (or subjective motion strength) in real/continuous time. The task is used together with a social condition to identify the (incidental, task-irrelevant) impact of another player on decision-making and confidence.
Strengths:
The innovation on the task alone is likely to be impactful for the field, extending recent continuous report (CPR) tasks to examine other aspects of perceptual decision-making and allowing more naturalistic readouts. One interesting and novel finding is the observation of dyadic convergence of confidence estimates even when the partner is incidental to the task performance, and that dyads tend to be more risk-seeking (indicating greater confidence) than when playing solo. The paper is well-written and clear.
Weaknesses:
(1) One concern with the novel task is whether confidence is disambiguated from a tracking of stimulus strength or coherence. The subjects' task is to track motion direction and use the eccentricity of the joystick to control the arc of a catcher - thus implementing a real-time sensitivity to risk (peri-decision wagering). The variable-width catcher has been used to good effect in other confidence/uncertainty tasks involving learning the spread of targets (the Nassar papers). But in the context of an RDK task, one simple strategy here is to map eccentricity directly to (subjective) motion coherence - such that the joystick position at any moment in time is a vector with motion direction and strength. This would still be an interesting task - but could be solved without invoking metacognition or the need to estimate confidence in one's motion direction decision (the analyses in Supplementary Figure 2 are nice in showing a dissociation from (objective) coherence, such that even within a coherence level, changes in eccentricity scale with direction precision - but this does not get around the potential conflation of confidence with fluctuations in motion energy).
In other words, in this deflationary framing, what the subjects might be doing is tracking two features of the world - motion strength and direction. This possibility needs to be ruled out if the authors want to claim a mapping between eccentricity and decision confidence (for instance, an ideal observer model of the task that set eccentricity proportional to instantaneous motion strength presumably would also sensibly accrue reward targets, without the need to compute confidence in the direction response). This would be straightforward to simulate and would establish a baseline model against which to compare claims about confidence (eg when evaluating additional social modulations). More generally it casts doubt on claims such as the one on line 210 that eccentricity was "chosen freely via metacognitive assessment of the current perceptual process, [and] can be treated as a proxy measure of subjective perceptual confidence."
One route to doing this would be to ask whether the eccentricity reports show statistical signatures of confidence that have been established for more classical punctate tasks. Here a key move has been to identify qualitative patterns in the frame of reference of choice accuracy - with confidence scaling positively with stimulus strength for correct decisions, and negatively with stimulus strength for incorrect decisions (the so-called X-pattern, for instance Sanders et al. 2016 Neuron https://pubmed.ncbi.nlm.nih.gov/27151640/).
(2) I was surprised not to see more analysis of the continuous report data as a function of (lagged) task variables. Some of this analysis is shown in Figure 2b relative to an (objective) direction change, and also in the cross-correlation plots in Supplementary Figure 1d. But to fully characterise the task behaviour it also seems important to ask how and whether fluctuations in motion energy (assuming that the RDK frames were recorded) during a steady state phase are affecting continuous reporting of direction and eccentricity, prior to asking how social information is incorporated into subjects' behaviour.
Minor points:
(1) Lines 295-298, isn't it guaranteed to observe these three behavioural patterns (both participants improving, both getting worse, only one improving while the other gets worse) even in random data?
(2) Lines 703-707, it wasn't clear what the AUC values referred to here (also in Figure 3) - what are the distributions that are being compared? I think part of the confusion here comes from AUC being mentioned earlier in the paper as a measure of metacognitive sensitivity (correct vs. incorrect trial distributions), whereas my impression here is that here AUC is being used to investigate differences in variables (eg confidence) between experimental conditions.
(3) Could the findings of the worse solo player benefitting more than the better solo player (Figure 4c) be partly due to a compressive ceiling effect - eg there is less room to move up the psychometric function for the higher-scoring player?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This manuscript explores the transcriptional landscape of high-grade serous ovarian cancer (HGSOC) using consensus-independent component analysis (c-ICA) to identify transcriptional components (TCs) associated with patient outcomes. The study analyzes 678 HGSOC transcriptomes, supplemented with 447 transcriptomes from other ovarian cancer types and noncancerous tissues. By identifying 374 TCs, the authors aim to uncover subtle transcriptional patterns that could serve as novel drug targets. Notably, a transcriptional component linked to synaptic signaling was associated with shorter overall survival (OS) in patients, suggesting a potential role for neuronal interactions in the tumor microenvironment. Given notable weaknesses like lack of validation cohort or validation using another platform (other than the 11 samples with ST), the data is considered highly descriptive and preliminary.
Strengths:
(1) Innovative Methodology:<br /> The use of c-ICA to dissect bulk transcriptomes into independent components is a novel approach that allows for the identification of subtle transcriptional patterns that may be overshadowed in traditional analyses.
(2) Comprehensive Data Integration:<br /> The study integrates a large dataset from multiple public repositories, enhancing the robustness of the findings. The inclusion of spatially resolved transcriptomes adds a valuable dimension to the analysis.
(3) Clinical Relevance:<br /> The identification of a synaptic signaling-related TC associated with poor prognosis highlights a potential new avenue for therapeutic intervention, emphasizing the role of the tumor microenvironment in cancer progression.
Weaknesses:
(1) Mechanistic Insights:<br /> While the study identifies TCs associated with survival, it provides limited mechanistic insights into how these components influence cancer progression. Further experimental validation is necessary to elucidate the underlying biological processes.
(2) Generalizability:<br /> The findings are primarily based on transcriptomic data from HGSOC. It remains unclear how these results apply to other subtypes of ovarian cancer or different cancer types.
(3) Innovative Methodology:<br /> Requires more validation using different platforms (IHC) to validate the performance of this bulk-derived data. Also, the lack of control over data quality is a concern.
(4) Clinical Application:<br /> Although the study suggests potential drug targets, the translation of these findings into clinical practice is not addressed. Probably given the lack of some QA/QC procedures it'll be hard to translate these results. Future studies should focus on validating these targets in clinical settings.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In the present study, Chen et al. investigate the role of Endophilin A1 in regulating GABAergic synapse formation and function. To this end, the authors use constitutive or conditional knockout of Endophilin A1 (EEN1) to assess the consequences on GABAergic synapse composition and function, as well as the outcome for PTZ-induced seizure susceptibility. The authors show that EEN1 KO mice show a higher susceptibility to PTZ-induced seizures, accompanied by a reduction in the GABAergic synaptic scaffolding protein gephyrin as well as specific GABAAR subunits and eIPSCs. The authors then investigate the underlying mechanisms, demonstrating that Endophilin A1 binds directly to gephyrin and GABAAR subunits, and identifying the subdomains of Endophilin A1 that contribute to this effect. Overall, the authors state that their study places Endophilin A1 as a new regulator of GABAergic synapse function.
Strengths:
Overall, the topic of this manuscript is very timely, since there has been substantial recent interest in describing the mechanisms governing inhibitory synaptic transmission at GABAergic synapses. The study will therefore be of interest to a wide audience of neuroscientists studying synaptic transmission and its role in disease. The manuscript is well-written and contains a substantial quantity of data.
Weaknesses:
A number of questions remain to be answered in order to be able to fully evaluate the quality and conclusions of the study. In particular, a key concern throughout the manuscript regards the way that the number of samples for statistical analysis is defined, which may affect the validity of the data analysed. Addressing this weakness will be essential to providing conclusive results that support the authors' claims.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Dendrotweaks provides its users with a solid tool to implement, visualize, tune, validate, understand, and reduce single-neuron models that incorporate complex dendritic arbors with differential distribution of biophysical mechanisms. The visualization of dendritic segments and biophysical mechanisms therein provide users with an intuitive way to understand and appreciate dendritic physiology.
Strengths:
(1) The visualization tools are simplified, elegant, and intuitive.
(2) The ability to build single-neuron models using simple and intuitive interfaces.
(3) The ability to validate models with different measurements.
(4) The ability to systematically and progressively reduce morphologically-realistic neuronal models.
Weaknesses:
(1) Inability to account for neuron-to-neuron variability in structural, biophysical, and physiological properties in the model-building and validation processes.
(2) Inability to account for the many-to-many mapping between ion channels and physiological outcomes. Reliance on hand-tuning provides a single biased model that does not respect pronounced neuron-to-neuron variability observed in electrophysiological measurements.
(3) Lack of a demonstration on how to connect reduced models into a network within the toolbox.
(4) Lack of a set of tutorials, which is common across many "Tools and Resources" papers, that would be helpful in users getting acquainted with the toolbox.
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osf.io osf.io
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Reviewer #1 (Public review):
Summary:
This manuscript uses a well-validated behavioral estimation task to investigate the degree to which optimistic belief updating was attenuated during the 2020 global pandemic. Online participants recruited during and outside of the pandemic estimated how likely different negative life events were to happen to them in the future and were given statistics about these events happening. Belief updating (measured as the degree to which estimations changed after viewing the statistics) was less optimistically biased during the pandemic (compared to outside of it). This resulted from reduced updating from "good news" (better than expected information). Computational models were used to try to unpack how statistics were integrated and used to revise beliefs. Two families of models were compared - an RL set of models where "estimation errors" (analogous to prediction errors in classic RL models) predict belief change and a Bayesian set of models where an implied likelihood ratio was calculated (derived from participants estimations of their own risk and estimation of the base rate risk) and used to predict belief change. The authors found evidence that the former set of models accounted for updating better outside of the pandemic, but the latter accounted for updating during the pandemic. In addition, the RL model provides evidence that learning was asymmetrically positively biased outside of the pandemic but symmetric during it (as a result of reduced learning rates from good news estimation errors).
Strengths:
Understanding whether biases in learning are fixed modes of information processing or flexible and adapt in response to environmental shocks (like a global pandemic or economic recession) is an important area of research relevant to a wide range of fields, including cognitive psychology, behavioral economics, and computational psychiatry. The study uses a well-validated task, and the authors conduct a power analysis to show that the sample sizes are appropriate. Furthermore, the authors test that their results hold in both a between-group analysis (the focus of the main paper) and a within-group analysis (mainly in the supplemental).
The finding that optimistic biases are reduced in response to acute stress, perceived threat, and depression has been shown before using this task both in the lab (social stress manipulation), in the real world (firefighters on duty), and clinical groups (patients with depression). However, the work does extend these findings here in important ways:
(1) Examining the effect of a new real-world adverse event (the pandemic).<br /> (2) The reduction in optimistic updating here arises due to reduced updating from positive information (previously, in the case of environmental threat, this reduction mainly arose from increased sensitivity to negative information).<br /> (3) Leveraging new RL-inspired computational approaches, demonstrating that the bias - and its attenuation - can be captured using trial-by-trial computational modeling with separate learning rates for positive and negative estimation errors.
Weaknesses:
Some interpretation and analysis (the computational modeling in particular) could be improved.
On the interpretation side, while the pandemic was an adverse experience and stressful for many people (including myself), the absence of any measures of stress/threat levels limits the conclusions one can draw. Past work that has used this task to examine belief updating in response to adverse environmental events took physiological (e.g., SCR, cortisol) and/or self-report (questionnaires) measures of mood. In SI Table 1, the authors possibly had some questionnaire measures along these lines, but this might be for the participants tested during the pandemic.
On the analysis side, it was unclear what the motivation was for the different sets of models tested. Both families of models test asymmetric vs symmetric learning (which is the main question here) and have similar parameters (scaling and asymmetry parameters) to quantify these different aspects of the learning process. Conceptually, the different behavioral patterns one could expect from the two families of models needed to be clarified. Do the "winning" models produce the main behavioral patterns in Figure 1, and are they in some way uniquely able to do so, for instance? How would updating look different for an optimistic RL learner versus an optimistic Bayesian RL learner? Would the asymmetry parameter in the former be correlated with the asymmetry parameter in the latter? Moreover, crucially, would one be able to reliably distinguish the models from one another under the model estimation and selection criteria that the authors have used here (presenting robust model recovery could help to show this)?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
First, the authors confirm the up-regulation of the main genes involved in the three branches of the Unfolded Protein Response (UPR) system in diet-induced obese mice in AT, observations that have been extensively reported before. Not surprisingly, IRE1a inhibition with STF led to an amelioration of the obesity and insulin resistance of the animals. Moreover, non-alcoholic fatty liver disease was also improved by the treatment. More novel are their results in terms of thermogenesis and energy expenditure, where IRE1a seems to act via activation of brown AT. Finally, mice treated with STF exhibited significantly fewer metabolically active and M1-like macrophages in the AT compared to those under vehicle conditions. Overall, the authors conclude that targeting IRE1a has therapeutical potential for treating obesity and insulin resistance.
The study has some strengths, such as the detailed characterization of the effect of STF in different fat depots and a thorough analysis of macrophage populations. However, the lack of novelty in the findings somewhat limits the study´s impact on the field.
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Reviewer #1 (Public review):
This study examined the interaction between two key cortical regions in the mouse brain involved in goal-directed movements, the rostral forelimb area (RFA) - considered a premotor region involved in movement planning, and the caudal forelimb area (CFA) - considered a primary motor region that more directly influences movement execution. The authors ask whether there exists a hierarchical interaction between these regions, as previously hypothesized, and focus on a specific definition of hierarchy - examining whether the neural activity in the premotor region exerts a larger functional influence on the activity in the primary motor area than vice versa. They examine this question using advanced experimental and analytical methods, including localized optogenetic manipulation of neural activity in either region while measuring both the neural activity in the other region and EMG signals from several muscles involved in the reaching movement, as well as simultaneous electrophysiology recordings from both regions in a separate cohort of animals.
The findings presented show that localized optogenetic manipulation of neural activity in either RFA or CFA resulted in similarly short-latency changes in the muscle output and in firing rate changes in the other region. However, perturbation of RFA led to a larger absolute change in the neural activity of CFA neurons. The authors interpret these findings as evidence for reciprocal, but asymmetrical, influence between the regions, suggesting some degree of hierarchy in which RFA has a greater effect on the neural activity in CFA. They go on to examine whether this asymmetry can also be observed in simultaneously recorded neural activity patterns from both regions. They use multiple advanced analysis methods that either identify latent components at the population level or measure the predictability of firing rates of single neurons in one region using firing rates of single neurons in the other region. Interestingly, the main finding across these analyses seems to be that both regions share highly similar components that capture a high degree of variability of the neural activity patterns in each region. Single units' activity from either region could be predicted to a similar degree from the activity of single units in the other region, without a clear division into a leading area and a lagging area, as one might expect to find in a simple hierarchical interaction. However, the authors find some evidence showing a slight bias towards leading activity in RFA. Using a two-region neural network model that is fit to the summed neural activity recorded in the different experiments and to the summed muscle output, the authors show that a network with constrained (balanced) weights between the regions can still output the observed measured activities and the observed asymmetrical effects of the optogenetic manipulations, by having different within-region local weights. These results put into question whether previous and current findings that demonstrate asymmetry in the output of regions can be interpreted as evidence for asymmetrical (and thus hierarchical) inputs between regions, emphasizing the challenges in studying interactions between any brain regions.
Strengths:
The experiments and analyses performed in this study are comprehensive and provide a detailed examination and comparison of neural activity recorded simultaneously using dense electrophysiology probes from two main motor regions that have been the focus of studies examining goal-directed movements. The findings showing reciprocal effects from each region to the other, similar short-latency modulation of muscle output by both regions, and similarity of neural activity patterns without a clear lead/lag interaction, are convincing and add to the growing body of evidence that highlight the complexity of the interactions between multiple regions in the motor system and go against a simple feedforward-like network and dynamics. The neural network model complements these findings and adds an important demonstration that the observed asymmetry can, in theory, also arise from differences in local recurrent connections and not necessarily from different input projections from one region to the other. This sheds an important light on the multiple factors that should be considered when studying the interaction between any two brain regions, with a specific emphasis on the role of local recurrent connections, that should be of interest to the general neuroscience community.
Weaknesses:
While the similarity of the activity patterns across regions and lack of a clear leading/lagging interaction are interesting observations that are mostly supported by the findings presented (however, see comment below for lack of clarity in CCA/PLS analyses), the main question posed by the authors - whether there exists an endogenous hierarchical interaction between RFA and CFA - seems to be left largely open. The authors note that there is currently no clear evidence of asymmetrical reciprocal influence between naturally occurring neural activity patterns of the two regions, as previous attempts have used non-natural electrical stimulation, lesions, or pharmacological inactivation. The use of acute optogenetic perturbations does not seem to be vastly different in that aspect, as it is a non-natural stimulation of inhibitory interneurons that abruptly perturbs the ongoing dynamics. Furthermore, the main finding that supports a hierarchical interaction is a difference in the absolute change of firing rates as a result of the optogenetic perturbation, a finding that is based on a small number of animals (N = 3 in each experimental group), and one which may be difficult to interpret. As the authors nicely demonstrate in their neural network model, the two regions may differ in the strength of local within-region inhibitory connections. Could this theoretically also lead to a difference in the effect of the artificial light stimulation of the inhibitory inter-neurons on the local population of excitatory projection neurons, driving an asymmetrical effect on the downstream region? Moreover, the manipulation was performed upon the beginning of the reaching movement, while the premotor region is often hypothesized to exert its main control during movement preparation, and thus possibly show greater modulation during that movement epoch. It is not clear if the observed difference in absolute change is dependent on the chosen time of optogenetic stimulation and if this effect is a general effect that will hold if the stimulation is delivered during different movement epochs, such as during movement preparation.
Another finding that is not clearly interpretable is in the analysis of the population activity using CCA and PLS. The authors show that shifting the activity of one region compared to the other, in an attempt to find the optimal leading/lagging interaction, does not affect the results of these analyses. Assuming the activities of both regions are better aligned at some unknown ground-truth lead/lag time, I would expect to see a peak somewhere in the range examined, as is nicely shown when running the same analyses on a single region's activity. If the activities are indeed aligned at zero, without a clear leading/lagging interaction, but the results remain similar when shifting the activities of one region compared to the other, the interpretation of these analyses is not clear.
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Reviewer #1 (Public review):
This study investigates how ant group demographics influence nest structures and group behaviors of Camponotus fellah ants, a ground-dwelling carpenter ant species (found locally in Israel) that build subterranean nest structures. Using a quasi-2D cell filled with artificial sand, the authors perform two complementary sets of experiments to try to link group behavior and nest structure: first, the authors place a mated queen and several pupae into their cell and observe the structures that emerge both before and after the pupae eclose (i.e., "colony maturation" experiments); second, the authors create small groups (of 5,10, or 15 ants, each including a queen) within a narrow age range (i.e., "fixed demographic" experiments) to explore the dependence of age on construction. Some of the fixed demographic instantiations included a manually induced catastrophic collapse event; the authors then compared emergency repair behavior to natural nest creation. Finally, the authors introduce a modified logistic growth model to describe the time-dependent nest area. The modification introduces parameters that allow for age-dependent behavior, and the authors use their fixed demographic experiments to set these parameters, and then apply the model to interpret the behavior of the colony maturation experiments. The main results of this paper are that for natural nest construction, nest areas, and morphologies depend on the age demographics of ants in the experiments: younger ants create larger nests and angled tunnels, while older ants tend to dig less and build predominantly vertical tunnels; in contrast, emergency response seems to elicit digging in ants of all ages to repair the nest.
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Reviewer #1 (Public review):
Summary:
The authors introduce a novel algorithm for the automatic identification of long-range axonal projections. This is an important problem as modern high-throughput imaging techniques can produce large amounts of raw data, but identifying neuronal morphologies and connectivities requires large amounts of manual work. The algorithm works by first identifying points in three-dimensional space corresponding to parts of labelled neural projections, these are then used to identify short sections of axons using an optimisation algorithm and the prior knowledge that axonal diameters are relatively constant. Finally, a statistical model that assumes axons tend to be smooth is used to connect the sections together into complete and distinct neural trees. The authors demonstrate that their algorithm is far superior to existing techniques, especially when dense labelling of the tissue means that neighbouring neurites interfere with the reconstruction. Despite this improvement, however, the accuracy of reconstruction remains below 90%, so manual proofreading is still necessary to produce accurate reconstructions of axons.
Strengths:
The new algorithm combines local and global information to make a significant improvement on the state-of-the-art for automatic axonal reconstruction. The method could be applied more broadly and might have applications to reconstructions of electron microscopy data, where similar issues of high-throughput imaging and relatively slow or inaccurate reconstruction remain.
Weaknesses:
There are three weaknesses in the algorithm and manuscript.
(1) The best reconstruction accuracy is below 90%, which does not fully solve the problem of needing manual proofreading.
(2) The 'minimum information flow tree' model the authors use to construct connected axonal trees has the potential to bias data collection. In particular, the assumption that axons should always be as smooth as possible is not always correct. This is a good rule-of-thumb for reconstructions, but real axons in many systems can take quite sharp turns and this is also seen in the data presented in the paper (Figure 1C). I would like to see explicit acknowledgement of this bias in the current manuscript and ideally a relaxation of this rule in any later versions of the algorithm.
(3) The writing of the manuscript is not always as clear as it could be. The manuscript would benefit from careful copy editing for language, and the Methods section in particular should be expanded to more clearly explain what each algorithm is doing. The pseudo-code of the Supplemental Information could be brought into the Methods if possible as these algorithms are so fundamental to the manuscript.
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Reviewer #1 (Public review):
Summary:
Zhang et al. addressed the question of whether hyperaltruistic preference is modulated by decision context, and tested how oxytocin (OXT) may modulate this process. Using an adapted version of a previously well-established moral decision-making task, healthy human participants in this study undergo decisions that gain more (or lose less, termed as context) meanwhile inducing more painful shocks to either themselves or another person (recipient). The alternative choice is always less gain (or more loss) meanwhile less pain. Through a series of regression analyses, the authors reported that hyperaltruistic preference can only be found in the gain context but not in the loss context, however, OXT reestablished the hyperaltruistic preference in the loss context similar to that in the gain context.
Strengths:
This is a solid study that directly adapted a previously well-established task and the analytical pipeline to assess hyperaltruistic preference in separate decision contexts. Context-dependent decisions have gained more and more attention in literature in recent years, hence this study is timely. It also links individual traits (via questionnaires) with task performance, to test potential individual differences. The OXT study is done with great methodological rigor, including pre-registration. Both studies have proper power analysis to determine the sample size.
Weaknesses:
Despite the strengths, multiple analytical decisions have to be explained, justified, or clarified. Also, there is scope to enhance the clarity and coherence of the writing - as it stands, readers will have to go back and forth to search for information. Last, it would be helpful to add line numbers in the manuscript during the revision, as this will help all reviewers to locate the parts we are talking about.
(1) Introduction:<br /> The introduction is somewhat unmotivated, with key terms/concepts left unexplained until relatively late in the manuscript. One of the main focuses in this work is "hyperaltruistic", but how is this defined? It seems that the authors take the meaning of "willing to pay more to reduce other's pain than their own pain", but is this what the task is measuring? Did participants ever need to PAY something to reduce the other's pain? Note that some previous studies indeed allow participants to pay something to reduce other's pain. And what makes it "HYPER-altruistic" rather than simply "altruistic"? Plus, in the intro, the authors mentioned that the "boundary conditions" remain unexplored, but this idea is never touched again. What do boundary conditions mean here in this task? How do the results/data help with finding out the boundary conditions? Can this be discussed within wider literature in the Discussion section? Last, what motivated the authors to examine the decision context? It comes somewhat out of the blue that the opening paragraph states that "We set out to [...] decision context", but why? Are there other important factors? Why decision context is more important than studying those others?
(2) Experimental Design:<br /> (2a) The experiment per se is largely solid, as it followed a previously well-established protocol. But I am curious about how the participants got instructed? Did the experimenter ever mention the word "help" or "harm" to the participants? It would be helpful to include the exact instructions in the SI.
(2b) Relatedly, the experimental details were not quite comprehensive in the main text. Indeed, the Methods come after the main text, but to be able to guide readers to understand what was going on, it would be very helpful if the authors could include some necessary experimental details at the beginning of the Results section.
(3) Statistical Analysis<br /> (3a) One of the main analyses uses the harm aversion model (Eq1) and the results section keeps referring to one of the key parameters of it (ie, k). However, it is difficult to understand the text without going to the Methods section below. Hence it would be very helpful to repeat the equation also in the main text. A similar idea goes to the delta_m and delta_s terms - it will be very helpful to give a clear meaning of them, as nearly all analyses rely on knowing what they mean.
(3b) There is one additional parameter gamma (choice consistency) in the model. Did the authors also examine the task-related difference of gamma? This might be important as some studies have shown that the other-oriented choice consistency may differ in different prosocial contexts.
(3c) I am not fully convinced that the authors included two types of models: the harm aversion model and the logistic regression models. Indeed, the models look similar, and the authors have acknowledged that. But I wonder if there is a way to combine them? For example:<br /> Choice ~ delta_V * context * recipient (*Oxt_v._placebo)<br /> The calculation of delta_V follows Equation 1.<br /> Or the conceptual question is, if the authors were interested in the specific and independent contribution of dalta_m and dalta_s to behavior, as their logistic model did, why did the authors examine the harm aversion first, where a parameter k is controlling for the trade-off? One way to find it out is to properly run different models and run model comparisons. In the end, it would be beneficial to only focus on the "winning" model to draw inferences.
(3d) The interpretation of the main OXT results needs to be more cautious. According to the operationalization, "hyperaltruistic" is the reduction of pain of others (higher % of choosing the less painful option) relative to the self. But relative to the placebo (as baseline), OXT did not increase the % of choosing the less painful option for others, rather, it decreased the % of choosing the less painful option for themselves. In other words, the degree of reducing other's pain is the same under OXT and placebo, but the degree of benefiting self-interest is reduced under OXT. I think this needs to be unpacked, and some of the wording needs to be changed. I am not very familiar with the OXT literature, but I believe it is very important to differentiate whether OXT is doing something on self-oriented actions vs other-oriented actions. Relatedly, for results such as that in Figure 5A, it would be helpful to not only look at the difference but also the actual magnitude of the sensitivity to the shocks, for self and others, under OXT and placebo.
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Reviewer #1 (Public review):
The paper by Auer et. makes several contributions:
(1) The study developed a novel approach to map the microstructural organization of the human amygdala by applying radiomics and dimensionality reduction techniques to high-resolution histological data from the BigBrain dataset.
(2) The method identified two main axes of microstructural variation in the amygdala, which could be translated to in vivo 7 Tesla MRI data in individual subjects.
(3) Functional connectivity analysis using resting-state fMRI suggests that microstructurally defined amygdala subregions had distinct patterns of functional connectivity to cortical networks, particularly the limbic, frontoparietal, and default mode networks.
(4) Meta-analytic decoding was used to suggest that the superior amygdala subregion's connectivity is associated with autobiographical memory, while the inferior subregion was linked to emotional face processing.
(5) Overall, the data-driven, multimodal approach provides an account of amygdala microstructure and possibly function that can be applied at the individual subject level, potentially advancing research on amygdala organization.
Although these are meritorious contributions there are some concerns that I will summarize below.
(1) The paper makes little-to-no contact with the monkey literature regarding the anatomy of amygdala subregions, their functionality, and their patterns of anatomical connectivity. This is surprising because such literature on non-human primates is a very important starting point for understanding the human amygdala. I recommend taking a careful look at the work by Helen Barbas, among others. There are too many papers to cite but a notable example is: Ghashghaei, H. T., Hilgetag, C. C., & Barbas, H. (2007). Sequence of information processing for emotions based on the anatomic dialogue between prefrontal cortex and amygdala. Neuroimage, 34(3), 905-923. The work of Amaral is also highly relevant. Furthermore, the authors subscribe to a model with LB, CM, and SF sectors. How does the SF sector relate to monkey anatomy?
(2) The authors use meta-analytical decoding via NeuroSynth. If the authors like those results of course they should keep them but the quality of coordinate reporting in the literature is insufficient to conclude much in the context of amygdala subregion function in my opinion. I believe the results reported are at most "somewhat suggestive".
(3) Another significant concern has to do with the results in Figure 3. The red and yellow clusters identified are quite distinct but the differences in functional connectivity are very modest. Figure 3C reveals very similar functional connectivity with the networks investigated. This is very surprising, and the authors should include a careful comparison with related findings in the literature. Overall, there is limited comparison between the observed results and those obtained via other methods. On a more pessimistic note, the results of Figure 3 seem to question the validity of the general approach.
(4) Some statements in the Discussion feel unwarranted. For example, "significant dissociation in functional connectivity to prefrontal structures that support self-referential, reward-related, and socio-affective processes." This feels way beyond what can be stated based on the analyses performed.
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Reviewer #1 (Public review):
Summary:
In this study, Fakhar et al. use a game-theoretical framework to model interregional communication in the brain. They perform virtual lesioning using MSA to obtain a representation of the influence each node exerts on every other node, and then compare the optimal influence profiles of nodes across different communication models. Their results indicate that cortical regions within the brain's "rich club" are most influential.
Strengths:
Overall, the manuscript is well-written. Illustrative examples help to give the reader intuition for the approach and its implementation in this context. The analyses appear to be rigorously performed and appropriate null models are included.
Weaknesses:
The use of game theory to model brain dynamics relies on the assumption that brain regions are similar to agents optimizing their influence, and implies competition between regions. The model can be neatly formalized, but is there biological evidence that the brain optimizes signaling in this way? This could be explored further. Specifically, it would be beneficial if the authors could clarify what the agents (brain regions) are optimizing for at the level of neurobiology - is there evidence for a relationship between regional influence and metabolic demands? Identifying a neurobiological correlate at the same scale at which the authors are modeling neural dynamics would be most compelling.
It is not entirely clear what Figure 6 is meant to contribute to the paper's main findings on communication. The transition to describing this Figure in line 317 is rather abrupt. The authors could more explicitly link these results to earlier analyses to make the rationale for this figure clearer. What motivated the authors' investigation into the persistence of the signal influence across steps?
The authors used resting-state fMRI data to generate functional connectivity matrices, which they used to inform their model of neural dynamics. If I understand correctly, their functional connectivity matrices represent correlations in neural activity across an entire fMRI scan computed for each individual and then averaged across individuals. This approach seems limited in its ability to capture neural dynamics across time. Modeling time series data or using a sliding window FC approach to capture changes across time might make more sense as a means of informing neural dynamics.
The authors evaluated their model using three different structural connectomes: one inferred from diffusion spectrum imaging in humans, one inferred from anterograde tract tracing in mice, and one inferred from retrograde tract-tracing in macaque. While the human connectome is presumably an undirected network, the mouse and macaque connectomes are directed. What bearing does experimentally inferred knowledge of directionality have on the derivation of optimal influence and its interpretation?
It would be useful if the authors could assess the performance of the model for other datasets. Does the model reflect changes during task engagement or in disease states in which relative nodal influence would be expected to change? The model assumes optimality, but this assumption might be violated in disease states.
The MSA approach is highly computationally intensive, which the authors touch on in the Discussion section. Would it be feasible to extend this approach to task or disease conditions, which might necessitate modeling multiple states or time points, or could adaptations be made that would make this possible?
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Reviewer #1 (Public review):
Summary:
Winkler et al. present brain activity patterns related to complex motor behaviour by combining whole-head magnetoencephalography (MEG) with subthalamic local field potential (LFP) recordings from people with Parkinson's disease. The motor task involved repetitive circular movements with stops or reversals associated with either predictable or unpredictable cues. Beta and gamma frequency oscillations are described, and the authors found complex interactions between recording sites and task conditions. For example, they observed stronger modulation of connectivity in unpredictable conditions. Moreover, STN power varied across patients during reversals, which differed from stopping movements. The authors conclude that cortex-STN beta modulation is sensitive to movement context, with potential relevance for movement redirection.
Strengths:
This study employs a unique methodology, leveraging the rare opportunity to simultaneously record both invasive and non-invasive brain activity to explore oscillatory networks.
Weaknesses:
It is difficult to interpret the role of the STN in the context of reversals because no consistent activity pattern emerged.
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Reviewer #1 (Public review):
Summary:
In this manuscript, Mendoza-Romero et al. investigate the effects of maternal high-fat diet (MHFD) on microglia and AgRP synaptic terminals in the hypothalamus of postnatal mice during lactation. The study employs 3D microglial morphology reconstruction and genetically targeted axonal labeling, offering a detailed examination of microglial changes and their implications for AgRP terminal density and body weight regulation, focusing on the PVN and ARC nuclei. The authors also use pharmacological (e.g., PLX5622) elimination of microglia to test the sufficiency of microglia to shape PVN AgRP+ synapses.
Strengths:
This is a well-written paper with a thorough introduction and discussion.
The impact of microglia on hypothalamic synaptic pruning is poorly characterized, so the findings herein are especially interesting.
Weaknesses:
(1) A cartoon paradigm of the HFD treatment window would be a helpful addition to Figure 1. Relatedly, the authors might consider qualifying MHFD as 'lactational MHFD.' Readers might miss the fact that the exposure window starts at birth.
(2) More details on the modeling pipeline are needed either in Figure 1 or text. Of the ~50 microglia that were counted (based on Figure 1J), were all 50 quantified for the morphological assessments? Were equal numbers used for the control and MHFD groups? Were the 3D models adjusted manually for accuracy? How much background was detected by IMARIS that was discarded? Was the user blind to the treatment group while using the pipeline? Were the microglia clustered or equally spread across the PVN?
(3) Suggest toning back some of the language. For example: "...consistent with enhanced activity and surveillance of their immediate microenvironment" (Line 195) could be "...perhaps consistent with...". Likewise, "profound" (Lines 194, 377) might be an overstatement.
(4) Representative images for AgRP+ cells (quantified in Figure 2J) are missing. Why not a co-label of Iba1+/AgRP+ as per Figure 1, 3? Also, what was quantified in Figure 2J - soma? Total immunoreactivity?
(5) For the PLX experiment:<br /> a) "...we depleted microglia during the lactation period" (Line 234). This statement suggests microglia decreased from the first injection at P4 and throughout lactation, which is inaccurate. PLX5622 effects take time, upwards of a week. Thus, if PLX5622 injections started at P4, it could be P11 before the decrease in microglia numbers is stable. Moreover, by the time microglia are entirely knocked down, the pups might be supplementing some chow for milk, making it unclear how much PLX5622 they were receiving from the dam, which could also impact the rate at which microglia repopulation commences in the fetal brain. Quantifying microglia across the P4-P21 treatment window would be helpful, especially at P16, since the PVN AgRP microglia phenotypes were demonstrated and roughly when pups might start eating some chow.
b) I am surprised that ~70% of the microglia are present at P21. Does this number reflect that microglia are returning as the pups no longer receive PLX5622 from milk from the dam? Does it reflect the poor elimination of microglia in the first place?
(6) Was microglia morphology examined for all microglia across the PVN? It is possible that a focus on PVNmpd microglia would reveal a stronger phenotype? In Figure 4H, J, AgRP+ terminals are counted in PVN subregions - PVNmpd and PVNpml, with PVNmpd showing a decrease of ~300 AgRP+ terminals in MHFD/Veh (rescued in MHFD/PLX5622). In Figure 1K, AgRP+ terminals across what appears to be the entire PVN decrease by ~300, suggesting that PVNmpd is driving this phenotype. If true, then do microglia within the PVNmpd display this morphology phenotype?
(7) What chow did the pups receive as they started to consume solid food? Is this only a MHFD challenge, or could the pups be consuming HFD chow that fell into the cage?
(8) Figure 5: Does internalized AgRP+ co-localize with CD68+ lysosomes? How was 'internalized' determined?
(9) Different sample sizes are used across experiments (e.g., Figure 4 NCD n=5, MHFD n=4). Does this impact statistical significance?
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Reviewer #1 (Public review):
Summary:
The study by Hu et al. investigated the role of olfactory ErbB4 in regulating olfactory information processing. The authors demonstrated that ErbB4 deletion impairs odor discrimination, sensitivity, habituation, and dishabituation by using an impressive combination of techniques from morphological to electrophysiology (both slice and in vivo) and from viral injection to cell-type-specific mutation to behavioral analysis. The findings underscore the crucial role of ErbB4 in olfactory PV neurons in modulating mitral cell function and odor perception.
Strengths:
This study contains a pretty comprehensive set of experiments.
Major concerns:
(1) Line 151 page 7, "PV-Erbb4+/+ mice (generated by crossing PV-Cre mice (Wen et al., 2010) with loxP flanked Erbb4 mice". Does this mean mice carrying PV-Cre and ErbB4 floxed allele? Or with the WT allele? This is confusing. Figures 2B and 2C, ErbB4 expression was evident in many cells that were not positive for PV. What are the identities of those cells? Are they important?
(2) In Figure 4, the authors performed tetrode recordings in awake head-fixed animals. Although individual neuron spikes could be obtained by spike-sorting, this is not a "single-unit" experiment due to the nature of this approach.
What is the odor used in Figure 4? How did the authors clean up the odor to limit the stimulation within 2 seconds? In what layer were the tetrodes placed? What is the putative cell type presented in Figure 4C? If Figure 4C is a representative neuron recorded, the odor-induced suppression of spike activity seems to be impaired in PV-ErbB4-/- animals. However, Figure 4D shows that suppressed neurons were similar between the two types of animals. Such comparisons among individual mice are difficult for in vivo electrophysiological experiments because the recorded cell type and placement of electrodes would be different. The authors should apply ErbB4 inhibitors to the same animals and compare the effects before and after. This would ensure the recoding of the same population of neurons.
(3) At a glance in the heatmap in Figure 4D, excited neurons were reduced in PV-ErbB4-/- mice, but not inhibited neurons. This was different from Figure 4L. The authors need to have a criteria or threshold to show how they categorized each population.
(4) Figure 4D, 4F and 4J seemed to be inconsistent. In Figure 4D before odor, there was no clear increase in the spontaneous activity in PV-ErbB4-/- mice; in Figure 4F-4G and 4J-4K, clearly, there was a high spontaneous activity in PV-ErbB4-/- mice.
(5) What are the neurons recorded in Figure 6E-6F? If they were MCs, loss of ErbB4 in PV neurons should not alter their intrinsic electrical properties. Rather GABAergic inputs could be altered. Indeed, the authors presented a reduction of GABAergic inputs from PV neurons to MCs.
(6) Figure 8E-8H, a better experiment would be specifically expressing ErbB4 or PV neurons. In Figure 8F and Figure 8I, was it the excitability after the current injection? Why not perform the spontaneous activity recording?
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Reviewer #1 (Public review):
Summary:
In this study from Zhu and colleagues, a clear role for MED26 in mouse and human erythropoiesis is demonstrated that is also mapped to amino acids 88-480 of the human protein. The authors also show the unique expression of MED26 in later-stage erythropoiesis and propose transcriptional pausing and condensate formation mechanisms for MED26's role in promoting erythropoiesis. Despite the author's introductory claim that many questions regarding Pol II pausing in mammalian development remain unanswered, the importance of transcriptional pausing in erythropoiesis has actually already been demonstrated (Martell-Smart, et al. 2023, PMID: 37586368, which the authors notably did not cite in this manuscript). Here, the novelty and strength of this study is MED26 and its unique expression kinetics during erythroid development.
Strengths:
The widespread characterization of kinetics of mediator complex component expression throughout the erythropoietic timeline is excellent and shows the interesting divergence of MED26 expression pattern from many other mediator complex components. The genetic evidence in conditional knockout mice for erythropoiesis requiring MED26 is outstanding. These are completely new models from the investigators and are an impressive amount of work to have both EpoR-driven deletion and inducible deletion. The effect on red cell number is strong in both. The genetic over-expression experiments are also quite impressive, especially the investigators' structure-function mapping in primary cells. Overall the data is quite convincing regarding the genetic requirement for MED26. The authors should be commended for demonstrating this in multiple rigorous ways.
Weaknesses:
(1) The authors state that MED26 was nominated for study based on RNA-seq analysis of a prior published dataset. They do not however display any of that RNA-seq analysis with regards to Mediator complex subunits. While they do a good job showing protein-level analysis during erythropoiesis for several subunits, the RNA-seq analysis would allow them to show the developmental expression dynamics of all subunit members.
(2) The authors use an EpoR Cre for red cell-specific MED26 deletion. However, other studies have now shown that the EpoR Cre can also lead to recombination in the macrophage lineage, which clouds some of the in vivo conclusions for erythroid specificity. That being said, the in vitro erythropoiesis experiments here are convincing that there is a major erythroid-intrinsic effect.
(3) The donor chimerism assessment of mice transplanted with MED26 knockout cells is a bit troubling. First, there are no staining controls shown and the full gating strategy is not shown. Furthermore, the authors use the CD45.1/CD45.2 system to differentiate between donor and recipient cells in erythroblasts. However, CD45 is not expressed from the CD235a+ stage of erythropoiesis onwards, so it is unclear how the authors are detecting essentially zero CD45-negative cells in the erythroblast compartment. This is quite odd and raises questions about the results. That being said, the red cell indices in the mice are the much more convincing data.
(4) The authors make heavy use of defining "erythroid gene" sets and "non-erythroid gene" sets, but it is unclear what those lists of genes actually are. This makes it hard to assess any claims made about erythroid and non-erythroid genes.
(5) Overall the data regarding condensate formation is difficult to interpret and is the weakest part of this paper. It is also unclear how studies of in vitro condensate formation or studies in 293T or K562 cells can truly relate to highly specialized erythroid biology. This does not detract from the major findings regarding genetic requirements of MED26 in erythropoiesis.
(6) For many figures, there are some panels where conclusions are drawn, but no statistical quantification of whether a difference is significant or not.
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Reviewer #1 (Public Review):
The authors investigate whether during free exploration of an environment with an internal structure of corridors and occasionally fluid-rewarded alleys, rat CA1 place cells generate multiple firing fields in repeating patterns, allowing the investigators to analyze whether firing field positional properties like alley orientation, and non-positional properties like heading, field-rate modulation and other properties are similar or different within and across single place cell place fields. They adopt a standard cognitive map analysis framework, conceiving each cell as an individual map element and characterizing each cell's individual activity independently of the activity of other cells, such that the main unit of analysis is a place field averaged across recording times of many minutes. Despite framing the work as an investigation of a fundamentally-subjective episodic memory system sensitive to hidden cognitive and attentional variables, the experiment and analyses are conceived as if the cells respond to positional and non-positional features of experience as static "inputs" that the investigators infer. These "inputs" are conceptualized as effectively stationary and steady, and they are not manipulated. The authors find that there are many "repeated" firing fields, that they tend to have similar orientation more than expected by chance, and that each field's rate is modulated distinctly by heading direction and other factors, leading them to conclude that each field's nonpositional inputs are "individually addressable." The authors do not consider alternative possibilities for which there are strong indications in the contemporary literature like 1) CA1 activity could be internally generated; 2) that there could be hidden cognitive variables that influence CA1 activity episodically and in non-stationary ways rather than consistently; 3) that CA1 cells exhibit mixed tuning to a variety of environmental and navigational variables; 4) that CA1 activity is better interpreted from the point-of-view of a neural ensemble or a neural manifold of conjoint neural activity that represents multiple information variables, or 5) that stable neural representations of information need not depend on stable stimulus-response properties of individual cells. In fact, the analyses provide evidence consistent with each of these alternatives, but they are not considered. There is a case to be made that the authors are allowed to ignore these alternatives because they properly engage the dogmatic point of view, in which case there is little to adjust in the manuscript, which is both well-conceived and well-executed in the classic (but not contemporary) norms of place cell investigations.
My comments are focused on improving the manuscript without insisting that the authors adopt alternative (contemporary) points of view, but requiring them to clarify their point of view and explain that there are alternatives.
(1) The authors define what they mean by "positional" and "non-positional" "inputs" later in the manuscript. Since the experimental apparatus and task have been designed to isolate these "inputs" the authors should in the initial description of the environment and task explain what the task does and does not allow them to analyze. Instead, they have repeatedly asserted that the environment is a hybrid of an open-field and a linear track environment. This may be the case, but so what? The authors need to better explain, up front, why that matters and what they will be able to investigate as a result. As written, this all seems to me rather vague and post hoc.
(2) The abstract states "Previous work implies a distinction between positional inputs to the hippocampus that provide information about an animal's location and non-positional inputs which provide information about the content of experience." While I understand what the authors mean, I want to point out that it is not straightforward to identify the "positional inputs" and the "non-positional inputs." What are they, how can they be measured? Is it not also possible that hippocampus generates "positional" information rather than receiving it, that is in fact the longstanding view of the cognitive map framework that the authors have adopted, and yet they frame the essential issue as one of differential receipt of positional and non-positional inputs. This seems to me imprecise and hard to defend but demonstrates the authors' opinion in framing this work. In my view a more objective and accurate statement might be "Previous work implies a distinction between hippocampal (positional) activity representing information about an animal's location and (non-positional) activity which represents information about the content of experience." This opinion about "inputs" is found throughout the manuscript over 50 times, starting with the title. While in my view this is not an objective treatment of the experimental design or data (positional and non-positional inputs are never identified or manipulated, they are merely inferred), I accept that the authors can say whatever they want so long as they make it clear to the reader that theirs is an opinion or assumption rather than a measurement. The manuscript is written as if the different inputs are identified and valid, rather than inferred.
(3) The abstract states "even though the animal's behavior was not constrained to 1-D trajectories" whereas page 13 states "but their trajectories were constrained to orthogonal directions by the city-maze architecture" and page 23 states "but their trajectories were constrained to a rectilinear grid." While I understand what the authors mean, the first statement appears to contradict the others. There are additional examples that I do not identify here. In any case, I would like to have seen examples of the animals' trajectories through the maze. A figure showing the raw trajectories and another after the unwanted behaviors have been filtered out should be given, allowing the reader to understand how much the animals tended to travel through the alleys, how much they turned and lingered within them, etc.
(4) The abstract ends with "These results demonstrate that the positional inputs that drive a cell to fire in similar locations across the maze can be behaviorally and temporally dissociated from the nonpositional inputs that alter the firing rates of the cell within its place fields, thereby increasing the flexibility of the system to encode episodic variables within a spatiotemporal framework provided by place cells." I don't see the evidence for the "thereby ..." claim. The authors are free to speculate and discuss but they should say they are speculating and/or discussing a possibility, rather than assert as if they have demonstrated a fact.
(5) The Introduction begins with "All behavior is embedded within a spatial and temporal framework." By this statement, I believe the authors mean to assert, or at least they cause a reader to understand that there is a spatial and temporal framework that is separate from the behaving subject. They will use this point of view to design their experiment around the utility of a city- maze. Since the authors appeal to cognitive map theory so much, I point out that O'Keefe and Nadel write in The Hippocampus as a Cognitive Map that "Space was a way of perceiving, not a thing to be perceived." Sentence number 2 of the book states "We shall argue that the hippocampus is the core of a neural memory system providing an objective spatial framework within which the items and events of an organism's experience are located and interrelated." Consistent with Kant and O'Keefe and Nadel, the present authors might more accurately state "All behavior is embedded within a subjective spatial and temporal framework." but then they will have to explain why they conceive of there being "positional inputs" to which they are measuring CA1 responses. This framing seems to me problematic and not logically self-consistent.
(6) On page 2 the authors assert "Neurons within the hippocampus respond to a wide array of sensory and otherwise nonspatial cues..." then they go on to list sensory features and "non-positional" features of experience to which CA1 cells respond. It seems to me they leave out a class of features of experience that might be considered "subjective spatial frames" that have been investigated by Gothard and Redish when they were in the McNaughton and Barnes lab, as well the Fenton and Muller labs, amongst others. All of these papers describe non-stationary, multi-stable place cell phenomena that are tied to subjective variables, which have the potential to undermine the premise of the present work's analyses and so they should be considered. I list a sample but certainly not all the work that might be considered.
Gothard KM, Skaggs WE, Moore KM, McNaughton BL (1996) Binding of hippocampal CA1 neural activity to multiple reference frames in a landmark-based navigation task. J Neurosci 16:823-835.
Gothard KM, Skaggs WE, McNaughton BL (1996) Dynamics of mismatch correction in the hippocampal ensemble code for space: interaction between path integration and environmental cues. J Neurosci 16:8027-8040.
Gothard KM, Hoffman KL, Battaglia FP, McNaughton BL (2001) Dentate gyrus and ca1 ensemble activity during spatial reference frame shifts in the presence and absence of visual input. J Neurosci 21:7284-7292.
Redish AD, Rosenzweig ES, Bohanick JD, McNaughton BL, Barnes CA (2000) Dynamics of hippocampal ensemble activity realignment: time versus space. J Neurosci 20:9298-9309.
Rosenzweig ES, Redish AD, McNaughton BL, Barnes CA (2003) Hippocampal map realignment and spatial learning. Nat Neurosci 6:609-615.
Jackson J, Redish AD (2007) Network dynamics of hippocampal cell-assemblies resemble multiple spatial maps within single tasks. Hippocampus 17:1209-1229
Lenck-Santini PP, Fenton AA, Muller RU (2008) Discharge properties of hippocampal neurons during performance of a jump avoidance task. J Neurosci 28:6773-6786.
Fenton AA, Lytton WW, Barry JM, Lenck-Santini PP, Zinyuk LE, Kubik S, Bures J, Poucet B, Muller RU, Olypher AV (2010) Attention-like modulation of hippocampus place cell discharge. J Neurosci 30:4613-4625.
Kelemen E, Fenton AA (2013) Key features of human episodic recollection in the cross-episode retrieval of rat hippocampus representations of space. PLoS Biol 11:e1001607.
(7) The Introduction asserts that "rate remapping" is a hypothesis. Rate remapping is a phenomenon, something that is observed. The interpretation of the observation as being the substrate of episodic memory is certainly a hypothesis that in my opinion has not been tested and is not being tested in the present work. After making the above statement, the authors go on to describe that firing rates differ across "repeated" firing fields, which seems to be a form of rate remapping, and predicted by the relevant hypothesis that different episodes of experience at the same locations are represented by different firing rates. This is very speculative and there are many other explanations.
(8) The Introduction ends with the statement "Here, we show that repeating fields of the same neuron do not always display the same nonpositional rate modulation, demonstrating that nonpositional cues are dissociable from, and more flexible than, the positional inputs onto place cells in a given environment." Apart from my concern about using the "input" terminology I which to point out that there is very little novel in this statement. It has been described many times before that on linear tracks CA1 firing fields are directionally modulated such that the field rates for traversals in one direction are different compared to field traversals in the opposite direction. Jackson and Redish (2007) cited above show this to be due to reference frame or map switching. That and other work allow one to state that "Others show that repeating fields of the same neuron do not always display the same nonpositional rate modulation, demonstrating that nonpositional cues are dissociable from, and more flexible than, the positional inputs onto place cells in a given environment." Either the present authors should acknowledge that they are demonstrating what others have already demonstrated, or they should more precisely describe what about their contribution is unique.
(9) Page 6 Methods - Data Filtering and Pre-processing. How did the authors handle theta cells and others that fired more or less everywhere but with spatial modulation?
(10) Page 9 Methods - Why was the session-wide activity used to normalize the firing rates for the activity vector input to the random forest classifier? The authors state "The normalized firing rate was computed as discussed above with the change that the session-wide activity in the alley was used." It seems to me better to have used the session-averaged firing rate map because the activity would be normalized by the expected positional firing. I imagine "The classifier used the population vector of firing rates as the input." is incorrect and the authors mean to state "The classifier used the population vector of normalized firing rates as the input."
(11) What does "spatially-gated" mean? The use of such jargon should be explained, or better avoided.
(12) Page 12: Since fields tend to have similar orientations, but not repeat at all geometrically similar locations, did they tend to be clustered? Was there a proximity feature to their distribution?
(13) Page 18 states "Thus, although there was a slight trend for repeating field ..." The authors are reporting a significant effect not a "slight trend." They do something similar in reporting Figure 5's result. Despite significant effects, they seem to think the findings are not large enough so state that repeating-field directionality is not conserved. It is fine to explain that a significant effect was small (for example give the effect size, which would have been welcome throughout) but as in these cases and others, the authors should be more objective in their reporting of the outcomes. Either a statistical test was or was not significant. It is not "a little" or "a lot" significant.
(14) Page 18: What do the authors mean by "topology?" Might they mean "topography?"
(15) Figure 6 shows field instability and multi-stability (termed temporal dynamics) as described on page 22. The recording sessions were 60 min. Is this impression simply due to long recording sessions? If 10 or 15 minutes of data were analyzed (which is more the norm), would similar instability be observed/detectable?
(16) I found the Discussion very confusing. On the one hand, there is an assertion that because the location of firing fields is stable there is a "positional code." How would that actually work? Any neural system has to signal by firing rates or firing coincidences across groups of cells (that are affected by changes in rate) so if there is firing field firing rate instability the authors should explain how position can be accurately decoded on a behaviorally-meaningful time scale. In fact, they should demonstrate such decoding explicitly. Just because there is modulation and instability, it is a rather long leap to assert that this is how episodic experience/memory is encoded (as stated at the end of the abstract and elsewhere for example on page 24: "The present data utilize repeating fields to suggest that, within an environment, the positional inputs are relatively rigid, whereas the nonpositional inputs are more flexible, allowing different repeating fields to show different directional preferences. In other words, fields are individually addressable with respect to the nonpositional inputs they receive; they do not inherit their nonpositional tuning as a global property of the cell." What does it mean that a field is "individually addressable?" How is that achieved by neurons? If the authors want to make such assertions they should explain and demonstrate how their assertions can be valid, given the data and findings. At least they should explain what they are assuming.<br /> The main findings seem related to the published finding that in large environments place cells have multiple firing fields, with distinct rates in each field, quite similar to what is here described in the city maze. In my opinion, positional representations can only plausibly work in such cases by using the conjoint population activity moment to moment, which necessarily marginalizes the value of individual firing fields, yet the present work focuses the discussion (and analyses) on interpretations of single firing fields (which they assert are individually addressable multiple times). I don't know what that means exactly and the authors should explain why maintaining the standard single-field perspective is appropriate and how position can be represented in such a system, given the data. In fact, I would have thought that the present findings would cause the authors to reject as invalid the framework they have adopted.
(17) This is a further example, on page 25 which asserts that "Directionality is affected by an animal's experience through the field (Navratilova et al., 2012), so it is possible the difference in experience between sampling fields on the same versus different corridors affects the directional tuning properties between them." I do not understand how "the difference in experience between sampling fields on the same versus different corridors affects the directional tuning properties between them." If I follow the logic then the so-called directionality would depend on experience and so only emerge after a certain time for experience, or else the firing during one traversal would need to be modulated by information about future traversals, which I suppose the authors would agree does not make sense.
(18) I found it at times confusing to follow the arguments because the terms "route" and "trajectory" and also "direction" and "heading" were used sometimes interchangeably and sometimes in ways that appear distinct.
(19) Page 25 states "One explanation for these data is that fields sampled along contiguous routes, without interruptions from heading change or reward delivery, are more likely to share their directionality." The authors should consider alternative explanations like reference frame shifts as mentioned in comment 6 above. These alternatives can be rejected based on data, but they should be considered because they seem to offer more parsimonious explanations for the observations than what the authors have offered. For example, what can explain the bimodality reported in Fig. 5G?
(20) The authors assert on page 15 that "In the present study, turns at the ends of corridors, along with reward deliveries, may be salient task boundaries at which point theta sequences are terminated. Fields active within the same theta sequence (typically same corridor fields) may be functionally coupled, while fields active on opposite sides of a theta sequence termination (different corridor fields) may be uncoupled and their tuning uncorrelated." The authors should check this. They recorded the LFPs. Why speculate when they can evaluate the speculation?
(21) The authors assert on page 26 "It is important to note that because a Pearson correlation was used, it is possible the fields are related in time with a phase shift, and we did not have the statistical power to test this possibility adequately." I either do not understand this statement or it is untrue. Please clarify.
(22) The authors continue on page 26, asserting "Thus, although it is clear that the place fields of repeating cells do not change their firing rates in synchrony, as if the cell had a global excitability change that made all its fields wax and wane together, it nonetheless remains an open question as to whether the subfields of repeating cells engage in certain types of competitive interactions or other network dynamics that couple changes in their firing rates in more complex ways." This statement implies that it might even be possible for firing fields in distinct and distant locations to be modulated together. Could the authors please explain how that is possible? A firing field is an observation that requires averaging over minutes and behavioral sampling across minutes. How might one cell be modulated to fire at a low rate during one minute and then at another minute later be modulated to fire at a high rate everywhere in the environment? Perhaps I am again not understanding the assertion - please clarify.
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Reviewer #1 (Public review):
Summary:
This paper describes the covalent interactions of small molecule inhibitors of carbonic anhydrase IX, utilizing a pre-cursor molecule capable of undergoing beta-elimination to form the vinyl sulfone and covalent warhead.
Strengths:
The use of a novel covalent pre-cursor molecule that undergoes beta-elimination to form the vinyl sulfone in situ. Sufficient structure-activity relationships across a number of leaving groups, as well as binding moieties that impact binding and dissociation constants.
Weaknesses:
No major weaknesses noted. Suggested corrections were addressed.
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Reviewer #1 (Public review):
Previous studies have used a randomly induced label to estimate the number of hematopoietic precursors that contribute to hematopoiesis. In particular, the McKinney-Freeman lab established a measurable range of precursors of 50-2500 cells using random induction of one of the 4 fluorescent proteins (FPs) of a Confetti reporter in the fetal liver to show that hundreds of precursors establish lifelong hematopoiesis. In the presented work, Liu and colleagues aim to extend the measurable range of precursor numbers previously established and enable measurement in a variety of contexts beyond embryonic development. To this end, the authors investigated whether the random induction of a given Confetti FP follows the principles of binomial distribution such that the variance inversely correlates with the precursor number. The authors validated their hypothesis and identified sampling conditions to minimize experimental error using a simplified in vitro system. They use tamoxifen-inducible Scl-CreER, active in hematopoietic stem and progenitor cells (HSPCs), to induce Confetti labeling and investigate whether they could extend their model to cell numbers below 50 with in vivo transplantation of high versus low numbers of Confetti total bone marrow (BM) cells. The data generated are generally robust. While the lower and upper limits of the model may show some small error or have not yet been completely validated experimentally, it extends the measurable range of precursor from 15 - 10^5 cells. The authors then apply their model to estimate the number of hematopoietic precursors that contribute to hematopoiesis in a variety of contexts including adult steady state, fetal liver, following myeloablation, and a genetic model of Fanconi anemia.
Their data highlight the importance of estimating precursor numbers and not just donor frequency in transplantation settings and show that native hematopoiesis is highly polyclonal. Their data also confirm previous findings from Ganuza et al, 2022 that demonstrate no major expansion of precursors between E11.5 - E14.5. Finally, their work reveals intact Fancc-/-precursor numbers following transplantation, suggesting that the observed reduced chimerism is due to defects in cell proliferation.
The conclusions are generally sound and based on high-quality data. As the authors note, future studies should validate the model using alternative Cre-drivers to exclude any potential functional difference between labelled and non-labelled cells. Although this system does not permit tracing of individual clones, the modeling presented allows measurements of clonal activity covering nearly the entire HSPC population (as recently estimated by Cosgrove et al, 2021) and can be applied to a wide range of in vivo contexts with relative ease.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This study serves as a proof of concept for KMO inhibition as a new non-hormonal treatment for endometriosis. The authors investigated KMO expression in human endometrial and endometriosis lesion tissues, confirmed that KNS898 effectively inhibits KMO and alleviates manifestations of endometriosis in mice - reduced endometriosis lesions and improved hyperalgesia and cage behaviour.
Strengths:
(1) Inhibition of KMO may present as a promising first-in-class non-hormonal therapeutic agent for patients suffering from endometriosis and the side-effects of hormonal treatments.<br /> (2) The expression of KMO in endometrial tissues was demonstrated in both human (multiple patients per AFS stage of disease) and mice tissues.<br /> (3) Measurement of multiple substrates/analytes of the KMO regulatory pathway was performed and demonstrated strong correlation to each other in response to KMO inhibition.<br /> (4) The aims of study (as proof-of-concept) were achieved in the study and the results support their conclusions.
Weaknesses:
If any dysregulation in the KMO/tryptophan metabolic activity, expression and/or pathway in endometriosis can be shown, this will strengthen the rationale for the use of KMO inhibitor in the disease.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Orlovski and his colleagues revealed an interesting phenomenon that SAP54-overexpressing leaf exposure to leafhopper males is required for the attraction of followed females. By transcriptomic analysis, they demonstrated that SAP54 effectively suppresses biotic stress response pathways in leaves exposed to the males. Furthermore, they clarified how SAP54, by targeting SVP, heightens leaf vulnerability to leafhopper males, thus facilitating female attraction and subsequent plant colonization by the insects.
Strengths:
The phenomenon of this study is interesting and exciting.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
By employing human primary microvascular endothelial cells, along with live confocal imaging, proteomics, and chemical validation studies, the authors reveal a novel cellular mechanism underlying mycolactone's effects in Buruli ulcer lesions. This finding provides important insights into the specific mechanisms of skin pathogenesis.
Strengths:
The techniques employed are state-of-the-art.
Weaknesses:
The study lacks genetic validation of the findings.
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Reviewer #1 (Public review):
Summary:
The investigators undertook detailed characterization of a previously proposed membrane targeting sequence (MTS), a short N-terminal peptide, of the bactofilin BacA in Caulobacter crescentus. Using light microscopy, single molecule tracking, liposome binding assays, and molecular dynamics simulations, they provide data to suggest that this sequence indeed does function in membrane targeting and further conclude that membrane targeting is required for polymerization. While the membrane association data are reasonably convincing, there are no direct assays to assess polymerization and some assays used lack proper controls as detailed below. Since the MTS isn't required for bactofilin polymerization in other bacterial homologues, showing that membrane binding facilitates polymerization would be a significant advance for the field.
Major concerns
(1) This work claims that the N-termina MTS domain of BacA is required for polymerization, but they do not provide sufficient evidence that the ∆2-8 mutant or any of the other MTS variants actually do not polymerize (or form higher order structures). Bactofilins are known to form filaments, bundles of filaments, and lattice sheets in vitro and bundles of filaments have been observed in cells. Whether puncta or diffuse labeling represents different polymerized states or filaments vs. monomers has not been established. Microscopy shows mis-localization away from the stalk, but resolution is limited. Further experiments using higher resolution microscopy and TEM of purified protein would prove that the MTS is required for polymerization.<br /> (2) Liposome binding data would be strengthened with TEM images to show BacA binding to liposomes. From this experiment, gross polymerization structures of MTS variants could also be characterized.<br /> (3) The use of the BacA F130R mutant throughout the study to probe the effect of polymerization on membrane binding is concerning as there is no evidence showing that this variant cannot polymerize. Looking through the papers the authors referenced, there was no evidence of an identical mutation in BacA that was shown to be depolymerized or any discussion in this study of how the F130R mutation might to analogous to polymerization-deficient variants in other bactofilins mentioned in these references.<br /> (4) Microscopy shows that a BacA variant lacking the native MTS regains the ability to form puncta, albeit mis-localized, in the cell when fused to a heterologous MTS from MreB. While this swap suggests a link between puncta formation and membrane binding the relationship between puncta and polymerization has not been established (see comment 1).<br /> (5) The authors provide no primary data for single molecule tracking. There is no tracking mapped onto microscopy images to show membrane localization or lack of localization in MTS deletion/variants. A known soluble protein (e.g. unfused mVenus) and a known membrane bound protein would serve as valuable controls to interpret the data presented. It also is unclear why the authors chose to report molecular dynamics as mean squared displacement rather than mean squared displacement per unit time, and the number of localizations is not indicated. Extrapolating from the graph in figure 4 D for example, it looks like WT BacA-mVenus would have a mobility of 0.5 (0.02/0.04) micrometers squared per second which is approaching diffusive behavior. Further justification/details of their analysis method is needed. It's also not clear how one should interpret the finding that several of the double point mutants show higher displacement than deleting the entire MTS. These experiments as they stand don't account for any other cause of molecular behavior change and assume that a decrease in movement is synonymous with membrane binding.<br /> (6) The experiments that map the interaction surface between the N-terminal unstructured region of PbpC and a specific part of the BacA bactofilin domain seem distinct from the main focus of the paper and the data somewhat preliminary. While the PbpC side has been probed by orthogonal approaches (mutation with localization in cells and affinity in vitro), the BacA region side has only been suggested by the deuterium exchange experiment and needs some kind of validation.
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Reviewer #1 (Public review):
Summary:
This paper tests the hypothesis that neuronal adaptation to spatial frequency affects the estimation of spatial population receptive field sizes as commonly measured using the pRF paradigm in fMRI. To this end, the authors modify a standard pRF setup by presenting either low or high SF (near full field) adaptation stimuli prior to the start of each run and interleaved between each pRF bar stimulus. The hypothesis states that adaptation to a specific spatial frequency (SF) should affect only a specific subset of neurons in a population (measured with an fMRI voxel), leaving the other neurons in the population intact, resulting in a shift in the tuning of the voxel in the opposite direction of the adapted stimulus (so high SF adaptation > larger pRF size and vice versa). The paper shows that this 'repelling' effect is robustly detectable psychophysically and is evident in pRF size estimates after adaptation in line with the hypothesized direction, thereby demonstrating a link between SF tuning and pRF size measurements in the human visual cortex.
Strengths:
The paper introduces a new experimental design to study the effect of adaptation on spatial tuning in the cortex, nicely combining the neuroimaging analysis with a separate psychophysical assessment.
The paper includes careful analyses and transparent reporting of single-subject effects, and several important control analyses that exclude alternative explanations based on perceived contrast or signal-to-noise differences in fMRI.
The paper contains very clear explanations and visualizations, and a carefully worded Discussion that helpfully contextualizes the results, elucidating prior findings on the effect of spatial frequency adaptation on size illusion perception.
Weaknesses:
The fMRI experiments consist of a relatively small sample size (n=8), of which not all consistently show the predicted pattern in all ROIs. For example, one subject shows a strong effect in the pRF size estimates in the opposite direction in V1. It's not clear if this subject is also in the psychophysical experiment and if there is perhaps a behavioral correlate of this deviant pattern. The addition of a behavioral task in the scanner testing the effect of adaptation could perhaps have helped clarify this (although arguably it's difficult to do psychophysics in the scanner). Although the effects are clearly robust at the group level here, a larger sample size could clarify how common such deviant patterns are, and potentially allow for the assessment of individual differences in adaption effects on spatial tuning as measured with fMRI, and their perceptual implications.
The psychophysical experiment in which the perceptual effects are shown included a neutral condition, which allowed for establishing a baseline for each subject and the discovery of an asymmetry in the effects with stronger perceptual effects after high SF adaptation compared to low SF. This neutral condition was lacking in fMRI, and thus - as acknowledged - this asymmetry could not be tested at the neural level, also precluding the possibility of comparing the obtained pRF estimates to the typical ranges found using standard pRF mapping procedures (without adaptation), or to compare the SNR using in the adaptation pRF paradigm with that of a regular paradigm, etc.
The results indicate quite some variability in the magnitude of the shift in pRF size across eccentricities and ROIs (Figure 5B). It would be interesting to know more about the sources of this variability, and if there are other effects of adaptation on the estimated retinotopic maps other than on pRF size (there is one short supplementary section on the effects on eccentricity tuning, but not polar angle).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This study addresses the issue of rapid skill learning and whether individual sequence elements (here: finger presses) are differentially represented in human MEG data. The authors use a decoding approach to classify individual finger elements, and accomplish an accuracy of around 94%. A relevant finding is that the neural representations of individual finger elements dynamically change over the course of learning. This would be highly relevant for any attempts to develop better brain machine interfaces - one now can decode individual elements within a sequence with high precision, but these representations are not static but develop over the course of learning.
Strengths:
The work follows a large body of work from the same group on the behavioural and neural foundations of sequence learning. The behavioural task is well established and neatly designed to allow for tracking learning and how individual sequence elements contribute. The inclusion of short offline rest periods between learning epochs has been influential because it has revealed that a lot, if not most of the gains in behaviour (ie speed of finger movements) occur in these so-called micro-offline rest periods.
The authors use a range of new decoding techniques, and exhaustively interrogate their data in different ways, using different decoding approaches. Regardless of the approach, impressively high decoding accuracies are observed, but when using a hybrid approach that combines the MEG data in different ways, the authors observe decoding accuracies of individual sequence elements from the MEG data of up to 94%.
Weaknesses:
There are a few concerns which the authors may well be able to resolve. These are not weaknesses as such, but factors that would be helpful to address as these concern potential contributions to the results that one would like to rule out.
Regarding the decoding results shown in Figure 2 etc, a concern is that within individual frequency bands, the highest accuracy seems to be within frequencies that match the rate of keypresses. This is a general concern when relating movement to brain activity, so is not specific to decoding as done here. As far as reported, there was no specific restraint to the arm or shoulder, and even then it is conceivable that small head movements would correlate highly with the vigor of individual finger movements. This concern is supported by the highest contribution in decoding accuracy being in middle frontal regions - midline structures that would be specifically sensitive to movement artefacts and don't seem to come to mind as key structures for very simple sequential keypress tasks such as this - and the overall pattern is remarkably symmetrical (despite being a unimanual finger task) and spatially broad. This issue may well be matching the time course of learning, as the vigor and speed of finger presses will also influence the degree to which the arm/shoulder and head move.
This is not to say that useful information is contained within either of the frequencies or broadband data. But it raises the question of whether a lot is dominated by movement "artefacts" and one may get a more specific answer if removing any such contributions.
A somewhat related point is this: when combining voxel and parcel space, a concern is whether a degree of circularity may have contributed to the improved accuracy of the combined data, because it seems to use the same MEG signals twice - the voxels most contributing are also those contributing most to a parcel being identified as relevant, as parcels reflect the average of voxels within a boundary. In this context, I struggled to understand the explanation given, ie that the improved accuracy of the hybrid model may be due to "lower spatially resolved whole-brain and higher spatially resolved regional activity patterns". Firstly, there will be a relatively high degree of spatial contiguity among voxels because of the nature of the signal measured, ie nearby individual voxels are unlikely to be independent. Secondly, the voxel data gives a somewhat misleading sense of precision; the inversion can be set up to give an estimate for each voxel, but there will not just be dependence among adjacent voxels, but also substantial variation in the sensitivity and confidence with which activity can be projected to different parts of the brain. Midline and deeper structures come to mind, where the inversion will be more problematic than for regions along the dorsal convexity of the brain, and a concern is that in those midline structures, the highest decoding accuracy is seen.
Some of these concerns could be addressed by recording head movement (with enough precision) to regress out these contributions. The authors state that head movement was monitored with 3 fiducials, and their timecourses ought to provide a way to deal with this issue. The ICA procedure may not have sufficiently dealt with removing movement-related problems, but one could eg relate individual components that were identified to the keypresses as another means for checking. An alternative could be to focus on frequency ranges above the movement frequencies. The accuracy for those still seems impressive, and may provide a slightly more biologically plausible assessment.
One question concerns the interpretation of the results shown in Figure 4. They imply that during the course of learning, entirely different brain networks underpin the behaviour. Not only that, but they also include regions that would seem rather unexpected to be key nodes for learning and expressing relatively simple finger sequences, such as here. What then is the biological plausibility of these results? The authors seem to circumnavigate this issue by moving into a distance metric that captures the (neural network) changes over the course of learning, but the discussion seems detached from which regions are actually involved; or they offer a rather broad discussion of the anatomical regions identified here, eg in the context of LFOs, where they merely refer to "frontoparietal regions".
If I understand correctly, the offline neural representation analysis is in essence the comparison of the last keypress vs the first keypress of the next sequence. In that sense, the activity during offline rest periods is actually not considered. This makes the nomenclature somewhat confusing. While it matches the behavioural analysis, having only key presses one can't do it in any other way, but here the authors actually do have recordings of brain activity during offline rest. So at the very least calling it offline neural representation is misleading to this reviewer because what is compared is activity during the last and during the next keypress, not activity during offline periods. But it also seems a missed opportunity - the authors argue that most of the relevant learning occurs during offline rest periods, yet there is no attempt to actually test whether activity during this period can be useful for the questions at hand here.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Mollá-Albaladejo et al. investigate the neurons downstream of GR64f and Gr66a, called G2Ns. They identify downstream neurons using trans-Tango labeling with RFP and then perform bulk RNA-seq on the RFP-sorted cells. Gene expression is up- or downregulated between the cell populations and between fed and starved states. They specifically identify Leukocinin as a neuropeptide that is upregulated in starved Gr66a cells. Leucokinin cells, identified by a GAL4 line indeed show higher expression when starved, especially in the SEZ. Furthermore, Leucokinin cells colocalize with the trans-Tango signal from downstream neurons of both GRs. This connection is confirmed with GRASP. According to EM data, Leucokinin cells in the SEZ receive a lot of input and connect to many downstream neurons. In behavior experiments performed with flies lacking Leucokinin neurons, flies show reduced responsiveness to sugar and bitter mixtures when starved. The authors suggest that Leucokinin neurons integrate bitter and sugar tastes and that their output is modified by a hunger state.
Strengths:
The authors use a multitude of tools to identify SELK neurons downstream of taste sensory neurons and as starvation-sensitive cells. This study provides an example of how combining genetic labeling, RNA-seq, and EM analysis can be combined to investigate neural circuits.
Weaknesses:
The authors do not show a functional connection between sensory neurons and SELK neurons. Additionally, data from RNA seq, anatomical studies, and EM analysis are sometimes contradictory in terms of connectivity. GRASP signal is not foolproof that cells are synaptically connected.
The authors describe a behavioral phenotype when flies are starved, however, they do not use a specific driver for the described cell type, thus they should also tone down their claims.
Generally, the authors do not provide a big advancement to the field and some of the results are contradictory with previous publications.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
This paper describes "Ais", a new software tool for machine-learning based segmentation and particle picking of electron tomograms. The software can visualise tomograms as slices and allows manual annotation for the training of a provided set of various types of neural networks. New networks can be added, provided they adhere to a python file with an (undescribed) format. Once networks have been trained on manually annotated tomograms, they can be used to segment new tomograms within the same software. The authors also set up an online repository to which users can upload their models, so they might be re-used by others with similar needs. By logically combining the results from different types of segmentations, they further improve the detection of distinct features. The authors demonstrate the usefulness of their software on various data sets. Thus, the software appears to be a valuable tool for the cryo-ET community that will lower the boundaries of using a variety of machine-learning methods to help interpret tomograms.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
In their manuscript "PDGFRRa signaling regulates Srsf3 transcript binding to affect PI3K signaling and endosomal trafficking" Forman and colleagues use iMEPM cells to characterize the effects of PDGF signaling on alternative splicing. They first perform RNA-seq using a one-hour stimulation with Pdgf-AA in control and Srsf3 knockdown cells. While Srsf3 manipulation results in a sizeable number of DE genes, PDGF does not. They then turn to examine alternative splicing, due to findings from this lab. They find that both PDGF and Srsf3 contribute much more to splicing than transcription. They find that the vast majority of PDGF-mediated alternative splicing depends upon Srsf3 activity and that skipped exons are the most common events with PDGF stimulation typically promoting exon skipping in the presence of Srsf3. They used eCLIP to identify RNA regions bound to Srsf3. Under both PDGF conditions, the majority of peaks were in exons with +PDGF having a substantially greater number of these peaks. Interestingly, they find differential enrichment of sequence motifs and GC content in stimulated versus unstimulated cells. They examine 2 transcripts encoding PI3K pathway (enriched in their GO analysis) members: Becn1 and Wdr81. They then go on to examine PDGFRRa and Rab5, an endosomal marker, colocalization. They propose a model in which Srsf3 functions downstream of PDGFRRa signaling to, in part, regulate PDGFRa trafficking to the endosome. The findings are novel and shed light on the mechanisms of PDGF signaling and will be broadly of interest. This lab previously identified the importance of PDGF naling on alternative splicing. The combination of RNA-seq and eCLIP is an exceptional way to comprehensively analyze this effect. The results will be of great utility to those studying PDGF signaling or neural crest biology.
Comments on the revised version:
The authors have fully addressed my previous comments and I have no further concerns.
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www.biorxiv.org www.biorxiv.org
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Reviewer #4 (Public review):
Summary:
This study describes an understudied migration pattern of dynamic non-breeding range using data from an Arctic raptor. Using data from GPS tags, the study describes the known pattern of fast migration during autumn and spring, and an undescribed pattern of slow migration, at much slower pace, throughout the over-wintering season.
Strengths:
The study presents a comprehensive analysis of the annual cycle of an interesting and undescribed migration system. The conceptual advancement is original and the data is rich and persuading. The Discussion part of the manuscript is well written.
Weaknesses:
Other sections of the manuscript need some more polish, both in terms of the terminology, the language and the logic of the presentation of the subject. The title is not good. During most of the text, the authors do not properly follow a certain terminology regarding migration, over-wintering, non-breeding range, and this is very confusing. So, consistency of the text is warranted. A bigger issue is the selection of latitudes (or the actual reason for movement) during the over-wintering period. The study claims that this relates to snow cover but fails to properly demonstrate it. It is likely that the birds move because of changes in snow cover rather than because of the level of snow cover. This is a testable prediction. A possible explanation is that there is a cost for moving further south and thus the birds are reluctant of moving unless they are forced to do it by the high snow cover. Another, similar and testable prediction is that the birds aim at selecting latitudes where snow cover is partial and move slowly during the winter to areas that are only partially covered by the snow with the progression of the winter. A modified, non-linear, snow cover analysis using GAMM could uncover such patterns.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In an era of increasing antibiotic resistance, there is a pressing need for the development of novel sustainable therapies to tackle problematic pathogens. In this study, the authors hypothesize that pyoverdines - metal-chelating compounds produced by fluorescent pseudomonads - can act as antibacterials by locking away iron, thereby arresting pathogen growth. Using biochemical, growth and virulence assays on 12 opportunistic pathogens strains, the authors demonstrate that pyoverdines induce iron starvation, but this affect was highly context dependent. This same effect has been demonstrated for plant pathogens, but not for human opportunistic pathogens exposed to natural siderophores. Only those pathogens lacking (1) a matching receptor to take up pyoverdine-bound iron and/or (2) the ability to produce strong iron chelators themselves experienced strong growth arrest. This would suggest that pyoverdines might not be effective against all pathogens, thereby potentially limiting the utility of pyoverdines as global antibacterials.
Strengths:
The work addresses an important and timely question - can pyoverdines be used as an alternative strategy to deal with opportunistic pathogens? In general, the work is well conducted with rigorous biochemical, growth and virulence assays. In line, the work is clearly written, and the findings are supported by high-quality figures.
Weaknesses:
I do not think there are any 'weaknesses' as such. The authors have taken all suggestions on board and this has greatly improved the quality and robustness of the work
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www.biorxiv.org www.biorxiv.org
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Joint Public Review:
Summary:
This study presents a strategy to efficiently isolate PcrV-specific BCRs from human donors with cystic fibrosis who have/had Pseudomonas aeruginosa (PA) infection. Isolation of mAbs that provide protection against PA may be a key to developing a new strategy to treat PA infection as the PA has intrinsic and acquired resistance to most antibiotic drug classes. Hale et al. developed fluorescently labeled antigen-hook and isolated mAbs with anti-PA activity. Overall, the authors' conclusion is supported by solid data analysis presented in the paper. Four of five recombinantly expressed PcrV-specific mAbs exhibited anti-PA activity in a murine pneumonia challenge model as potent as the V2L2MD mAb (equivalent to gremubamab). However, therapeutic potency for these isolated mAbs is uncertain as the gremubamab has failed in Phase 2 trials. Clarification of this point would greatly benefit this paper.
Strengths:
(1) High efficiency of isolating antigen-specific BCRs using an antigenic hook.
(2) The authors' conclusion is supported by data.
Weaknesses:
Although the authors state that the goal of this study was to generate novel protective mAbs for therapeutic use (P12; Para. 2), it is unclear whether PcrV-specific mAbs isolated in this study have therapeutic potential better than the gremubamab, which has failed in Phase 2 trials. Four of five PcrV-specific mAbs isolated in this study reduced bacterial burdens in mice as potent as, but not superior to, gremubamab-equivalent mAb. Clarification of this concern by revising the text or providing experimental results that show better potential than gremubamab would greatly benefit this paper.
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Reviewer #1 (Public review):
In their paper, Kang et al. investigate rigidity sensing in amoeboid cells, showing that, despite their lack of proper focal adhesions, amoeboid migration of single cells is impacted by substrate rigidity. In fact, many different amoeboid cell types can durotax, meaning that they preferentially move towards the stiffer side of a rigidity gradient.
The authors observed that NMIIA is required for durotaxis and, buiding on this observation, they generated a model to explain how durotaxis could be achieved in the absence of strong adhesions. According to the model, substrate stiffness alters the diffusion rate of NMAII, with softer substrates allowing for faster diffusion. This allows for NMAII accumulation at the back, which, in turn, results in durotaxis.
The evidence provided for durotaxis of non adherent (or low-adhering) cells is strong. I am particularly impressed by the fact that amoeboid cells can durotax even when not confined. I wish to congratulate the authors for the excellent work, which will fuel discussion in the field of cell adhesion and migration.
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Reviewer #1 (Public review):
In their paper, Kang et al. investigate rigidity sensing in amoeboid cells, showing that, despite their lack of proper focal adhesions, amoeboid migration of single cells is impacted by substrate rigidity. In fact, many different amoeboid cell types can durotax, meaning that they preferentially move towards the stiffer side of a rigidity gradient.
The authors observed that NMIIA is required for durotaxis and, buiding on this observation, they generated a model to explain how durotaxis could be achieved in the absence of strong adhesions. According to the model, substrate stiffness alters the diffusion rate of NMAII, with softer substrates allowing for faster diffusion. This allows for NMAII accumulation at the back, which, in turn, results in durotaxis.
The evidence provided for durotaxis of non adherent (or low-adhering) cells is strong. I am particularly impressed by the fact that amoeboid cells can durotax even when not confined. I wish to congratulate the authors for the excellent work, which will fuel discussion in the field of cell adhesion and migration.
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www.biorxiv.org www.biorxiv.org
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Joint Public review:
Summary
This manuscript offers significant insights into the impact of maternal obesity on oocyte methylation and its transgenerational effects. Chao and colleagues demonstrated the potential mechanisms behind the DNA methylation changes. The major observations of the work include transgenerational DNA methylation changes in offspring of maternal obesity and metabolites such as methionine and melatonin which correlated with the epigenetic changes. Exogenous melatonin treatment could reverse the effects of obesity. The authors further hypothesized that the linkage may be mediated by the cAMP/PKA/CREB pathway to regulate the expression of DNMTs. This work has done lots of breeding and DNA Methylation analysis across multiple generations, which provides solid data for future research. The results of this work may benefit from deeper data analysis to make more causal analyses and conclusions more concrete.
Strengths
The study employs comprehensive methodologies, including transgenerational breeding experiments, whole genome bisulfite sequencing, and metabolomics analysis, and provides the convincing data.
Weaknesses
The results of this work are correlational, which may require further analysis to establish more concrete conclusions on causal relationships.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this work by Wang et al., the authors use single-molecule super-resolution microscopy together with biochemical assays to quantify the organization of Nipah virus fusion protein F (NiV-F) on cell and viral membranes. They find that these proteins form nanoscale clusters which favors membrane fusion activation, and that the physical parameters of these clusters are unaffected by protein expression level and endosomal cleavage. Furthermore, they find that the cluster organization is affected by mutations in the trimer interface on the NiV-F ectodomain and the putative oligomerization motif on the transmembrane domain, and that the clusters are stabilized by interactions among NiV-F, the AP2-complex, and the clathrin coat assembly. This work improves our understanding of the NiV fusion machinery, which may also have implications for our understanding of the function of other viruses.
Strengths:
The conclusions of this paper are well-supported by the presented data. This study sheds light on the activation mechanisms underlying the NiV fusion machinery.
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arxiv.org arxiv.org
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Reviewer #1 (Public review):
Summary:
The authors make a new contribution with careful computational validation/exploration of their method on synthetic and real-world datasets. Overall, I find their results significant and their presentation compelling.
Strengths:
The authors provide extensive computational validation of their approach to synthetic and real-world datasets of increasing complexity.
Weaknesses:
The authors should provide a comparison of their approach to other state-of-the-art neural network-based methods. Without this, it is difficult to tell which aspects of their approach (novel coupling metric, or network architecture) are most important for their results.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
The manuscript by Menon et al describes a set of simulations of alpha-Synuclein (aSYN) and analyses of these and previous simulations in the presence of a small molecule.
Comments on latest version:
I have read the authors' response to my comments as well as to the other reviewers. Summarizing briefly, I don't think they provide substantial answer to the questions/comments by me or reviewer 3, and generally do not quantify the results/effects data. I still remain unconvinced about the analyses and conclusions. Rather than rewriting another set of comments, I think it will be more useful for all (authors and readers) simply to be able to see the entire set of reviews and responses together with the paper.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
UGGTs are involved in the prevention of premature degradation for misfolded glycoproteins, by utilizing UGGT1-KO cells and a number of different ERAD substrates. They proposed a concept by which the fate of glycoproteins can be determined by a tug-of-war between UGGTs and EDEMs.
Strengths:
The authors provided a wealth of data to indicate that UGGT1 competes with EDEMs, which promotes the glycoprotein degradation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This is an interesting study on the role of FGF signaling in the induction of primitive streak-like cells (PS-LC) in human 2D-gastruloids. The authors use a previously characterized standard culture that generates a ring of PS-LCs (TBXT+) and correlate this with pERK staining. A requirement for FGF signaling in TBXT induction is demonstrated via pharmacological inhibition of MEK and FGFR activity. A second set of culture conditions (with no exogenous FGFs) suggests that endogenous FGFs are required for pERK and TBXT induction. The authors then characterize, via scRNA-seq, various components of the FGF pathway (genes for ligands, receptors, ERK regulators, and HSPG regulation). They go on to characterize the pFGFR1, receptor isoforms, and polarized localization of this receptor. Finally, they perform FGF4 inhibition and use a cell line with a limited FGF17 inactivation (heterozygous null) and show that loss of these FGFs reduces PS-LC and derivative cell types.
Strengths:
(1) As the authors point out, the role of FGF signaling in gastrulation is less well understood than other signaling pathways. Hence this is a valuable contribution to that field.
(2) The FGF4 and FGF17 loss-of-function experiments in Figure 5 are very intriguing. This is especially so given the intriguing observation that these FGFs appear to be dominating in this model of human gastrulation, in contrast to what FGFs dominate in mice, chicks, and frogs.
(3) In general this paper is valuable as a further development of the Human gastruloid system and the role of FGF signaling in the induction of PS-CLs. The wide net that the authors cast in characterizing the FGF ligand gene, receptor isoforms, and downstream components provides a foundation for future work. As the authors write near the beginning of the Discussion "Many questions remain."
Weaknesses:
(1) FGFs are cell survival factors in various aspects of development. The authors fail to address cell death due to loss of FGF signaling in their experiments. For example, in Figure 1E (which requires statistical analysis) and 1G (the bottom FGFRi row), there appears to be a significant amount of cell loss. Is this due to cell death? The authors should address the question of whether the role of FGF/ERK signaling is to keep the cells alive.
(2) Regarding the sparse cells in 1G, is there a reduction in cell number only with FGFRi and not MEKi? Is this reproducible? Gattiglio et al (Development, 2023, PMID: 37530863) present data supporting a "community effect" in the FGF-induced mesoderm differentiation of mouse embryonic stem cells. Could a community effect be at play in this human system (especially given the images in the bottom row of 1G)? If the authors don't address this experimentally they should at least address the ideas in Gattoglio et al.
(3) Do the FGF4 and FGF17 LOF experiments in Figure 5 affect cell numbers like FGFRi in Figure 1? Why examine PS-LC induction only in FGF17 heterozygous cells and not homozygous FGF17 nulls?
(4) The idea that FGF8 plays a dominant role during gastrulation of other species but not humans is so intriguing it warrants deeper testing. The authors dismiss FGF8 because its mRNA "...levels always remained low." (line 363) as well as the data published in Zhai et al (PMID: 36517595) and Tyser et al (PMID: 34789876). But there are cases in mouse development where a gene was expressed at levels so low, that it might be dismissed, and yet LOF experiments revealed it played a role or even was required in a developmental process. The authors should consider FGF8 inhibition or inactivation to explore its potential role, despite its low levels of expression.
(5) Redundancy is a common feature in FGF genetics. What is the effect of inhibiting FGF4 in FGF17 LOF cells?
(6) I suggest stating that the authors take more caution in describing FGF gradients. For example, in one Results heading they write "Endogenous FGF4 and FGF17 gradients underly the ERK activity pattern.", implying an FGF protein gradient. However, they only present data for FGF mRNA , not protein. This issue would be clarified if they used proper nomenclature for gene, mRNA (italics), and protein (no italics) throughout the paper.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Walton et al. set out to isolate new phages targeting the opportunistic pathogen Pseudomonas aeruginosa. Using a double ∆fliF ∆pilA mutant strain, they were able to isolate 4 new phages, CLEW-1. -3, -6, and -10, which were unable to infect the parental PAO1F Wt strain. Further experiments showed that the 4 phages were only able to infect a ∆fliF strain, indicating a role of the MS-protein in the flagellum complex. Through further mutational analysis of the flagellum apparatus, the authors were able to identify the involvement of c-di-GMP in phage infection. Depletion of c-di-GMP levels by an inducible phosphodiesterase renders the bacteria resistant to phage infection, while elevation of c-di-GMP through the Wsp system made the cells sensitive to infection by CLEW-1. Using TnSeq, the authors were able to not only reaffirm the involvement of c-di-GMP in phage infection but also able to identify the exopolysaccharide PSL as a downstream target for CLEW-1. C-di-GMP is a known regulator of PSL biosynthesis. The authors show that CLEW-1 binds directly to PSL on the cell surface and that deletion of the pslC gene resulted in complete phage resistance. The authors also provide evidence that the phage-PSL interaction happens during the biofilm mode of growth and that the addition of the CLEW-1 phage specifically resulted in a significant loss of biofilm biomass. Lastly, the authors set out to test if CLEW-1 could be used to resolve a biofilm infection using a mouse keratitis model. Unfortunately, while the authors noted a reduction in bacterial load assessed by GFP fluorescence, the keratitis did not resolve under the tested parameters.
Strengths:
The experiments carried out in this manuscript are thoughtful and rational and sufficient explanation is provided for why the authors chose each specific set of experiments. The data presented strongly supports their conclusions and they give present compelling explanations for any deviation. The authors have not only developed a new technique for screening for phages targeting P. aeruginosa, but also highlight the importance of looking for phages during the biofilm mode of growth, as opposed to the more standard techniques involving planktonic cultures.
Weaknesses:
While the paper is strong, I do feel that further discussions could have gone into the decision to focus on CLEW-1 for the majority of the paper. The paper also doesn't provide any detailed information on the genetic composition of the phages. It is unclear if the phages isolated are temperate or virulent. Many temperate phages enter the lytic cycle in response to QS signalling, and while the data as it is doesn't suggest that is the case, perhaps the paper would be strengthened by further elimination of this possibility. At the very least it might be worth mentioning in the discussion section.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Abdelmageed et al. investigate age-related changes in the subcellular localization of DNA polymerase kappa (POLK) in the brains of mice. POLK has been actively investigated for its role in translesion DNA synthesis and involvement in other DNA repair pathways in proliferating cells, very little is known about POLK in a tissue-specific context, let alone in post-mitotic cells. The authors investigated POLK subcellular distribution in the brains of young, middle-aged, and old mice via immunoblotting of fractioned tissue extracts and immunofluorescence (IF). Immunoblotting revealed a progressive decrease in the abundance of nuclear POLK, while cytoplasmic POLK levels concomitantly increased. Similar findings were present when IF was performed on brain sections. Further, IF studies of the cingulate cortex (Cg1), the motor cortex (M1, M2), and the somatosensory (S1) cortical regions all showed an age-related decline in nuclear POLK. Nuclear speckles of POLK decrease in each region, meanwhile, the number of cytoplasmic POLK granules decreases in all four regions, but granule size is increasing. The authors report similar findings for REV1, another Y-family DNA polymerase.
The authors then investigate the colocalization of POLK with other DNA damage response (DDR) proteins in either pyramidal neurons or inhibitory interneurons. At 18 months of age, DNA damage marker gH2AX demonstrated colocalization with nuclear POLK, while strong colocalization of POLK and 8-oxo-dG was present in geriatric mice. The authors find that cytoplasmic POLK granules colocalize with stress granule marker G3BP1, suggesting that the accumulated POLK ends up in the lysosome.
Brain regions were further stained to identify POLK patterns in NeuN+ neurons, GABAergic neurons, and other non-neuronal cell types present in the cortex. Microglia associated with pyramidal neurons or inhibitory interneurons were found to have a higher abundance of cytoplasmic POLK. The authors also report that POLK localization can be regulated by neuronal activity induced by Kainic acid treatment. Lastly, the authors suggest that POLK could serve as an aging clock for brain tissue, but POLK deserves further characterization and correlation to functional changes before being considered as a biomarker.
Strengths:
Investigation of TLS polymerases in specific tissues and in post-mitotic cells is largely understudied. The potential changes in sub-cellular localization of POLK and potentially other TLS polymerases open up many questions about DNA repair and damage tolerance in the brain and how it can change with age.
Weaknesses:
The work is quite novel and interesting, and the authors do suggest some potentially interesting roles for POLK in the brain, but these are in and of themselves a bit speculative. The majority of the findings of this paper draw upon findings from POLK antibody and its presumed specificity for POLK. However, this antibody has not been fully validated and needs further work. Further validation experiments using Polk-deficient or knocked-down cells to investigate antibody specificity for both immunoblotting and immunofluorescence should be performed. More mechanistic investigation is needed before POLK could be considered as a brain aging clock.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
This study examined the effects of uncertainty over states (i.e., stimuli) and uncertainty over rewards (i.e., reward probability) on human learning and decision-making in a simple reinforcement learning task. The authors proposed two hypotheses: (1) high uncertainty over states reduces the learning rate, and (2) visual salience drives decision-making. A Bayesian learner is proposed to support the first hypothesis and several regression analyses confirm this finding. Furthermore, the analysis of salience bias also supports the second hypothesis.
Strengths:
(1) The experiment is simple and solid.
(2) The experimental design is clever and consistent with several well-established paradigms.
Weaknesses:
(1) One of my main concerns is that the first conclusion "high uncertainty over states reduces learning rate" is not new and has been shown recently in Yoo et al. (2023). In that study, a slower learning rate was found when stimuli were perceptually similar. It seems to me that the only difference here is that simple Gabor patches are used instead of e.g., green vegetable images in that study. The conclusion is exactly the same.
(2) The second hypothesis should be more explicit. Instead of claiming "A drives B", can you show specific predictions for the direction of this influence? For example, given the same expected value, do human learners prefer to choose a high-contrast stimulus? and why?
(3) The analyses of salience bias support the second hypothesis. However, If I understand it correctly, there is no salience parameter (i.e., absolute contrast of each stimulus) in the decision process, according to Eqs. 4,5, and 6 in the Methods. In other words, the Bayesian learner should not exhibit a salience bias. The question then became, why do human learners have such a bias? What are the underlying mechanisms of the salience bias?
(4) If high perceptual uncertainty reduces the learning rate, why does the normative agent, which takes perceptual uncertainty into account, learn faster than the categorical agent, which has no perceptual uncertainty at all? Did I miss something?
(5) The learning algorithm is different from the standard Q-learning modeling approach. Better to include more explanation of why this type of learning algorithm is Bayesian optimal?
(6) Similar to the above, Bayesian modeling here only confirms that high perceptual uncertainty reduces the learning rate in an optimal Bayesian learner. Two questions remain elusive: (a) whether human learners are close to the Bayesian learner (i.e., near optimal). It seems that (a) is unlikely given several suboptimal heuristics (e.g., confirmation bias) found in humans. Then the question is (b) how optimal learning and suboptimal heuristics are combined in the human learning process. One of the major disadvantages of this study is that no new model is proposed to fit trial-by-trial human choices. I believe that building formal process models is the key to improving this study.
(7) The writing should be substantially improved. The main concern here is that the authors used several seemingly related but ambiguous words to represent the same concept. For example, "perceptual uncertainty" in Figures 1 & 2 indicate the contrast differences between two patches. But page 5 line 9 includes "belief-state uncertainty". Are they the same concept? Moreover, on page 18 line 17, if I understand it correctly, "perceptual uncertainty" here indicates sensory noise not contrast differences. Please carefully check all terminologies and use a single and concrete one to represent a concept throughout the paper.
(8) Similarly, is the "task state" on page 17 the same as the "perceptual state" in Figure 1&2?
(9) The Methods section could also be improved. For example, I am not sure how Eq. 5 is derived. Also, page 18 line 16 states that "in our simulations, we manipulated...'. I did not find any information about the simulation. How was the simulation performed? Did I miss something?
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pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
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ZFIN: ZDB-GENO-060207-1
DOI: 10.1016/j.cub.2023.09.003
Resource: (ZFIN Cat# ZDB-GENO-060207-1,RRID:ZFIN_ZDB-GENO-060207-1)
Curator: @evieth
SciCrunch record: RRID:ZFIN_ZDB-GENO-060207-1
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public review):
This work shows that resistance profiles to a variety of drugs are variable between different mycobacterial species and are not correlated with growth rate or intrabacterial compound concentration (at least for linezolid, bedaquiline, and Rifampicin). Note that intrabacterial compound concentration does not distinguish between cytosolic and periplasmic/cell wall-associated drugs. The susceptibility profiles for a wide range of mycobacteria tested under the same conditions against 15 commonly used antimycobacterial drugs provide the first recorded cross-species comparison which will be a valuable resource for the scientific community. To understand the reasons for the high Rifampicin resistance seen in many mycobacteria, the authors confirm the presence of the arr gene known to encode a Rif ribosyltransferase involved in Rif resistance in M. smegmatis in the resistant mycobacteria after confirming the absence of on-target mutations in the RpoB RRDR. Metabolomic analyses confirm the presence of ribosylated Rif in some of the naturally resistant mycobacteria which may not be entirely surprising but an important confirmation. Presumably M. branderi is highly resistant despite lacking the arr homolog due to the rpoB S45N mutation. M. flavescens has an MIC similar to that of M. smegmatis, despite having both Arr-1 and Arr-X. Various Arr-1 and Arr-X proteins are expressed and characterized for catalytic activity which shows that Arr-X is a faster enzyme,, especially with respect to more hydrophobic rifamycins. M. flavescens has similar MIC values to Rifapentine and Rifabutin to M. smegmatis. Thus, the Arr-1 versus Arr-X comparison does not provide a complete explanation for the underlying reasons driving natural Rif resistance in mycobacteria. Downregulation of Arr-X expression in M. conceptionense confers increased sensitivity to Rifabutin confirming its role as a rifamycin-inactivating enzyme.
Overall, the comparison of cross-species susceptibility profiles is novel; the demonstration that MIC is not correlated with intracellular drug concentration is important but not sufficiently interrogated, the demonstration that Arr-X is also a Rif ADP-ribosyltransferase is a good confirmation and shows that it is more efficient than Arr-1 on hydrophobic rifamycins is interesting but maybe not entirely surprising. The manuscript seems to have two parts that are related, but the rifamycin modification aspect of the work is not strongly linked to the first part since it interrogates the modification of one drug but not the common cause of natural resistance for other drugs.
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Reviewer #1 (Public review):
In this manuscript, the authors aimed to show that SF1 and QKI compete for the intron branch point sequence ACUAA and provide evidence that QKI represses inclusion when bound to it.
Major strengths of this manuscript include:<br /> (1) Identification of the ACUAA-like motif in exons regulated by QKI and SF1.<br /> (2) The use of the splicing reporter and mutant analysis to show that upstream and downstream ACUAAC elements in intron 10 of RAI are required for repressing splicing.<br /> (3) The use of proteomic to identify proteins in C2C12 nuclear extract that binds to the wild type and mutant sequence.<br /> (4) The yeast studies showing that ectopic lethality when Qki5 expression was induced, due to increased mis-splicing of transcripts that contain the ACUAA element.
The authors conclusively show that the ACUAA sequence is bound by QKI and provide strong evidence that this leads to differences in exons inclusion and exclusion. In animal cells, and especially in human, branchpoint sequences are degenerate but seem to be recognized by specific splicing factors. Although a subset of splicing factors shows tissue-specific expression patterns most don't, suggesting that yet-to-be-identified mechanisms regulate splicing. This work suggests that an alternate mechanism could be related to the binding affinity of specific RNA binding factors for branchpoint sequences coupled with the level of these different splicing factors in a given cell.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Shigella flexneri is a bacterial pathogen that is an important globally significant cause of diarrhea. Shigella pathogenesis remains poorly understood. In their manuscript, Saavedra-Sanchez et al report their discovery that a secreted E3 ligase effector of Shigella, called IpaH1.4, mediates the degradation of a host E3 ligase called RNF213. RNF213 was previously described to mediate ubiquitylation of intracellular bacteria, an initial step in their targeting of xenophagosomes. Thus, Shigella IpaH1.4 appears to be an important factor in permitting evasion of RNF213-mediated host defense.
Strengths:
The work is focused, convincing, well-performed, and important. The manuscript is well-written.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public review):
This study highlights the role of role of telomeres in modulating IL-1 signaling and tumor immunity. The authors demonstrate a strong correlation between telomere length and IL-1 signaling by analyzing TNBC patient samples and tumor-derived organoids. Mechanistic insights revealed that non-telomeric TRF2 binding at the IL-1R1. The observed effects on NF-kB signaling and subsequent alterations in cytokine expression contribute significantly to our understanding of the complex interplay between telomeres and the tumor microenvironment. Furthermore, the study reports that the length of telomeres and IL-1R1 expression is associated with TAM enrichment. However, the manuscript lacks in-depth mechanistic insights into how telomere length affects IL-1R1 expression Overall, this work broadens our understanding of telomere biology.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary/Strengths:
This manuscript describes a stimulating contribution to the field of human motor control. The complexity of control and learning is studied with a new task offering a myriad of possible coordination patterns. Findings are original and exemplify how baseline relationships determine learning.
Weaknesses:
A new task is presented: it is a thoughtful one, but because it is a new one, the manuscript section is filled with relatively new terms and acronyms that are not necessarily easy to rapidly understand.
First, some more thoughts may be devoted to the take-home message. In the title, I am not sure manipulating a stick with both hands is a key piece of information. Also, the authors appear to insist on the term 'implicit', and I wonder if it is a big deal in this manuscript and if all the necessary evidence appears in this study that control and adaptation are exclusively implicit. As there is no clear comparison between gradual and abrupt sessions, the authors may consider removing at least from the title and abstract the words 'implicit' and 'implicitly'. Most importantly, the authors may consider modifying the last sentence of the abstract to clearly provide the most substantial theoretical advance from this study.
It seems that a substantial finding is the 'constraint' imposed by baseline control laws on sensorimotor adaptation. This seems to echo and extend previous work of Wu, Smith et al. (Nat Neurosci, 2014): their findings, which were not necessarily always replicated, suggested that the more participants were variable in baseline, the better they adapted to a systematic perturbation. The authors may study whether residual errors are smaller or adaptation is faster for individuals with larger motor variability in baseline. Unfortunately, the authors do not present the classic time course of sensorimotor adaptation in any experiment. The adaptation is not described as typically done: the authors should thus show the changes in tip movement direction and stick-tilt angle across trials, and highlight any significant difference between baseline, early adaptation, and late adaptation, for instance. I also wonder why the authors did not include a few no-perturbation trials after the exposure phase to study after-effects in the study design: it looks like a missed opportunity here. Overall, I think that showing the time course of adaptation is necessary for the present study to provide a more comprehensive understanding of that new task, and to re-explore the role of motor variability during baseline for sensorimotor adaptation.
The distance between hands was fixed at 15 cm with the Kinarm instead of a mechanical constraint. I wonder how much this distance varied and more importantly whether from that analysis or a force analysis, the authors could determine whether one hand led the other one in the adaptation.
I understand the distinction between task- and end-effector irrelevant perturbation, and at the same time results show that the nervous system reacts to both types of perturbation, indicating that they both seem relevant or important. In line 32, the errors mentioned at the end of the sentence suggest that adaptation is in fact maladaptive. I think the authors may extend the Discussion on why adaptation was found in the experiments with end-effector irrelevant and especially how an internal (forward) model or a pair of internal (forward) models may be used to predict both the visual and the somatosensory consequences of the motor commands.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public review):
Summary:
The authors long term goals are to understand the utility of precisely phased cortex stimulation regimes on recovery of function after spinal cord injury (SCI). In prior work the authors explored effects of contralesion cortex stimulation. Here, they explore ipsilesion cortex stimulation in which the ipsilesion corticospinal fibers that cross at the pyramidal decussation are spared. The authors explore the effects of such stimulation in intact rats and rats with a hemisection lesion at thoracic level ipsilateral to the stimulated cortex. The appropriately phased microstimulation enhances contralateral flexion and ipsilateral extension, presumably through lumbar spinal cord crossed extension interneuron systems. This microstimulation improves weight bearing in the ipsilesion hindlimb soon after injury, before any normal recovery of function would be seen. The contralateral homologous cortex can be lesioned in intact rats without impacting the microstimulation effect on flexion and extension during gait. In two rats ipsilateral flexion responses are noted, but these are not clearly demonstrated to be independent of the contralateral homologous cortex remaining intact.
Strengths:
This paper adds to prior data on cortical microstimulation by the authors' laboratory in interesting ways. First, the strong effects of the spared crossed fibers from ipsi-lesional cortex in parts of the ipsi-lesion leg's step cycle and weight support function are solidly demonstrated. This raises the interesting possibility that stimulating contra-lesion cortex as reported previously may execute some of its effects through callosal coordination with the ipsi-lesion cortex tested here. This is also now discussed by the authors and may represent a significant aspect of these data. The authors demonstrate solidly that ablation of the contra-lesional cortex does not impede the effects reported here. I believe this has not been shown for the contra-lesional cortex microstimulation effects reported earlier, but I may be wrong.<br /> Effects and neuroprosthetic control of these effects are explored well in the ipsi-lesion cortex tests here.
Weaknesses:
Some data is based on only a few rats. For example (N=2) for ipsilateral flexion effects of microstimulation. N=3 for homologous cortex ablation, and only ipsi extension is tested it seems. However, these data clearly point the way and replication is likely.
Likely Impacts:
This data adds in significant ways to prior work by the authors, and an understanding of how phased stimulation in cortical neuroprosthetics may aid in recovery of function after SCI, especially if a few ambiguities in writing and interpretation are fully resolved.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 - Public Review
Summary:
Jin, Briggs, and colleagues use light sheet imaging to reconstruct the islet three-dimensional Ca2+ network. The authors find that early/late responding (leader) cells are dynamic over time, and located at the islet periphery. By contrast, highly connected or hub cells are stable and located toward the islet center. Suggesting that the two subpopulations are differentially regulated by fuel input, glucokinase activation only influences leader cell phenotype, whereas hubs remain stable.
Strengths:
The studies are novel in providing the first three-dimensional snapshot of the beta cell functional network, as well as determining the localization of some of the different subpopulations identified to date. The studies also provide some consensus as to the origin, stability, and role of such subpopulations in islet function.
Weaknesses:
Experiments with metabolic enzyme activators do not take into account the influence of cell viability on the observed Ca2+ network data. Limitations of the imaging approach used need to be recognized and evaluated/discussed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors comprehensively present data from single cell RNA sequencing and spatial transcriptomics experiments of the juvenile male and female mouse vomeronasal organ, with a particular emphasis on the neuronal populations found in this sensory tissue. The use of these two methods effectively maps the locations of relevant cell types in the vomeronasal organ at a level of depth beyond what is currently known. Targeted analysis of the neurons in the vomeronasal organ produced several important findings, notably the common co-expression of multiple vomeronasal type 1 receptors (V1Rs), vomeronasal type 2 receptors (V2Rs), and both V1R+V2Rs by individual neurons, as well as the presence of a small but noteworthy population of neurons expressing olfactory receptors (ORs) and associated signal transduction molecules. Additionally, the authors identify transcriptional patterns associated with neuronal development/maturation, producing lists of genes that can be used and/or further investigated by the field. Finally, the authors report the presence of coordinated combinatorial expression of transcription factors and axon guidance molecules associated with multiple neuronal types, providing the framework for future studies aimed at understanding how these patterns relate to the complex glomerular organization in the accessory olfactory bulb. Several of these conclusions have been reached by previous studies, partially limiting the overall impact of the current work. However, when combined, these results provide important insights into the cellular diversity in the vomeronasal organ that are likely to support multiple future studies of the vomeronasal system.
Strengths:
The comprehensive analysis of the data provides a wealth of information for future research into vomeronasal organ function. The targeted analysis of neuronal gene transcription demonstrates the co-expression of multiple receptors by individual neurons, and confirms the presence of a population of OR-expressing neurons in the vomeronasal organ. Although many of these findings have been noted by others, the depth of analysis here validates and extends prior findings in an effective manner. The use of spatial transcriptomics to identify the locations of specific cell types is especially useful and produces a template for the field's continued research into the various cell types present in this complex sensory tissue. Overall, the manuscript's biggest strength is found in the richness of the data presented, which will not only support future work in the broader field of vomeronasal system function but also provide insights into others studying complex sensory tissues.
Weaknesses:
The inherent weaknesses of single cell RNA sequencing studies based on the 10x Genomics platforms (need to dissociate tissues, limited depth of sequencing, etc.) is acknowledged. However, the authors document their extensive attempts to avoid making false positive conclusions through the use of software tools designed for this purpose. Because of its complexity, there are some portions of the manuscript where the data are difficult to interpret as presented, but this is a relatively minor weakness. The data resulting from the use of the Resolve Biosciences spatial transcriptomics platform are somewhat difficult to interpret because the methods are proprietary and presented in an opaque manner. That said, the resulting data provide useful links between transcriptional identities and cellular locations, which is not possible without the use of such tools.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The fungal cell wall is a very important structure for the physiology of a fungus but also for the interaction of pathogenic fungi with the host. Although a lot of knowledge on the fungal cell wall has been gained, there is lack of understanding of the meaning of ß-1,6-glucan in the cell wall. In the current manuscript, the authors studied in particular this carbohydrate in the important human-pathogenic fungus Candida albicans. The authors provide a comprehensive characterization of cell wall constituents under different environmental and physiological conditions, in particular of ß-1,6-glucan. Also, β-1,6-glucan biosynthesis was found to be likely a compensatory reaction when mannan elongation was defective. The absence of β-1,6-glucan resulted in a significantly sick growth phenotype and complete cell wall reorganization. The manuscript contains a detailed analysis of the genetic and biochemical basis of ß-1,6-glucan biosynthesis which is apparently in many aspects similar to yeast. Finally, the authors provide some initial studies on immune modulatory effects of ß-1,6-glucan.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
This work presents CTFFIND5, a new version of the software for determination of the Contrast Transfer Function (CTF) that models the distortions introduced by the microscope in cryoEM images. CTFFIND5 can take acquisition geometry and sample thickness into consideration to improve CTF estimation.
To estimate tilt (tilt angle and tilt axis), the input image is split into tiles and correlation coefficients are computed between their power spectra and a local CTF model that includes the defocus variation according to a tilted plane. As a final step, by applying a rescaling factor to the power spectra of the tiles, an average tilt-corrected power spectrum is obtained used for diagnostic purposes and estimate the goodness of fit. This global procedure and the rescaling factor resemble those used in Bsoft, Warp, etc, with determination of the tilt parameters being a feature specific of CTFFIND5 (and formerly CTFTILT). The performance of the algorithm is evaluated with tilted 2D crystals and tilt-series, demonstrating accurate tilt estimation in general.
CTFFIND5 represents the first CTF determination tool that considers the thickness-related modulation envelope of the CTF firstly described by McMullan et al. (2015) and experimentally confirmed by Tichelaar et al. (2020). To this end, CTFFIND5 uses a new CTF model that takes the sample thickness into account. CTFFIND5 thus provides more accurate CTF estimation and, furthermore, gives an estimation of the sample thickness, which may be a valuable resource to judge the potential for high resolution. To evaluate the accuracy of thickness estimation in CTFFIND5, the authors use the Lambert-Beer law on energy-filtered data and also tomographic data, thus demonstrating that the estimates are reasonable for images with exposure around 30 e/A2. While consideration of sample thickness in CTF determination sounds ideally suited for cryoET, practical application under the standard acquisition protocols in cryoET (exposure of 3-5 e/A2 per image) is still limited. In this regard, the authors are precise in the conclusions and clearly identify the areas where thickness-aware CTF determination will be valuable at present: in situ single particle analysis and in vitro single particle cryoEM of large specimens (e.g. viral particles).
In conclusion, the manuscript introduces novel methods inside CTFFIND5 that improve CTF estimation, namely acquisition geometry and sample thickness. The evaluation demonstrates the performance of the new tool, with fairly accurate estimates of tilt axis, tilt angle and sample thickness and improved CTF estimation. The manuscript critically defines the current range of application of the new methods in cryoEM.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this study from Zhou, Wang, and colleagues, the authors utilize biventricular electromechanical simulations to illustrate how different degrees of ionic remodeling can contribute to different ECG morphologies that are observed in either acute or chronic post-myocardial infarction (MI) patients. Interestingly, the simulations show that abnormal ECG phenotypes - associated with higher risk of sudden cardiac death - are predicted to have almost no correspondence with left ventricular ejection fraction, which is conventionally used as a risk factor for arrhythmia.
Strengths:
The numerical simulations are state-of-the-art, integrating detailed electrophysiology and mechanical contraction predictions, which are often modeled separately. The population of ventricular simulations provide mechanistic interpretation, down to the level of single cell ionic current remodeling, for different types of ECG morphologies observed in post-MI patients. Collectively, these results demonstrate compelling and significant evidence for the need of incorporating additional risk factors for assessing post-MI patients.
The authors have addressed all of my previous concerns in this updated version.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public review):
Summary:
The article 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 and considerably improved the manuscript with experiments and more solid data analysis compared to the first version
Weaknesses:
Some conceptual issues are still present. This is a mechanistic paper done completely in vitro, all references to the in vivo situation are speculative and should be absolutely avoided unless the authors are citing in vivo work.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Madigan et al. assembled an interesting study investigating the role of the MuSK-BMP signaling pathway in maintaining adult mouse muscle stem cell (MuSC) quiescence and muscle function before and after trauma. Using a full body and MuSC-specific genetic knockout system, they demonstrate that MuSK is expressed on MuSCs and that eliminating the BMP binding domain from the MuSK gene (i.e., MuSK-IgG KO) in mice at homeostasis leads to reduced PAX7+ cells, increased myonuclear number, and increase myofiber size, which may be due to a deficit in maintaining quiescence. Additionally, after BaCl2 injury, MuSK-IgG KO mice display accelerated repair after 7 days post-injury (dpi) in males only. Finally, RNA profiling using nCounter technology showed that MuSK-IgG KO MuSCs express genes that may be associated with the activated state.
Strengths:
Overall, the biology regulating MuSC quiescence is still relatively unexplored, and thus, this work provides a new mechanism controlling this process. The experiments discussed in the paper are technically sound with great complementary mouse models (full body versus tissue-specific mouse KO) used to validate their hypothesis. Additionally, the paper is well written with all the necessary information in the legends, methods, and figures being reported.
Weaknesses:
While the data largely supports the author's conclusions, I do have a few points to consider when reading this paper.
(1) For Figure 1, while I appreciate the author's confirming MuSK RNA and protein in MuSCs, I do think they should (a) quantify the RNA using qPCR and (b) determine the percentage of MuSCs expressing MuSK protein in their single fiber system in multiple biological replicates. This information will help us understand if MuSK is expressed in 1/10 or 10/10 PAX7-expressing MuSCs. Also, it will help place their phenotypes into the right context, especially when considering how much of the PAX7-pool is expressing MuSK from the beginning.
(2) Throughout the paper the argument is made that MuSK-IgG KO (full body and MuSC-specific KOs) are more activated and/or break quiescence more readily, but there is no attempt to test directly. Therefore, the authors should consider measuring the activation dynamics (i.e., break from quiescence) of MuSCs directly (EdU assays or live-cell imaging) in culture and/or in muscle in vivo (EdU assays) using their various genetic mouse models.
(3) For Figure 2, given that mice are considered adults by 3 months, it is really surprising how just two months later they are starting to see a phenotype (i.e., reduced PAX7-cells, increased number of myonuclei, and increased myofiber size)-which correlates with getting older. Given that aged MuSCs have activation defects (i.e., stuck somewhere in the quiescence cycle), a pending question is whether their phenotype gets stronger in aged mice, like 18-24 months. If yes, the argument that this pathway should be used in a therapeutic sense would be strengthened.
(4) For Figure 4, the same question as in point (2), the increase in fiber sizes by 7dpi in MuSK-IgG KO males is minimal (going from ~23 to 27 by eye) and no difference at a later time point when compared to WT mice. However, if older mice are used (18-24 months old) - which are known to have repair deficits-will the regenerative phenotype in MuSK-IgG KO mice be more substantial and longer lasting?
(5) For Figure 6, this gene set is not glaringly obvious as being markers of MuSC activation (i.e., no MyoD), so it's hard for the readers to know if this gene set is truly an activation signature. Also, the Shcherbina et al. data presented as a column with * being up or down (i.e. differentially expressed) is not helpful, since you don't know whether those mRNAs in that dataset are going up with the activation process. Addressing this point as well as my point (1) will further strengthen the author's conclusions about the MuSK-IgG KO MuSCs not being able to maintain quiescence as effectively.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors perform irCLIP of neuronal progenitor cells to profile eIF3-RNA interactions upon short-term neuronal differentiation. The data shows that eIF3 mostly interacts with 3'-UTRs - specifically, the poly-A signal. There appears to be a general correlation between eIF3 binding to 3'-UTRs and ribosome occupancy, which might suggest that eIF3 binding promotes protein synthesis, possibly through inducing mRNA closed-loop formation.
Strengths:
The study provides a wealth of new data on eIF3-mRNA interactions and points to the potential new concept that eIF3-mRNA interactions are polyadenylation-dependent and correlate with ribosome occupancy.
Weaknesses:
(1) A main limitation is the correlative nature of the study. Whereas the evidence that eIF3 interacts with 3-UTRs is solid, the biological role of the interactions remains entirely unknown. Similarly, the claim that eIF3 interactions with 3'-UTR termini require polyadenylation but are independent of poly(A) binding proteins lacks support as it solely relies on the absence of observable eIF3 binding to poly-A (-) histone mRNAs and a seeming failure to detect PABP binding to eIF3 by co-immunoprecipitation and Western blotting. In contrast, LC-MS data in Supplementary File 1 show ready co-purification of eIF3 with PABP.
(2) Another question concerns the relevance of the cellular model studied. irCLIP is performed on neuronal progenitor cells subjected to neuronal induction for 2 hours. This short-term induction leads to a very modest - perhaps 10% - and very transient 1-hour-long increase in translation, although this is not carefully quantified. The cellular phenotype also does not appear to change and calling the cells treated with differentiation media for 2 hours "differentiated NPCs" seems a bit misleading. Perhaps unsurprisingly, the minor "burst" of translation coincides with minor effects on eIF3-mRNA interactions most of which seem to be driven by mRNA levels. Based on the ~15-fold increase in ID2 mRNA coinciding with a ~5-fold increase in ribosome occupancy (RPF), ID2 TE actually goes down upon neuronal induction.
(3) The overlap in eIF3-mRNA interactions identified here and in the authors' previous reports is minimal. Some of the discrepancies may be related to the not well-justified approach for filtering data prior to assessing overlap. Still, the fundamentally different binding patterns - eIF3 mostly interacting with 5'-UTRs in the authors' previous report and other studies versus the strong preference for 3'-UTRs shown here - are striking. In the Discussion, it is speculated that the different methods used - PAR-CLIP versus irCLIP - lead to these fundamental differences. Unfortunately, this is not supported by any data, even though it would be very important for the translation field to learn whether different CLIP methodologies assess very different aspects of eIF3-mRNA interactions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The manuscript by Bohra et al. describes the indirect effects of ligand-dependent gene activation on neighboring non-target genes. The authors utilized single-molecule RNA-FISH (targeting both mature and intronic regions), 4C-seq, and enhancer deletions to demonstrate that the non-enhancer-targeted gene TFF3, located in the same TAD as the target gene TFF1, alters its expression when TFF1 expression declines at the end of the estrogen signaling peak. Since the enhancer does not loop with TFF3, the authors conclude that mechanisms other than estrogen receptor or enhancer-driven induction are responsible for TFF3 expression. Moreover, ERα intensity correlations show that both high and low levels of ERα are unfavorable for TFF1 expression. The ERa level correlations are further supported by overexpression of GFP-ERa. The authors conclude that transcriptional machinery used by TFF1 for its acute activation can negatively impact the TFF3 at peak of signaling but once, the condensate dissolves, TFF3 benefits from it for its low expression.
Strengths:
The findings are indeed intriguing. The authors have maintained appropriate experimental controls, and their conclusions are well-supported by the data.
Weaknesses:
There are some major and minor concerns that related to approach, data presentation and discussion. But I think they can be fixed with more efforts.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
This work sets out to elucidate mechanistic intricacies in inflammatory responses in pneumonia in the context of aging process (Terc deficiency - telomerase functionality).
Strengths:
Very interesting, conceptually speaking, approach that is by all means worth pursuing. An overall proper approach to the posited aim.
Weaknesses:
The work is heavily underpowered and may have statistical deficits. This precludes at its current state drawing unequivocal conclusions.
I remain at my initial position regarding the weaknesses.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The manuscript entitled "Staphylococcus aureus counters organic acid anion-mediated inhibition of peptidoglycan cross-linking through robust alanine racemase activity" by Panda, S et al. reports an extensive biochemical analysis of the result from a Tn screen that identified alr1 as being required for acetic acid tolerance. In the end, they demonstrate that reduced D-Ala pools in the ∆alr1 mutant lead to a drastic reduction in D-Ala-D-Ala dipeptide. They show that this is due to the ability of organic acid anions to limit the D-Ala-D-Ala ligase enzyme Ddl. They demonstrate that:
(1) Acetate exposure in the ∆alr1 results in reduced D-Ala-D-Ala dipeptide, but not the monomers.
(2) Acetate can bind to purified Ddl in vitro.
(3) This binding results in reduced enzyme activity.
(4) Other organic acid anions such as lactate, proprionate, and itaconitate can also inhibit Ddl.
The experiments are clearly described and logically laid out.
Comments on revised version:
Given that multiple reviewers noted that determining intracellular acetate levels would strengthen the impact of this manuscript, I still think the comment listed below should be dealt with. Radioactivity is not necessary for this. There are enzymatic kits that will allow for the accurate determination of acetate from a lysate of a known number of cells. This can be used to determine intracellular acetate levels.
(1) It is kind of tricky, but it is possible to measure intracellular acetate. That might be of interest to know where in the Ddl inhibition curve the cells actually are.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
The authors use fluorescence lifetime imaging (FLIM) and tmFRET to resolve resting vs. active conformational heterogeneity and free energy differences driven by cGMP and cAMP in a tetrameric arrangement of CNBDs from a prokaryotic CNG channel.
Strengths:
The data are excellent and provide detailed measures of the probability to adopt resting vs. activated conformations with and without bound ligands.
Weaknesses:
A limitation is that only the cytosolic fragments of the channel were studied.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
In this study, the authors developed a novel radiotherapy sensitivity score (NPC-RSS) for nasopharyngeal carcinoma patients using machine learning algorithms. They identified 18 key genes associated with radiosensitivity and demonstrated that NPC-RSS could effectively predict radiotherapy response in both public and in-house datasets. Furthermore, they found that the key genes of NPC-RSS were closely related to immune characteristics, the expression of radiosensitivity-related genes, and signaling pathways involved in disease progression. The authors validated the consistency of expression of two key genes, SMARCA2 and CD9, with NPC-RSS in their own cell lines. They also showed that the radiosensitive group, classified by NPC-RSS, exhibited a more enriched and activated state of immune infiltration compared to the radioresistant group.
Strengths:
(1) The study employed a comprehensive approach by integrating multiple machine learning algorithms to develop a robust predictive model for radiotherapy sensitivity in nasopharyngeal carcinoma patients.<br /> (2) The predictive performance of NPC-RSS was validated using both public and in-house datasets, demonstrating its potential clinical applicability.<br /> (3) The authors conducted extensive analyses to investigate the biological mechanisms underlying the association between NPC-RSS and radiotherapy response, including immune characteristics, radiosensitivity-related gene expression, and relevant signaling pathways.<br /> (4) The consistency of key gene expression with NPC-RSS was validated in the authors' own cell lines, providing additional experimental evidence.
Weaknesses:
(1) The sample size of the in-house dataset used for training the model was relatively small (34 patients), which might limit the generalizability of the findings.<br /> (2) The authors did not perform functional experiments to directly validate the roles of the identified key genes in radiotherapy sensitivity, relying instead on associations with immune features and signaling pathways.<br /> (3) The study did not discuss the potential limitations of using machine learning algorithms, such as the risk of overfitting and the need for larger, diverse datasets for more robust model development and validation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public review):
Summary:
Intravital microscopy (IVM) is a powerful tool that facilitates live imaging of individual cells over time in vivo in their native 3D tissue environment. Extracting and analysing multi-parametric data from IVM images however is challenging, particularly for researchers with limited programming and image analysis skills. In this work, Rios-Jimenez and Zomer et al have developed a 'zero-code' accessible computational framework (BEHAV3D-Tumour Profiler) designed to facilitate unbiased analysis of IVM data to investigate tumour cell dynamics (via the tool's central 'heterogeneity module') and their interactions with the tumour microenvironment (via the 'large-scale phenotyping' and 'small-scale phenotyping' modules). It is designed as an open-source modular Jupyter Notebook with a user-friendly graphical user interface and can be implemented with Google Colab, facilitating efficient, cloud-based computational analysis at no cost.
To demonstrate the utility of BEHAV3D-TP, they apply the pipeline to timelapse IVM imaging datasets to investigate the in vivo migratory behaviour of fluorescently labelled DMG cells in tumour-bearing mice. Using the tool's 'heterogeneity module' they were able to identify distinct single-cell behavioural patterns (based on multiple parameters such as directionality, speed, displacement, and distance from tumour edge) which was used to group cells into distinct categories (e.g. retreating, invasive, static, erratic). They next applied the framework's 'large-scale phenotyping' and 'small-scale phenotyping' modules to investigate whether the tumour microenvironment (TME) may influence the distinct migratory behaviours identified. To achieve this, they combine TME visualisation in vivo during IVM (using fluorescent probes to label distinct TME components) or ex vivo after IVM (by large-scale imaging of harvested, immunostained tumours) to correlate different tumour behavioural patterns with the composition of the TME. They conclude that this tool has helped reveal links between TME composition (e.g. degree of vascularisation, presence of tumour-associated macrophages) and the invasiveness and directionality of tumour cells, which would have been challenging to identify when analysing single kinetic parameters in isolation.
A key limitation of the pipeline is that it does not overcome the main challenges and bottlenecks associated with processing and extracting quantitative cellular data from timelapse and longitudinal intravital images. This includes correcting breathing-induced movement artifacts, automated registration of longitudinal images taken over days/weeks, and accurate, automated segmentation and tracking of individual cells over time. Indeed, there are currently no standardised computational methods available for IVM data processing and analysis, with most laboratories relying on custom-built solutions or manual methods. This isn't made explicit in the manuscript early on (described below), and the researchers rely on expensive software packages such as IMARIS for image processing and data extraction to feed the required parameters into their pipeline. This limitation unfortunately reduces the likely impact of BEHAV3D-TP on the IVM field.
Nonetheless, this computational framework appears to represent a useful and comparatively user-friendly tool to analyse dynamic multi-parametric data to help identify patterns in cell migratory behaviours, and to assess whether these behaviours might be influenced by neighbouring cells and structures in their microenvironment. When combined with other methods, it, therefore, has the potential to be a valuable addition to a researcher's IVM analysis 'tool-box'.
Strengths:
(1) The figures are clearly presented, and the manuscript is easy to follow.
(2) The pipeline appears to be intuitive and user-friendly for researchers with limited computational expertise. A detailed step-by-step video is also included to support its uptake.
(3) The different computational modules have been tested using a relevant dataset.
(4) All code is open source, and the pipeline can be implemented with Google Colab.
(5) The tool combines multiple dynamic parameters extracted from time-lapse IVM images to identify single-cell behavioural patterns and to cluster cells into distinct groups sharing similar behaviours, and provides avenues to map these onto in vivo or ex vivo imaging data of the tumour microenvironment.
Weaknesses:
(1) As highlighted above, the tool does not facilitate the extraction of quantitative kinetic cellular parameters (e.g. speed, directionality, persistence, and displacement) from intravital images. Indeed, to use the tool researchers must first extract dynamic cellular parameters from their IVM datasets, requiring access to expensive software (e.g. IMARIS as used here) and/or above-average computational expertise to develop and use custom-made open-source solutions. This limitation is not made explicit or discussed in the text.
(2) The number of cells (e.g. per behavioural cluster), and the number of independent mice, represented in each result figure, is not included in the figure legends and are difficult to ascertain from the methods.
(3) The data used to test the pipeline in this manuscript is currently not available, making it difficult to assess its usability. It would be important to include this for researchers to use as a 'training dataset'.
(4) Precisely how the BEHAV3D-TP large-scale phenotyping module can map large-scale spatial phenotyping data generated using LSR-3D imaging data and Cytomap to 3D intravital imaging movies is unclear. Further details in the text and methods would be beneficial to aid understanding.
(5) The analysis provides only preliminary evidence in support of the authors' conclusions on DMG cell migratory behaviours and their relationship with components of the tumour microenvironment. Conclusions should therefore be tempered in the absence of additional experiments and controls.
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Reviewer #1 (Public review):
Summary:
The authors sought to identify unknown factors involved in the repair of uracil in DNA through a CRISPR knockout screen.
Strengths:
The screen identified both known and unknown proteins involved in DNA repair resulting from uracil or modified uracil base incorporation into DNA. The conclusion is that the protein activity of METTL3, which converts A nucleotides to 6mA nucleotides, plays a role in the DNA damage/repair response. The importance of METTL3 in DNA repair, and its colocalization with a known DNA repair enzyme, UNG2, is well characterized.
Weaknesses:
This reviewer identified no major weaknesses in this study. The manuscript could be improved by tightening the text throughout, and more accurate and consistent word choice around the origin of U and 6mA in DNA. The dUTP nucleotide is misincorporated into DNA, and 6mA is formed by methylation of the A base present in DNA. Using words like 6mA "deposition in DNA" seems to imply it results from incorporation of a methylated dATP nucleotide during DNA synthesis.
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Reviewer #1 (Public review):
Summary:
This article identifies ADGR3 as a candidate GPCR for mediating beige fat development. The authors use human expression data from Human Protein Atlas and Gtex databases and combine this with experiments performed in mice and a murine cell line. They refer to a GPCR bioactivity screening tool PRESTO-Salsa, with which it was found that Hesperetin activates ADGR3. From their experiments, authors conclude that Hesperetin activates ADGR3, inducing a Gs-PKA-CREB axis resulting in adipose thermogenesis.
Strengths:
The authors analyze human data from public databases and perform functional studies in mouse models. They identify a new GPCR with a role in thermogenic activation of adipocytes.
Considerations:
Selection of ADGRA3 as a candidate GPCR relevant for mediating beiging in humans:
The authors identify GPCRs that are expressed more highly in murine iBAT compared to iWAT in response to cold and assess which of these GPCRs are expressed in human subcutaneous or visceral adipocytes. Although this strategy will identify GPCRs that are expressed at higher levels in brown fat compared to beige and thus possibly more active in thermogenic function, the relevance in choosing GPCRs that also are expressed in unstimulated human white adipocytes should be considered. Thermogenic activity is not normally present in human white adipocytes. It would have strengthened the GPCR selection if the authors instead had assessed the intersection with human brown adipocytes that were activated with norepinephrine.
Strategy to investigate the role of ADGRA3 in WAT beiging:
Having identified ADGRA3 as their candidate receptor, the authors investigated the receptor in mouse models, the murine inguinal adipocyte cell line 3T3 and in human subcutaneous adipose progenitors (HAdsc) differentiated in vitro. Calling the human cells "beige" is a stretch as these cells are derived from a white adipose depot. The authors do observe regulation in UCP1 and abundance of mitochondria following modification of ADGRA3 in the cells. However, in future studies, it should be considered if the receptor rather plays a role in differentiation per se, and perhaps not specifically in thermogenic differentiation/activity.
According to the Human Protein Atlas and Gtex databases, ADGRA3 is not only expressed in adipocytes, but also in other tissues and cell types. The authors address this by measuring the expression in a panel of these tissues, demonstrating a knockdown not only in the adipose tissue, but also in the liver and less pronounced in the muscle (Figure S2). It should thus be emphasized that the decreased TG levels in serum and liver in the mice might in fact depend on Adgra3 overexpression in the liver. Even though this might not have been the purpose of the experiment, it is important to highlight this as it could serve as hypothesis building for future studies of the function of this receptor.
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Reviewer #1 (Public review):
Summary:
The mammalian Shieldin complex consisting of REV7 (aka MAD2L2, MAD2B) and SHLD1-3 affects pathway usage in DSB repair favoring non-homologous endjoining (NHEJ) at the expense of homologous recombination (HR) by blocking resection and/or priming fill-in DNA synthesis to maintain or generate near blunt ends suitable for NHEJ. While the budding yeast Saccharomyces cerevisiae does not have homologs to SHLD1-3, it does have Rev7, which was identified to function in conjunction with Rev3 in the translesion DNA polymerase zeta. Testing the hypothesis that Rev7 also affect DSB resection in budding yeast, the work identified a direct interaction between Rev7 and the Rad50-Mre11-Xrs2 complex by two-hybrid and direct protein interaction experiments. Deletion analysis identified that the 42 amino acid C-terminal region was necessary and sufficient for the 2-hybrid interaction. Direct biochemical analysis of the 42 aa peptide was not possible. Rev7 deficient cells were found to be sensitive to HU only in synergy with G2 tetraplex forming DNA. Importantly, the 42 aa peptide alone suppressed this phenotype. Biochemical analysis with full-length Rev7 and a C-terminal truncation lacking the 42 aa region shows G4-specific DNA binding that is abolished in the C-terminal truncation and with a substrate containing mutations to prevent G4 formation. Rev7 lacks nuclease activity but inhibits the dsDNA exonuclease activity of Mre11. The C-terminal truncation protein lacking the 42 aa region also showed some inhibition suggesting the involvement of additional binding sites besides the 42 aa region. Also, the Mre11 ssDNA endonuclease activity is inhibited by Rev7 but not the degradation of linear ssDNA. Rev7 does not affect ATP binding by Rad50 but inhibits in a concentration-dependent manner the Rad50 ATPase activity. The C-terminal truncation protein lacking the 42 aa region also showed some inhibition but significantly less than the full-length protein. Using an established plasmid-based NHEJ assay, the authors provide strong evidence that Rev7 affects NEHJ, showing a four-fold reduction in this assay. The mutations in the other Pol zeta subunits, Rev3 and Rev1, show a significantly smaller effect (~25% reduction). A strain expressing only the Rev7 C-terminal 42 aa peptide showed no NHEJ defect, while the truncation protein lacking this region exhibited a smaller defect than the deletion of REV7. The conclusion that Rev7 supports NHEJ mainly through the 42 aa region was validated using a chromosomal NHEJ assay. The effect on HR was assessed using a plasmid:chromosome system containing G4 forming DNA. The rev7 deletion strain showed an increase in HR in this system in the presence and absence of HU. Cells expressing the 42 aa peptide were indistinguishable from wild type as were cells expressing the Rev7 truncation lacking the 42 aa region. The authors conclude that Rev7 suppresses HR, but the context appears to be system-specific and the conclusion that Rev7 abolished HR repair of DSBs is unwarranted and overly broad.
Strength:
This is a well-written manuscript with well-executed experiments which suggest that Rev7 inhibits MRX-mediated resection to favor NEHJ during DSB repair. This finding is novel and provides insight into the potential mechanism of how the human Shieldin complex might antagonize resection.
Weaknesses:
The nuclease experiments were conducted using manganese as a divalent cation, and it is unclear whether there is an effect with the more physiological magnesium cation. The data largely support the conclusions, although the effect of Rev7 on HR is less well documented, as only a highly specialized assay is used that does not warrant the broad conclusion drawn. Specifically, the results that the Rev7 c-terminal truncation lacking the 42 aa region still suppresses HR is unexpected and unexplained.
In this revision the authors addressed most of my concerns by text revisions and addition of new data.
The new two hybrid data showing that the 42 amino acid segment interacts with MRN are valuable. However, it may not be clear to which subunit the 42 aa segment binds, as in the yeast 2H system the chromosomally encoded subunits are present or were the 2H experiments conducted in an MRN deletion background?. This could be acknowledged.
The material and methods section was updated to indicate use of 5 mM MnCl2 and 5 mM MgCl2 in the exonuclease assay but not the endonuclease assay. Please check if this is correct. Why the difference between both assays? There is a concern that the absence of ATP and Mg affects the endonuclease assay.
The addition of Dmc1 as a specificity control for the ATPase inhibition is nice and shows a specific effect. The use of Sae2 associated nuclease activity as a specificity control for the nuclease inhibition is problematic. There has been considerable debate about the Sae2 associated nuclease activity, which seems to have been solved by the Cejka lab showing that Sae2 is a cofactor of MRN without intrinsic nuclease activity (e.g. https://pubmed.ncbi.nlm.nih.gov/25231868/). Or do the authors want to suggest that Sae2 has intrinsic nuclease activity? The control may still be useful mentioning that the nuclease is associated but not intrinsic and citing the relevant papers.
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