- Last 7 days
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Reviewer #1 (Public Review):
Summary:
The current manuscript uses electron spin resonance spectroscopy to understand how the dynamic behavior and conformational heterogeneity of the LPS transport system change during substrate transport and in response to the membrane, bound nucleotide (or transition state analog) and accessory subunits. The study builds on prior structural studies to expand our molecular understanding of this highly significant bacterial transport system.
Strengths
This series of well-designed and well-executed experiments provide new mechanistic insights into the dynamic behavior of the LPS transport system. Notable new insights provided by this study include its indication of the spatial organization of the LptC domain, which was poorly resolved in structures, and how the LptC domain modulates the dynamic behavior of the gate through which lipids access the binding site. In addition, a mass spectrometry approach designed to examine LPS binding at different stages in the nucleotide-dependent conformational cycle provides insight into the order of operations of LPS binding and transport.
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Reviewer #1 (Public Review):
In this study, the Authors used a stopped-flow method to investigate the kinetics of substrate translocation through the channel in hexameric ClpB, an ATP-dependent bacterial protein disaggregase. They engineered a series of polypeptides with the N-terminal RepA ClpB-targeting sequence followed by a variable number of folded titin domains. The Authors detected translocation of the substrate polypeptides by observing the enhancement of fluorescence from a probe located at the substrate's C-terminus. The total time of the substrates' translocation correlated with their lengths, which allowed the Authors to determine the number of residues translocated by ClpB per unit time.
Strengths:
This study confirms a previously proposed model of processive translocation of polypeptides through the channel in ClpB. The novelty of this work is in a clever design of a series of kinetic experiments with an engineered substrate that includes stably folded domains. This approach produced a quantitative description of the reaction rates and kinetic step sizes. Another valuable aspect is that the method can be used for other translocases from the AAA+ family to characterize their mechanism of substrate processing.
Weaknesses:
The main limitation of the study is in using a single non-physiological substrate of ClpB, which does not replicate physical properties of the aggregated cellular proteins and includes a non-physiological ClpB-targeting sequence. Another limitation is in the use of ATPgammaS to stimulate the substrate processing. It is not clear how relevant the results are to the ClpB function in living cells with ATP as the source of energy, a multitude of various aggregated substrates without targeting sequences that need ClpB's assistance, and in the presence of the co-chaperones.
Evidence that ATPgammaS without ATP can provide sufficient energy for substrate translocation and unfolding is missing in the paper because the rate of phosphate release from ATPgammaS has not been determined. Thus, it is not clear if the observed translocation is linked to an actual chemical energy input or is a result of a diffusion-driven ratchet mediated by a substrate-trapping ClpB conformation obtained in the presence of ATPgammaS.
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Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors delineate the crucial role of the SIRT2-ACSS2 axis in ACSS2 degradation. They demonstrate that SIRT2 acts as an ACSS2 deacetylase specifically under nutrient stress conditions, notably during amino acid deficiency. The SIRT2-mediated deacetylation of ACSS2 at K271 consequently triggers its proteasomal degradation. Additionally, they illustrate that acetylation of ACSS2 at K271 enhances ACSS2 protein levels, thereby promoting De Novo lipogenesis.
Strengths:
The findings presented in this manuscript are clearly interesting.
Weaknesses:
Further support is required for the model put forward by the authors.
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Reviewer #1 (Public Review):
Summary:
The authors want to determine the role of the sperm hook of the house mouse sperm in movement through the uterus. They use transgenic lines with fluorescent labels to sperm proteins, and they cross these males to C57BL/6 females in pathogen-free conditions. They use 2-photon microscopy on ex vivo uteri within 3 hours of mating and the appearance of a copulation plug. There are a total of 10 post-mating uteri that were imaged with 3 different males. They provide 10 supplementary movies that form the basis for some of the quantitative analysis in the main body figures. Their data suggest that the role of the sperm hook is to facilitate movement along the uterine wall.
Strengths:
Ex vivo live imaging of fluorescently labeled sperm with 2-photon microscopy is a powerful tool for studying the behavior of sperm.
Weaknesses:
The paper is descriptive and the data are correlations.
The authors cannot directly test their proposed function of the sperm hook in sliding and preventing backward slipping.
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Reviewer #1 (Public Review):
Summary:
This study investigated the co-option of IGF2BP2, an RNA binding protein by ZIKV proteins. Designed experiments evaluated if IFG2BP2 co-localized to sites of viral RNA replication, interacted with ZIKV proteins and how ZIKV infection changed the IGF2BP2 interactome.
Strengths:
The authors have used multiple interdisciplinary techniques to address several questions regarding the interaction of ZIKV proteins and IGF2BP2.
The findings could be exciting if concerns are addressed, specifically regarding how ZIKV infection alters the interactome of IGF2BP2.
Comments on thee revised version:
Following response to reviews, the authors have addressed a majority of the concerns with the exception of the western blots:
As requested in the previous review, the authors did quantify the western blot data for half of the blot in 2A, but did not quantify blots in D and E. Please quantify ALL blots. Also, the first two lanes of 2A. The same goes for 4A only infected is quantified, please quantify Mock as well. In the quantification of 4C, all lanes should be quantified, not only the NS5 from C. Also, unclear which lanes were quantified (H/PF/2013 or MR766)? Also, quantification needs to be generally shown as a graph and not included on top of the western blot.
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Combined Public Reviews:
Summary:
This study presents an immunotherapeutic strategy for treating mouse cutaneous squamous cell carcinoma (mCSCC) using a passive immunity-like strategy. The researcher induced tumors in healthy mice skin, then isolated the tumor cells and injected into other healthy mice to produce anti-tumor antibodies, and then administered these antibodies back into tumor-bearing mice. Results showed a reduction in tumor volume and altered expression of several cancer markers (p53, Bcl-xL, NF-κB, Bax). The analysis of results suggests a promising impact of antibody-rich serum in treating mouse cutaneous squamous cell carcinoma (mCSCC).
Strengths:
The approach does seem to have effect on preventing tumor progression, from both the tumor size and the cancer hallmarks expression level.
Weaknesses:
Despite the strength of the study, there are a few drawbacks in the study design and statistical analysis:
(1) Regarding the statistical analysis, the use of a paired t-test might be suboptimal for assessing the trend from weeks 15 to 17. It is recommended to consider alternative methods such as repeated measures ANOVA or linear regression to better capture and interpret the trend over this time period.
(2) To affirm the antibodies' role in the observed immune response, isolating antibodies rather than employing whole serum could provide more conclusive evidence. Comparative analyses with antibody-free serum or serum from healthy, non-immunized mice would clarify antibodies' specific contributions versus other serum components. The control group does not account for the potential immunostimulatory effects of serum injection itself. A better control would be tumor-bearing mice receiving serum from healthy non-mCSCC-exposed mice.
Response to author's rebuttal:
I acknowledge the value of evaluating serum therapy as a whole, considering the complex interactive networks and potential synergies involved. However, to scientifically understand and assess serum therapy, it remains essential to decompose the serum and identify the effective components. This decomposition would allow for a comparison of individual components with the overall effectiveness, thereby elucidating any synergistic effects.<br /> While I agree that identifying specific epitopes and paratopes is indeed challenging and may exceed the scope of academic research, the use of methods such as Protein A purification or other techniques to isolate antibodies and cytokines from the serum is both necessary and feasible. This approach would enable a more detailed analysis of the individual effects of these components. I understand that the authors might not have that much resource, and I acknowledge this limitation. Nonetheless, other than this aspect, I believe the authors have adequately addressed my other concerns.
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Reviewer #1 (Public Review):
In this study, Le Moigne and coworkers shed light on the structural details of the Sedoheptulose-1,7-Bisphosphatase (SBPase) from the green algae Chlamydomonas reinhardtii. The SBPase is part of the Calvin cycle and catalyzes the dephosphorylation of sedoheptulose-1,7-bisphosphate (SBP), which is a crucial step in the regeneration of ribulose-1,5-bisphosphate (RuBP), the substrate for Rubisco. The authors determine the crystal structure of the CrSBPase in an untreated, oxidized state. Based on this structure, potential active site residues and sites of post-translational modifications are identified. Furthermore, the authors determine the CrSBPase structure in a reduced state revealing the disruption of a disulfide bond in close proximity to the dimer interface. The authors then use molecular dynamics (MD) to gain insights into the redox-controlled dynamics of the CrSBPase and investigate the oligomerization of the protein using small-angle X-ray scattering (SAXS) and size-exclusion chromatography. Despite the difference in oligomerization, disruption of this disulfide bond did not impact the activity of CrSBPase, suggesting additional thiol-dependent regulatory mechanisms modulating the activity of the CrSBPase.
The authors provide interesting new findings on a redox-mechanism that modulates the oligomeric behavior of the SBPase. Comparisons of the Chlamydomonas structure to the previously determined SBPase structure from the moss Physcomitrium patens confirm a high structural similarity between the two proteins suggesting that this mechanism might be evolutionary conserved. Future research will have to address this question experimentally, also considering potential cooperativity between the subunits to confirm the link between oligomerization and SBPase activity.
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Reviewer #1 (Public Review):
Summary:
Mao and colleagues re-analysed published spatial, bulk and single-cell transcriptomic datasets from primary colorectal cancers and colorectal cancer derived liver metastases. The analyses of paired cancer and non-cancer tissue samples showed that T cells are enriched in tumour tissue, accompanied by a reduction in the fraction of NK cells in the cancer tissue transcriptional datasets. Furthermore, the authors show that tumour tissue has higher fraction of GZMK+ (resting) NK cells and suggested a correlation between the presence of these cells and poor prognosis for cancer patients. In contrast, the increased frequency of KIR2DL4+ (activated) NK cells correlates with improved survival of cancer patients.
Strengths:
Authors performed a comprehensive analysis of published datasets, integrating spatial and single-cell transcriptomic data, which allowed them to discover enrichment of GZMK+ NK cells in cancer tissues.
Weakness:
The authors provided insufficient experimental evidence to support their claim that GZMK+ NK cells contribute to worse prognosis for cancer patients or promote cancer progression. While one can visually observe an increased fraction of GZMK+ NK cells compared to KIR2DL4+ NK cells in cancer tissues, no quantification is shown. They did not present any preclinical (animal model) or clinical data suggesting a causal relationship between NK cells and tumour growth. Thus, while a correlation may exist between the presence of GZMK+ NK cells and poorer tumour prognosis, causation cannot be claimed based on the available evidence. Furthermore, the in vitro data provided is limited to a single NK cell line derived from a lymphoma patient, which does not fully represent the diversity and functionality of human NK cells.
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Reviewer #1 (Public Review):
In the manuscript "Mechanistic target of rapamycin (mTOR) pathway in Sertoli cells regulates age-dependent changes in sperm DNA methylation", the authors proposed to test if the balance of mTOR complexes in Sertoli cells may play a significant role in age-dependent changes in the sperm epigenome. The paper could be of interest and has a good scientific aim but there are too many drawbacks that hamper the initial enthusiasm. All sections need extensive revision. The paper is mostly descriptive without a mechanistic-orientated explanation for the observed results.
Comments on revised version:
I am not sure that the authors have made an attempt to clearly answer the reviewers comments that aimed to improve the quality of the manuscript. It stands as mostly descriptive and with limited interest as it is.
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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.
Weaknesses:
(1) Despite the authors restraint in interpreting the three states of the spliceosome observed by cyroEM as sequential intermediates along the splicing pathway, it would be helpful to the general reader to explicitly acknowledge the alternative possibility that the difference states simply reflect decomposition from one intermediate during isolation of the complex (i.e., the loss of protein is an in vitro artifact, if an informative one).<br /> (2) The authors acknowledge that for prp8 suppressors of the fyv6 deletion, suppression may be indirect, as originally proposed by the Query and Konarska labs - that is, that defects in the second step conformation of the spliceosome can be indirectly suppressed by compensating, destabilizing mutations in the first step spliceosome. Whereas some of the other suppressors of the fyv6 deletion can be interpreted as impacting directly the second step spliceosome (e.g., because the gene product is only present in the second step conformation), it seems that many more suppressors beyond prp8 mutants, especially those corresponding to bulky substitutions, which would more likely destabilize than stabilize, could similarly act indirectly by destabilization of first step conformation. The authors should acknowledge this where appropriate (e.g., for factors like Prp8 that are present in both first and second step conformations).
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Reviewer #1 (Public Review):
Summary:
This study sought to reveal the potential roles of m6A RNA methylation in gene dosage regulatory mechanisms, particularly in the context of aneuploid genomes in Drosophila. Specifically, this work looked at the relationships between the expression of m6A regulatory factors, RNA methylation status, classical and inverse dosage effects, and dosage compensation. Using RNA sequencing and m6A mapping experiments, an in-depth analysis was performed to reveal changes in m6A status and expression changes across multiple aneuploid Drosophila models. The authors propose that m6A methylation regulates MOF and, in turn, deposition of H4K16Ac, critical regulators of gene dosage in the context of genomic imbalance.
Strengths:
This study seeks to address an interesting question with respect to gene dosage regulation and the possible roles of m6A in that process. Previous work has linked m6A to X-inactivation in humans through the Xist lncRNA, and to the regulation of the Sxl in flies. This study seeks to broaden that understanding beyond these specific contexts to more broadly understand how m6A impacts imbalanced genomes in other contexts.
Weaknesses:
The methods being used particularly for analysis of m6A at both the bulk and transcript-specific level are not sufficiently specific or quantitative to be able to confidently draw the conclusions the authors seek to make. MeRIP m6A mapping experiments can be very valuable, but differential methylation is difficult to assess when changes are small (as they often are, in this study but also m6A studies more broadly). For instance, based on the data presented and the methods described, it is not clear that the statement that "expression levels at m6A sites in aneuploidies are significantly higher than that in wildtype" is supported. MeRIP experiments are not quantitative, and since there are far fewer peaks in aneuploidies, it stands to reason that more antibody binding sites may be available to enrich those fewer peaks to a larger extent. But based on the data as presented (figure 2D) this conclusion was drawn from RPKM in IP samples, which may not fully account for changing transcript abundances in absolute (expression level changes) and relative (proportion of transcripts in input RNA sample) terms.
The bulk-level m6A measurements as performed here also cannot effectively support these conclusions, as they are measured in total RNA. The focus of the work is mRNA m6A regulators, but m6A levels measured from total RNA samples will not reflect mRNA m6A levels as there are other abundance RNAs that contain m6A (including rRNA). As a result, conclusions about mRNA m6A levels from these measurements are not supported.
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Reviewer #1 (Public Review):
Summary:<br /> In this manuscript, the authors use gene functional analysis, pharmacology and live imaging to develop a proposed model of diverse G protein family signalling that takes place in the papillae during the ascidian Ciona larval adhesion to regulate the timing of initiation of the morphological changes of metamorphosis. Their experiments provide solid evidence that antagonistic G protein signalling regulates cAMP levels in the papillae, which provides a threshold for triggering metamorphosis that is reflective of a larva keeping a strong and sustained level of contact with a substrate for a minimum period of approximately half an hour. The authors discuss their reasoning and address different specific aspects of their proposed timing mechanism to provide a logical flow to the manuscript. The results are nicely linked to<br /> the ecology of Ciona larval settlement and will be of interest to developmental biologists, neurobiologists, molecular biologists, marine biologists as well as provide information relevant to antifouling and aquaculture sectors.
First, they knock down the G proteins Gaq and Gas to show that these genes are important for Ciona larval metamorphosis. They then provide evidence that the Gaq protein acts through a Ca2+ pathway mediated by phospholipase C and inositol triphosphate by showing that inositol phosphate and phospholipase C gene knockdown also inhibits metamorphosis, while overexpression of Gaq or phospholipase C allows larvae to undergo metamorphosis even in the absence of their mechanosensory cue, which is deprived by removing the posterior half of the tail and culturing the larvae on agar-coated dishes. The authors used calcium imaging which is a genetically encoded fluorescent calcium sensor to show that Gq knockdown larvae lack a Ca2+ spike in their papillae after mechanostimulation, confirming that Gaq acts through a Ca2+ pathway. Similarly the authors show that overexpression of Gas also enables larvae to metamorphose in the absence of mechanostimulation, suggesting a role for both Gaq and Gas in this process.
To confirm that Gas acts through cAMP signalling, the authors use pharmacological treatment or overexpression of a photoactivating adenylate cyclase to increase cAMP, and show that this also enables larvae to metamorphose in the absence of mechanostimulation, but only<br /> when their adhesive papillae are still present. Transcriptome data indicate that both Gs and Gq pathway genes are expressed in the adhesive papillae of the Ciona larva. One missing detail seems to be the need for evidence that cAMP is elevated in the papillae directly as a result of Gs activation. The authors use a fluorescent cAMP indicator, Pink Flamindo, to show that cAMP increases in the papillae upon adhesion to a substrate. Complementary to this, larvae that fail to undergo metamorphosis lack a cAMP increase in papillae. However, it is unclear whether the measured larvae that failed to undergo metamorphosis were wildtype or Gas knockdown larvae. If they were Gas knockdown larvae, this could provide evidence that cAMP does act downstream of the Gas activation.
The authors then provide evidence that GABA signalling within the papillae is acting downstream of the G proteins to induce metamorphosis. Transcriptome data shows that the genes for the GABA-producing enzyme, and for GABAb receptors, are both expressed in papillae. Pharmacological experiments show that GABA induces metamorphosis in the absence of mechanosensory cues, but only in larvae that retain their papillae. To show that GABA signalling within the papillae, rather than from the brain of the larva is important, the authors also demonstrate that anterior segments of larvae lacking the brain can also be stimulated to metamorphose by GABA, and show changes in gene expression caused by GABA.
The authors then use a combination of pharmacology and knockdown experiments in the presence or absence of mechanosensory cues to show that Gq/Ca2+ signalling acts upstream of Gs/cAMP signalling. As the elevation of cAMP by pharmacology or photoactivating adenylate cyclase rescued GABA pathway mutant larvae, the Gq and Gs pathways were concluded to be downstream of GABA signaling. However, GABA treatment could still induce Gaq- and Gas-knockdown larvae to metamorphose, suggesting an alternative pathway to metamorphosis, which the authors deduce to be through a third G protein, Gai. They identify an unusual Gai protein that based on transcriptome data is strongly expressed in the papillae. Gai knockdown larvae fail to metamorphose but are rescued by GABA treatment, which can be explained by a potential additional Gai protein being still present (transcriptome evidence suggests this although it is not further confirmed experimentally, for example by hybridization, immunohistochemistry, fluorescent labelling, or knockdown). The authors then use overexpression and knockdown experiments to show that the Gai protein acts through Gβγi complex to activate phospholipase C. Their experiments also indicate a potential for a complementary or compensatory role for Gai and Gaq signalling through Gβγi. By inhibiting the potassium channel GIRK through knockdown, and the MAPK pathway gene MEK1/2 by pharmacology, the authors also establish a role for these in their proposed model of signalling, allowing GABA and cAMP to compensate or interact with each other.
Strengths:<br /> The strength of this paper is the meticulous and extensive experiments, which are carefully designed to be able to precisely target specific genes in the putative signalling pathway to build step by step a complex model that can demonstrate how metamorphosis of the ascidian larva is timed so as to only undergo metamorphosis when strongly attached to a<br /> suitable substrate. The unique possibility of inhibiting mechanosensory-induced metamorphosis by removing some of the tail and smoothing the attachment substrate allows the authors to investigate potential effects on both activation and inhibition of metamorphosis, and to confirm that specific signalling pathways are clearly downstream of the initial<br /> mechanosensory stimulation. The study is also clear about which aspects of the model still remain unknown, such as which ligands and receptors may be responsible for the binding and activation of Gaq and Gas. Experiments testing metamorphosis of just the anterior region of the larvae nicely demonstrates the need for signalling in the region of the papillae, as do experiments where the papillae are removed, which then block metamorphosis in treatments that would otherwise stimulate it. The final model is a nice end point and makes a clear summary of how the extensive experiments all fit together into a cohesive potential signalling network, which can be built upon in the future.
Weaknesses:<br /> The paper has few weaknesses, however the main difficulty it poses is that due to the sheer number of precise experiments carried out and the complexity of the interwoven signalling pathways, it quickly becomes very difficult to follow exactly what is going on when and why or to keep track of the story as it develops. To improve this, an initial section in the results could be included showing a summary of the known G proteins in Ciona, their types and potential downstream signalling or upstream receptors, where known, and their expression levels in papillae. This could be in the form of a table and/or include the phylogenetic tree from the supplementary data. This would help clarify why the study first focuses on Gaq and Gas, and only later looks at Gai. This could be supplemented by a schematic workflow giving an overview of the experimental process of the study. A second minor weakness (understandable as the focus of the study is metamorphosis induced by mechanosensory stimulation) is that the study does not take into account any potential role for other types of sensory modalities (light, chemicals) that may also feed into the regulation of Ciona larval metamorphosis. This aspect would be interesting to discuss in light of the recent paper suggesting that some sensory cells in the Ciona adhesive papillae are polymodal and detect both chemicals and mechanical stimuli (Hoyer et al. 2024 Current Biology 34(6): 1168 - 1182).
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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 a 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 the immune modulatory effects of ß-1,6-glucan.
Strengths:
The findings are very well documented, and the data are clear and obtained by sophisticated biochemical methods. It is impressive that the authors successfully optimized methods for the analyses and quantification of ß-1-6-glucan under different environmental conditions and in different mutant strains.
Weaknesses:
However, although already very interesting, at this stage there are some loose ends that need to be combined to strengthen the manuscript. For example, the immunological studies are rather preliminary and need at least some substantiation. Also, at this stage, the manuscript in some places remains a bit too descriptive and needs the elucidation of potential causalities.
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Reviewer #1 (Public Review):
Summary:<br /> In this study, Masroor Ahmad Paddar and his/her colleagues explore the noncanonical roles of ATG5 and membrane atg8ylation in regulating retromer assembly and function. They begin by examining the interactomes of ATG5 and expand the scope of these effects to include homeostatic responses to membrane stress and damage.
Strengths:<br /> This study provides novel insights into the noncanonical function of ATG8ylation in endosomal cargo sorting process.
Weaknesses:<br /> The direct mechanism by which ATG8ylation regulates the retromer remains unsolved.
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Reviewer #1 (Public Review):
By mapping H3K4me2 in mouse oocytes and pre-implantation embryos, the authors aim to elucidate how this histone modification is erased and re-established during the parental-to-zygotic transition, as well as how the reprogramming of H3K4me2 regulates gene expression and facilitates zygotic genome activation.
Employing an improved CUT&RUN approach, the authors successfully generated H3K4me2 profiling data from a limited number of embryos. While the profiling experiments are very well executed, several weaknesses, particularly in data analysis, are apparent:
(1) The study emphasizes H3K4me2, which often serves as a precursor to H3K4me3, a well-studied modification during early development. Analyzing the new H3K4me2 dataset alongside published H3K4me3 data is crucial for comprehensively understanding epigenetic reprogramming post-fertilization and the interplay between histone modifications. However, the current analysis is preliminary and lacks depth.
(2) Tranylcypromine (TCP) is known as an irreversible inhibitor of monoamine oxidase and LSD1. While the authors suggest TCP inhibits the expression of LSD2, this assertion is questionable. Given TCP's potential non-specific effects in cells, conclusions related to the experiments using TCP should be made with caution.
(3) Some batches of H3K4me2 antibody are known to cross-react with H3K4me3. Has the H3K4me2 antibody used in CUT&RUN been tested for such cross-reactivity? Heatmaps in the figures indeed show similar distribution for H3K4me2 and H3K4me3, further raising concerns about antibody specificity.
(4) Certain statements lack supporting references or figures (examples on page 9 can be found on line 245, line 254, and line 258).
(5) Extensive language editing is recommended to clarify ambiguous sentences. Additionally, caution should be taken to avoid overstatement - most analyses in this study only suggest correlation rather than causality.
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Reviewer #1 (Public Review):
Summary:<br /> 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:<br /> (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:<br /> (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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Reviewer #1 (Public Review):
In this study, the authors conducted a single-cell RNA sequencing analysis of the cellular and transcriptional landscape of the gastric cancer tumor microenvironment, stratifying patients according to their H. pylori status into currently infected, previously infected, and non-infected patients. The authors comprehensively dissect various cellular compartments, including epithelial, stromal, and immune cells, and describe specific cell types and signatures to be associated with H. pylori infection, including i) inflammatory and EMT signatures in malignant epithelial cells, ii) inflammatory CAFs in stromal cells, iii) Angio-TAMs, TREM2+ TAMs, exhausted and suppressive T cells in immune cells. Looking at ligand-receptor interactions as well as correlations between cell type abundances, they suggest that iCAFs interact with immunosuppressive T cells via a NECTIN2-TIGIT axis, as well as Angio-TAMs through a VEGFA/B-VEGFR1 axis and thereby promote immune escape, tumor angiogenesis and resistance to immunotherapy.
The authors conduct a comprehensive and thorough analysis of the complex tumor microenvironment of gastric cancer, both single-cell RNA sequencing data as well as the analysis seem of high quality and according to best practices. The authors validate their findings using external datasets, and include some prognostic value of the identified signatures and cell types. However, most of their conclusions throughout the manuscript are based on the comparison between HPGC and healthy controls, which is not a valid comparison to determine which of the phenotypes are specifically driven by HP infection, e.g. Tregs are high in all GC types, independent of HP status. The same holds true for TREM+ TAMs and iCAFs, which are higher in GC in general. This makes it very difficult to assess the actual HP-driven signatures and cell types. Also, when looking at the correlation/transcriptional differences across different cell types and cellular interactions, the authors do not explicitly define if they are looking at the whole dataset (including healthy controls?) or only at certain patients (HPGC?), which again makes it difficult to interpret the results.
The authors aim to confirm some of their findings via immunofluorescence, which in principle is a great approach to validate their results. However, to be able to conclude that e.g. suppressive TIGIT+ T cells are located close to NECTIN2+ malignant epithelium and that this might facilitate immune escape in HPGC (Figure 4K), the authors should include stains that show that this is not the case in the other groups (nonHPGC, exHPGC and HC). The same holds true for Figure 5G.
In summary, this study provides a valuable resource on the cellular and transcriptional heterogeneity of the tumor microenvironment in gastric cancers, distinguishing between positive, negative, and previously positive HP-infected gastric cancer patients. Given that HP is the main risk factor for gastric cancer development, the study provides valuable insights into HP-driven transcriptional signatures and how these might contribute to this increased risk, however, the study would highly benefit from a clearer and more stringent comparison between HPGC and nonHPGC.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, Li and colleagues have found mircoRNAs that affect levels of metamorphosis-regulating genes that can also affect levels of sesquiterpenoids (juvenile hormone and related compounds) and ecdysteriods, which regulate the timing and stages of insects, respectively. They first compared the transcriptomes of Drosophila at the third larval instar and at the white pre-pupa stage. They found thousands of differences in gene transcript levels between males and females, and between the two different stages. Among those genes that were differentially regulated they saw that genes involved in insect hormone biosynthesis were disproportionately represented. Many of the differentially regulated genes were involved in the insect hormone biosynthesis pathway and ascorbate and alderete metabolism. MicroRNAs were also differentially expressed during metamorphosis and were separately identified. The authors then considered genes and whether the differentially expressed microRNAs might regulate transcripts known to be involved in sesquiterpenoid production. In silico analysis of microRNAs predicted a list of 17 microRNAs that can regulate transcripts of sesquiterpenoid biosynthesis genes. The authors then used an in vitro luciferase assay to validate the binding and downregulation of 10 of the microRNAs to genes involved with sesquiterpenoid production in S2 cells.
Li and colleagues then focus on two genes they found were bound by microRNAs that have established roles in metamorphosis. The microRNAs miR-34 and miR-277 bind transcripts of two protein-coding genes that regulate metamorphosis Kr-h1, which encodes a transcription factor that is a JH-inducible transcription factor, and Allatostatin C Receptor 1, (AstC-R1), a G-protein coupled receptor that regulates the corpora allatum, the gland that produces sesquiterpenoids. Using a LAMP assay, one of the microRNAs, miR-277 was shown to bind to both AstC-R1 and Kr-h1 in in vivo whole-animal extracts. There is no mention of binding between either protein-coding transcript and the miR-34 microRNA. Temporal expression of all four transcripts shows that their abundance is anti-correlated; stages of high miR-34 or miR-277 expression correlate with low AstC-R1 or Kr-h1 expression. Homozygous deletions of both mircroRNAs result in 23% lethality, five days after adult eclosion. The authors also generated specific mutants in miR-34 or miR-277 and find differences in the expression of AstC-R1 and Kr-h1 and sex-specific differences in both sesquiterpenoids and ecdysteroids in the knock-out lines. If there were phenotypes associated with the specific knock-outs, those were not mentioned. Next, the authors examined the transcriptomes of the miR-3277 and miR-34 mutants and found several other GO-terms enriched among the differentially expressed genes. However, the sesquiterpenoid pathway and ascorbate and alderete metabolism are not listed.
Strengths:
This is an interesting manuscript that could make an important contribution to our understanding of the roles of micro RNAs at metamorphosis, and potentially of how sex-specific differences arise during metamorphosis. Strengths of the paper include the functional validation of microRNA binding, in vitro and in vivo-, as well as the characterization of sesquiterpenoid and ecdysteroid titers. The authors have also used CRISPR to generate specific knock-outs of miR-34 and miR-277. The transcriptomes will be a resource for future work to mine for differences in gene expression during metamorphosis.
Weaknesses:
(1) Spatial Expression of miR-34 and miR-277. If miR-34 and miR-277 regulate AstC-R1 and Kr-h1, then they must be expressed in the same cells. Although the authors show that the microRNAs do bind to the transcripts of AstC-R1 and Kr-h1 in S2 cells, and miR-277 binds AstC-R1 and Kr-h1 in vivo whole-animal homogenates, we do not know if the microRNAs are ever in the cells where AstC-R1 or Kr-h1 are expressed. AstC-R1 is only expressed in a few cells in the brain, so it is not at all certain that it is co-expressed with either microRNA. The creation of enhancer lines or in situ hybridization in Drosophila is straightforward and would sort this out.
(2) Phenotypes. Although a double deletion was used and specific knock-outs of both miR-34 and miR-277 were generated, the analysis of the mutants is very superficial. For the homozygous deletion of both microRNAs miR-34 and miR-277, only a decrease in survivorship was observed a full six days after adult eclosion - after the end of metamorphosis. No phenotype for either miR-34KO or miR-277-KO was given. The authors cite the work of others who have found specific phenotypes after manipulation of sesquiterpenoids or ecdysteroids, like Riddiford and Ashburner, but do not use any of these many studies to help them characterize the phenotype. If the loss of miR-34 and miR-277 affects so many pathways (including MAPK signaling, TGF-beta signaling, FoxO signaling, and Wnt signaling), as well as global titers of metamorphic hormones, then there shouldn't there be something different in the development to discuss?
(3) I think the reliance on GO term enrichment is getting in the way of biology. For instance, I would not describe Kr-h1 as a sesquiterpenoid biosynthesis pathway gene. Yet the authors say they were motivated to examine microRNA regulation of Kr-h1 because they saw differences in levels of the sesquiterpenoid biosynthesis pathway between WL3 and WPP, a period which also saw differences in expression of some microRNAs. I understand that Kr-h1 expression is regulated by JH, a sesquiterpenoid, but it is not directly involved with JH production, so relying on GO term enrichment has made the decision to focus on Kr-h1 feel arbitrary.
(4) The transcriptomes of miR-34 and miR-277 should have revealed genes encoding members of the sesquiterpenoid biosynthesis pathway as well as AstC-R1 and Kr-h1, but neither was mentioned. The functional tests of miR-34 and miR-277 were performed because they were shown to affect the levels of expression of genes in the sesquiterpenoid biosynthesis pathway. Figure 2 shows a significant decrease in AstC-R1 and Kr-h1 transcripts after the loss of miR-34 and miR-277. However, the results do not mention either (Lines 250-264). Instead, there is a list of 10 different GO terms (like arginine and proline metabolism or fatty acid degradation) that were enriched in miR-34 and miR-277 transcriptomes. If any of those ten types have any relationship to Kr-h1, AstC-R1, or metamorphosis, that has not been explained.
(5) Not enough care was taken in describing the stages. The methods describe wandering larvae (WL3) and white pre-pupa (WPP) for the transcriptomes, but in the text, different terms are used, like "larva", "pupa" and "L3 larvae instars" "early pupae" "late L3". Also, it seems like the small RNA libraries for sequencing were taken from "L3 larvae", but the stage of the L3 larvae was not mentioned. Staging is important, especially during metamorphosis, since differences in expression are expected to exist between different stages of L3, between early vs late wandering, and between WPP and early pupal stages.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The paper titled "STAG3 promotes exit from pluripotency through post-transcriptional mRNA regulation in the cytoplasm" suggests a new and unexpected role for STAG3, a protein traditionally associated with the cohesin complex during meiosis, in regulating the exit from pluripotency in mouse embryonic stem cells (mESCs). While STAG3 is traditionally studied for its role in meiosis, this paper reveals that STAG3 is expressed in mouse embryonic stem cells (mESCs) and primordial germ cell-like cells (PGCLCs) and may be necessary for PGCLC-like specification and exit from pluripotency. In ESCs, the study reports that STAG3 is found in the cytoplasm, where it interacts with various RNA-binding proteins (RBPs) and localizes to centrosomes. Knockdown of STAG3 disrupts centrosome stability and RNA-induced silencing complex (RISC) components, leading to the misregulation of mRNAs such as DPPA3, Nanog, and TNRC6C. In summary, this study expands the known functions of STAG3 beyond cohesin, highlighting a potential role in cytoplasmic post-transcriptional regulation.
The authors perform a comprehensive characterization of RNA and protein changes in ESCs and differentiated cells upon loss of STAG3, providing preliminary and intriguing insights. However, there are several aspects that require further exploration:
(1) A rescue experiment for the STAG3 RNAi is missing, making it unclear whether the observed effects are indeed due to the knockdown of STAG3.
(2) While the paper identifies several interactions and effects of STAG3, it lacks detailed mechanistic insights into how STAG3 regulates specific mRNAs and proteins. Specifically, it is unclear which proteins directly interact with STAG3 or recruit STAG3 to RNP complexes. AlphaFold may help in this analysis.
(3) It is unclear whether this is an alternative STAG3 isoform or if STAG3 is modified. What dictates its interaction with cohesin versus RNPs?
(5) Are there unique features or sequence barcodes present on the misregulated RNAs?
(6) Does STAG3 associate with a single type of RNP or is it present in all types?
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arxiv.org arxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> The authors used multiple approaches to study salt effects in liquid-liquid phase separation (LLPS). Results on both wild-type Caprin1 and mutants and on different types of salts contribute to a comprehensive understanding.
Strengths:<br /> The main strength of this work is the thoroughness of investigation. This aspect is highlighted by the multiple approaches used in the study, and reinforced by the multiple protein variants and different salts studied.
Weaknesses:<br /> (1) The multiple computational approaches are a strength, but they're cruder than explicit-solvent all-atom molecular dynamics (MD) simulations and may miss subtle effects of salts. In particular, all-atom MD simulations demonstrate that high salt strengthens pi-types of interactions (ref. 42 and MacAinsh et al, https://www.biorxiv.org/content/10.1101/2024.05.26.596000v3).
(2) The paper can be improved by distilling the various results into a simple set of conclusions. By example, based on salt effects revealed by all-atom MD simulations, MacAinsh et al. presented a sequence-based predictor for classes of salt dependence. Wild-type Caprin1 fits right into the "high net charge" class, with a high net charge and a high aromatic content, showing no LLPS at 0 NaCl and an increasing tendency of LLPS with increasing NaCl. In contrast, pY-Caprin1 belongs to the "screening" class, with a high level of charged residues and showing a decreasing tendency of LLPS.
(3) Mechanistic interpretations can be further simplified or clarified. (i) Reentrant salt effects (e.g., Fig. 4a) are reported but no simple explanation seems to have been provided. Fig. 4a,b look very similar to what has been reported as strong-attraction promotor and weak-attraction suppressor, respectively (ref. 50; see also PMC5928213 Fig. 2d,b). According to the latter two studies, the "reentrant" behavior of a strong-attraction promotor, CL- in the present case, is due to Cl-mediated attraction at low to medium [NaCl] and repulsion between Cl- ions at high salt. Do the authors agree with this explanation? If not, could they provide another simple physical explanation? (ii) The authors attributed the promotional effect of Cl- to counterion-bridged interchain contacts, based on a single instance. There is another simple explanation, i.e., neutralization of the net charge on Caprin1. The authors should analyze their simulation results to distinguish net charge neutralization and interchain bridging; see MacAinsh et al.
(4) The authors presented ATP-Mg both as a single ion and as two separate ions; there is no explanation of which of the two versions reflects reality. When presenting ATP-Mg as a single ion, it's as though it forms a salt with Na+. I assume NaCl, ATP, and MgCl2 were used in the experiment. Why is Cl- not considered? Related to this point, it looks like ATP is just another salt ion studied and much of the Results section is on NaCl, so the emphasis of ATP ("Diverse Roles of ATP" in the title is somewhat misleading.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
During vertebrate gastrulation, mesendoderm cells are initially specified by morphogens (e.g. Nodal) and segregate into endoderm and mesoderm in part based on Nodal concentrations. Using zebrafish genetics, live imaging, and single-cell multi-omics, the manuscript by Cheng et al presents evidence to support a claim that anterior endoderm progenitors derive primarily from prechordal plate progenitors, with transcriptional regulators goosecoid (Gsc) and ripply1 playing key roles in this cell fate determination. Such a finding would represent a significant advance in our understanding of how anterior endoderm is specified in vertebrate embryos.
Strengths:
Live imaging-based tracking of PP and endo reporters (Figure 2) is well executed and convincing, though a larger number of individual cell tracks will be needed. Currently, only a single cell track (n=1) is provided.
Weaknesses:
(1) The central claim of the paper - that the anterior endoderm progenitors arise directly from prechordal plate progenitors - is not adequately supported by the evidence presented. This is a claim about cell lineage, which the authors are attempting to support with data from single-cell profiling and genetic manipulations in embryos and explants. The construction of gene expression (pseudo-time) trajectories, while a modern and powerful approach for hypothesis generation, should not be used as a substitute for bona fide lineage tracing methods. If the authors' central hypothesis is correct, a CRE-based lineage tracing experiment (e.g. driving CRE using a PP marker such as Gsc) should be able to label PP progenitor cells that ultimately contribute to anterior endoderm-derived tissues. Such an experiment would also allow the authors to quantify the relative contribution of PP (vs non-PP) cells to the anterior endoderm, which is not possible to estimate from the indirect data currently provided. Note: while the present version of the manuscript does describe a sox17:CRE lineage tracing experiment, this actually goes in the opposite direction that would be informative (sox:17:CRE-marked descendants will be a mixture of PP-derived and non-PP derived cells, and the Gsc-based reporter does not allow for long-term tracking the fates of these cells).
(2) The authors' descriptions of gene expression patterns in the single-cell trajectory analyses do not always match the data. For example, it is stated that goosecoid expression marks progenitor cells that exist prior to a PP vs endo fate bifurcation (e.g. lines 124-130). Yet, in Figure 1C it appears that in fact goosecoid expression largely does not precede (but actually follows) the split and is predominantly expressed in cells that have already been specified into the PP branch. Likewise, most of the cells in the endo branch (or prior) appear to never express Gsc. While these trends do indeed appear to be more muddled in the explant data (Figure 1H), it still seems quite far-fetched to claim that Gsc expression is a hallmark of endoderm-PP progenitors.
(3) The study seems to refer to "endoderm" and "anterior endoderm" somewhat interchangeably, and this is potentially problematic. Most single-cell-based analyses appearing in the study rely on global endoderm markers (sox17, sox32) which are expressed in endodermal precursors along the entire ventrolateral margin. Some of these cells are adjacent to the prechordal plate on the dorsal side of the gastrula, but many (most in fact) are quite some distance away. The microscopy-based evidence presented in Figure 2 and elsewhere, however, focuses on a small number of sox17-expressing cells that are directly adjacent to, or intermingled with, the prechordal plate. It, therefore, seems problematic for the authors to generalize potential overlaps with the PP lineage to the entire endoderm, which includes cells in ventral locations. It would be helpful if the authors could search for additional markers that might stratify and/or mark the anterior endoderm and perform their trajectory analysis specifically on these cells.
(4) It is not clear that the use of the nodal explant system is allowing for rigorous assessment of endoderm specification. Why are the numbers of endoderm cells so vanishingly few in the nodal explant experiments (Figure 1H, 3H), especially when compared to the embryo itself (e.g. Figures 1C-D)? It seems difficult to perform a rigorous analysis of endoderm specification using this particular model which seems inherently more biased towards PP vs. endoderm than the embryo itself. Why not simply perform nodal pathway manipulations in embryos?
(5) The authors should not claim that proximity in UMAP space is an indication of transcriptional similarity (lines 207-208), especially for well-separated clusters. This is a serious misrepresentation of the proper usage of the UMAP algorithm. The authors make a similar claim later on (lines 272-274).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors wanted to identify genes that are critical for regulating the asymmetric fates of limbal stem cells and their transit amplified progeny in the central cornea. To this end, they utilized an in vivo cell cycle reporter to isolate proliferating basal cells from the anterior ocular surface epithelium and performed single-cell RNA-seq. This strategy revealed distinct basal cell identities with unique expression profiles of structural genes and transcription factors. The authors then focused on the Sox9 transcription factor implicated in stem cell regulation. It was differentially expressed between limbal stem cells and their progeny in the central cornea. Lineage tracing analysis confirmed that Sox9 marks long-lived limbal stem cells. Conditional deletion of Sox9 led to abnormal differentiation and squamous metaplasia in the central cornea. The authors suggest that Sox9 is required for the switch to asymmetric fate and commitment toward differentiation, as transit cells exit the limbal niche. By inhibiting the terminal differentiation of corneal progenitors and forcing them into continuous symmetric divisions, the Sox9 loss-of-function phenotype was replicated.
Strengths:
Thus, the paper shows the important role of Sox9 in the spatial regulation of asymmetric fate in the corneal epithelium and its proliferation and cell differentiation. The work is elegantly done using several models that converge on the main conclusions. It is very novel and delineates a new player in determining corneal epithelial cell fate. The experiments are well done, and the data are credible.
Weaknesses:
This reviewer has some minor concerns mostly related to data interpretation and the use of the LSC term.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Fuchsberger et al. demonstrate a set of experiments that ultimately identifies the de novo synthesis of GluA1-, but not GluA2-containing Ca2+ permeable AMPA receptors as a key driver of dopamine-dependent LTP (DA-LTP) during conventional post-before-pre spike-timing dependent (t-LTD) induction. The authors further identify adenylate cyclase 1/8, cAMP, and PKA as the crucial mitigators of these actions. While some comments have been identified below, the experiments presented are thorough and address the aims of the manuscript, figures are presented clearly (with minor comments), and experimental sample sizes and statistical analyses are suitable. Suitable controls have been utilized to confirm the role of Ca2+ permeable AMPAR. This work provides a valuable step forward built on convincing data toward understanding the underlying mechanisms of spike-timing-dependent plasticity and dopamine.
Strengths:
Appropriate controls were used.
The flow of data presented is logical and easy to follow.
The quality of the data, except for a few minor issues, is solid.
Weaknesses:
The drug treatment duration of anisomycin is longer than the standard 30-45 minute duration (as is the 500uM vs 40uM concentration) typically used in the field. Given the toxicity of these kinds of drugs long term it's unclear why the authors used such a long and intense drug treatment.
With some of the normalizations (such as those in S1) there are dramatic differences in the baseline "untreated" puromycin intensities - raising some questions about the overall health of slices used in the experiments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors are attempting to use the internal workings of a language hierarchy model, comprising phonemes, syllables, words, phrases, and sentences, as regressors to predict EEG recorded during listening to speech. They also use standard acoustic features as regressors, such as the overall envelope and the envelopes in log-spaced frequency bands. This is valuable and timely research, including the attempt to show differences between normal-hearing and hearing-impaired people in these regards.
I will start with a couple of broader questions/points, and then focus my comments on three aspects of this study: The HM-LSTM language model and its usage, the time windows of relevant EEG analysis, and the usage of ridge regression.
Firstly, as far as I can tell, the OSF repository of code, data, and stimuli is not accessible without requesting access. This needs to be changed so that reviewers and anybody who wants or needs to can access these materials.
What is the quantification of model fit? Does it mean that you generate predicted EEG time series from deconvolved TRFs, and then give the R2 coefficient of determination between the actual EEG and predicted EEG constructed from the convolution of TRFs and regressors? Whether or not this is exactly right, it should be made more explicit.
About the HM-LSTM:
• In the Methods paragraph about the HM-LSTM, a lot more detail is necessary to understand how you are using this model. Firstly, what do you mean that you "extended" it, and what was that procedure? And generally, this is the model that produces most of the "features", or regressors, whichever word we like, for the TRF deconvolution and EEG prediction, correct? A lot more detail is necessary then, about what form these regressors take, and some example plots of the regressors alongside the sentences.<br /> • Generally, it is necessary to know what these regressors look like compared to other similar language-related TRF and EEG/MEG prediction studies. Usually, in the case of e.g. Lalor lab papers or Simon lab papers, these regressors take the form of single-sample event markers, surrounded by zeros elsewhere. For example, a phoneme regressor might have a sample up at the onset of each phoneme, and a word onset regressor might have a sample up at the onset of each word, with zeros elsewhere in the regressor. A phoneme surprisal regressor might have a sample up at each phoneme onset, with the value of that sample corresponding to the rarity of that phoneme in common speech. Etc. Are these regressors like that? Or do they code for these 5 linguistic levels in some other way? Either way, much more description and plotting is necessary in order to compare the results here to others in the literature.<br /> • You say that the 5 regressors that are taken from the trained model's hidden layers do not have much correlation with each other. However, the highest correlations are between syllable and sentence (0.22), and syllable and word (0.17). It is necessary to give some reason and interpretation of these numbers. One would think the highest correlation might be between syllable and phoneme, but this one is almost zero. Why would the syllable and sentence regressors have such a relatively high correlation with each other, and what form do those regressors take such that this is the case?<br /> • If these regressors are something like the time series of zeros along with single sample event markers as described above, with the event marker samples indicating the onset of the relevant thing, then one would think e.g. the syllable regressor would be a subset of the phoneme regressor because the onset of every syllable is a phoneme. And the onset of every word is a syllable, etc.
For the time windows of analysis:
• I am very confused, because sometimes the times are relative to "sentence onset", which would mean the beginning of sentences, and sometimes they are relative to "sentence offset", which would mean the end of sentences. It seems to vary which is mentioned. Did you use sentence onsets, offsets, or both, and what is the motivation?<br /> • If you used onsets, then the results at negative times would not seem to mean anything, because that would be during silence unless the stimulus sentences were all back to back with no gaps, which would also make that difficult to interpret.<br /> • If you used offsets, then the results at positive times would not seem to mean anything, because that would be during silence after the sentence is done. Unless you want to interpret those as important brain activity after the stimuli are done, in which case a detailed discussion of this is warranted.<br /> • For the plots in the figures where the time windows and their regression outcomes are shown, it needs to be explicitly stated every time whether those time windows are relative to sentence onset, offset, or something else.<br /> • Whether the running correlations are relative to sentence onset or offset, the fact that you can have numbers outside of the time of the sentence (negative times for onset, or positive times for offset) is highly confusing. Why would the regressors have values outside of the sentence, meaning before or after the sentence/utterance? In order to get the running correlations, you presumably had the regressor convolved with the TRF/impulse response to get the predicted EEG first. In order to get running correlation values outside the sentence to correlate with the EEG, you would have to have regressor values at those time points, correct? How does this work?<br /> • In general, it seems arbitrary to choose sentence onset or offset, especially if the comparison is the correlation between predicted and actual EEG over the course of a sentence, with each regressor. What is going on with these correlations during the middle of the sentences, for example? In ridge regression TRF techniques for EEG/MEG, the relevant measure is often the overall correlation between the predicted and actual, calculated over a longer period of time, maybe the entire experiment. Here, you have calculated a running comparison between predicted and actual, and thus the time windows you choose to actually analyze can seem highly cherry-picked, because this means that most of the data is not actually analyzed.<br /> • In figures 5 and 6, some of the time window portions that are highlighted as significant between the two lines have the lines intersecting. This looks like, even though you have found that the two lines are significantly different during that period of time, the difference between those lines is not of a constant sign, even during that short period. For instance, in figure 5, for the syllable feature, the period of 0 - 200 ms is significantly different between the two populations, correct? But between 0 and 50, normal-hearing are higher, between 50 and 150, hearing-impaired are higher, and between 150 and 200, normal-hearing are higher again, correct? But somehow they still end up significantly different overall between 0 and 200 ms. More explanation of occurrences like these is needed.
Using ridge regression:
• What software package(s) and procedure(s) were specifically done to accomplish this? If this is ridge regression and not just ordinary least squares, then there was at least one non-zero regularization parameter in the process. What was it, how did it figure in the modeling and analysis, etc.?<br /> • It sounds like the regressors are the hidden layer activations, which you reduced from 2,048 to 150 non-acoustic, or linguistic, regressors, per linguistic level, correct? So you have 150 regressors, for each of 5 linguistic levels. These regressors collectively contribute to the deconvolution and EEG prediction from the resulting TRFs, correct? This sounds like a lot of overfitting. How much correlation is there from one of these 150 regressors to the next? Elsewhere, it sounds like you end up with only one regressor for each of the 5 linguistic levels. So these aspects need to be clarified.<br /> • For these regressors, you are comparing the "regression outcomes" for different conditions; "regression outcomes" are the R2 between predicted and actual EEG, which is the coefficient of determination, correct? If this is R2, how is it that you have some negative numbers in some of the plots? R2 should be only positive, between 0 and 1.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
Cells cultured in high glucose tend to repress mitochondrial biogenesis and activity, a prevailing phenotype type called Crabtree effect that observed in different cell types and cancer. Many signaling pathways have been put forward to explain this effect. Vengayil et al proposed a new mechanism involved in Ubp3/Ubp10 and phosphate that controls the glucose repression of mitochondria. The central hypothesis is that ∆ubp3 shift the glycolysis to trehalose synthesis, therefore lead to the increase of Pi availability in the cytosol, then mitochondrial received more Pi and therefore the glucose repression is reduced.
Strengths:
The strength is that the authors used an array of different assays to test their hypothesis. Most assays were well-designed and controlled.
Weaknesses:
The author addressed my major concerns.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary.
The objective of this study was to further our understanding of the brain mechanisms associated with facial expressions of pain. To achieve this, participants' facial expressions and brain activity were recorded while they received noxious heat stimulation. The authors then used a decoding approach to predict facial expressions from functional magnetic resonance imaging (fMRI) data. They found a distinctive brain signature for pain facial expressions (FEPS). This signature had minimal overlap with brain signatures reflecting other components of pain phenomenology, such as signatures reflecting subjective pain intensity or negative effects.
Strength.
The authors used a rigorous approach involving multivariate brain decoding to predict the occurrence and intensity of pain facial expressions during noxious heat stimulation. The analyses are solid and well-conducted. This is an important study of fundamental and clinical relevance.
Weakness.
Despite those major strengths, the main weakness of the study is that the design and analyses do not allow us to know if the FEPS is really specific to pain expressions. Based on the analysis, it is possible to conclude that this brain signature is present when a participant is in a state of pain and displays a facial expression. However, it is possible that it would also be present when a participant experiences (another) negative state and displays (another) facial expression. It will be important, in future work, to investigate the specificity of this brain signature.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript investigates the regulation of chlorophyll biosynthesis in rice embryos, focusing on the role of OsNF-YB7. The rigorous experimental approach, combining genetic, biochemical, and molecular analyses, provides a robust foundation for these findings. The research achieves its objectives, offering new insights into chlorophyll biosynthesis regulation, with the results convincingly supporting the authors' conclusions.
Strengths:
The major strengths include the detailed experimental design and the findings regarding OsNF-YB7's inhibitory role.
Weaknesses:
However, the manuscript's discussion on the practical implications for agriculture and the evolutionary analysis of regulatory mechanisms could be expanded.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Kundu et al. investigated the effects of pre-exposure to a non-pathogenic Leptospira strain in prevention of severe disease following subsequent infection by a pathogenic strain. They utilized a single or double exposure method to the non-pathogen prior to challenge with a pathogenic strain. They found that prior exposure to a non-pathogen prevented many of the disease manifestations of the pathogen. Bacteria, however, were able to disseminate, colonize the kidneys, and be shed in the urine. This is important foundational work to describe a novel method of vaccination against leptospirosis. Numerous studies have attempted to use recombinant proteins to vaccinate against leptospirosis, with limited success. The authors provide a new approach that takes advantage of the homology between a non-pathogen and a pathogen to provide heterologous protection. This will provide a new direction in which we can approach creating vaccines against this re-emerging disease.
Strengths:
The major strength of this paper is that it is one of the first studies utilizing a live non-pathogenic strain of Leptospira to immunize against severe disease associated with leptospirosis. They utilize two independent experiments (a single and double vaccination) to define this strategy. This represents a very interesting and novel approach to vaccine development. This is of clear importance to the field.
The authors use a variety of experiments to show the protection imparted by pre-exposure to the non-pathogen. They look at disease manifestations such as death and weight loss. They define the ability of Leptospira to disseminate and colonize the kidney. They show the effects infection has on kidney architecture and a marker of fibrosis. And they begin to define the immune response in both of these exposure methods. This provides evidence of the numerous advantages this vaccination strategy may have. Thus, this study provides an important foundation for future studies utilizing this method to protect against leptospirosis.
Weaknesses:
A direct comparison between single and double exposure to the non-pathogen is not possible with the data presented. The ages of mice infected were different between the single (8 weeks) and double (10 weeks) exposure methods, thus the phenotypes associated with LIC infection are different at these two ages. The authors state that this is expected, but do not provide a reasoning for this drastic difference in phenotypes. It cannot be determined if double-vaccination would provide an additional benefit, which is of importance to future work developing any vaccine treatment. An experiment directly comparing the two exposure methods while infecting mice at the same age would be of great relevance to and strengthen this work.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The "optorepressilator", an optically controllable genetic oscillator based on the famous E. coli 3-repressor (LacI, TetR, CI) oscillator "repressilator", was developed. An individual repressilator shows a stable oscillation of the protein levels with a relatively long period that extends a few doubling times of E. coli, but when many cells oscillate, their phases tend to desynchronize. The authors introduced an additional optically controllable promoter through a conformal change of CcaS protein and let it control how much additional CI is produced. By tightly controlling the leak from the added promoter, the authors successfully kept the original repressilator oscillation when the added promoter was not activated. In contrast, the oscillation was stopped by expressing the additional CI. Using this system, the authors showed that it is possible to synchronise the phase of the oscillation, especially when the activation happens as a short pulse at the right phase of the repressilator oscillation. The authors further show that, by changing the frequency of the short pulses, the repressilator was entrained to various ratios to the pulse period, and the author could reconstruct the so-called "Arnold tongues", the signature of entrainment of the nonlinear oscillator to externally added periodic perturbation. The behaviour is consistent with the simplified mathematical model that simulates the protein concentration using ordinary differential equations.
Strengths:
Optical control of the oscillation of the protein clock is a powerful and clean tool for studying the synthetic oscillator's response to perturbation in a well-controlled and tunable manner. The article utilizes the plate reader setup for population average measurements and the mother machine setup for single-cell measurements, and they complement nicely to acquire necessary information.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors use a combination of biochemistry and cryo-EM studies to explore a complex between the cap binding complex and an RNA binding protein, ALYREF, that coordinates mRNA processing and export.
Strengths:
The biochemistry and structural biology are supported by mutagenesis that tests the model in vitro. The structure provides new insight into how key events in RNA processing and export are likely to be coordinated.
Weaknesses:
The authors provide biochemical studies to confirm the interactions that they identify; however, they do not perform any studies to test these models in cells or explore the consequences for mRNA export from the nucleus. In fact, several of the amino acids that they identified in ALYREF that are critical for the interaction, as determined by their own biochemical studies are conserved in budding yeast Yra1 (residues E124/E128 are E/Q in budding yeast and residues Y135/V138/P139 are F/S/P), where the impact on poly(A) RNA export from the nucleus could be readily evaluated. The authors mention the potential for future studies in the manuscript, but they do not perform any analysis in this study that would explore the contributions of these new interactions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study provides the detailed molecular mechanism of how OGT, an O-GlcNac transferase, promotes cancer progression. Using loss-of-function OGT models, the authors demonstrated that OGT cleaves HCF-1, an important guardian of genomic stability. The resulting genomic instability in OGT-knockout tumors leads to cytosolic DNA accumulation, the activation of cGAS-mediated type I IFN responses, and increased CD8+ T cell infiltration into the tumors. Moreover, treatment with OGT inhibitor synergized with anti-PDL1 immune-checkpoint blockade.
Strengths:
Novel findings of how OGT promotes tumor progression.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors of this study developed a software application, which aims to identify images as either "friendly" or "unfriendly" for readers with deuteranopia, the most common color-vision deficiency. Using previously published algorithms that recolor images to approximate how they would appear to a deuteranope (someone with deuteranopia), authors first manually assessed a set of images from biology-oriented research articles published in eLife between 2012 and 2022, as well as an additional hold-out set of 2000 articles selected randomly from the PubMed Central Open Access Subset. The researchers identified 636 out of 4964 images as difficult to interpret ("unfriendly") for deuteranopes in the eLife dataset. In the PubMed Central dataset 104 out of 1191 non-grayscale images were identified as unfriendly. The results for the eLife dataset show a decrease in "unfriendly" images over time and a higher probability for articles from cell-oriented research fields to contain "unfriendly" images.
The researchers used the manually classified images from eLife to develop, train, and validate an automated screening tool. They also created a user-friendly web application of the tool, where users can upload images and be informed about the status of each image as "friendly" or "unfriendly" for deuteranopes.
Strengths:
The authors have identified an important accessibility issue in the scientific literature: the use of color combinations that make figures difficult to interpret for people with color-vision deficiency. The metrics proposed and evaluated in the study are a valuable theoretical contribution. The automated screening tool they provide is well-documented, open source, and relatively easy to install and use. It has the potential to provide a useful service to the scientists who want to make their figures more accessible. The data are open and freely accessible, well documented, and a valuable resource for further research. The manuscript is well-written, logically structured, and easy to follow.
Weaknesses:
(1) The authors themselves acknowledge the limitations that arise from the way they defined what constitutes an "unfriendly" image. There is a missed chance here to have engaged deuteranopes as stakeholders earlier in the experimental design. This would have allowed to determine to what extent spatial separation and labelling of problematic color combinations responds to their needs and whether setting the bar at a simulated severity of 80% is inclusive enough. A slightly lowered barrier is still a barrier to accessibility.
(2) The use of training images from a single journal limits the generalizability of the empirical findings as well as of the automated screening tool itself. This is evidenced by a decrease in performance of the tool on the holdout dataset from PubMed Central. Machine-learning algorithms are highly configurable but also notorious for their lack of transparency and for being easily biased by the training data set. A quick and unsystematic test of the web application shows that the classifier works well for electron microscopy images but fails at recognizing the classical diagnostic images for color-vision deficiency (Ishihara test images) as "unfriendly". A future iteration of the tool should be trained on a wider variety of images, ideally enriched with diagnostic images found in scientific publications.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors fabricated a novel cancer vaccine using endogenous virus-like particles with tumor neoantigen. The vaccine ePAC was proven to elicit strong immune stimulation with an increased killing effect against tumor cells in 2 mouse models.
Strengths:
The author achieved high protein loading and transfection efficiency using PEG10 self-assembly while packaging tumor neoantigens inside for cancer immunotherapy. The author also enhanced the targeting effect towards dendritic cells by surface modification using CpG-ODN.
Weaknesses:
There were some minor issues but they have been resolved in the revision process. It would be great if the authors could compare this with commercially available treatments and other vaccines.
Discussion:
Since the ePAC vaccine particle functions as a delivery platform, it can be tailored to different tumors when packed with their specific tumor neoantigens. Thus, the ePAC platform can be potentially employed in a broad range of cancer vaccine therapies. It would be exciting to see this platform being developed for other major cancer types.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript aimed at elucidating the substrate specificity of two M23 endopeptidase Lysostaphin (LSS) and LytM in S. aureus. Endopeptidases are known to cleave the glycine-bridges of staphylococcal cell wall peptidoglycan (PG). To address this question, various glycine-bridge peptides were synthesized as substrates, the catalytic domain of LSS and LytM were recombinantly expressed and purified, and the reactions were analyzed using solution-state NMR. The major finding is that LytM is not only a Gly-Gly endopeptidase, but also cleaves D-Ala-Gly. Technically, the advantage of using real-time NMR was emphasized in the manuscript. The study explores an interesting aspect of cell wall hydrolases in terms of substrate-level regulation. It potentially identified new enzymatic activity of LytM. However, the biological significance and relevance of the conclusions remain clear, as the results are mostly from synthetic substrates.
Strengths:
The study explores an interesting aspect of cell wall hydrolases in terms of substrate-level regulation. It potentially identified new enzymatic activity of LytM.
Comments on the revised version:
The authors have addressed most of my concerns. I agree that the physiological functions of LytM are not in the scope of the current study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript aimed to investigate the emergence of emotional sensitivity and its relationship with gestational age. Using an oddball paradigm and event-related potentials, the authors conducted an experiment in 120 healthy neonates with a gestational age range of 35 to 40 weeks. A significant developmental milestone was identified at 37 weeks gestational age, marking a crucial juncture in neonatal emotional responsiveness.
Strengths:
This study has several strengths, by providing profound insights into the early development of social-emotional functioning and unveiling the role of gestational age in shaping neonatal perceptual abilities. The methodology of this study demonstrates rigor and well-controlled experimental design, particularly involving matched control sounds, which enhances the reliability of the research. Their findings not only contribute to the field of neurodevelopment, but also showcase potential clinical applications, especially in the context of autism screening and early intervention for neurodevelopmental disorders.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
A nice study trying to identify the relationship between E. coli O157 from cattle and humans in Alberta, Canada.
Strengths:
(1) The combined human and animal sampling is a great foundation for this kind of study.
(2) Phylogenetic analyses seem to have been carried out in a high-quality fashion.
Weaknesses:
I think there may be a problem with the selection of the isolates for the primary analysis. This is what I'm thinking:
(1) Transmission analyses are strongly influenced by the sampling frame.
(2) While the authors have randomly selected from their isolate collections, which is fine, the collections themselves are not random.
(3) The animal isolates are likely to represent a broad swathe of diversity, because of the structured sampling of animal reservoirs undertaken (as I understand it).
(4) The human isolates are all from clinical cases. Clinical cases of the disease are likely to be closely related to other clinical cases, because of outbreaks (either detected, or undetected), and the high ascertainment rate for serious infections.
(5) Therefore, taking an equivalent number of animal and clinical isolates, will underestimate the total diversity in the clinical isolates because the sampling of the clinical isolates is less "independent" (in the statistical sense) than sampling from the animal isolates.
(6) This could lead to over-estimating of transmission from cattle to humans.
(7) "We hypothesize that the large proportion of disease associated with local transmission systems is a principal cause of Alberta's high E. coli O157:H7 incidence" - this seems a bit tautological. There is a lot of O157 because there's a lot of transmission. What part of the fact it is local means that it is a principal cause of high incidence? It seems that they've observed a high rate of local transmission, but the reasons for this are not apparent, and hence the cause of Alberta's incidence is not apparent. Would a better conclusion not be that "X% of STEC in Alberta is the result of transmission of local variants"? And then, this poses a question for future epi studies of what the transmission pathway is.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> In this study, Zhao and colleagues investigate inflammasome activation by E. tarda infections. They show that E. tarda induces the activation of the NLRC4 inflammasome as well as the non-canonical pathway in human THP1 macrophages. Further dissecting NLRC4 activation, they find that T3SS translocon components eseB, eseC and eseD are necessary for NLRC4 activation and that delivery of purified eseB is sufficient to trigger NAIP-dependent NLRC4 activation. Sequence analysis reveals that eseB shares homology within the C-terminus with T3SS needle and rod proteins, leading the authors to test if this region is necessary for inflammasome activation. They show that the eseB CT is required and that it mediates interaction with NAIP. Finally, they that homologs of eseB in other bacteria also share the same sequence and that they can activate NLRC4 in a HEK293T cell overexpression system.
Strengths:<br /> This is a very nice study that convincingly shows that eseB and its homologs can be recognized by the human NAIP/NLRC4 inflammasome. The experiments are well designed, controlled and described, and the papers is convincing as a whole.
Weaknesses:<br /> The authors need to discuss their study in the context of previous papers that have shown an important role for E. tarda flagellin in inflammasome activation and test whether flagellin and/or E. tarda T3SSs needle or rod can activate NLRC4.
The authors show that eseB and its homologs can activate NLRC4, but there are also other translocon proteins that are very different such as YopB or PopB. and share little homology with eseB. It would be nice to include a section comparing the different type 3 secretion systems. are there 2 different families of T3SSs, those that feature translocon components that are recognized by NAIP-NLRC4 and those that cannot be recognized?
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www.biorxiv.org www.biorxiv.org
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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.
Weaknesses:
(1) It will be interesting to monitor the levels of another MIM insertase namely, OXA1. This will help to understand whether some of the observed changes in levels of OXPHOS subunits are related to alterations in the amounts of this insertase.
(2) The authors did not provide explanations for several key findings like:<br /> A. Figure 3: How do the authors explain that although TIMM17 and TIMM23 were found to be significantly reduced by Western analysis they were not detected as such by the Mass Spec. method?<br /> B. How do the authors explain the higher levels of some proteins in the TIMM50 mutated cells?<br /> C. Can the authors elaborate on why mutated cells are impaired in their ability to switch their energetic emphasis to glycolysis when needed?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Time periods in which experience regulates early plasticity in sensory circuits are well established, but the mechanisms that control these critical periods are poorly understood. In this manuscript, Leier and Foden and colleagues examine early-life critical periods that regulate the Drosophila antennal lobe, a model sensory circuit for understanding synaptic organization. Using early-life (0-2 days old) exposure to distinct odorants, they show that constant odor exposure markedly reduces the volume, synapse number, and function of the VM7 glomerulus. The authors offer evidence that these changes are mediated by invasion of ensheathing glia into the glomerulus where they phagocytose connections via a mechanism involving the engulfment receptor Draper.
This manuscript is a striking example of a study where the questions are interesting, the authors spent a considerable amount of time to clearly think out the best experiments to ask their questions in the most straightforward way, and expressed the results in a careful, cogent, and well-written fashion. It was a genuine delight to read this paper. I have two experimental suggestions that would really round out existing work to better support the existing conclusions and some instances where additional data or tempered language in describing results would better support their conclusions. Overall, though, this is an incredibly important finding, a careful analysis, and an excellent mechanistic advance in understanding sensory critical period biology.
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ecoevorxiv.org ecoevorxiv.org
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Reviewer #1 (Public Review):
Summary:
This article presents a meta-analysis that challenges established abundance-occupancy relationships (AORs) by utilizing the largest known bird observation database. The analysis yields contentious outcomes, raising the question of whether these findings could potentially refute AORs.
Strengths:
The study employed an extensive aggregation of datasets to date to scrutinize the abundance-occupancy relationships (AORs).
Weaknesses:
While the dataset employed in this research holds promise, a rigorous justification of the core assumptions underpinning the analytical framework is inadequate. The authors should thoroughly address the correlation between checklist data and global range data, ensuring that the foundational assumptions and potential confounding factors are explicitly examined and articulated within the study's context.
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Annotators
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> The authors present experimental and numerical results on the motility Magnetospirillum gryphiswaldense MSR-1, a magnetotactic bacterium living in sedimentary environments. The authors manufactured microfluidic chips containing three-dimensional obstacles of irregular shape, that match the statistical features of the grains observed in the sediment via micro-computer tomography. The bacteria are furthermore subject to an external magnetic field, whose intensity can be varied. The key quantity measured in the experiments is the throughput ratio, defined as the ratio between the number of bacteria that reach the end of the microfluidic channel and the number of bacteria entering it. The main result is that the throughput ratio is non-monotonic and exhibits a maximum at magnetic field strength comparable with Earth's magnetic field. The authors rationalize the throughput suppression at large magnetic fields by quantifying the number of bacteria trapped in corners between grains.
Strengths:<br /> While magnetotactic bacteria's general motility in bulk has been characterized, we know much less about their dynamics in a realistic setting, such as a disordered porous material. The micro-computer tomography of sediments and their artificial reconstruction in a microfluidic channel is a powerful method that establishes the rigorous methodology of this work. This technique can give access to further characterization of microbial motility. The coupling of experiments and computer simulations lends considerable strength to the claims of the authors, because the model parameters (with one exception) are directly measured in the experiments.
Weaknesses:<br /> The main weakness of the manuscript pertains to the discussion of the statistical significance of the experimental throughput ratio. Especially when comparing results at zero and 50 micro Tesla. The simulations seem to predict a stronger effect than seen in the experiments. The authors do not address this discrepancy.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> The paper investigates the interplay between fluid flow and biofilm development using Pseudomonas aeruginosa PAO1 in microfluidic channels. By combining experimental observations with mathematical modeling, the study identifies the significant impact of nutrient limitation and hydrodynamic forces on biofilm growth and detachment. The authors demonstrate that nutrient limitation drives the longitudinal distribution of biomass, while flow-induced detachment influences the maximum clogging and temporal dynamics. The study highlights that pressure buildup plays a critical role in biofilm detachment, leading to cyclic episodes of sloughing and regrowth. A stochastic model is used to describe the detachment process, capturing the apparent randomness of sloughing events. The findings offer insights into biofilm behavior during clogging and fouling, potentially relevant to infections, environmental processes, and engineering applications.
Strengths:<br /> This paper demonstrates a strong integration of experimental work and mathematical modeling, providing a comprehensive understanding of biofilm dynamics in straight microfluidic channel. The simplicity of the microchannel geometry allows for accurate modeling, and the findings have the potential to be applied to more complex geometries. The detailed analysis of nutrient limitation and its impact on biofilm growth offers valuable insights into the conditions that drive biofilm formation. The model effectively describes biofilm development across different stages, capturing both initial growth and cyclic detachment processes. While cyclic pressure buildup has been studied previously, the incorporation of a stochastic model to describe detachment events is a novel and significant contribution, capturing the complexity and randomness of biofilm behavior. Finally, the investigation of pressure buildup and its role in cyclic detachment and regrowth enhances our understanding of the mechanical forces at play, making the findings applicable to a wide range of technological and clinical contexts.
Weaknesses:<br /> The study achieves its primary goal of integrating experiments and modeling to understand the coupling between flow and biofilm growth and detachment in a microfluidic channel, but it should have highlighted the weaknesses of the methods. I list the ones that, in my opinion, are the main ones:
• The study does not consider biofilm porosity, which could significantly affect the flow and forces exerted on the biofilm. Porosity could impact the boundary conditions, such as the no-slip condition, which should be validated experimentally.<br /> • The research suggests EPS development as a stage in biofilm growth but does not probe it using lectin staining. This makes it impossible to accurately assess the role of EPS in biofilm development and detachment processes.<br /> • While the force and flow are three-dimensional, the images are taken in two dimensions. The paper does not clearly explain how the 2D images are extrapolated to make 3D assessments, which could lead to inaccuracies.<br /> • Although the findings are tested using polysaccharide-deficient mutants, the results could have been analyzed in greater detail. A more thorough analysis would help to better understand the role of matrix composition on the stochastic model of detachment.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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ZDB-GENO-060207-1
DOI: 10.1016/j.cub.2023.07.021
Resource: (ZFIN Cat# ZDB-GENO-060207-1,RRID:ZFIN_ZDB-GENO-060207-1)
Curator: @vtello
SciCrunch record: RRID:ZFIN_ZDB-GENO-060207-1
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This manuscript builds upon the authors' previous work on the cross-talk between transcription initiation and post-transcriptional events in yeast gene expression. These prior studies identified an mRNA 'imprinting' phenomenon linked to genes activated by the Rap1 transcription factor (TF), a surprising role for the Sfp1 TF in promoting RNA polymerase II (RNAPII) backtracking, and a role for the non-essential RNAPII subunits Rpb4/7 in the regulation of mRNA decay and translation. Here the authors aimed to extend these observations to provide a more coherent picture of the role of Sfp1 in transcription initiation and subsequent steps in gene expression. They provide evidence for (1) a physical interaction between Sfp1 and Rpb4, (2) Sfp1 binding and stabilization of mRNAs derived from genes whose promoters are bound by both Rap1 and Sfp1 and (3) an effect of Sfp1 on Rpb4 binding or conformation during transcription elongation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Wu et al. introduce a novel approach to reactivate the Muller glia cell cycle in the mouse retina by simultaneously reducing p27Kip1 and increasing cyclin D1 using a single AAV vector. The approach effectively promotes Muller glia proliferation and reprograming without disrupting retinal structure or function. Interestingly, reactivation of the Muller glia cell cycle downregulates IFN pathway, which may contribute to the induced retinal regeneration. The results presented in this manuscript may offer a promising approach for developing Müller glia cell-mediated regenerative therapies for retinal diseases.
Strengths:
The data are convincing and supported by appropriate, validated methodology. These results are both technically and scientifically exciting and are likely to appeal to retinal specialists and neuroscientists in general.
Weaknesses:
There are some data gaps that need to be addressed.
(1) Please label the time points of AAV injection, EdU labeling, and harvest in Figure 1B.
(2) What fraction of Müller cells were transduced by AAV under the experimental conditions?
(3) It seems unusually rapid for MG proliferation to begin as early as the third day after CCA injection. Can the authors provide evidence for cyclin D1 overexpression and p27 Kip1 knockdown three days after CCA injection?
(4) The authors reported that MG proliferation largely ceased two weeks after CCA treatment. While this is an interesting finding, the explanation that it might be due to the dilution of AAV episomal genome copies in the dividing cells seems far-fetched.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript the authors re-examine the developmental origin of cortical oligodendrocyte (OL) lineage cells using a combination of strategies, focussing on the question of whether the LGE generates cortical OL cells. The paper is interesting to myelin biologists, the methods used are appropriate and, in general, the study is well-executed, thorough, and persuasive, but not 100% convincing.
Strengths, weaknesses, and recommendations:
The first evidence presented that the LGE does not generate OLs for the cortex is that there are no OL precursors 'streaming' from the LGE during embryogenesis, unlike the MGE (Figure 1A). This in itself is not strong evidence, as they might be more dispersed. In fact, in the images shown, there is no obvious 'streaming' from the MGE either. Note that in Figure 1 there is no reference to the star that is shown in the figure.
The authors then electroporate a reporter into the LGE at E13.5 and examine the fate of the electroporated cells (Figures 1C-E). They find that electroporated cells became neurons in the striatum and in the cortex but no OLs for the cortex. There are two issues with this: first, there is no quantification, which means there might indeed be a small contribution from the LGE that is not immediately obvious from snapshot images. Second, it is unexpected to find labelled neurons in the cortex at all since the LGE does not normally generate neurons for the cortex! Electroporations are quite crude experiments as targeting is imprecise and variable and not always discernible at later stages. For example, in Figure 1D, one can see tdTOM+ cells near the AEP, as well as the striatum. Hence, IUE cannot on its own be taken as proof that there is no contribution of the LGE to the cortical OL population.
The authors then use an alternative fate-mapping approach, again with E13.5 electroporations (Figure 2). They find only a few GFP+ cells in the cortex at E18 (Figures 2C-D) and P10 (Figure 2E) and these are mainly neurons, not OL lineage cells. Again, there is no quantification.
Figure 3 is more convincing, but the experiments are incomplete. Here the authors generate triple-transgenic mice expressing Cre in the cortex (Emx1-Cre) and the MGE (Nkx2.1-Cre) as well as a strong nuclear reporter (H2B-GFP). They find that at P0 and P10, 97-98% of OL-lineage cells (SOX10+ or PDGFRA+) in the cortex are labelled with GFP (Figure 3). This is a more convincing argument that the LGE/CGE might not contribute significant numbers of OL lineage cells to the cortex, in contrast to the Kessaris et at. (2006) paper, which showed that Gsh2-Cre mice label ~50% of SOX10+ve cells in the motor cortex at P10. The authors of the present paper suggest that the discrepancy between their study and that of Kessaris et al. (2006) is based on the authors' previous observation (Zhang et al 2020) (https://doi.org/10.1016/j.celrep.2020.03.027) that GSH2 is expressed in intermediate precursors of the cortex from E18 onwards. If correct, then Kessaris et al. might have mistakenly attributed Gsh2-Cre+ lineages to the LGE/CGE when they were in fact intrinsic to the cortex. However, the evidence from Zhang et al 2020 that GSH2 is expressed by cortical intermediate precursors seems to rest solely on their location within the developing cortex; a more convincing demonstration would be to show that the GSH2+ putative cortical precursors co-label for EMX1 (by immunohistochemistry or in situ hybridization), or that they co-label with a reporter in Emx1-driven reporter mice. This demonstration should be simple for the authors as they have all the necessary reagents to hand. Without these additional data, the assertion that GSX2+ve cells in the cortex are derived from the cortical VZ relies partly on an act of faith on the part of the reader.
Note that Tripathi et al. (2011, "Dorsally- and ventrally-derived oligodendrocytes have similar electrical properties but myelinate preferred tracts." J. Neurosci. 31, 6809-6819) found that the Gsh-Cre+ OL lineage contributed only ~20% of OLs to the mature cortex, not ~50% as reported by Kessaris et al. (2006). If it is correct that these Gsh2-derived OLs are from the cortical anlagen as the current paper claims, then it would raise the possibility that the ventricular precursors of GSH2+ intermediate progenitors are not uniformly distributed through the cortical VZ but are perhaps localized to some part of it. Then the contribution of Gsh2-derived OLs to the cortical population could depend on precisely where one looks relative to that localized source. It would be a nice addition to the current manuscript if the authors could explore the distribution of their GSH2+ intermediate precursors throughout the developing cortex. In any case, Tripathi et al. (2011) should be cited.
Finally, the authors deleted Olig2 in the MGE and found a dramatic reduction of PDGFRA+ and SOX10+ cells in the cortex at E14 and E16 (Figure 4A-F). This further supports their conclusion that, at least at E16, there is no significant contribution of OLs from ventral sources other than the MGE/AEP. This does not exclude the possibility that the LGE/CGE generates OLs for the cortex at later stages. Hence, on its own, this is not completely convincing evidence that the LGE generates no OL lineage cells for the cortex.
Comments on the latest version:
The revised manuscript has addressed the issues we raised previously. The addition of the new Figure 3 supplement 1A-C demonstrating that Gsx2+ve cells in the cortex are generated from Emx1-Cre precursors is convincing, although there is nothing to prove that the GFP+, Gsh2+ double-labelled nuclei are oligodendrocyte lineage and not, for example, astrocytes. It would be helpful to include a Gsh2, Olig2 (or Gsh2, Sox10) double-label image to prove this point. Also, to make the figure more clear, the authors should also show a small area at high magnification, splitting the green and red channels so that the reader can see more clearly that all the red cells are also green.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript reports the effects of a heterozygous mutation in the KCNT1 potassium channels on the properties of ion currents and firing behavior of excitatory and inhibitory neurons in the cortex of mice expressing KCNT1-Y777H. In humans, this mutation as well as multiple other heterozygotic mutations produce very severe early-onset seizures and produce a major disruption of all intellectual function. In contrast, in mice, this heterozygous mutation appears to have no behavioral phenotype or any increased propensity to seizures. A relevant phenotype is, however, evident in mice with the homozygous mutation, and the authors have previously published the results of similar experiments with the homozygotes. As perhaps expected, the neuronal effects of the heterozygous mutation presented in this manuscript are generally similar but markedly smaller than the previously published findings on homozygotes. There are, however, some interesting differences, particularly on PV+ interneurons, which appear to be more excitable than wild type in the heterozygotes but more excitable in the heterozygotes. This raises the interesting question, which has been explicitly discussed by the authors in the revised manuscript, as to whether the reported changes represent homeostatic events that suppress the seizure phenotype in the mouse heterozygotes or simply changes in excitability that do not reach the threshold for behavioral outcomes.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors show for the first time that deleting GLS from rod photoreceptors results in the rapid death of these cells. The death of photoreceptor cells could result from loss of synaptic activity because of a decrease in glutamate, as has been shown in neurons, changes in redox balance, or nutrient deprivation.
Strengths:
The strength of this manuscript is that the author shows a similar phenotype in the mice when Gls was knocked out early in rod development or the adult rod. They showed that rapid cell death is through apoptosis, and there is an increase in the expression of genes responsive to oxidative stress.
Weaknesses:
In this manuscript, the authors show a "metabolic dependency of photoreceptors on glutamine catabolism in vivo". However, there is a potential bias in their thinking that glutamine metabolism in rods is similar to cancer cells where it feeds into the TCA cycle. They should consider that as in neurons, GLS1 activity provides glutamate for synaptic transmission. The modest rescue shown by providing α-ketoglutarate in the drinking water suggests that glutamine isn't a key metabolic substrate for rods when glucose is plentiful. The ERG studies performed on the iCre-Glsflox/flox mice showed a large decrease in the scotopic b wave at saturating flashes which could indicate a decrease in glutamate at the rod synapse as stated by the authors. While EM micrographs of wt and iCre-Glsflox/flox mice were shown for the outer retina at p14, the synapse of the rods needs to be examined by EM.
The authors note that the outer segments are shorter but they do not address whether there is a decrease in the number of cones.
Rod-specific Gls ko mice with an inducible promoter were generated by crossing the Pde6g-CreERT2 and homozygous for either the WT or floxed Gls allele (IND-cKO). In Figure 3 the authors document that by western blots and antibody labeling the GLS1 expression is lost in the IND-cKO 10 days post tamoxifen. OCT images show a decrease in the thickness of the outer nuclear layer between 17 and 38 days post-TAM. Ergs should be performed on the animals at 10 and 30 days post TAM, before and after major structural changes in rod photoreceptor cells, to determine if changes in light-stimulated responses are observed. These studies could help to parse out the cause of photoreceptor cell death.
The studies in Figure 4 were all performed on iCre-Glsflox/flox and control mice at p14, why weren't the IND-cKO mice used for these studies since the findings would not be confounded by development?
In all rescue studies, the endpoint was an ONL thickness, which only addressed rod cell death. The authors should also determine whether there are small improvements in the ERG, which would distinguish the role of GLS in preventing oxidative stress.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The research by Lin Chao, Chun Kuen Chen, Chao Shi, and Camilla U. Rang addresses the asymmetric distribution of ribosomes in single E. coli cells during aging by time-lapse microscopy, as well as its correlation to protein misfolding. The presented research is an important contribution to the field of protein biosynthesis pathways and their link to aging, especially in regard to the thorough analysis of variation in cells elongation rate in old and new daughter cells derived from old and new mother cells.
Comments on current version:
I thank the authors for their thoughtful responses. Yet the centrality of protein aggregate distribution analysis to this manuscript requires further evidence to support the link to ribosome asymmetrical distribution and aging.
The authors suggest this is beyond the scope of this study. This then requires a major revising of the study, as in its current form, it is one of its main claims.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study presents careful biochemical experiments to understand the relationship between LRRK2 GTP hydrolysis parameters and LRRK2 kinase activity. The authors report that incubation of LRRK2 with ATP increases the KM for GTP and decreases the kcat. From this they suppose an autophosphorylation process is responsible for enzyme inhibition. LRRK2 T1343A showed no change, consistent with it needing to be phosphorylated to explain the changes in G-domain properties. The authors propose that phosphorylation of T1343 inhibits kinase activity and influences monomer-dimer transitions.
Strengths:
The strengths of the work are the very careful biochemical analyses and interesting results for wild type LRRK2.
Weaknesses:
The conclusions related to the involvement of a monomer-dimer transition are to this reviewer, premature and an independent method needs to be utilized to bolster this aspect of the story.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Rohde et al. discuss how single cells isolated from the presomitic mesoderm of the zebrafish embryo follow a cell-autonomous differentiation "programme", which is dependent on the initial anteroposterior position in the embryo.
Strengths:
This work and, in particular, the comparison to cellular behaviour in vivo presents a detailed description of the oscillatory system that brings the developmental biology forward in their understanding of somitogenesis.<br /> The main novelty lies in the direct comparison of these isolated single cells to single cells tracked within the developing embryo. This allows them to show that isolated cells follow a similar path of differentiation without direct contact to neighbours or the presence of external morphogen gradients. Based on this, the authors propose an internal timer that starts ticking as cells traverse the presomitic mesoderm, while external signals modify this behaviour.
There are a few direct questions that follow up from this study, for instance, intercellular synchronization influences the variability of the timer. However, I agree with the authors that such experiments are out of the scope of this study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper the researchers aimed to address whether bees causally understand string-pulling through a series of experiments. I first briefly summarize what they did:
- In experiment 1, the researchers trained bees without string and then presented them with flowers in the test phase that either had connected or disconnected strings, to determine what their preference was without any training. Bees did not show any preference.
- In experiment 2, bees were trained to have experience with string and then tested on their choice between connected vs. disconnected string.
- Experiment 3 was similar except that instead of having one option which was an attached string broken in the middle, the string was completely disconnected from the flower.
- In experiment 4, bees were trained on green strings and tested on white strings to determine if they generalize across color.
- In experiment 5, bees were trained on blue strings and tested on white strings.
- In experiment 6, bees were trained where black tape covered the area between the string and the flower (i.e. so they would not be able to see/ learn whether it was connected or disconnected).
- In experiments 2-6, bees chose the connected string in the test phase.
- In experiment 7, bees were trained as in expt 3 and then tested where string was either disconnected or coiled i.e. still being 'functional' but appearing different.
- In experiment 8, bees were trained as before and then tested on string that was in a different coiled orientation, either connected or disconnected.
- In experiments 7 and 8 the bees showed no preference.
Strengths:
I appreciate the amount of work that has gone into these experiments and think they are a nice, thorough set of experiments. I enjoyed reading the paper and felt that it was overall well-written and clear. I think experiment 1 shows that bees do not have an untrained understanding of the function of the string in this context. The rest of the experiments indicate that with training, bees have a preference for unbroken over broken string and likely use visual cues learned during training to make this choice. They also show that as in other contexts, bees readily generalize across different colors.
The 'weaknesses' that I previously listed were dealt with by the authors in the revised version of the manuscript. I think the only point that we disagreed on was relating to the ecological relevance of the task to the bees.
Here is my previous comment:
I think the paper would be made stronger by considering the natural context in which the bee performs this behavior. Bees manipulate flowers in all kinds of contexts, and scrabble with their legs to achieve nectar rewards. Rather than thinking that it is pulling a string, my guess would be that the bee learns that a particular motor pattern within their usual foraging repertoire (scrabbling with legs), leads to a reward. I don't think this makes the behavior any less interesting - in fact, I think considering the behavior through an ecological lens can help make better sense of it.
The authors disagreed, writing the following:
"Here we respectfully disagree. The solving of Rubik s cube by humans could be said to be version of finger movements naturally required to open nuts or remove ticks from fur, but this is somewhat beside the point: it s not the motor<br /> sequences that are of interest, but the cognition involved. A general approach in work on animal intelligence and cognition is to deliberately choose paradigms that are outside the animals daily routines this is what we have done here, in asking whether there is means end comprehension in bee problem solving. Like comparable studies on this question in other animals, the experiments are designed to probe this question, not one of ecological validity."
I think the difference would be that humans know that they are doing a rubik's cube whereas I do not think that the bee knows that it is pulling string- I think the bee thinks that it is foraging on a flower. Therefore, I stand by my statement that I think it's worth considering what the bee is experiencing in this task and how it relates to what it would be doing while foraging. I think that as animal cognition researchers we can design tasks that are distinct from what the animal would naturally encounter to ask specific questions about what they are thinking- but that we can never remove the ecological context since the animal will always be viewing the task through that lens. However, I think this may be a philosophical difference in opinion and I am happy with the manuscript as it stands.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
This manuscript by Amen, Yoo and Fabra-Garcia et al describes a human monoclonal antibody B1E11K, targeting EENV repeats which are present in parasite antigens such as Pfs230, RESAs and Pf11.1. The authors isolated B1E11K using an initial target agnostic approach for antibodies that would bind gamete/gametocyte lysate which they made 14 mAbs. Following a suite of highly appropriate characterization methods from Western blotting of recombinant proteins to native parasite material, use of knockout lines to validate specificity, ITC, peptide mapping, SEC-MALS, negative stain EM and crystallography, the authors have built a compelling case that B1E11K does indeed bind EENV repeats. In addition, using X-ray crystallography they show that two B1E11K Fabs bind to a 16 aa RESA repeat in a head-to-head conformation using homotypic interactions and provide a separate example from CSP, of affinity-matured homotypic interactions.
The authors have addressed most of our previous comments in their revised manuscript.
One of the main conclusions in the paper is the binding of B1E11K to RESAs which are blood stage antigens that are exported to the infected parasite surface. In the future, it would be interesting to understand if B1E11K mAb binds to the red cell surface of infected blood stage parasites to understand its cellular localization in those stages.
Materials and Methods:<br /> PBMC sampling: While the authors have provided clarification that they obtained informed consent from the PBMC donor, they have not added the ethics approval codes in this section.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript introduced a new behavioral apparatus to regulate the animal's behavioral state naturally. It is a thermal maze where different sectors of the maze can be set to different temperatures; once the rest area of the animal is cooled down, it will start searching for a warmer alternative region to settle down again. They recorded with silicon probes from the hippocampus in the maze and found that the incidence of SWRs was higher at the rest areas and place cells representing a rest area were preferentially active during rest-SWRs as well but not during non-REM sleep.
Strengths:
The maze can have many future applications, e.g., see how the duration of waking immobility can influence learning, future memory recall, or sleep reactivation. It represents an out-of-the-box thinking to study and control less-studies aspects of the animals' behavior.
Weaknesses:
The impact is only within behavioral research and hippocampal electrophysiology.
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www.biorxiv.org www.biorxiv.org
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Joint Public Review
The present study explored the principles that allow cells to maintain complex subcellular proteinaceous structures despite the limited lifetimes of the individual protein components. This is particularly critical in the case of neurons, where the size and protein composition of synapses define synaptic strength and encode memory.
PSD95 is an abundant synapse protein that acts as a scaffold in the recruitment of transmitter receptors and other signaling proteins and is required for memory formation. The authors used super-resolution microscopy to study PSD95 super-complexes isolated from the brains of mice expressing tagged PSD variants (Halo-Tag, mEos, GFP). Their results show compellingly that a large fraction (~25%) of super-complexes contains two PSD95 copies about 13 nm apart, that there is substantial turnover of PSD95 proteins in super-complexes over a period of seven days, and that ~5-20% of the super-complexes contain new and old PSD95 molecules. This percentage is higher in synaptic fractions as compared to total brain lysates, and highest in isocortex samples (~20%). These important findings support the hypothesis put forward by Crick that sequential subunit replacement gives synaptic super-complexes long lifetimes and thus aids in memory maintenance. Overall, this is a very interesting study that provides key insights into how synaptic protein complexes are formed and maintained. On the other hand, the actual role of these PSD95 super-complexes in long-term memory storage remains unknown. Specifically, a direct correlation between PSD95 stability and memory formation remains hypothetical - but the present findings indicate important new directions for studying the mechanisms that control postsynaptic protein organisation and the maintenance of postsynaptic proteinaceous substructures.
Strengths
(1) The study employed an appropriate and validated methodology.<br /> (2) Large numbers of PSD95 super-complexes from three different mouse models were imaged and analyzed, providing adequately powered sample sizes.<br /> (3) State-of-the-art super-resolution imaging techniques (PALM and MINFLUX) were used, providing a robust, high-quality, cross-validated analysis of PSD95 protein complexes that is useful for the community.<br /> (4) The result that PSD95 proteins in dimeric complexes are on average 12.7 nm apart is useful and has implications for studies on the nanoscale organization of PSD95 at synapses.<br /> (5) The finding that postsynaptic protein complexes can continue to exist while individual components are being renewed is important for our understanding of synapse maintenance and stability.<br /> (6) The data on the turnover rate of PSD95 in super-complexes from different brain regions provide a first indication of potentially meaningful differences in the lifetime of super-complexes between brain regions.
Weaknesses
(1) The manuscript emphasizes the hypothesis that stable super-complexes, maintained through sequential replacement of subunits, might underlie the long-term storage of memory. While an interesting idea, this notion requires considerably more research. The presented experimental data are indeed consistent with this notion, but there is no evidence that these complexes are causally related to memory storage.<br /> (2) Much of the presented work is performed on biochemically isolated protein complexes. The biochemical isolation procedures rely on physical disruption and detergents that are known to alter the composition and structure of complexes in certain cases. Thus, it remains unclear how the protein complexes described in this study relate to PSD95 complexes in intact synapses.<br /> (3) Because not all GFP molecules mature and fold correctly in vitro and the PSD95-mEos mice used were heterozygous, the interpretation of the corresponding quantifications is not straightforward.<br /> (4) It was not tested whether different numbers of PSD95 molecules per super-complex might contribute to different retention times of PSD95, e.g. in synaptic vs. total-forebrain super-complexes.<br /> (5) The conclusion that the population of 'mixed' synapses is higher in the isocortex than in other brain regions is not supported by statistical analysis.<br /> (6) The validity of conclusions regarding PSD95 degradation based on relative changes in the occurrence of SiR-Halo-positive puncta is limited.
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www.biorxiv.org www.biorxiv.org
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Public Review (Joint Version of all Reviewers)
Cav1.4 calcium channels control voltage-dependent calcium influx at photoreceptor synapses, and congenital loss of Cav1.4 function causes stationary night blindness CSNB2. Based on a broad portfolio of methodological approaches - genetic mouse models, immunolabeling and microscopic imaging, serial block-face-SEM, ERGs, and electrophysiology - the authors show that cone photoreceptor synapse development is strongly perturbed in the absence of Cav1.4 protein, and that expression of a nonconducting Cav1.4 channel mitigates these perturbations. Further data indicate that Cav3 channels are present, which, according to the authors, may compensate for the loss of Cav1.4 calcium currents and thus maintain cone synaptic transmission. These data, which are in agreement with a similar study by the same authors on rod photoreceptor synapses, help to explain what functional defects exactly cause CSNB2 and why it is accompanied by only mild visual impairment.
The strengths of the present study are its conceptual and experimental soundness, the broad spectrum of cutting-edge methodological approaches pursued, and the convincing differential analysis of mutant phenotypes. Weaknesses mainly concern the fact that the mechanism by which Cav3 channels might partially compensate for the loss of Cav1.4 calcium currents remains unclear.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This paper applies methods for segmentation, annotation, and visualization of acoustic analysis to zebra finch song. The paper shows that these methods can be used to predict the stage of song development and to quantify acoustic similarity. The methods are solid and are likely to provide a useful tool for scientists aiming to label large datasets of zebra finch vocalizations. The paper has two main parts: 1) establishing a pipeline/ package for analyzing zebra finch birdsong and 2) a method for measuring song imitation.
Strengths:
It is useful to see existing methods for syllable segmentation compared to new datasets.
It is useful, but not surprising, that these methods can be used to predict developmental stage, which is strongly associated with syllable temporal structure.
It is useful to confirm that these methods can identify abnormalities in deafened and isolated songs.
Weaknesses:
For the first part, the implementation seems to be a wrapper on existing techniques. For instance, the first section talks about syllable segmentation; they made a comparison between whisperseg (Gu et al, 2024), tweetynet (Cohen et al, 2022), and amplitude thresholding. They found that whisperseg performed the best, and they included it in the pipeline. They then used whisperseg to analyze syllable duration distributions and rhythm of birds of different ages and confirmed past findings on this developmental process (e.g. Aronov et al, 2011). Next, based on the segmentation, they assign labels by performing UMAP and HDBScan on the spectrogram (nothing new; that's what people have been doing). Then, based on the labels, they claimed they developed a 'new' visualization - syntax raster ( line 180 ). That was done by Sainburg et. al. 2020 in Figure 12E and also in Cohen et al, 2020 - so the claim to have developed 'a new song syntax visualization' is confusing. The rest of the paper is about analyzing the finch data based on AVN features (which are essentially acoustic features already in the classic literature).
The second part may be something new, but there are opportunities to improve the benchmarking. It is about the pupil-tutor imitation analysis. They introduce a convolutional neural network that takes triplets as an input (each tripled is essentially 3 images stacked together such that you have (anchor, positive, negative), Anchor is a reference spectrogram from, say finch A; positive means a different spectrogram with the same label as anchor from finch A, and negative means a spectrogram not related to A or different syllable label from A. The network is then trained to produce a low-dimensional embedding by ensuring the embedding distance between anchor and positive is less than anchor and negative by a certain margin. Based on the embedding, they then made use of earth mover distance to quantify the similarity in the syllable distribution among finches. They then compared their approach performance with that of sound analysis pro (SAP) and a variant of SAP. A more natural comparison, which they didn't include, is with the VAE approach by Goffinet et al. In this paper (https://doi.org/10.7554/eLife.67855, Fig 7), they also attempted to perform an analysis on the tutor pupil song.
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www.forbes.com www.forbes.com
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Annotation 1
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This paper attempts to measure the complex changes of consciousness in the human brain as a whole. Inspired by the perturbational complexity index (PCI) from classic research, authors introduce simulation PCI (𝑠𝑃𝐶𝐼) of a time series of brain activity as a measure of consciousness. They first use large-scale brain network modeling to explore its relationship with the network coupling and input noise. Then the authors verify the measure with empirical data collected in previous research.
Strengths:
The conceptual idea of the work is novel. The authors measure the complexity of brain activity from the perspective of dynamical systems. They provide a comparison of the proposed measure with four other indexes. The text of this paper is very concise, supported by experimental data and theoretical model analysis.
Weaknesses:
(1) Consciousness is a network phenomenon. The measure defined by the authors is to consider the maximal sPCI across the nodes stimulated. This measure is based on the time series of one node. The measure may be less effective in quantifying the ill relationship between nodes. This may contribute to the less predictive power of anesthesia (Figure 4b).
(2) One of the focuses of the work is the use of a dynamic model of brain networks. The explanation of the model needs to be in more detail.
(3) The equations should be checked. For example, there should be no max on the left side of the first equation on page 13.
(4) The quality of the figures should be improved.
(5) Figure 4 should be discussed and analyzed more in the text.
(6) The usage of the terms PCI and sPCI should be distinguished.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary
This interesting study, which has greatly improved in the current revised version, explores the mechanism behind an increased susceptibility of daf-18/PTEN mutant nematodes to paralyzing drugs that exacerbate cholinergic transmission. The authors use state-of-the-art genetics and neurogenetics coupled with locomotor behavior monitoring and neuroanatomical observations using gene expression reporters to show that the susceptibility occurs due to low levels of DAF-18/PTEN in developing inhibitory GABAergic neurons early during larval development (specifically, during the larval L1 stage). DAF-18/PTEN is convincingly shown to act cell-autonomously in these cells upstream of the PI3K-PDK-1-AKT-DAF-16/FOXO pathway, consistent with its well-known role as an antagonist of this conserved signaling pathway. The authors exclude a role for the TOR pathway in this process and present evidence implicating selectivity towards-developing GABAergic neurons of the ventral nerve cord in comparison to excitatory cholinergic neurons. Finally, the authors show that a diet supplemented with a ketogenic body, β-hydroxybutyrate, which also counteracts the PI3K-PDK-1-AKT pathway, promoting DAF-16/FOXO activity, partially rescues the proper development (morphology and function) of GABAergic neurons in daf-18/PTEN mutants, but only if the diet is provided early during larval development. This strongly suggests that the critical function of DAF-18/PTEN in developing inhibitory GABAergic neurons is to prevent excessive PI3K-PDK-1-AKT activity during this critical and particularly sensitive period of their development in juvenile L1 stage worms. Whether or not the sensitivity of GABAergic neurons to DAF-18/PTEN function is a defining and widespread characteristic of this class of neurons in C. elegans and other animals, or rather a particularity of the early developmental stage of the GABAergic neurons investigated remains to be determined.
Strengths:
The study reports interesting and important findings, advancing the knowledge of how daf-18/PTEN and the PI3K-PDK-1-AKT pathway can influence neurodevelopment, and providing a valuable paradigm to study the selectivity of gene activities towards certain neurons. It also defines a solid paradigm to study the potential of dietary interventions (such as ketogenic diets) or other drug treatments to counteract (prevent or revert?) neurodevelopment defects and stimulate DAF-16/FOXO activity.
Weaknesses:
The fact that other non-GABAergic C. elegans neurons (i.e., AIY and HSN neurons) are also sensitive to DAF-18/PTEN activity during development suggests that the particular sensitivity observed in the GABAergic ventral nerve cord neurons in this study could be unrelated to their neurotransmitter class (GABAergic) per se, but rather to some other neuronal property (a critical period of plasticity or activity-based wiring?) that these neurons share with the AIY and HSN neurons, and not with the other surveyed ventral nerve cord neurons (the excitatory cholinergic neurons). The relevance of this possibility within the framework of understanding the role of DAF-18/PTEN in E/I imbalance across clades is not fully clear at this stage.
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www.biorxiv.org www.biorxiv.org
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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:
Using chromaffin cells as a powerful model system for studying secretion, the authors study the regulatory role of complexin in secretion. Complexin is still enigmatic in its regulatory role, as it both provides inhibitory and facilitatory functions in release. The authors perform an extensive structure-function analysis of both the C- and N-terminal regions of complexin. There are several interesting findings that significantly advances our understanding of cpx/SNARe interactions in regulating release. C-terminal amphipathic helix interferes with SNARE complex assembly and thus clamps fusion. There are acidic residues in the C-term that may be seen as putative interaction partners for Synaptotagmin. The N-terminus of Complexin promoting role may be associated with an interaction with Syt1. In particular the putative interaction with Syt1 is of high interest and supported by quite strong functional and biochemical evidence. The experimental approaches are state of the art, and the results are of the highest quality and convincing throughout. They are adequate and intelligently discussed in the rich context of the standing literature. Whilst there are some concerns about whether the facilitatory actions of complexion have to be tightly linked to Syt1 interactions, the proposed model will significantly advance the field by providing new directions in future research.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Glaser et al present ExA-SPIM, a light-sheet microscope platform with large volumetric coverage (Field of view 85mm^2, working distance 35mm ), designed to image expanded mouse brains in their entirety. The authors also present an expansion method optimized for whole mouse brains, and an acquisition software suite. The microscope is employed in imaging an expanded mouse brain, the macaque motor cortex and human brain slices of white matter.<br /> This is impressive work, and represents a leap over existing light-sheet microscopes. As an example, it offers a ~ fivefold higher resolution than mesoSPIM (https://mesospim.org/), a popular platform for imaging large cleared samples. Thus while this work is rooted in optical engineering, it manifests a huge step forward and has the potential to become an important tool in the neurosciences.
Strengths:
-ExA-SPIM features an exceptional combination of field of view, working distance, resolution and throughput.
-An expanded mouse brain can be acquired with only 15 tiles, lowering the burden on computational stitching. That the brain does not need to be mechanically sectioned is also seen as an important capability.
-The image data is compelling, and tracing of neurons has been performed. This demonstrates the potential of the microscope platform.
Weaknesses:
-There is a general question about the scaling laws of lenses, and expansion microscopy, which in my opinion remained unanswered: In the context of whole brain imaging, a larger expansion factor requires a microscope system with larger volumetric coverage, which in turn will have lower resolution (Figure 1B). So what is optimal? Could one alternatively image a cleared (non-expanded) brain with a high resolution ASLM system (Chakraborty, Tonmoy, Nature Methods 2019, potentially upgraded with custom objectives) and get similar effective resolution as the authors get with expansion? This is not meant to diminish the achievement, but it was unclear if the gains in resolution from the expansion factor are traded off by the scaling laws of current optical systems.
-It was unclear if 300 nm lateral and 800 nm axial resolution is enough for many questions in neuroscience. Segmenting spines, distinguishing pre- and postsynaptic densities, or tracing densely labeled neurons might be challenging. A discussion about the necessary resolution levels in neuroscience would be appreciated.
-Would it be possible to characterize the aberrations that might be still present after whole brain expansion? One approach could be to image small fluorescent nanospheres behind the expanded brain, and recover the pupil function via phase retrieval. But even full width half maximum (FWHM) measurements of the nanospheres' images would give some idea of the magnitude of the aberrations.
Review of the revised manuscript:
The authors have carefully addressed my concerns and suggestions.
I appreciate the extended discussion on tissue clearing compared to expansion. I would recommend substantiating some of the statements though with references, or in other instances expanding a little further. I would encourage the authors to consider the points below. But there is also another path to actually reduce that specific discussion, if the conclusion is that it opened more questions than answers.
Specifically, here are some points in the paragraph that discusses tissue clearing and expansion that could be improved:<br /> -The statement "Spherical aberration increases with NA" reads nonspecific to me. I think a more precise formulation would be "The effect of spherical aberration (e.g. loss of Strehl ratio) increases with NA. The stated third power law would also benefit from a reference.<br /> -The statement "the index of refraction gradients in tissue decreases with the third power of the expansion factor..." reads a bit odd. "Gradients in refractive index" would be more consistent with the usage of r.i. throughout the manuscript.<br /> For the third power law, it might be important to know what drives the remaining refractive index variation in expansion microscopy. If it is the labels and their linkers, then indeed, they get increasingly diluted as their amount remains constant. However, if the aberrations are caused by the polymer gel, I would assume you would need more monomer material for higher expansion factors? Thus, I was not fully sure about the scaling law in this case. If there is a reference where this was explored in detail, that would resolve this issue.
-The statement that aberrations scale with gradients in refractive index also needs either a reference, or an explanation for the reader. I think figure S4 was supposed to illustrate this, but was not referenced in the discussion (and could be clarified, see comment below).
To me, the discussion focused strongly on tissue clearing vs expansion. What was left out in the discussion was if larger expansion factors would be favorable (i.e. whole brain imaging with 10-20X expansion instead of 4-5X). Some arguments implicitly seemed to stipulate that a larger expansion factor would optically be favorable. But Figure S7 highlights another tradeoff with the decay in sensitivity and Figure 1b provides the technological constraints on lens design. So as a reader, I was not fully sure if the next frontier should be 10-20X expansion brain imaging, or if 4-5X is currently a sweet spot.
Further comments:
Please explain the variables in Figure S4, such as F, WD and d. It was unclear to me what the RI profile should mean in the bottom row. Naively, the figure of merit would be the optical path length that is integrated along the different rays, as this leads to a variation in the wavefront.
Figure S5: I would caution to say the SNR was quantified, but rather say it was estimated (in the shot noise limit). Was the background subtracted for the SNR measurements?<br /> Squaring the SNR estimates, it looks like the photon counts went down ~10-fold from z=2mm to z=25mm. That is a larger reduction in signal than I had expected. If it was based solely on aberrations, a 10-fold drop in Strehl ratio seems significant (potentially smaller if we assume the light-sheet also underwent aberrations). Are there other factors that could explain the signal reduction (maybe from the labeling side)?<br /> Further on Figure S5: Fourier transforms (power spectrum) and single line profiles are in my opinion not the best way to quantify resolution. Could the authors perform image decorrelation analysis on the region of interest (Descloux, A., Kristin Stefanie Grußmayer, and Aleksandra Radenovic. "Parameter-free image resolution estimation based on decorrelation analysis." Nature methods 2019) or Fourier ring correlation? This would give in some sense an average resolving power in that depth, and would remove the bias from picking a line profile.
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Reviewer #1 (Public Review):
Abreo et al., performed a detailed multidisciplinary analysis of a pathogenic variant of the KCNQ2 ion channel subunit identified in a child with neonatal-onset epilepsy and neurodevelopmental disorders. These analyses revealed multiple molecular and cellular mechanisms associated with this variant, and providing important insights into what distinguishes distinct pathogenic variants of KCNQ2 associated with self-limited familial neonatal epilepsy versus those leading to developmental and epileptic encephalopathy, and how they may mechanistically differ, to result in different extents of developmental impairment. The authors first provide a detailed clinical description of the patient heterozygous for a novel pathogenic variant encoding KCNQ2 G256W. They then model the structure of the G256W variant based on recent cryo-EM structures of KCNQ2 and other ion channel subunits and find that while the affected position is quite distinct from the channel pore, it participates in a novel, evolutionarily conserved set of amino acids that form a network of hydrogen bonds that stabilize the structure of the pore domain. They then undertake a series of rigorous and quantitative laboratory experiments in which the KCNQ2 G256W variant is coexpressed exogenously with WT KCNQ2 and KCNQ3 subunits in heterologous cells, and endogenously in novel gene edited mice generated for this study. This includes detailed electrophysiological analyses in the transfected heterologous cells revealing the dominant-negative phenotype of KCNQ2 G256W. They find altered firing properties in hippocampal CA1 neurons in brain slices from the heterozygous KCNQ2 G256W mice. They next show that the expression and localization of KCNQ channels is altered in brain neurons from heterozygous KCNQ2 G256W mice, suggesting that this variant impacts KCNQ2 trafficking and stability. Together, these laboratory studies reveal that the molecular and cellular mechanisms shaping KCNQ channel expression, localization and function are impacted at multiple levels by the variant encoding KCNQ2 G256W, likely contributing to the clinical features of the child heterozygous for this variant relative to patients harboring distinct KCNQ2 pathogenic variants.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The hypothesis is based on the idea that inversions capture genetic variants that have antagonistic effects on male sexual success (via some display traits) and survival of females (or both sexes) until reproduction. Furthermore, a sufficiently skewed distribution of male sexual success will tend to generate synergistic epistasis for male fitness even if the individual loci contribute to sexually selected traits in an additive way. This should favor inversions that keep these male-beneficial alleles at different loci together at a cis-LD. A series of simulations are presented and show that the scenario works at least under some conditions. While a polymorphism at a single locus with large antagonistic effects can be maintained for a certain range of parameters, a second such variant with somewhat smaller effects tends to be lost unless closely linked. It becomes much more likely for genomically distant variants that add to the antagonism to spread if they get trapped in an inversion; the model predicts this should drive accumulation of sexually antagonistic variants on the inversion versus standard haplotype, leading to the evolution of haplotypes with very strong cumulative antagonistic pleiotropic effects. This idea has some analogies with one of predominant hypotheses for the evolution of sex chromosomes, and the authors discuss these similarities. The model is quite specific, but the basic idea is intuitive and thus should be robust to the details of the model assumption. It makes perfect sense in the context of the geographic pattern of inversion frequencies.
To provide empirical support for this idea, the authors study the dynamics of inversions in population cages over one generation, tracking their frequencies through amplicon sequencing at three time points: (young adults), embryos and very old adult offspring of either sex (>2 months from adult emergence). Out of four inversions included in the experiment, two show patterns consistent with antagonistic effects on male sexual success (competitive paternity) and the survival of offspring, especially females, until an old age, which the authors interpret as consistent with their theory.
There are several reasons why the support from these data for the proposed theory is not waterproof.
(1) As I have already pointed out in my previous review, survival until 2 months (in fact, it is 10 weeks and so 2.3 months) of age is of little direct relevance to fitness, whether under natural conditions or under typical lab conditions.
The authors argue this objection away with two arguments<br /> First, citing Pool (2015) they claim that the average generation time (i.e. the average age at which flies reproduce) in nature is 24 days. That paper made an estimate of 14.7 generations per year under the North Carolina climate. As also stated in Pool (2015), the conditions in that locality for Drosophila reproduction and development are not suitable during three months of the year. This yields an average generation length of about 19.5 days during the 9 months during which the flies can reproduce. On the highly nutritional food used in the lab and at the optimal temperature of 25 C, Drosophila need about 11-12 days to develop from egg to adult. Even assuming these perfect conditions, the average age (counted from adult eclosion) would be about 8 days. In practice, larval development in nature is likely longer for nutritional and temperature reasons, and thus the genomic data analyzed by Pool imply that the average adult age of reproducing flies in nature would be about 5 days, and not 24 days, and even less 10 weeks. This corresponds neatly to the 2-6 days median life expectancy of Drosophila adults in the field based on capture-recapture (e.g., Rosewell and Shorrocks 1987).<br /> Second, the authors also claim that survival over a period of 2 month is highly relevant because flies have to survive long periods where reproduction is not possible. However, to survive the winter flies enter a reproductive diapause, which involves profound physiological changes that indeed allow them to survive for months, remaining mostly inactive, stress resistant and hidden from predators. Flies in the authors' experiment were not diapausing, given that they were given plentiful food and kept warm. It is still possible that survival to the ripe old age of 10 weeks under these conditions still correlates well with surviving diapause under harsh conditions, but if so, the authors should cite relevant data. Even then, I do not think this allows the authors to conclude that longevity is "the main selective pressure" on Drosophila (l. 936).
(2) It appears that the "parental" (in fact, paternal) inversion frequency was estimated by sequencing sires that survived until the end of the two-week mating period. No information is provided on male mortality during the mating period, but substantial mortality is likely given constant courtship and mating opportunities. If so, the difference between the parental and embryo inversion frequency could reflect the differential survival of males until the point of sampling rather than / in addition to sexual selection.
(3) Finally, irrespective of the above caveats, the experimental data only address one of the elements of the theoretical hypothesis, namely antagonistic effects of inversions on reproduction and survival, notably that of females. It does not test for two other key elements of the proposed theory: the assumption of frequency-dependence of selection on male sexual success, and the prediction of synergistic epistasis for male fitness among genetic variants in the inversion. To be fair, particularly testing the latter prediction would be exceedingly difficult. Nonetheless, these limitations of the experiment mean that the paper is much stronger theoretical than empirical contribution.
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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 their 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 of clinical importance for antimalarial treatments but also deepens our understanding of protein function evolution. While I understand these experiments are challenging to conduct in malaria parasites, the data quality of some of the experiments could be improved. For example, most of the Western blots and Southern blots are not of high quality.
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Reviewer #1 (Public Review):
Summary:
This paper investigates the effects of the explicit recognition of statistical structure and sleep consolidation on the transfer of learned structure to novel stimuli. The results show a striking dissociation in transfer ability between explicit and implicit learning of structure, finding that only explicit learners transfer structure immediately. Implicit learners, on the other hand, show an intriguing immediate structural interference effect (better learning of novel structure) followed by successful transfer only after a period of sleep.
Strengths:
This paper is very well written and motivated, and the data are presented clearly with a logical flow. There are several replications and control experiments and analyses that make the pattern of results very compelling. The results are novel and intriguing, providing important constraints on theories of consolidation. The discussion of relevant literature is thorough. In summary, this work makes an exciting and important contribution to the literature.
Weaknesses:
There have been several recent papers that have identified issues with alternative forced choice (AFC) tests as a method of assessing statistical learning (e.g. Isbilen et al. 2020, Cognitive Science). A key argument is that while statistical learning is typically implicit, AFC involves explicit deliberation and therefore does not match the learning process well. The use of AFC in this study thus leaves open the question of whether the AFC measure benefits the explicit learners in particular, given the congruence between knowledge and testing format, and whether, more generally, the results would have been different had the method of assessing generalization been implicit. Prior work has shown that explicit and implicit measures of statistical learning do not always produce the same results (eg. Kiai & Melloni, 2021, bioRxiv; Liu et al. 2023, Cognition).
Given that the explicit/implicit classification was based on an exit survey, it is unclear when participants who are labeled "explicit" gained that explicit knowledge. This might have occurred during or after either of the sessions, which could impact the interpretation of the effects.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The study by Nelson et al. is focused on the formation of the Drosophila Posterior Signaling Center (PSC) which ultimately acts as a niche to support hematopoietic stem cells of the lymph gland (LG). Using a combination of genetics and live imaging, the authors show that PSC cells migrate as a tight collective and associate with multiple tissues during a trajectory that positions them at the posterior of the LG.<br /> This is an important study that identifies Slit-Robo signaling as a regulator of PSC morphogenesis, and highlights the complex relationship of interacting cell types - PSC, visceral mesoderm (VM), and cardioblasts (CBs) - in the coordinated development of these three tissues during organ development. However, one point requiring clarification is the idea that PSC cells exhibit a collective cell migration; it is not clear that the cells are migrating rather than being pushed to a more dorsal position through dorsal closure and/or other similar large-scale embryo movement. This does not detract from the very interesting analysis of PSC morphogenesis as presented.
Strengths:
(1) Using the expression of Hid or Grim to ablate associated tissues, they find evidence that the VM and CB of the dorsal vessel affect PSC migration/morphology whereas the alary muscles do not. Slit is expressed by both VM and CBs, and therefore Slit-Robo signaling was investigated as PSCs express Robo.
(2) Using a combination of approaches, the authors convincingly demonstrate that Slit expression in the CBs and VM acts to support PSC positioning. A strength is the ability to knockdown slit levels in particular tissue types using the Gal4 system and RNAi.
(3) Although in the analysis of robo mutants, the PSC positioning phenotype is weaker in the individual mutants (robo1 and robo2) with only the double mutant (robo1,robo2) exhibiting a phenotype comparable to the slit RNAi. The authors make a reasonable argument that Slit-Robo signaling has an intrinsic effect, likely acting within PSCs because PSCs show a phenotype even when CBs do not (Figure 4G).
(4) New insight into dorsal vessel formation by VM is presented in Figure 4A, B, as loss of the VM can affect dorsal vessel morphogenesis. This result additionally points to the VM as important.
Weaknesses:
(1) The authors are cautioned to temper the result that Slit-Robo signaling is intrinsic to PSC since the loss of robo may affect other cell types (besides CBs and PSCs) to indirectly affect PSC migration/morphogenesis. In fact, in the robo2, robo1 mutant, the VM appears to be incorrectly positioned (Figure 4G).
(2) If possible, the authors should use RNAi to knockdown Robo1 and Robo2 levels specifically in the PSCs if a Gal4 is available; might Antp.Gal4 (Fig 1K) be useful? Even if knockdown is achieved in PSCs+CBs, this would be a better/complementary experiment to support the approach outlined in Figure 4D.
(3) Movies are hard to interpret, as it seems unclear that the PSCs actively migrate rather than being pushed/moved indirectly due to association with VM and CBs/dorsal vessel.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors describe a massively parallel reporter assays (MPRA) screen focused on identifying polymorphisms in 5' and 3' UTRs that affect translation efficiency and thus might have a functional impact on cells. The topic is of timely interest, and indeed, several related efforts have recently been published and preprinted (e.g., https://pubmed.ncbi.nlm.nih.gov/37516102/ and https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635273/). This study has several major issues with the results and their presentation.
Major comments:
(1) The main issue is that it appears that the screen has largely failed, yet the reasons for that are unclear, which makes it difficult to interpret. The authors start with a library that includes approximately 6,000 variants, which makes it a medium-sized MPRA. But then, only 483 pairs of WT/mutated UTRs yield high-confidence information, which is already a small number for any downstream statistical analysis, particularly since most don't actually affect translation in the reporter screen setting (which is not unexpected). It is unclear why >90% of the library did not give high-confidence information. The profiles presented as base-case examples in Figure 2B don't look very informative or convincing. All the subsequent analysis is done on a very small set of UTRs that have an effect, and it is unclear to this reviewer how these can yield statistically significant and/or biologically relevant associations.
(2) From the variants that had an effect, the authors go on to carry out some protein-level validations and see some changes, but it is not clear if those changes are in the same direction as observed in the screen.
(3) The authors follow up on specific motifs and specific RBPs predicted to bind them, but it is unclear how many of the hits in the screen actually have these motifs, or how significant motifs can arise from such a small sample size.
(4) It is particularly puzzling how the authors can build a machine learning predictor with >3,000 features when the dataset they use for training the model has just a few dozens of translation-shifting variants.
(5) The lack of meaningful validation experiments altering the SNPs in the endogenous loci by genome editing limits the impact of the results.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Even though this is not the first report that the mutation in the DNAH12 gene causes asthenoteratozoospermia, the current study explores the sperm phenotype in-depth. The authors show experimentally that the said mutation disrupts the proper axonemal arrangement and recruitment of DNALI1 and DNAH1 - proteins of inner dynein arms. Based on these results, the authors propose a functional model of DNAH12 in proper axonemal development. Lastly, the authors demonstrate that the male infertility caused by the studies mutation can be rescued by ICSI treatment at least in the mouse. This study furthers our understanding of male infertility caused by a mutation of axonemal protein DNAH12, and how this type of infertility can be overcome using assisted reproductive therapy.
Strengths:<br /> This is an in-depth functional study, employing multiple, complementary methodologies to support the proposed working model.
Weaknesses:
The study strength could be increased by including more controls such as peptide blocking of the inhouse raised mouse and rat DNAH12 antibodies, and mass spectrometry of control IP with beads/IgG only to exclude non-specific binding. Objective quantifications of immunofluorescence images and WB seem to be missing. At least three technical replicates of western blotting of sperm and testis extracts could have been performed to demonstrate that the decrease of the signal intensity between WT and mutant was not caused by a methodological artifact.
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors reveal a new role for SDG7 in the regulation of H3K36me2 and me3. SDG7 appear to be functionally redundant to SDG8 as the double mutant presents lower levels of H3K36me and stronger phenotypes than either single mutant, however, their mechanisms of action might differ as the proteins displayed different localization on their target genes, with SDG7 localizing preferentially to TSS and TES while SDG8 covers the gene body. SDG7 binds preferentially to PREs, which recruit PRC2 for H3K27me3 deposition. The authors therefore present an interesting model where SDG7 evicts PRC2 from silenced genes, leading to a loss of H3K27me3. This would allow the transcriptional activation of the genes and the deposition of H3K36me3.
Strengths:
Overall, the manuscript is well-written and organized, although some paragraphs need clarifications. The figures are clear and well designed and the proposed model is compelling. While the manuscript is already interesting as it is, I think addressing the following questions would elevate it even more and refine the proposed model:
Weaknesses/potential aspects to address:
(1) It is still unclear whether SDG7 directly catalyzes H3K36me or if it promotes its deposition simply by eviction of PRC2. The AlphaFold and structure analyses show a significant similarity between the catalytic domains which would support the first possibility, but some more experiments would be required to prove this more definitively.
(2) Does SDG7 directly recognize the PRE (as suggested by the model in Figure 5F) or is it recruited by some transcription factors? Is SDG7 known to interact with any of the PRC2 recruiters?
(3) Line154/Figure 2A: The metagene plot for H3K36me3 shows a lower level on the gene body but a higher peak in sdg7sdg8 double mutants compared to the Wild-type, which is a bit surprising, especially considering that the immunostaining in reference 19 showed a near complete loss of H3K36me3 signal in the same double mutant. Can this higher peak be an artifact from the normalization strategy, or due to the existence of different subpopulations of genes?
Indeed, on the genome tracks presented by the authors, the hypomethylated genes show a loss of signal on the entire gene body, and not a higher peak near the TSS. It might be interesting to generate metagene plots for H3K36me3 hypo and hyper-methylated genes, to see if the higher peak at the TSS is solely due to the hyper-methylated genes.
(4) Figure 2C: More than 40% of differentially methylated genes are actually hypermethylated, but the authors do not discuss this at all. What are those genes, are they targeted by SDG7 or 8? Could they be responsible for the higher peak at the TSS observed in the double mutant? (see previous comment).
(5) Figure 2C and D: The method section states that the ChIP-seq was performed on 5-day-old seedlings, while the legend of this figure mentions root and shoot samples but this does not appear in the figure itself. There is also mention of shoot and root samples in Supplementary Tables 1 and 2. The authors should clarify which tissue was used for the data presented in Figure 2 and correct the legends or the methods accordingly.
(6) Line 270/Fig 4K and L: The text mentions looking at the 838 genes "downregulated in clf sdg7 sdg8 relative to sdg7 sdg8" and in the overlap, the authors identified FLC. However, in Figure 5D, FLC is upregulated in clf sdg7-sdg8 compared to sdg7-sdg8, not downregulated as mentioned in line 270. The Venn diagram in Figure 4L mentions "sdg vs clf sdg up", which would fit the pattern seen in Figure 5D, but the number of genes (838) matches the number of downregulated genes in the sdg7sdg8 vs clf s dg7sdg8 volcano plot.
I would actually expect the phenotype rescue to be caused by genes that are up in Wt vs clf, down in Wt vs sdg7-sdg8, and back up in sdg7-sdg8 vs clf-sdg7-sdg8, not "up/down/down" as mentioned in the text: genes would be downregulated in sdg7-sdg8 because of a loss of H3K36me and therefore hypermethylation of H3K27, but in the absence of CLF, this hypermethylation is reversed and the genes are upregulated in the triple mutant compared to the sdg7-sdg8 mutant. This is also what the authors see and describe in their cluster analysis in Figure 4M and line 280, mentioning an upregulation in clf-sdg7-sdg8 vs sdg7-sdg8. Could the authors please clarify these discrepancies between the different subplots and within the text itself? Was there maybe some error plotting the volcano plot and/or Venn diagram?
In general, as this part is quite complicated, maybe it would benefit from a clearer explanation from the authors as to why they look at those particular overlaps, so that the reader can more easily follow their train of thought.
(7) Figure 4N/Line 286: How were these 828 genes identified? Is it stemming from a clf-sdg7-sdg8 vs sdg7-sdg8 comparison? The legend says "genes shown by white color in Fig. 4M", do the authors mean the two clusters previously described?
(8) Line 300: "suggesting that SDG8 primarily mediates target gene expression in conjunction with PAF1C". This statement is based on overlapping genes that are downregulated in sdg7-sdg8 double mutant and paf1c mutants but concludes only on the role of SDG8. I feel that to state that SDG8 regulates expression in conjunction with PAF1C, the authors should rather examine the genes downregulated in the sdg8 mutant, especially considering the reduced overlap between genes downregulated in sdg8 and sdg7-sdg8 (according to Figure 2C, only 30% of the genes downregulated in sdg8 are also downregulated in the double mutant), or this statement should be corrected to also include SDG7.
Maybe it would be easier to read the figure if the authors created a master list of genes downregulated in at least one of the paf1c mutants they examined (as they anyway do not examine in detail the contribution of each individual paf1c mutant), and overlap it with the genes downregulated in sdg7, sdg8 or sdg7-sdg8.
(9) Line 326: "We also discovered that SDG7 and SDG8 overcome PRC2-mediated silencing, leading to a switch from H3K27 methylation to H3K36 methylation during growth and development." While part of this statement is supported by the ChIP data presented in Figure 4E, I think a ChIP for H3K36me2 and/or me3 is necessary to prove the existence of a K27me to K36me switch.
(10) Line 347: The authors state that SDG8 is located at the TSS and 3' end of genes, but on line 187 they state that it occupies the gene body (which is supported by the plot in Figure 3A).
(11) Line 351: The authors suggest a role of RNApolII in the deposition of K36me, but their data are not sufficient to support this hypothesis. The transcriptome data show that both SDGs and PAF1C regulate a similar set of genes, but they do not show data demonstrating that RNApolII is necessary for the deposition of K36me. It might be interesting to examine H3K36me levels in a paf1c mutant to further consolidate their hypothesis.
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Reviewer #1 (Public Review):
Summary:<br /> Both flies and mammals have D1-like and D2-like dopamine receptors, yet the role of D2-like receptors in Drosophila learning and memory remains underexplored. The paper by Qi et al. investigates the role of the D2-like dopamine receptor D2R in single pairs of dopaminergic neurons (DANs) during single-odor aversive learning in the Drosophila larva. First, they use confocal imaging to screen driver strains with expression in only single pairs of dopaminergic neurons. Next, they use thermogenetic manipulations of one pair of DANs (DAN-c1) to implicate DAN-c1 activity during larval aversive learning. They then use confocal imaging to demonstrate expression of D2R in the DANs and mushroom body of the larval brain. Finally, they show that optogenetic activation during training phenocopies D2R knockdown in these neurons: aversive learning is impaired when DAN-c1 is targeted, while appetitive and aversive learning are impaired when the mushroom body is manipulated. Qi et al. thus propose a model in which D2R limits excessive dopamine release to facilitate successful olfactory learning.
Strengths:<br /> The paper reproduces prior findings by Qi and Lee (2014), which demonstrated that D2R knockdown in DL1 DANs or the mushroom body impairs aversive olfactory learning in Drosophila larvae. The authors extended this previous work by screening 57 GAL4 drivers to identify tools that drive expression in individual DANs and used one of the tools, the R76F02-AD; R55C10-DBD driver, to manipulate DAN-c1 neurons with greater specificity. They also show that GFP-tagged D2R is expressed in most DANs and the mushroom body. Although the authors only train larvae with a single odor, they demonstrate that driving D2R knockdown in DAN-c1 neurons impairs aversive learning, as do other loss-of-function manipulations of DAN-c1 neurons.
Weaknesses:<br /> The authors claim to have identified drivers that label single DANs in Figure 1, but their confocal images in Figure S1 suggest that many of those drivers label additional neurons in the larval brain. It is also not clear why only some of the 57 drivers are displayed in Figure S1.<br /> Critically, R76F02-AD; R55C10-DBD labels more than one neuron per hemisphere in Figure S1c, and the authors cite Xie et al. (2018) to note that this driver labels two DANs in adult brains. Therefore, the authors cannot argue that the experiments throughout their paper using this driver exclusively target DAN-c1.<br /> Missing from the screen of 57 drivers is the driver MB320C, which typically labels only PPL1-γ1pedc in the adult and should label DAN-c1 in the larva. If MB320C labels DAN-c1 exclusively in the larva, then the authors should repeat their key experiments with MB320C to provide more evidence for DAN-c1 involvement specifically.<br /> The authors claim that the SS02160 driver used by Eschbach et al. (2020) labels other neurons in addition to DAN-c1. Could the authors use confocal imaging to show how many other neurons SS02160 labels? Given that both Eschbach et al. and Weber et al. (2023) found no evidence that DAN-c1 plays a role in larval aversive learning, it would be informative to see how SS02160 expression compares with the driver the authors use to label DAN-c1.<br /> The claim that DAN-c1 is both necessary and sufficient in larval aversive learning should be reworded. Such a claim would logically exclude any other neuron or even the training stimuli from being involved in aversive learning (see Yoshihara and Yoshihara (2018) for a detailed discussion of the logic), which is presumably not what the authors intended because they describe the possible roles of other DANs during aversive learning in the discussion.<br /> Moreover, if DAN-c1 artificial activation conveyed an aversive teaching signal irrespective of the gustatory stimulus, then it should not impair aversive learning after quinine training (Figure 2k). While the authors interpret Figure 2k (and Figure 5) to indicate that artificial activation causes excessive DAN-c1 dopamine release, an alternative explanation is that artificial activation compromises aversive learning by overriding DAN-c1 activity that could be evoked by quinine.<br /> The authors should not necessarily expect that D2R enhancer driver strains would reflect D2R endogenous expression, since it is known that TH-GAL4 does not label p(PAM) dopaminergic neurons. Their observations of GFP-tagged D2R expression could be strengthened with an anti-D2R antibody such as that used by Lam et al., (1999) or Love et al., (2023).<br /> Finally, the authors could consider the possibility other DANs may also mediate aversive learning via D2R. Knockdown of D2R in DAN-g1 appears to cause a defect in aversive quinine learning compared with its genetic control (Figure S4e). It is unclear why the same genetic control has unexpectedly poor aversive quinine learning after training with propionic acid (Figure S5a). The authors could comment on why RNAi knockdown of D2R in DAN-g1 does not similarly impair aversive quinine learning (Figure S5b).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this manuscript, Ferhat and colleagues describe their study aimed at developing a blood-brain barrier (BBB) penetrant agent that could induce hypothermia and provide neuroprotection from the sequelae of status epilepticus (SE) in mice. Hypothermia is used clinically in an attempt to reduce neurological sequelae of injury and disease. Hypothermia can be effective, but physical means used to reduce core body temperature are associated with untoward effects. Pharmacological means to induce hypothermia could be as effective with fewer untoward complications. Intracerebroventricularly applied neurotensin can cause hypothermia; however, neurotensin applied peripherally is degraded and does not cross the BBB. Here the authors develop and characterize a neurotensin conjugate that can reach the brain, induce hypothermia, and reduce seizures, cognitive changes, and inflammatory changes associated with status epilepticus.
Strengths:
(1) In general, the study is well-reasoned, well-designed, and seemingly well-executed.
(2) Strong dose-response assessment of multiple neurotensin conjugates in mice.
(3) Solid assessment of binding affinity, in vitro stability in blood, and brain uptake of the conjugate.
(4) Appropriate inclusion of controls for SE and for drug injections. However, perhaps a vehicle control could have been employed.
(5) Multifaceted assessment of neurodegeneration, inflammation, and mossy fiber sprouting in the different groups.
(6) Inclusion of behavioral assessments.
(7) Evaluates NSTR1 receptor distribution in multiple ways; however, does not evaluate changes in receptor distribution or ping wo/w SE and/or various drugs.
(8) Demonstrates that this conjugate can induce hypothermia and have positive effects on the sequelae of SE. Could have a great impact on the application of pharmacologically-induced hypothermia as a neuroprotective measure in patients.
Weaknesses:
(1) The authors make the claim, repeatedly, that the hypothermia caused by the neurotensin conjugate is responsible for the effects they see; however, what they really show is that the conjugate causes hypothermia AND has favorable effects on the sequelae of SE. They need to discuss that they did not administer the conjugate without allowing the pharmacological hypothermia (e.g., by warming the animal, etc.).
(2) In the status epilepticus studies, it is unclear how or whether they monitored animals for the development of spontaneous seizures. Can the authors please describe this?
(3) They do not evaluate changes in receptor distribution or ping wo/w SE and/or various drugs.
(4) It is not clear why several different mouse strains were employed.
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- Aug 2024
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arxiv.org arxiv.org
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Reviewer #1 (Public Review):
Carignano et al propose an extension of the self-returning random walk (SRRW) model for chromatin to include excluded volume aspects and use it to investigate generic local and global properties of the chromosome 3D organization inside eukaryotic nuclei. In particular, they focus on chromatin volumic density, contact probability and domain size and suggest that their framework can recapitulate several experimental observations and predict the effect of some perturbations.
Strengths:<br /> • The developed methodology is convincing and may offer an alternative - less computationally demanding - framework to investigate the single-cell and population structural properties of 3D genome organization at multiple scales.<br /> • Compared to the previous SRRW model, it allows for investigation of the role of excluded volume locally.<br /> • They perform some experiments to compare with model predictions and show consistency between the two.
Weaknesses:<br /> • The model currently cannot fully account for specific mechanisms that may shape the heterogeneous, complex organization of chromosomes (TAD at specific positions, A/B compartmentalization, promoter-enhancer loops, etc.).<br /> • By construction of their framework, excluded volume only impacts locally the polymer organization and larger-scale properties for which excluded volume could be a main actor (formation of chromosome territories [Rosa & Everaers, PLoS CB 2009], bottle-brush effects due to loop extrusion [Polovnikov et al, PRX 2023], etc.) cannot be captured.<br /> • Comparisons with experiments are solid but are not clearly quantified.
Impact:<br /> Building on the presented framework in the future to incorporate TAD and compartments may offer an interesting model to study the single-cell heterogeneity of chromatin organization. But currently, in this reviewer's opinion, standard polymer modeling frameworks may offer more possibilities.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this work, the authors present a novel, multi-layer computational model of motor control to produce realistic walking behaviour of a Drosophila model in the presence of external perturbations and under sensory and motor delays. The novelty of their model of motor control is that it is modular, with divisions inspired by the fly nervous system, with one component based on deep learning while the rest are based on control theory. They show that their model can produce realistic walking trajectories. Given the mostly reasonable assumptions of their model, they convincingly show that the sensory and motor delays present in the fly nervous system are the maximum allowable for robustness to unexpected perturbations.
Their fly model outputs torque at each joint in the leg, and their dynamics model translates these into movements, resulting in time-series trajectories of joint angles. Inspired by the anatomy of the fly nervous system, their fly model is a modular architecture that separates motor control at three levels of abstraction:<br /> (1) oscillator-based model of coupling of phase angles between legs,<br /> (2) generation of future joint-angle trajectories based on the current state and inputs for each leg (the trajectory generator), and<br /> (3) closed-loop control of the joint-angles using torques applied at every joint in the model (control and dynamics).
These three levels of abstraction ensure coordination between the legs, future predictions of desired joint angles, and corrections to deviations from desired joint-angle trajectories. The parameters of the model are tuned in the absence of external perturbations using experimental data of joint angles of a tethered fly. A notable disconnect from reality is that the dynamics model used does not model the movement of the body and ground contacts as is the case in natural walking, nor the movement of a ball for a tethered fly, but instead something like legs moving in the air for a tethered fly.
In order to validate the realism of the generated simulated walking trajectories, the authors compare various attributes of simulated to real tethered fly trajectories and show qualitative and quantitative similarities, including using a novel metric coined as Kinematic Similarity (KS). The KS score of a trajectory is a measure of the likelihood that the trajectory belongs to the distribution of real trajectories estimated from the experimental data. While such a metric is a useful tool to validate the quality of simulated data, there is some room for improvement in the actual computation of this score. For instance, the KS score is computed for any given time-window of walking simulation using a fraction of information from the joint-angle trajectories. It is unclear if the remaining information in joint-angle trajectories that are not used in the computation of the KS score can be ignored in the context of validating the realism of simulated walking trajectories.
The authors validate simulated walking trajectories generated by the trained model under a range of sensorimotor delays and external perturbations. The trained model is shown to generate realistic joint-angle trajectories in the presence of external perturbations as long as the sensorimotor delays are constrained within a certain range. This range of sensorimotor delays is shown to be comparable to experimental measurements of sensorimotor delays, leading to the conclusion that the fly nervous system is just fast enough to be robust to perturbations.
Strengths:
This work presents a novel framework to simulate Drosophila walking in the presence of external perturbations and sensorimotor delay. Although the model makes some simplifying assumptions, it has sufficient complexity to generate new, testable hypotheses regarding motor control in Drosophila. The authors provide evidence for realistic simulated walking trajectories by comparing simulated trajectories generated by their trained model with experimental data using a novel metric proposed by the authors. The model proposes a crucial role in future predictions to ensure robust walking trajectories against external perturbations and motor delay. Realistic simulations under a range of prediction intervals, perturbations, and motor delays generating realistic walking trajectories support this claim. The modular architecture of the framework provides opportunities to make testable predictions regarding motor control in Drosophila. The work can be of interest to the Drosophila community interested in digitally simulating realistic models of Drosophila locomotion behaviors, as well as to experimentalists in generating testable hypotheses for novel discoveries regarding neural control of locomotion in Drosophila. Moreover, the work can be of broad interest to neuroethologists, serving as a benchmark in modelling animal locomotion in general.
Weaknesses:
As the authors acknowledge in their work, the control and dynamics model makes some simplifying assumptions about Drosophila physics/physiology in the context of walking. For instance, the model does not incorporate ground contact forces and inertial effects of the fly's body. It is not clear how these simplifying assumptions would affect some of the quantitative results derived by the authors. The range of tolerable values of sensorimotor delays that generate realistic walking trajectories is shown to be comparable with sensorimotor delays inferred from physiological measurements. It is unclear if this comparison is meaningful in the context of the model's simplifying assumptions. The authors propose a novel metric coined as Kinematic Similarity (KS) to distinguish realistic walking trajectories from unrealistic walking trajectories. Defining such an objective metric to evaluate the model's predictions is a useful exercise, and could potentially be applied to benchmark other computational animal models that are proposed in the future. However, the KS score proposed in this work is calculated using only the first two PCA modes that cumulatively account for less than 50% of the variance in the joint angles. It is not obvious that the information in the remaining PCA modes may not change the log-likelihood that occurs in the real walking data.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript described a clinical trial to understand the different treatment durations of loperamide in preventing pyrotinib-induced diarrhea. The authors concluded that no significant differences were observed between 21-day and 42-day loperamide durations in preventing grade {greater than or equal to} grade 3 diarrhea. The authors suggested that considering the economic cost and patient compliance, 21-day loperamide prophylaxis might represent a more pragmatic and appropriate approach for clinical application.
Strengths:
It is essential to understand if loperamide for primary prevention of diarrhea helps or not for postoperative treatment with nab-paclitaxel and pyrotinib in HER2-positive patients. This clinical trial would answer this question eventually.
Weaknesses:
(1) There are no patients who have not received prophylactic treatment for diarrhea to serve as a control group. This limited the finding that if the loperamide for primary prevention of diarrhea benefits or not for postoperative treatment with nab-paclitaxel and pyrotinib in HER2-positive patients. This would not help much for the guidance of clinical use of the loperamide for primary prevention of diarrhea.
(2) The clinical trial needs double-blinding for evaluation of treatment. In this manuscript, the blinding was not employed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Colomb et al have further explored the mechanisms of action of a family of three immunodulatory proteins produced by the murine gastrointestinal nematode parasite Heligmosomoides polygyrus bakeri. The family of HpARI proteins binds to the alarmin interleukin 33 and depending on family members, exhibits differential activities, either suppressive or enhancing. The present work extends previous studies by this group showing the binding of DNA by members of this family through a complement control protein (CCP1) domain. Moreover, they identify two members of the family that bind via this domain in a non-specific manner to the extracellular matrix molecule heparan sulphate through a basic charged patch in CCP1. The authors thus propose that binding to DNA or heparan sulphate extends the suppressive action of these two parasite molecules, whereas the third family member does not bind and consequently has a shorter half-life and may function via diffusion.
Strengths:
A strength of the work is the multifaceted approach to examining and testing their hypotheses, using a well-established and well-defined family of immunomodulatory molecules using multiple approaches including an in vivo setting.
Weaknesses:
There are a few weaknesses of the approach. Perhaps some discussion and speculation as to how these three family members might operate in concert during Heligmosomoides polygyrus bakeri infection would help place the biology of these molecules in context for the reader, e.g. when and where they are produced.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Yang. Hu et al. investigated the molecular mechanism that cause astrocyte activation and its implications for multiple sclerosis. This study focuses on the enzyme PKM2, known for its role in glycolysis, and its nuclear translocation in reactive astrocytes in a mouse model of multiple sclerosis (EAE). Preventing the nuclear translocation of PKM2 reduces astrocyte activation, proliferation, glycolysis, and inflammatory cytokine secretion. Importantly, the study reveals that TRIM21 controls PKM2's nuclear translocation through ubiquitination, promoting its nuclear import and enhancing its activity. Single-cell RNA sequencing and immunofluorescence confirm TRIM21 upregulation in EAE astrocytes, and alteration of TRIM21 levels affect PKM2-dependent glycolysis and proliferation. Their findings suggest that targeting the TRIM21-PKM2 axis could be a therapeutic strategy for treating neurological diseases involving astrocyte activation.
Strength:
This work provides a comprehensive exploration of PKM2's nuclear role and its interaction with TRIM21 in EAE, offering new insights for therapeutic strategies targeting metabolic reprogramming in astrocyte activation. The strength of the study is the use of advanced techniques such as single cell RNA sequencing, in vitro and in vivo knockdown techniques to support the data. With the addition of new data and explanations in the manuscript, the authors have rendered their claimed ideas more supportive.
Weakness:
The revisions and implementation of suggestions have greatly improved the overall quality of the manuscript. I would like to thank the authors for carefully evaluating all the suggestions and for providing extra explanations and response figures. However, there are still some points that need to be corrected and clarified.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Federer et al. tested AAVs designed to target GABAergic cells and parvalbumin-expressing cells in marmoset V1. Several new results were obtained. First, AAV-h56D targeted GABAergic cells with high specificity but in ways that varied across serotype and layer. Second, AAV-PHP.eB.S5E2 targeted parvalbumin-expressing neurons with similarly high specificity. Third, immunohistochemical GABA and PV signals were attenuated near viral injection sites.
A strength of this study is the analysis of marker gene expression at AAV injection sites. Some endogenous genes are difficult to detect following AAV injections, which is an important observation. A second contribution is the demonstration that AAV-S5E2 drives transgene expression selectively in parvalbumin-expressing neurons when vectors are delivered intraparenchymally (the study introducing AAV-S5E2 used intravenous injections).
A weakness of this study is that the data set is small. Which of the results would hold up had a larger number of injections been made into a larger number of marmosets remains unclear.
A major goal of this study was to quantify the specificity and coverage of AAV-h56D and AAV-S5E2 vectors in marmoset cortex. This goal was achieved. This report provides a valuable guide for other investigators using these tools. It also provides a rigorous survey of the laminar distributions of GABA+ and PV+ neurons in marmoset V1 which has value independent of the viral injections.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors of this manuscript characterize new anion conducting that is more red-shifted in its spectrum than prior variants called MsACR1. An additional mutant variant of MsACR1 that is renamed raACR has a 20 nm red-shifted spectral response with faster kinetics. Due to the spectral shift of these variants, the authors proposed that it is possible to inhibit expression of MsACR1 and raACR with lights at 635 nm in vivo and in vitro. The authors were able to demonstrate inhibition in vitro and in vivo with 635 nm light. Overall the new variants with unique properties should be able to suppress neuronal activities with red-shifted light stimulation.
Strengths:
The authors were able to identify a new class of anion conducting channelrhodopsin and have variants that respond strongly to lights with wavelength >550 nm. The authors were able to demonstrate this variant, MsACR1, can alter behavior in vivo with 635 nm light.
The second major strength of the study is the development of a red-shifted mutant of MsACR1 that has faster kinetics and 20 nm red-shifted from a single mutation.
Weaknesses:
There are many claims not supported by the evidence provided in the submitted version of the manuscript and would require further experiments to support such claims.
(1) From the data shown, the red-shifted raACR work much less efficiently than MsACR1 even with 635 nm light illumination both in vivo (Figure 4D) and in vitro (Figure 3E) despite the 20 nm red-shift. This is inconsistent with the benefits and effects of red-shifting the spectrum in raACR. The authors claimed that this is due to the faster kinetics of raACR which is plausible from the data shown in Fig 3E but this could be experimentally shown if more examples of continuous illumination and pulsed illumination (such as the one shown in Fig 3D) can be shown in supplemental figures. If this is truly due to the off-kinetics, the spikes would appear after the termination of the pulses but there is little difference in the cases of continuous illumination or during illumination. The fact that 635nm is equally effective as raACR suggests that there is an overall stronger effect of MsACR1 that compensates for the red-shift of raACR.
(2) There are limited comparisons to existing variants of ACRs under the same conditions in the manuscript overall. There should be more parallel comparison with gtACR1, ZipACR and RubyACR in identical conditions in cultured cell line, cultured neurons and in vivo. In terms of overall performance, efficiency, expression in identical conditions. Without this information, it is unclear whether the effects at 635 nm is due to the expression level which can compensate for the spectral shift (which may be the case for MsACR1). The authors stated they are saving this data for another manuscript, this is important data for the current manuscript which should be presented in the existing manuscript.
(3) Despite being able to activate the channelrhodopsin with 635 nm light, the main utility of the variant would be transcranial stimulation which were not demonstrated here.
(4) For the in vivo characterization, there is no mention of animal number and results from Fig 4 and 5 appear to come from multiple samples from a single animal. This is not sufficient scientific evidence to support the claims. Fig 4 and 5 should have statistical analysis from multiple animals and not multiple measurements from single animals in each of the conditions.
(5) As reviewer 2 also pointed out, there is a lack of proper controls (in addition to the low number of animals). The authors point out the current absence of technicians in the laboratory, this should not be a reason to not attempt or do the experiments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> This study investigated spatial representations in deep feedforward neural network models (DDNs) that were often used in visual tasks. The authors create a three-dimensional virtual environment, and let a simulated agent randomly forage in a smaller two-dimensional square area. The agent "sees" images of the room within its field of view from different locations and heading directions. These images were processed by DDNs. Analyzing model neurons in DDNs, they found response properties similar to those of place cells, border cells and head direction cells in various layers of deep nets. A linear readout of network activity can recover key spatial variables. In addition, after removing neurons with strong place/border/head direction selectivity, one can still decode these spatial variables from the remaining neurons in the DNNs. Based on these results, the authors argue that that the notion of functional cell types in spatial cognition is misleading.
Strengths:<br /> This paper contains interesting and original ideas, and I enjoy reading it. Most previous studies (e.g., Banino, Nature, 2018; Cueva & Wei, ICLR, 2018; Whittington et al, Cell, 2020) using deep network models to investigate spatial cognition mainly relied on velocity/head rotation inputs, rather than vision (but see Franzius, Sprekeler, Wiskott, PLoS Computational Biology, 2007). Here, the authors find that, under certain settings, visual inputs alone may contain enough information about the agent's location, head direction and distance to the boundary, and such information can be extracted by DNNs. If confirmed, this is potentially an interesting and important observation.
Weaknesses:<br /> While the findings reported here are interesting, it is unclear whether they are the consequence of the specific model setting, and how well they would generalize. Furthermore, I feel the results are over-interpreted. There are major gaps between the results actually shown and the claim about the "superfluousness of cell types in spatial cognition". Evidence directly supporting the overall conclusion seems to be weak at the moment.
Major concerns:
(1) The authors reported that, in their model setting, most neurons throughout the different layers of CNNs show strong spatial selectivity. This is interesting and perhaps also surprising. It would be useful to test/assess this prediction directly based on existing experimental results. It is possible that the particular 2-d virtual environment used is special. The results will be strengthened if similar results hold for other testing environments.
In particular, examining the pictures shown in Fig. 1A, it seems that local walls of the 'box' contain strong oriented features that are distinct across different views. Perhaps the response of oriented visual filters can leverage these features to uniquely determine the spatial variable. This is concerning because this is a very specific setting that is unlikely to generalize.
(2) Previous experimental results suggest that various function cell types discovered in rodent navigation circuits persist in dark environments. If we take the modeling framework presented in this paper literally, the prediction would be that place cells/head direction cells should go away in darkness. This implies that key aspects of functional cell types in the spatial cognition are missing in the current modeling framework. This limitation needs to be addressed or explicitly discussed.
(3) Place cells/border cell/ head direction cells are mostly studied in the rodent's brain. For rodents, it is not clear whether standard DNNs would be good models of their visual systems. It is likely that rodent visual system would not be as powerful in processing visual inputs as the DNNs used in this study.
(4) The overall claim that those functional cell types defined in spatial cognition are superfluousness seems to be too strong based on the results reported here. The paper only studied a particular class of models, and arguably, the properties of these models have a major gap to those of real brains. Even though, in the DNN models simulated in this particular virtual environment, (i) most model neurons have strong spatial selectivity; (ii) removing model neurons with the strongest spatial selectivity still retain substantial spatial information, why this is relevant to the brain? The neural circuits may operate in a very different regime. Perhaps a more reasonable interpretation of the results would be: these results raise the possibility that those strongly selective neurons observed in the brain may not be essential for encoding certain features, as something like this is observed in certain models. It is difficult to draw definitive conclusions about the brain based on the results reported.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):<br /> Summary:<br /> This interesting and well written article by Tuckowski et al. summarizes work connecting the flavin-containing monooxygenase FMO-4 with increased lifespan through a mechanism involving calcium signaling in the nematode Caenorhabditis elegans.
The authors have previously studied another fmo in worms, FMO-2, prompting them to look at additional members of this family of proteins. They show that fmo-4 is up in dietary restricted worms and necessary for the increased lifespan of these animals as well as of rsks-1 (s6 kinase) knockdown animals. They then show that overexpression of fmo-4 is sufficient to significantly increase lifespan, as well as healthspan and paraquat resistance. Further, they demonstrate that overexpression of fmo-4 solely in the hypodermis of the animal recapitulates the entire effect of fmo-4 OE.
In terms of interactions between fmo-2 and fmo-4 they show that fmo-4 is necessary for the previously reported effects of fmo-2 on lifespan, while the effects of fmo-4 do not depend on fmo-2.
Next the authors use RNASeq to compare fmo-4 OE animals to wild type. Their analyses suggested the possibility that FMO-4 was modulating calcium signaling, and through additional experiments specifically identified the calcium signaling genes crt-1, itr-1, and mcu-1 as important fmo-4 interactors<br /> in this context. As previously published work has shown that loss of the worm transcription factor atf-6 can extend lifespan through crt-1, itr-1 and mcu-1, the authors asked about interactions between fmo-4 and atf-6. They showed that fmo-4 is necessary for both lifespan extension and increased paraquat resistance upon RNAi knockdown of atf-6.
Overall this clearly written manuscript summarizes interesting and novel findings of great interest in the biology of aging and suggests promising avenues for future work in this area.
Strengths:<br /> This paper contains a large number of careful, well executed and analysed experiments in support of its existing conclusions, and which also point toward significant future directions for this work. In addition it is clear and very well written.
Weaknesses:<br /> Within the scope of the current work there are no major weaknesses. That said, the authors themselves note pressing questions beyond the scope of this study that remain unanswered. For instance, the mechanistic nature of the interactions between FMO-4 and the other players in this story, for example in terms of direct protein-protein interactions, is not at all understood yet. Further, powerful tools such as GCaMP expressing animals will enable a much more detailed understanding of what exactly is happening to calcium levels, and where and when it is happening, in these animals.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This manuscript by Kleinman & Foster investigates the dependence of hippocampal replay on VTA activity. They recorded neural activity from the dorsal CA1 region of the hippocampus while chemogenetically silencing VTA dopamine neurons as rats completed laps on a linear track with reward delivery at each end. Reward amount changed across task epochs within a session on one end of the track. The authors report that VTA activity is necessary for an increase in sharp-wave rate to remain localized to the feeder that undergoes a change in reward magnitude, an effect that was especially pronounced in a novel environment. They follow up on this result with a second experiment in which reward magnitude varies unpredictably at one end of the linear track and report that changes in sharp-wave rate at the variable location reflect both the amount of reward rats just received there, in addition to a smaller modulation that is reminiscent of reward prediction error coding, in which the previous reward rats received at the variable location affects the magnitude of the subsequent change in sharp-wave rate that occurs on the present visit.
This work is technically innovative, combining neural recordings with chemogenetic inactivation. The question of how VTA activity affects replay in the hippocampus is interesting and important given that much of the work implicating hippocampal replay in memory consolidation and planning comes from reward-motivated behavioral tasks. Enthusiasm for the manuscript is dampened by some technical considerations about the chemogenetic portion of the experiments. Additionally, there are some interpretational issues related to whether changes in reward magnitude affected sharp-wave rate directly, or whether the reported changes in sharp-wave rate alter behavior and these behavioral changes affect sharp-wave rate.
Major issues:
Chemogenetics validation
Little validation is provided for the chemogenetic manipulations. The authors report that animals were excluded due to lack of expression but do not quantify/document the extent of expression in the animals that were included in the study. There's no independent verification that VTA was actually inhibited by the chemogenetic manipulation besides the experimental effects of interest.
The authors report a range of CNO doses. What determined the dose that each rat received? Was it constant for an individual rat? If not, how was the dose determined? The authors may wish to examine whether any of their CNO effects were dependent on dose.
The authors tested the same animal multiple times per day with relatively little time between recording sessions. Can they be certain that the effect of CNO wore off between sessions? Might successive CNO injections in the same day have impacted neural activity in the VTA differently? Could the chemogenetic manipulation have grown stronger with each successive injection (or maybe weaker due to something like receptor desensitization)? The authors could test statistically whether the effects of CNO that they report do not depend on the number of CNO injections a rat received over a short period of time.
Motivational considerations
In a similar vein, running multiple sessions per day raises the possibility that rats' motivation was not constant across all data collection time points. The authors could test whether any measures of motivation (laps completed, running speed) changed across the sessions conducted within the same day. This is a particularly tricky issue, because my read of the methods is that saline sessions were only conducted as the first session of any recording day, which means there's a session order/time of day and potential motivational confound in comparing saline to CNO sessions.
Statistics, statistical power, and effect sizes
Throughout the manuscript, the authors employ a mixture of t-tests, ANOVAs, and mixed-effects models. Only the mixed effects models appropriately account for the fact that all of this data involves repeated measurements from the same subject. The t-tests are frequently doubly inappropriate because they both treat repeated measures as independent and are not corrected for multiple comparisons.
The number of animals in these studies is on the lower end for this sort of work, raising questions about whether all of these results are statistically reliable and likely to generalize. This is particularly pronounced in the reward volatility experiment, where the number of rats in the experimental group is halved to just two. The results of this experiment are potentially very exciting, but the sample size makes this feel more like pilot data than a finished product.
The effect sizes of the various manipulations appear to be relatively modest, and I wonder if the authors could help readers by contextualizing the magnitude of these results further. For instance, when VTA inactivation increases mis-localization of SWRs to the unchanged end of the track, roughly how many misplaced sharp-waves are occurring within a session, and what would their consequence be? On this particular behavioral task, it's not clear that the animals are doing worse in any way despite the mislocalization of sharp-waves. And it seems like the absolute number of extra sharp-waves that occur in some of these conditions would be quite small over the course of a session, so it would be helpful if the authors could speculate on how these differences might translate to meaningful changes in processes like consolidation, for instance.
How directly is reward affecting sharp-wave rate?
Changes in reward magnitude on the authors' task cause rats to reallocate how much time they spent at each end. Coincident with this behavioral change, the authors identify changes in the sharp-wave rate, and the assumption is that changing reward is altering the sharp-wave rate. But it also seems possible that by inducing longer pauses, increased reward magnitude is affecting the hippocampal network state and creating an occasion for more sharp-waves to occur. It's possible that any manipulation so altering rats' behavior would similarly affect the sharp-wave rate.
For instance, in the volatility experiment, on trials when no reward is given sharp-wave rate looks like it is effectively zero. But this rate is somewhat hard to interpret. If rats hardly stopped moving on trials when no reward was given, and the hippocampus remained in a strong theta network state for the full duration of the rat's visit to the feeder, the lack of sharp-waves might not reflect something about reward processing so much as the fact that the rat's hippocampus didn't have the occasion to emit a sharp-wave. A better way to compute the sharp-wave rate might be to use not the entire visit duration in the denominator, but rather the total amount of time the hippocampus spends in a non-theta state during each visit. Another approach might be to include visit duration as a covariate with reward magnitude in some of the analyses. Increasing reward magnitude seems to increase visit duration, but these probably aren't perfectly correlated, so the authors might gain some leverage by showing that on the rare long visit to a low-reward end sharp-wave rate remains reliably low. This would help exclude the explanation that sharp-wave rate follows increases in reward magnitude simply because longer pauses allow a greater opportunity for the hippocampus to settle into a non-theta state.
The authors seem to acknowledge this issue to some extent, as a few analyses have the moments just after the rat's arrival at a feeder and just before departure trimmed out of consideration. But that assumes these sorts of non-theta states are only occurring at the very beginning and very end of visits when in fact rats might be doing all sorts of other things during visits that could affect the hippocampus network state and the propensity to observe sharp-waves.
Minor issues
The title/abstract should reflect that only male animals were used in this study.
The title refers to hippocampal replay, but for much of the paper the authors are measuring sharp-wave rate and not replay directly, so I would favor a more nuanced title.
Relatedly, the interpretation of the mislocalization of sharp-waves following VTA inactivation suggests that the hippocampus is perhaps representing information inappropriately/incorrectly for consolidation, as the increased rate is observed both for a location that has undergone a change in reward and one that has not. However, the authors are measuring replay rate, not replay content. It's entirely possible that the "mislocalized" replays at the unchanged end are, in fact, replaying information about the changed end of the track. A bit more nuance in the discussion of this effect would be helpful.
The authors use decoding accuracy during movement to determine which sessions should be included for decoding of replay direction. Details on cross-validation are omitted and would be appreciated. Also, the authors assume that sessions failed to meet inclusion criteria because of ensemble size, but this information is not reported anywhere directly. More info on the ensemble size of included/excluded sessions would be helpful.
For most of the paper, the authors detect sharp-waves using ripple power in the LFP, but for the analysis of replay direction, they use a different detection procedure based on the population firing rate of recorded neurons. Was there a reason for this switch? It's somewhat difficult to compare reported sharpwave/replay rates of the analyses given that different approaches were used.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, the authors re-analyzed Experiment 1 of a public dataset (Rademaker et al, 2019, Nature Neuroscience) which includes fMRI and behavioral data recorded while participants held an oriented grating in visual working memory (WM) and performed a delayed recall task at the end of an extended delay period. In that experiment, participants were pre-cued on each trial as to whether there would be a distracting visual stimulus presented during the delay period (filtered noise or randomly oriented grating). In this manuscript, the authors focused on identifying whether the neural code in the retinotopic cortex for remembered orientation was 'stable' over the delay period, such that the format of the code remained the same, or whether the code was dynamic, such that information was present, but encoded in an alternative format. They identify some time points - especially towards the beginning/end of the delay - where the multivariate activation pattern fails to generalize to other time points and interpret this as evidence for a dynamic code. Additionally, the authors compare the representational format of remembered orientation in the presence vs absence of a distracting stimulus, averaged over the delay period. This analysis suggested a 'rotation' of the representational subspace between distracting orientations and remembered orientations, which may help preserve simultaneous representations of both remembered and viewed stimuli.
Strengths:
(1) Direct comparisons of coding subspaces/manifolds between time points and task conditions is an innovative and useful approach for understanding how neural representations are transformed to support cognition.
(2) Re-use of existing datasets substantially goes beyond the authors' previous findings by comparing the geometry of representational spaces between conditions and time points, and by looking explicitly for dynamic neural representations
Weaknesses:
(1) Only Experiment 1 of Rademaker et al (2019) is reanalyzed. The previous study included another experiment (Expt 2) using different types of distractors which did result in distractor-related costs to neural and behavioral measures of working memory. The Rademaker et al (2019) study uses these two results to conclude that neural WM representations are protected from distraction when distraction does not impact behavior, but conditions that do impact behavior also impact neural WM representations. Considering this previous result is critical for relating the present manuscript's results to the previous findings, it seems necessary to address Experimentt 2's data in the present work
(2) Primary evidence for 'dynamic coding', especially in the early visual cortex, appears to be related to the transition between encoding/maintenance and maintenance/recall, but the delay period representations seem overall stable, consistent with previous findings
(3) Dynamicism index used in Figure 1f quantifies the proportion of off-diagonal cells with significant differences in decoding performance from the diagonal cell. It's unclear why the proportion of time points is the best metric, rather than something like a change in decoding accuracy. This is addressed in the subsequent analysis considering coding subspaces, but the utility of the Figure 1f analysis remains weakly justified.
(4) There is no report of how much total variance is explained by the two PCs defining the subspaces of interest in each condition, and timepoint. It could be the case that the first two principal components in one condition (e.g., sensory distractor) explain less variance than the first two principal components of another condition.
(5) Converting a continuous decoding metric (angular error) to "% decoding accuracy" serves to obfuscate the units of the actual results. Decoding precision (e.g., sd of decoding error histogram) would be more interpretable and better related to both the previous study and behavioral measures of WM performance.
(6) This report does not make use of behavioral performance data in the Rademaker et al (2019) dataset.
(7) Given there were observed differences between individual retinotopic ROIs in the temporal cross-decoding analyses shown in Figure 1, the lack of data presented for the subspace analyses for the corresponding individual ROIs is a weakness
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this work Jeong and colleagues focus on exploring the role of the acyltransferase ZDHHC9 in myelinating OLs in particular in the palmitoylation of several myelin proteins. After confirming the specific enrichment of the Zdhhc9 transcript in mouse and human OLs, the authors examine the subcellular localization of the protein in vitro and observed that in comparison with other isoforms, ZDHHC9 localizes at OLs cell bodies and at discrete puncta in the processes. These observations (Figures 1 and 2) led the authors to hypothesize that ZDHHC9 plays an important role in myelination. No gross changes were detected in OL development in Zdhhc9 KO mice and analyses from P28 Zdhhc9 KO mice crossed with Mobp-EGFP reporter mice did not show changes in EGFP+ OL differentiation (Figure 3). However, and given the observed subcellular localization of ZDHHC9 in OL processes (Figure 2) and the observation that the percentage of unmyelinated axons is increased in Zdhhc9 KO (Figure 6), early time points to examine the differentiated pools of OLs and their capacity to extend processes/contact axons need to be considered.
Maturation of OL in Zdhhc9 KO was examined by crossing Zdhhc9 KO with Pdgfra-CreER; R26- EGFP and following the newly EGFP-labelled OPCs following tamoxifen administration. No changes in the numbers of EGFP+ OL were detected. The authors concluded that the loss of ZDHHC9 does not alter oligodendrogenesis in either the young or mature CNS. The authors observed defects in Zdhhc9 KO OL protrusions that they attributed to abnormal OL membrane expansion (Fig 4 and 5). Can they show evidence for this?
The authors report that Zdhhc9 KO primary and secondary branches in OL were longer, some contained spheroid-like swellings and the OL protrusion complexity was higher. However, these data is partially contradictory to what they show in OL differentiation experiments in vitro (Fig 7). There is also no evidence for increased membrane expansion in Zdhhc9 knockdown myelin forming cells in culture. How to reconcile this?
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Reviewer #1 (Public Review):
Summary:
In the paper, Yan and her colleagues investigate at which stage of development different categorical signals can be detected with EEG using a steady-state visual evoked potential paradigm. The study reports the development trajectory of selective responses to five categories (i.e., faces, limbs, corridors, characters, and cars) over the first 1.5 years of life. It reveals that while responses to faces show significant early development, responses to other categories (i.e., characters and limbs) develop more gradually and emerge later in infancy. The paper is well-written and enjoyable, and the content is well-motivated and solid.
Strengths:
(1) This study contains a rich dataset with a substantial amount of effort. It covers a large sample of infants across ages (N=45) and asks an interesting question about when visual category representations emerge during the first year of life.
(2) The chosen category stimuli are appropriate and well-controlled. These categories are classic and important for situating the study within a well-established theoretical framework.
(3) The brain measurements are solid. Visual periodicity allows for the dissociation of selective responses to image categories within the same rapid image stream, which appears at different intervals. This is important for the infant field, as it provides a robust measure of ERPs with good interpretability.
Weaknesses:
The study would benefit from a more detailed explanation of analysis choices, limitations, and broader interpretations of the findings. This includes:<br /> a) improving the treatment of bias from specific categories (e.g., faces) towards others;<br /> b) justifying the specific experimental and data analysis choices;<br /> c) expanding the interpretation and discussion of the results.
I believe that giving more attention to these aspects would improve the study and contribute positively to the field.
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Reviewer #1 (Public Review):
This work presents a replicable difference in predictive processing between subjects with and without tinnitus. In two independent MEG studies and using a passive listening paradigm, the authors identify an enhanced prediction score in tinnitus subjects compared to control subjects. In the second study, individuals with and without tinnitus were carefully matched for hearing levels (next to age and sex), increasing the probability that the identified differences could truly be attributed to the presence of tinnitus. Results from the first study could successfully be replicated in the second, although the effect size was notably smaller.
Throughout the manuscript, the authors provide a thoughtful interpretation of their key findings and offer several interesting directions for future studies. Their conclusions are fully supported by their findings. Moreover, the authors are sufficiently aware of the inherent limitations of cross-sectional studies.
Strengths:
The robustness of the identified differences in prediction scores between individuals with and without tinnitus is remarkable, especially as successful replication studies are rare in the tinnitus field. Moreover, the authors provide several plausible explanations for the decline of the effect size observed in the second study.
The rigorous matching for hearing loss, in addition to age and sex, in the second study is an important strength. This ensures that the identified differences cannot be attributed to differences in hearing levels between the groups.
The used methodology is explained clearly and in detail, ensuring that the used paradigms may be employed by other researchers in future studies. Moreover, the registering of the data collection and analysis methods for Study 2 as a Registered Report should be commended, as the authors have clearly adhered to the methods as registered.
Weaknesses:
Although the authors have been careful to match their experimental groups for age, sex, and hearing loss, there are other factors that may confound the current results. For example, subjects with tinnitus might present with psychological comorbidities such as anxiety and depression. The authors' exclusion of distress as a candidate for explaining the found effects is based solely on an assessment of tinnitus-related distress, while it is currently not possible to exclude the effects of elevated anxiety or depression levels on the results. Additionally, as the authors address in the discussion, the presence of hyperacusis may also play a role in predictive processing in this population.
The authors write that sound intensity was individually determined by presenting a short audio sequence to the participants and adjusting the loudness according to an individual pleasant volume. Neural measurements made during listening paradigms might be influenced by sound intensity levels. The intensity levels chosen by the participants might therefore also have an effect on the outcomes. The authors currently do not provide information on the sound intensity levels in the experimental groups, making it impossible to assess whether sound intensity levels might have played a role.
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Reviewer #1 (Public Review):
Summary:
The manuscript by Ozcan et al., presents compelling evidence demonstrating the latent potential of glial precursors of the adult cerebral cortex for neuronal reprogramming. The findings substantially advance our understanding of the potential of endogenous cells in the adult brain to be reprogrammed. Moreover, they describe a molecular cocktail that directs reprogramming toward corticospinal neurons (CSN).
Strengths:
Experimentally, the work is compelling and beautifully designed, with no major caveats. The main conclusions are fully supported by the experiments. The work provides a characterization of endogenous progenitors, genetic strategies to isolate them, and proof of concept of exploiting these progenitors' potential to produce a specific desired neuronal type with "a la carte" combination of transcription factors.
Weaknesses:
Some issues need to be addressed or clarified before publication. The manuscript requires editing. It is dense and rich in details while in other parts there are a few mistakes.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This paper presents a compelling and comprehensive study of decision-making under uncertainty. It addresses a fundamental distinction between belief-based (cognitive neuroscience) formulations of choice behavior with reward-based (behavioral psychology) accounts. Specifically, it asks whether active inference provides a better account of planning and decision making, relative to reinforcement learning. To do this, the authors use a simple but elegant paradigm that includes choices about whether to seek both information and rewards. They then assess the evidence for active inference and reinforcement learning models of choice behavior, respectively. After demonstrating that active inference provides a better explanation of behavioral responses, the neuronal correlates of epistemic and instrumental value (under an optimized active inference model) are characterized using EEG. Significant neuronal correlates of both kinds of value were found in sensor and source space. The source space correlates are then discussed sensibly, in relation to the existing literature on the functional anatomy of perceptual and instrumental decision-making under uncertainty.
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Reviewer #1 (Public Review):
The manuscript by Feng et al. reported that the Endothelin B receptor (ETBR) expressed by the satellite glial cells (SGCs) in the dorsal root ganglions (DRG) acted to inhibit sensory axon regeneration in both adult and aged mice. Thus, pharmacological inhibition of ETBR with specific inhibitors resulted in enhanced sensory axon regeneration in vitro and in vivo. In addition, sensory axon regeneration significantly reduces in aged mice and inhibition of ETBR could restore such defect in aged mice. Moreover, the study provided some evidence that the reduced level of gap junction protein connexin 43 might act downstream of ETBR to suppress axon regeneration in aged mice. Overall, the study revealed an interesting SGC-derived signal in the DRG microenvironment to regulate sensory axon regeneration. It provided additional evidence that non-neuronal cell types in the microenvironment function to regulate axon regeneration via cell-cell interaction.
However, the molecular mechanisms by which ETBR regulates axon regeneration are unclear, and the manuscript's structure is not well organized, especially in the last section. Some discussion and explanation about the data interpretation are needed to improve the manuscript.
(1) The result showed that the level of ETBR did not change after the peripheral nerve injury. Does this mean that its endogenous function is to limit spontaneous sensory axon regeneration? In other words, the results suggest that SGCs expressing ETBR or vascular endothelial cells expressing its ligand ET-1 act to suppress sensory axon regeneration. Some explanation or discussion about this is necessary. Moreover, does the protein level of ETBR or its ligand change during aging?
(2) In ex vivo experiments, NGF was added to the culture medium. Previous studies have shown that adult sensory neurons could initiate fast axon growth in response to NGF within 24 hours. In addition, dissociated sensory neurons could also initiate spontaneous regenerative axon growth without NGF after 48 hours. Some discussion or rationale is needed to explain the difference between NGF-induced or spontaneous axon growth of culture adult sensory neurons and the roles of ETBR and SGCs.
(3) In cultured dissociated sensory neurons, inhibiting ETBR also enhanced axon growth, which meant the presence of SGCs surrounding the sensory neurons. Some direct evidence is needed to show the cellular relationship between them in culture.
(4) In Figure 3, the in vivo regeneration experiments first showed enhanced axon regeneration either 1 day or 3 days after the nerve injury. The study then showed that inhibiting ETBR could enhance sensory axon growth in vitro from uninjured naïve neurons or conditioning lesioned neurons. To my knowledge, in vivo sensory axon regeneration is relatively slow during the first 2 days after the nerve injury and then enters the fast regeneration mode on the 3rd day, representing the conditioning lesion effect in vivo. Some discussion is needed to compare the in vitro and the in vivo model of axon regeneration.
(5) In Figure 5, the study showed that the level of connexin 43 increased after ETBR inhibition in either adult or aged mice, proposing an important role of connexin 43 in mediating the enhancing effect of ETBR inhibition on axon regeneration. However, in the study, there was no direct evidence supporting that ETBR directly regulates connexin 43 expression in SGCs. Moreover, there was no functional evidence that connexin 43 acted downstream of ETBR to regulate axon regeneration.
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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 the 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 it in its current state from drawing unequivocal conclusions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The report describes the control of the activity of the RNA-activated protein kinase, PKR, by the Vaccinia virus K3 protein. Repressive binding of K3 to the kinase prevents phosphorylation of its recognised substrate, EIF2α (the α subunit of the Eukaryotic Initiation Factor 2). The interaction of K3 is probed by saturation mutation within four regions of PKR chosen by modelling the molecules' interaction. They identify K3-resistant PKR variants that recognise that the K3/EIF2α-binding surface of the kinase is malleable. This is reasonably interpreted as indicating the potential adaptability of this antiviral protein to combat viral virulence factors.
Strengths:
This is a well-conducted study that probes the versatility of the antiviral response to escape a viral inhibitor. The experimentation is very diligent, generating and screening a large number of variants to recognise the malleability of residues at the interface between PKR and K3.
Weaknesses:
These are minor. The protein interaction between PKR and K3 has been previously well-explored through phylogenetic and functional analyses and molecular dynamics studies, as well as with more limited site-directed mutational studies using the same experimental assays. Accordingly, these findings largely reinforce what had been established rather than making major discoveries.
There are some presumptions:
It isn't established that the different PKR constructs are expressed equivalently so there is the contingency that this could account for some of the functional differences.
Details about the confirmation of PKR used to model the interaction aren't given so it isn't clear how accurately the model captures the active kinase state. This is important for the interaction with K3/EIF2α.
Not all regions identified to form the interface between PKR and K3 were assessed in the experimentation. It isn't clear why residues between positions 332-358 weren't examined, particularly as this would have made this report more complete than preceding studies of this protein interaction.
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Reviewer #1 (Public Review):
Summary:
Torsekar et al. use a leaf litter decomposition experiment across seasons, and in an aridity gradient, to provide a careful test of the role of different-sized soil invertebrates in shaping the rates of leaf litter decomposition. The authors found that large-sized invertebrates are more active in the summer and small-sized invertebrates in the winter. The summed effects of all invets then translated into similar levels of decomposition across seasons. The system breaks down in hyper-arid sites.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Wang and colleagues identify biallelic variants of DNAH3 in four unrelated Han Chinese infertile men through whole-exome sequencing, which contributes to abnormal sperm flagellar morphology and ultrastructure. To investigate the importance of DNAH3 in male infertility, the authors generated crispant Dnah3 knockout (KO) male mice. They observed that KO mice are also infertile, showing a severe reduction in sperm movement with abnormal IDA (inner dynein arms) and mitochondrion structure. Moreover, nonfunctional DNAH3 expression decreased the expression of IDA-associated proteins in the spermatozoa of patients and KO mice, which are involved in the disruption of sperm motility. Interestingly, the infertility of patients and KO mice is rescued by intracytoplasmic sperm injection (ICSI). Taken together, the authors propose that DNAH3 is a novel pathogenic gene for asthenoterozoospermia and male infertility.
Strengths:
This work investigates the role of DNAH3 in sperm mobility and male infertility. By using gold-standard molecular biology techniques, the authors demonstrate with exquisite resolution the importance of DNAH3 in sperm morphology, showing strong evidence of its role in male infertility. Overall, this is a very interesting, well-written, and appealing article. All aspects of the study design and methods are well described and appropriate to address the main question of the manuscript. The conclusions drawn are consistent with the analyses conducted and supported by the data.
Weaknesses:
The paper is solid, and in its current form, I have not detected relevant weaknesses.
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Reviewer #1 (Public Review):
Summary:
This study uses an online cognitive task to assess how reward and effort are integrated in a motivated decision-making task. In particular the authors were looking to explore how neuropsychiatric symptoms, in particular, apathy and anhedonia, and circadian rhythms affect behavior in this task. Amongst many results, they found that choice bias (the degree to which integrated reward and effort affect decisions) is reduced in individuals with greater neuropsychiatric symptoms, and late chronotypes (being an 'evening person').
Strengths:
The authors recruited participants to perform the cognitive task both in and out of sync with their chronotypes, allowing for the important insight that individuals with late chronotypes show a more reduced choice bias when tested in the morning.<br /> Overall, this is a well-designed and controlled online experimental study. The modelling approach is robust, with care being taken to both perform and explain to the readers the various tests used to ensure the models allow the authors to sufficiently test their hypotheses.
Weaknesses:
This study was not designed to test the interactions of neuropsychiatric symptoms and chronotypes on decision making, and thus can only make preliminary suggestions regarding how symptoms, chronotypes and time-of-assessment interact.
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Reviewer #1 (Public Review):
Summary:
The work in the manuscript utilized patch-clamp techniques to explore the electrophysiological characteristics of VIP interneurons in the early stages of AD using the 3xTg mouse model. The study revealed that VIP interneurons exhibited prolonged action potentials and reduced firing rates. These changes could not be attributed to modifications in input signals or morphological transformations. The authors attributed aberrant VIP activity to the accumulation of beta-amyloid in those interneurons.
The decreased frequency of VIP inhibitory events were associated with no observed changes in excitatory drive to these interneurons. Consequently, heightened activity in the general population of CA1 interneurons was observed during a decision-making task and an object recognition test. In light of these findings, the authors concluded that the altered firing patterns of VIP interneurons may initiate early-stage dysfunction in hippocampal CA1 circuits, potentially influencing the progression of AD pathology.
Strengths:
Overall the work is novel and moves the field of Alzheimer's disease forward in a significant way. The manuscript reports a novel concept of aberrant activity in VIP interneurons during the early stages of AD thus contributing to dysfunctions of the CA1 microcircuit. This results in enhancement of the inhibitory tone on the primary cells of CA1. Thus, the disinhibition by VIP interneurons of Principal Cells is dampened. The manuscript was skillfully composed, the study was of strong scientific rigor featuring well-designed experiments. Necessary controls were present. Both sexes were included.
Major limitations were not adequately addressed in the revised manuscript
(1) The authors attributed aberrant circuit activity to accumulation of "Abeta intracellularly" inside IS-3 cells. That is problematic. 6E10 antibody recognizes amyloid plaques in addition to Amyloid Precursor Protein (APP) as well as the C99 fragment. There are no plaques at the ages 3xTg mice were examined. Lack of plaques was addressed in revised manuscript. The staining shown in Fig. 1a is of APP/C99 inside neurons, not abeta accumulations in neurons. At the ages of 3-6 months, 3xTg mice start producing and releasing extracellular abeta oligomers and potentially tau oligomers as well (Takeda et al., 2013 PMID: 23640054; Takeda et al., 2015 PMID: 26458742 and others). Emerging literature suggests that extracellular not intracellular abeta and tau oligomers disrupt circuit function. Thus, a more likely explanation of extracellular abeta and tau oligomers disrupting the activity of VIP neurons is plausible. Presence of intracellular abeta is currently controversial in the field and needs to be discussed as such. Some of the references added in the revised version of the manuscript are erroneously cited. The authors provide no original data in support of "intracellular" abeta.
(2) Authors suggest that their animals do not exhibit loss of synaptic connections and show Fig. 3d in support of that suggestion. However, imaging with confocal microscopy of 70 micron thick sections would not allow resolution of pre- and post-synaptic terminals. More sensitive measures such as electron microscopy or array tomography are the appropriate techniques to pursue. It is important for the authors to either remove that data from the manuscript or address/discuss the limitations of their technique in the discussion section. There is a possibility of loss of synaptic connections in their mouse model at the ages examined. Discussion of that possibility and of the limitations of the methodology used is missing.
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Reviewer #1 (Public Review):
In this study, the authors address a fundamental unresolved question in cerebellar physiology: do synapses between granule cells (GCs) and Purkinje cells (PCs) made by the ascending part of the axon (AA) have different synaptic properties to those made by parallel fibers? This is an important question because GCs integrate sensorimotor information from many brain areas with a precise and complex topography.
The authors argue that GCs located close to the PCs essentially contact PC dendrites through the ascending part of their axon. They demonstrate that high-frequency (100 Hz) joint stimulation of distant parallel fibers and local GCs potentiates AA-PC synapses, while parallel fiber-PC synapses are depressed. On the basis of paired pulse ratio analysis, they concluded that evoked plasticity was postsynaptic. When individual pathways are stimulated alone, no LTP is observed. This associative plasticity appears to be sensitive to timing, as stimulation of parallel fibers first results in depression, while stimulation of the AA pathway has no effect. NMDA, mGluR1 and GABAA receptors are involved in this plasticity.
Overall, associative modulation of synaptic transmission is convincing, and the experiments carried out support this conclusion.
One of its weaknesses is that it contradicts the numerous experiments conducted by many groups that have studied plasticity at this connection (e.g. Bouvier et al 2016, Piochon et al 2016, Binda et al, 2016, Schonewille et al 2021). According to the literature, high-frequency stimulation of parallel fibers leads to postsynaptic potentiation under many different experimental conditions (blocked or unblocked inhibition, stimulation protocols, internal solution composition). This discrepancy was not investigated experimentally.
Another weakness is the lack of evidence that AAs have been stimulated. Indeed, without filling the PC with fluorescent dye or biocytin during the experiment, and without reconstructing the anatomical organization, it is difficult to assess whether the stimulating pipette is actually positioned in the GC cluster that potentially contacts the PC with AAs. Although the idea that AAs repeatedly contact the same Purkinje cell has been propagated, to the reviewer's knowledge, no direct demonstration of this hypothesis has yet been published. In fact, what has been demonstrated (Walter et al 2009; Spaeth et al 2022) is that GCs have a higher probability of being connected to nearby PCs, but not necessarily associated with AAs.
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Reviewer #1 (Public Review):
Summary:
Heer and Sheffield used 2 photon imaging to dissect the functional contributions of convergent dopamine and noradrenaline inputs to the dorsal hippocampus CA1 in head restrained mice running down a virtual linear path. Mice were trained to collect water reward at the end of the track and on test days, calcium activity was recorded from dopamine (DA) axons originating in ventral tegmental area (VTA, n=7) and noradrenaline axons from the locus coeruleus (LC, n=87) under several conditions. When mice ran laps in a familiar environment, VTA DA axons exhibited ramping activity along the track that correlated with distance to reward and velocity to some extent, while LC input activity remained constant across the track, but correlated invariantly with velocity and time to motion onset. A subset of recordings taken when the reward was removed showed diminished ramping activity in VTA DA axons, but no changes in the LC axons, confirming that DA axon activity is locked to reward availability. When mice were subsequently introduced to a new environment, the ramping to reward activity in the DA axons disappeared, while LC axons showed a dramatic increase in activity lasting 90s (6 laps) following the environment switch. In the final analysis, the authors sought to disentangle LC axon activity induced by novelty vs. behavioral changes induced by novelty by removing periods in which animals were immobile, and established that the activity observed in the first 2 laps reflected novelty-induced signal in LC axons.
The revised manuscript included additional evidence of increased (but transient) signal in LC axons after a transition to a novel environment during periods of immobility, and also that a change from dark to familiar environment induces a peak in LC axon activity, showing that LC input to dCA1 may not solely signal novelty.
Strengths:
The results presented in this manuscript provide insights into the specific contributions of catecholaminergic input to the dorsal hippocampus CA1 during spatial navigation in a rewarded virtual environment, offering a detailed analysis at the resolution of single axons. The data analysis is thorough and possible confounding variables and data interpretation are carefully considered.
Weaknesses:
Aspects of the methodology, data analysis, and interpretation diminish the overall significance of the findings, as detailed below.
The LC axonal recordings are well powered, but the DA axonal recordings are severely underpowered, with recordings taken from a mere 7 axons (compare to 87 LC axons). Additionally, 2 different calcium indicators with differential kinetics and sensitivity to calcium changes (GCaMP6S and GCaMP7b) were used (n=3, n=4 respectively) and the data pooled. This makes it very challenging to draw any valid conclusions from the data, particularly in the novelty experiment. The surprising lack of novelty-induced DA axon activity may be a false negative. Indeed, at least 1 axon (axon 2) appears to be showing novelty-induced rise in activity in Figure 3C. Changes in activity in 4/7 axons are also referred to as a 'majority' occurrence in the manuscript, which again is not an accurate representation of the observed data
The authors conducted analysis on recording data exclusively from periods of running in the novelty experiment to isolate the effects of novelty from novelty-induced changes in behavior. However, if the goal is to distinguish between changes in locus coeruleus (LC) axon activity induced by novelty and those induced by motion, analyzing LC axon activity during periods of immobility would enhance the robustness of the results.
The authors attribute the ramping activity of the DA axons to the encoding of the animals' position relative to reward. However, given the extensive data implicating the dorsal CA1 in timing, and the remarkable periodicity of the behavior, the fact that DA axons could be signalling temporal information should be considered.
The authors should explain and justify the use of a longer linear track (3m, as opposed to 2m in the DAT-cre mice) in the LC axon recording experiments.
AFTER REVISIONS:
The authors have addressed my concerns in a thorough manner. The reviewer also appreciates the increased transparency of reporting in the revised manuscript.
Listed below are some remaining comments.<br /> The increase in LC activity with any change in environment (from familiar to novel or from dark to familiar) suggests that LC input acts not solely as a novelty signal, but as a general arousal or salience signal in response to environmental changes. Based on this, I have a couple of questions:
• Is the overall claim that LC input to the dHC signals novelty still valid based on observed findings - as claimed throughout the manuscript?<br /> • Would the omission of a reward be considered a salient change in the environment that activates LC signals, or is the LC not involved with processing reward-related information? Has the activity of LC and VTA axons been analysed in the seconds following reward presentation and/or omission?
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Reviewer #1 (Public Review):
Summary:<br /> Du et al. report 16 new well-preserved specimens of atiopodan arthropods from the Chengjiang biota, which demonstrate both dosal and vental anatomies of a pothential new taxon of atiopodans that are closely related to trolobites. Authors assigned their specimens to Acanthomeridion serratum, and proposed A. anacanthus as a junior subjective synonym of Acanthomeridion serratum. Critially, the presence of ventral plates (interpreted as cephalic liberigenae), together with phylogenic results, lead authors to conclude that the cephalic sutures originated multiple times within the Artiopoda.
Strengths:<br /> New specimens are highly qualified and informative. The morphology of dorsal exoskeleton, except for the supposed free cheek, were well illustrated and described in detail, which provide a wealth of information for taxonmic and phylogenic analyses.
Weaknesses:<br /> The weaknesses of this work is obvious in a number of aspects. Technically, ventral morphlogy is less well revealed and is poorly illustrated. Additional diagrams are necessary to show the trunk appendages and suture lines. Taxonomically, I am not convinced by authors' placement. The specimens are markedly different from either Acanthomeridion serratum Hou et al. 1989 or A. anacanthus Hou et al. 2017. The ontogenetic description is extremely weak and the morpholical continuity is not established. Geometric and morphomitric analyses might be helpful to resolve the taxonomic and ontogenic uncertainties. I am confused by author's description of free cheek (libragena) and ventral plate. Are they the same object? How do they connect with other parts of cephalic shield, e.g. hypostome and fixgena. Critically, homology of cephalic slits (eye slits, eye notch, doral suture, facial suture) not extensivlely discussed either morphologically or functionally. Finally, authors claimed that phylogenic results support two separate origins rather than a deep origin. However, the results in Figure 4 can be explain a deep homology of cephalic suture in molecular level and multiple co-options within the Atiopoda.
Comments on the revised version:
I have seen the extensive revision of the manuscript. The main point "Multiple origins of dorsal ecdysial sutures in atiopoans" is now partially supported by results presented by the authors. I am still unsatisfied with descriptions and interpretations of critical features newly revealed by authors. The following points might be useful for the author to make further revisions.
(1) The antennae were well illustrated in a couple of specimens, while it was described in a short sentence.<br /> (2) There are also imprecise descriptions of features.<br /> (3) Ontogeny of the cephalon was not described.<br /> (3) The critical head element is the so called "ventral plate". How this element connects with the cephalic shield is not adequately revealed. The authors claimed that the suture is along the cephalic margin. However, the lateral margin of cephalon is not rounded but exhibit two notches (e.g. Fig 3C) . This gives an indication that the supposed ventral plates have a dorsal extension to fit the notches. Alternatively, the "ventral plate" can be interpreted as a small free cheek with a large ventral extension, providing evidence for librigenal hypothesis.
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Reviewer #1 (Public Review):
In this paper the authors provide a characterisation of auditory responses (tones, noise, and amplitude modulated sounds) and bimodal (somatosensory-auditory) responses and interactions in the higher order lateral cortex (LC) of the inferior colliculus (IC) and compare these characteristic with the higher order dorsal cortex (DC) of the IC - in awake and anaesthetised mice. Dan Llano's group have previously identified gaba'ergic patches (modules) in the LC distinctly receiving inputs from somatosensory structures, surrounded by matrix regions receiving inputs from auditory cortex. They here use 2P calcium imaging combined with an implanted prism to - for the first time - get functional optical access to these subregions (modules and matrix) in the lateral cortex of IC in vivo, in order to also characterise the functional difference in these subparts of LC. They find that both DC and LC of both awake and anaesthetised appears to be more responsive to more complex sounds (amplitude modulated noise) compared to pure tones and that under anesthesia the matrix of LC is more modulated by specific frequency and temporal content compared to the gaba'ergic modules in LC. However, while both LC and DC appears to have low frequency preferences, this preference for low frequencies is more pronounced in DC. Furthermore, in both awake and anesthetized mice somatosensory inputs are capable of driving responses on its own in the modules of LC, but very little in the matrix. The authors now compare bimodal interactions under anaesthesia and awake states and find that effects are different in some cases under awake and anesthesia - particularly related to bimodal suppression and enhancement in the modules.
The paper provides new information about how subregions with different inputs and neurochemical profiles in the higher order auditory midbrain process auditory and multisensory information, and is useful for the auditory and multisensory circuits neuroscience community.
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Reviewer #2 (Public Review):
Ma X. et al proposed that A. muciniphila was a key strain that promotes the proliferation and differentiation of intestinal stem cells through acting on the Wnt/b-catenin signaling pathway. They used various models, such as piglet model, mouse model and intestinal organoids to address how A. muciniphila and B. fragilis offer the protection against ETEC infection. They showed that FMT with fecal samples, A. muciniphila or B. fragilis protected piglets and/or mice from ETEC infection, and this protection is manifested as reduced intestinal inflammation/bacterial colonization, increased tight junction/Muc2 proteins, as well as proper Treg/Th17 cells. Additionally, they demonstrated that A. muciniphila protected basal-out and/or apical-out intestinal organoids against ETEC infection via Wnt signaling.
Comments on revised version:
Please add proper references to indicate the invasion of ETEC into organoids after 1 h of infection.
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Reviewer #1 (Public Review):
Summary:
The authors originally investigated the function of p53 isoforms with an alternative C-terminus encoded by the Alternatively Spliced (AS) exon in place of exon 11 encoding the canonical "α" C-terminal domain. For this purpose, the authors create a mouse model with a specific deletion of the AS exon.
Strengths:
Interestingly, wt or p53ΔAS/ΔAS mouse embryonic fibroblasts did not differ in cell cycle control, expression of well-known p53 target genes, proliferation under hyperoxic conditions, or the growth of tumor xenografts. However, p53-AS isoforms were shown to confer male-specific protection against lymphomagenesis in Eμ-Myc transgenic mice, prone to highly penetrant B-cell lymphomas. In fact, p53ΔAS/ΔAS Eμ-Myc mice were less protected from developing B-cell lymphomas compared to WT counterparts. The important difference that the authors find between WT and p53ΔAS/ΔAS Eμ-Myc males is a higher number of immature B cells in p53ΔAS/ΔAS vs WT mice. Higher expression of Ackr4 and lower expression of Mt2 was found in p53+/+ Eμ-Myc males compared to p53ΔAS/ΔAS counterparts, suggesting that these two transcripts are in part regulators of B-cell lymphomagenesis and enrichment for immature B cells.
The manuscript integrates an elegant genetic approach with in vivo analyses providing a robust set of data which strengthens the role of p53 isoforms in leukemogenesis.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary
This article delves into the role of Ecdysone in regulating female sexual receptivity in Drosophila. The researchers discovered that PTTH, a positive regulator of Ecdysone production, hurts the receptivity of adult virgin females. Specifically, the researchers found that losing larval PTTH before metamorphosis significantly increases female receptivity immediately after adult eclosion. In addition, Ecdysone, through its receptor EcR-A, is necessary during metamorphic neurodevelopment for the proper development of P1 neurons, as its silencing leads to morphological changes associated with reduced adult female receptivity. Furthermore, Torso enhances receptivity in the adult stage. The molecular mechanisms linking each molecule to female receptivity have yet to be fully understood; therefore, the involvement of the juvenile-to-adult hormonal pathway (PTTH/Torso/ecdysone) in female receptivity is not proven.
Strengths
(1) Robust Methodology and Experimental Design: The study employs a comprehensive and well-structured experimental approach, combining genetic manipulations, behavioral assays, and molecular analyses. This multi-faceted methodology allows for a thorough investigation of the role of PTTH and Ecdysone in regulating female sexual receptivity in Drosophila. The use of specific gene knockouts, RNA interference, and overexpression techniques provides strong evidence supporting the findings.<br /> (2) Clear and Substantial Findings: The authors provide compelling data showing that PTTH negatively regulates female receptivity during the larval stage, which is rescued by Ecdysone feeding. Instead, metamorphic Ecdysone has a positive role during neurodevelopment. The experiments demonstrate this dual and temporally distinct role of PTTH/Ecdysone, shedding light on a complex hormonal regulation mechanism.<br /> (3) Clarification of Experimental Details: In response to the initial review, the authors have clarified important experimental details, such as the precise timing of genetic manipulations and the specific developmental stages examined. This clarification enhances the reproducibility and understanding of the study.
Weaknesses
(1) Unresolved Contradictions and Complexity in Results: Despite the detailed responses, the paper still presents complex and somewhat contradictory findings regarding the roles of PTTH, Torso, and Ecdysone. The observed increase in EcR-A expression in PTTH mutants and the nuanced explanation regarding the feedforward relationship, while insightful, do not fully resolve the initial confusion about the differing effects of PTTH and Ecdysone manipulations on female receptivity. This required more exploration.<br /> (2) Insufficient Exploration of Mechanistic Pathways: The potential mechanisms underlying the role of PTTH/Torso-Ecdysone across different developmental stages remain underexplored. While the authors suggest a feedforward relationship and possible interaction with other neurons, these hypotheses are not thoroughly tested or elaborated upon, leaving gaps in the mechanistic understanding.<br /> (3) Limited Scope of Validation Experiments: While the authors addressed some reviewer concerns about validation, the scope remains somewhat limited. The lack of existing PTTH mutants and the challenges in manipulating PTTH expression without affecting receptivity suggests that further work is needed to validate these pathways robustly. The inability to fully replicate the PTTHdelete phenotype through other means leaves some questions unanswered.<br /> (4). Complexity in Interpretation of dsx-Positive Neurons: The relevance of dsx-positive neurons in the context of PTTH's effects on female receptivity remains ambiguous. Although the authors provide some context, the biological significance of these observations is not fully clarified.
Conclusion<br /> The manuscript presents a well-conceived study with significant findings that advance the understanding of hormonal regulation of female receptivity in Drosophila. However, complexities in the data and unresolved mechanistic questions suggest that further work is needed to clarify the exact pathways and interactions involved. The authors' responses to feedback have strengthened the paper, but additional experiments and more thorough mechanistic exploration would enhance the robustness and clarity of the conclusions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Willems and colleagues test whether unexpected shock omissions are associated with reward-related prediction errors by using an axiomatic approach to investigate brain activation in response to unexpected shock omission. Using an elegant design that parametrically varies shock expectancy through verbal instructions, they see a variety of responses in reward-related networks, only some of which adhere to the axioms necessary for prediction error. In addition, there were associations between omission-related responses and subjective relief. They also use machine learning to predict relief-related pleasantness and find that none of the a priori "reward" regions were predictive of relief, which is an interesting finding that can be validated and pursued in future work.
Strengths:
The authors pre-registered their approach and the analyses are sound. In particular, the axiomatic approach tests whether a given region can truly be called a reward prediction error. Although several a priori regions of interest satisfied a subset of axioms, no ROI satisfied all three axioms, and the authors were candid about this. A second strength was their use of machine learning to identify a relief-related classifier. Interestingly, none of the ROIs that have been traditionally implicated in reward prediction error reliably predicted relief, which opens important questions for future research.
Weaknesses:
The authors have done many analyses to address weaknesses in response to reviews. I will still note that given that one third of participants (n=10) did not show parametric SCR in response to instructions, it seems like some learning did occur. As prediction error is so important to such learning, a weakness of the paper is that conclusions about prediction error might differ if dynamic learning were taken into account using quantitative models.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Winged seeds or ovules from the Devonian are crucial to understanding the origin and early evolutionary history of wind dispersal strategy. Based on exceptionally well-preserved fossil specimens, the present manuscript documented a new fossil plant taxon (new genus and new species) from the Famennian Series of Upper Devonian in eastern China and demonstrated that three-winged seeds are more adapted to wind dispersal than one-, two- and four-winged seeds by using mathematical analysis.
Strengths:
The manuscript is well organised and well presented, with superb illustrations. The methods used in the manuscript are appropriate.
Weaknesses:
I would only like to suggest moving the "Mathematical analysis of wind dispersal of ovules with 1-4 wings" section from the supplementary information to the main text, leaving the supplementary figures as supplementary materials.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> Medina-Feliciano et al. investigated the single cell transcriptomic profile of holoturian regenerating intestine following evisceration, a process used to expel their viscera in response to predation. Using single cell RNA-sequencing and standard analysis such as "Find cluster markers", "Enrichment analysis of Gene Ontology" and "RNA velocity", they identify 13 cell clusters and potential identity. Based merely on bioinformatic analysis they identified potentially proliferating clusters and potential trajectories of cell differentiation. This manuscript represents a useful dataset that can provide candidate cell types and cell markers for more in-depth functional analysis for gaining a better understanding of the holoturian intestine regeneration. The conclusions of this paper are supported only by bioinformatic analyses, since the in vivo validation through HCR does not sufficiently support them.
Strengths:<br /> - The Authors are providing a single cell dataset obtained from sea cucumber regenerating their intestine. This represents a first fundamental step to an unbiased approach to better understand this regeneration process and the cellular dynamics taking part in it.<br /> - The Authors run all the standard analyses providing the reader with a well digested set of information about cell clusters, potential cell types, potential functions and potential cell differentiation trajectories.
Weaknesses:<br /> - The entire study is based on only 2 adult animals, that were used for both the single cell dataset and the HCR. Additionally, the animals were caught from the ocean preventing information about their age or their life history. This makes the n extremely small and reduces the confidence of the conclusions.<br /> - All the fluorescent pictures present in this manuscript present red nuclei and green signals being not color-blind friendly. Additionally, many of the images lack sufficient quality to determine if the signal is real. Additional images of a control animal (not eviscerated) and of a negative control would help data interpretation. Finally, in many occasions a zoomed out image would help the reader to provide context and have a better understanding of where the signal is localized.<br /> - The Authors frequently report the percentage of cells with a specific feature (either labelled or expressing a certain gene or belonging to a certain cluster). This number can be misleading since that is calculated after cell dissociation and additional procedures (such as staining or sequencing and dataset cleanup) that can heavily bias the ratio between cell types. Similarly, the Authors cannot compare cell percentage between anlage and mesentery samples since that can be affected by technical aspects related to cell dissociation, tissue composition and sequencing depth.<br /> - The Authors decided to validate only a few clusters and in many cases there are no positive controls (such as specific localization, specific function, changes between control and regenerating animals, co-stain) that could actually validate the cluster identity and the specificity of the selected marker. There is no validation of the trajectory analysis and there is no validation of the proliferating cluster with H3P or BrdU stainings.<br /> - It is not clear what is already known about holothurian intestine regeneration and what are the new findings in this manuscript. The Authors reference several papers throughout the whole result sectioning mentioning how the steps of regeneration, the proliferating cells, some of the markers and some of the cell composition of mesenteries and anlages was already known.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Dalal and Haddad investigated how neurons in the olfactory bulb are synchronized in oscillatory rhythms at gamma frequency. Temporal coordination of action potentials fired by projection neurons can facilitate information transmission to downstream areas. In a previous paper (Dalal and Haddad 2022, https://doi.org/10.1016/j.celrep.2022.110693), the authors showed that gamma frequency synchronization of mitral/tufted cells (MTCs) in the olfactory bulb enhances the response in the piriform cortex. The present study builds on these findings and takes a closer look at how gamma synchronization is restricted to a specific subset of MTCs in the olfactory bulb. They combined odor and optogenetic stimulations in anesthetized mice with extracellular recordings.<br /> The main findings are that lateral synchronization of MTCs at gamma frequency is mediated by granule cells (GCs), independent of the spatial distance, and strongest for MTCs with firing rates close to 40 Hz. The authors conclude that this reveals a simple mechanism by which spatially distributed neurons can form a synchronized ensemble. In contrast to lateral synchronization, they found no evidence for the involvement of GCs in lateral inhibition of nearby MTCs.
Strengths:
Investigating the mechanisms of rhythmic synchronization in vivo is difficult because of experimental limitations for the readout and manipulation of neuronal populations at fast timescales. Using spatially patterned light stimulation of opsin-expressing neurons in combination with extracellular recordings is a nice approach. The paper provides evidence for an activity-dependent synchronization of MTCs in gamma frequency that is mediated by GCs.
Weaknesses:
An important weakness of the study is the lack of direct evidence for the main conclusion - the synchronization of MTCs in gamma frequency. The data shows that paired optogenetic stimulation of MTCs in different parts of the olfactory bulb increases the rhythmicity of individual MTCs (Figure 1) and that combined odor stimulation and GC stimulation increases rhythmicity and gamma phase locking of individual MTCs (Figure 4). However, a direct comparison of the firing of different MTCs is missing. This could be addressed with extracellular recordings at two different locations in the olfactory bulb. The minimum requirement to support this conclusion would be to show that the MTCs lock to the same phase of the gamma cycle. Also, showing the evoked gamma oscillations would help to interpret the data.
Another weakness is that all experiments are performed under anesthesia with ketamine/medetomidine. Ketamine is an antagonist of NMDA receptors and NMDA receptors are critically involved in the interactions of MTCs and GCs at the reciprocal synapses (see for example Lage-Rupprecht et al. 2020, https://doi.org/10.7554/eLife.63737; Egger and Kuner 2021, https://doi.org/10.1007/s00441-020-03402-7). This should be considered for the interpretation of the presented data.
Furthermore, the direct effect of optogenetic stimulation on GCs activity is not shown. This is particularly important because they use Gad2-cre mice with virus injection in the olfactory bulb and expression might not be restricted to granule cells and might not target all subtypes of granule cells (Wachowiak et al., 2013, https://doi.org/10.1523/JNEUROSCI.4824-12.2013). This should be considered for the interpretation of the data, particularly for the absence of an effect of GC stimulation on lateral inhibition.
Several conclusions are only supported by data from example neurons. The paper would benefit from a more detailed description of the analysis and the display of some additional analysis at the population level:
- What were the criteria based on which the spots for light-activation were chosen from the receptive field map?
- The absence of an effect on firing rate for paired stimulations is only shown for one example (Figure 1c). A quantification of the population level would be interesting.
- Only one example neuron is shown to support the conclusion that "two different neural circuits mediate suppression and entrainment" in Figure 3. A population analysis would provide more evidence.
- Only one example neuron is shown to illustrate the effect of GC stimulation on gamma rhythmicity of MTCs in Figures 4 f,g.
- In Figure 5 and the corresponding text, "proximal" and "distal" GC activation are not clearly defined.
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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.
(1) It would be important for the authors to show if the findings of this study hold for metastatic cancers since most deaths occur due to metastasis and tumor heterogeneity changes when cancer progresses to metastasis. The authors should use the Hartwig data and show if metastatic cancers are enriched for 3'UTR mutations.
(2) Figure 2 should show the distribution of 3'UTR mutations by cancer type especially since authors go on to use colorectal cancer only for validations. It would be helpful to bring Figures S3A and S3C to this panel since these findings make the connections to cancer biology. Are any molecular functions enriched in addition to biological processes? Are kinases, phosphatases, etc more or less affected by 3'UTR mutations?
(3) Figure 3 looks at the co-occurrence of 3'UTR mutations with non-synonymous mutations but what about copy number change? You would expect the loss of the other allele to be enriched. Along the same line, are these data phased? Do you know that the non-synonymous mutations are in the other allele or in the same allele that shows 3'UTR mutation?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study investigated the mechanism underlying Congenital NAD Deficiency Disorder (CNDD) using a mouse model with loss of function of the HAAO enzyme which mediates a key step in the NAD de novo synthesis pathway. This study builds on the observation that the kynurenine pathway is required in the conceptus, as HAAO null embryos are sensitive to maternal deficiency of NAD precursors (vitamin B3) and tryptophan, and narrows the window of sensitivity to a 3-day period.
An important finding is that de novo NAD synthesis occurs in an extra-embryonic tissue, the visceral yolk sac, before the liver develops in the embryo. It is suggested that lack of this yolk sac activity leads to impaired NAD supply in the embryo leading to structural abnormalities found later in development.
Strengths:
Previous studies show a requirement for HAAO activity for the normal development of embryos. Abnormalities develop under conditions of maternal vitamin B3 deficiency, indicating a requirement for NAD synthesis in the conceptus. Analysis of scRNA-seq datasets combined with metabolite analysis of yolk sac tissue shows that the NAD synthesis pathway is expressed and functional in the yolk sac from E10.5 onwards (prior to liver development).
HAAO enzyme assay enabled quantification of enzyme activity in relevant tissues including the liver (from E12.5), placenta, and yolk sac (from E11.5).
Comprehensive metabolite analysis of the NAD synthesis pathway supports the predicted effects of Haao knockout and provides analysis of the yolk sac, placenta, and embryo at a series of stages.
The dietary study (with lower vitamin B3 in maternal diet from E7.5-10.5) is an incremental addition to previous studies that imposed similar restrictions from E7.5-12.5.
Nevertheless, this emphasises the importance of the synthesis pathway on the conceptus at stages before the liver activity is prominent.
Weaknesses:
The current dietary study narrows the period when deficiency can cause malformations (analysed at E18.5), and altered metabolite profiles (eg, increased 3HAA, lower NAD) are detected in the yolk sac and embryo at E10.5. However, without analysis of embryos at later stages in this experiment it is not known how long is needed for NAD synthesis to be recovered - and therefore until when the period of exposure to insufficient NAD lasts. This information would inform the understanding of the developmental origin of the observed defects.
More importantly, there is still a question of whether in addition to the yolk sac, there is HAAO activity within the embryo itself prior to E12.5 (when it has first been assayed in the liver - Figure 1C). The prediction is that within the conceptus (embryo, chorioallantoic placenta, and visceral yok sac) the embryo is unlikely to be the site of NAD synthesis prior to liver development. Reanalysis of scRNA-seq (Fig 1B) shows expression of all the enzymes of the kynurenine pathway from E9.5 onwards. However, the expression of another available dataset at E10.5 (Fig S3) suggested that expression is 'negligible'. While the expression in Figure 1B, Figure S1 is weak this creates a lack of clarity about the possible expression of HAAO in the hepatocyte lineage, or especially elsewhere in the embryo prior to E10.5 (corresponding to the period when the authors have demonstrated that de novo NAD synthesis in the conceptus is needed). Given these questions, a direct analysis of RNA and/or protein expression in the embryos at E7.5-10.5 would be helpful.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors aim to measure the apoptotic fraction of motorneurons in developing zebrafish spinal cord to assess the extent of neuronal apoptosis during the development of a vertebrate embryo in an in vivo context.
Strengths:
The transgenic fish line tg (mnx1:sensor C3) appears to be a good reagent for motorneuron apoptosis studies, while further validation of its motorneuron specificity should be performed.
Weaknesses:
The results do not support the conclusions. The main "selling point" as summarized in the title is that the apoptotic rate of zebrafish motorneurons during development is strikingly low (~2% ) as compared to the much higher estimate (~50%) by previous studies in other systems. The results used to support the conclusion are that only a small percentage (under 2%) of apoptotic cells were found over a large population at a variety of stages 24-120hpf. This is fundamentally flawed logic, as a short-time window measure of percentage cannot represent the percentage in the long term. For example, at any year under 1% of the human population dies, but over 100 years >99% of the starting group will have died. To find the real percentage of motorneurons that died, the motorneurons born at different times must be tracked over the long term or the new motorneuron birth rate must be estimated.
A similar argument can be applied to the macrophage results. Here the authors probably want to discuss well-established mechanisms of apoptotic neuron clearance such as by glia and microglia cells.
The conclusion regarding the timing of axon and cell body caspase activation and apoptosis timing also has clear issues. The ~minutes measurement is too long as compared to the transport/diffusion timescale between the cell body and the axon, caspase activity could have been activated in the cell body, and either caspase or the cleaved sensor moves to the axon in several seconds. The authors' results are not high-frequency enough to resolve these dynamics
Many statements suggest oversight of literature, for example, in the abstract "However, there is still no real-time observation showing this dying process in live animals.".
Many statements should use more scholarly terms and descriptions from the spinal cord or motor neuron, neuromuscular development fields, such as line 87 "their axons converged into one bundle to extend into individual somite, which serves as a functional unit for the development and contraction of muscle cells"
The transgenic line is perhaps the most meaningful contribution to the field as the work stands. However, the mnx1 promoter is well known for its non-specific activation - while the images suggest the authors' line is good, motor neuron markers should be used to validate the line. This is especially important for assessing this population later as mnx1 may be turned off in mature neurons.
Overall, this work does not substantiate its biological conclusions and therefore does not advance the field. The transgenic line has the potential to address the questions raised but requires different sets of experiments. The line and the data as reported are useful on their own by providing a short-term rate of apoptosis of the motorneuron population.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Shao et al. investigate the contribution of different cortical areas to working memory maintenance and control processes, an important topic involving different ideas about how the human brain represents and uses information when it is no longer available to sensory systems. In two fMRI experiments, they demonstrate that the human frontal cortex (area sPCS) represents stimulus (orientation) information both during typical maintenance, but even more so when a categorical response demand is present. That is, when participants have to apply an added level of decision control to the WM stimulus, sPCS areas encode stimulus information more than conditions without this added demand. These effects are then expanded upon using multi-area neural network models, recapitulating the empirical gradient of memory vs control effects from visual to parietal and frontal cortices. In general, the experiments and analyses provide solid support for the authors' conclusions, and control experiments and analyses are provided to help interpret and isolate the frontal cortex effect of interest. However, I suggest some alternative explanations and important additional analyses that would help ensure an even stronger level of support for these results and interpretations.
Strengths:
- The authors use an interesting and clever task design across two fMRI experiments that is able to parse out contributions of WM maintenance alone along with categorical, rule-based decisions. Importantly, the second experiment only uses one fixed rule, providing both an internal replication of Experiment 1's effects and extending them to a different situation when rule-switching effects are not involved across mini-blocks.
- The reported analyses using both inverted encoding models (IEM) and decoders (SVM) demonstrate the stimulus reconstruction effects across different methods, which may be sensitive to different aspects of the relationship between patterns of brain activity and the experimental stimuli.
- Linking the multivariate activity patterns to memory behavior is critical in thinking about the potential differential roles of cortical areas in sub-serving successful working memory. Figure 3 nicely shows a similar interaction to that of Figure 2 in the role of sPCS in the categorization vs. maintenance tasks.
- The cross-decoding analysis in Figure 4 is a clever and interesting way to parse out how stimulus and rule/category information may be intertwined, which would have been one of the foremost potential questions or analyses requested by careful readers. However, I think more additional text in the Methods and Results to lay out the exact logic of this abstract category metric will help readers better interpret the potential importance of this analysis and result.
Weaknesses:
- Selection and presentation of regions of interest: I appreciate the authors' care in separating the sPCS region as "frontal cortex", which is not necessarily part of the prefrontal cortex, on which many ideas of working memory maintenance activity are based. However, to help myself and readers interpret these findings, at a minimum the boundaries of each ROI should be provided as part of the main text or extended data figures. Relatedly, the authors use a probabilistic visual atlas to define ROIs in the visual, parietal, and frontal cortices. But other regions of both lateral frontal and parietal cortices show retinotopic responses (Mackey and Curtis, eLife, 2017: https://elifesciences.org/articles/22974) and are perhaps worth considering. Do the inferior PCS regions or inferior frontal sulcus show a similar pattern of effects across tasks? And what about the middle frontal gyrus areas of the prefrontal cortex, which are most analogous to the findings in NHP studies that the authors mention in their discussion, but do not show retinotopic responses? Reporting the effects (or lack thereof) in other areas of the frontal cortex will be critical for readers to interpret the role of the frontal cortex in guiding WM behavior and supporting the strongly worded conclusions of broad frontal cortex functioning in the paper. For example, to what extent can sPCS results be explained by visual retinotopic responses? (Mackey and Curtis, eLife, 2017: https://elifesciences.org/articles/22974).
- When looking at the time course of effects in Figure 2, for example, the sPCS maintenance vs categorization effects occur very late into the WM delay period. More information is needed to help separate this potential effect from that of the response period and potential premotor/motor-related influences. For example, are the timecourses shifted to account for hemodynamic lag, and if so, by how much? Do the sPCS effects blend into the response period? This is critical, too, for a task that does not use a jittered delay period, and potential response timing and planning can be conducted by participants near the end of the WM delay. For example, the authors say that " significant stimulus representation in EVC even when memoranda had been transformed into a motor format (24)". But, I *think* this paper shows the exact opposite interpretation - EVC stimulus information is only detectable when a motor response *cannot* be planned (https://elifesciences.org/articles/75688). Regardless, parsing out the timing and relationship to response planning is important, and an ROI for M1 or premotor cortex could also help as a control comparison point, as in reference (24).
- Interpreting effect sizes of IEM and decoding analysis in different ROIs. Here, the authors are interested in the interaction effects across maintenance and categorization tasks (bar plots in Figure 2), but the effect sizes in even the categorization task (y-axes) are always larger in EVC and IPS than in the sPCS region... To what extent do the authors think this representational fidelity result can or cannot be compared across regions? For example, a reader may wonder how much the sPCS representation matters for the task, perhaps, if memory access is always there in EVC and IPS? Or perhaps late sPCS representations are borrowing/accessing these earlier representations? Giving the reader some more intuition for the effect sizes of representational fidelity will be important. Even in Figure 3 for the behavior, all effects are also seen in IPS as well. More detail or context at minimum is needed about the representational fidelity metric, which is cited in ref (35) but not given in detail. These considerations are important given the claims of the frontal cortex serving such an important for flexible control, here.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
The authors report the results of a randomized clinical trial of taVNS as a neuromodulation technique in SAH patients. They found that taVNS appears to be safe without inducing bradycardia or QT prolongation. taVNS also increased parasympathetic activity, as assessed by heart rate variability measures. Acute elevation in heart rate might be a biomarker to identify SAH patients who are likely to respond favorably to taVNS treatment. The latter is very important in light of the need for acute biomarkers of response to neuromodulation treatments.
Comments:
(1) Frequency domain heart rate variability measures should be analyzed and reported. Given the short duration of the ECG recording, the frequency domain may more accurately reflect autonomic tone.
(2) How was the "dose" chosen (20 minutes twice daily)?
(3) The use of an acute biomarker of response is very important. A bimodal response to taVNS has been previously shown in patients with atrial fibrillation (Kulkarni et al. JAHA 2021).
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feministai.pubpub.org feministai.pubpub.org
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Advocate for and adopt guidelines that establish accountability and transparency for algorithmic decision making (ADM) in both the public and private sectors.
Llamado a la acción
Acciones algorítmicas equitativas para corregir los sesgos y barreras de la vida real que impiden que las mujeres y las niñas logren la participación plena y el disfrute igualitario de los derechos.
Instituciones públicas para pilotar y liderar: Acción afirmativa para algoritmos implementados cuando las instituciones públicas pilotan ADM. Basar los pilotos en investigaciones de ciencias sociales nuevas y de larga data que asignan incentivos sociales, subsidios o becas donde las mujeres tradicionalmente han sido dejadas atrás en sistemas anteriores. Esta es una agenda positiva para promover los valores de igualdad que hemos adoptado durante mucho tiempo, para corregir la visibilidad, la calidad y la influencia de las mujeres proporcionales a la población.
Adopción por parte del sector público y privado de evaluaciones de impacto algorítmico (AIA): un marco de autoevaluación diseñado para respetar el derecho del público a conocer los sistemas de IA que impactan sus vidas en términos de principios de responsabilidad y equidad.
Pruebas rigurosas a lo largo del ciclo de vida de los sistemas de IA: las pruebas deben tener en cuenta los orígenes y el uso de los datos de entrenamiento, los datos de prueba, los modelos, la interfaz de programación de aplicaciones (API) y otros componentes a lo largo del ciclo de vida de un producto. Las pruebas deben cubrir ensayos previos al lanzamiento, auditorías independientes, certificación y monitoreo continuo para detectar sesgos y otros daños. La ADM debe mejorar la calidad de la experiencia humana, no controlarla.
Marcos legales sólidos para promover la rendición de cuentas: incluida la posible expansión de poderes para agencias sectoriales específicas o la creación de nuevos términos de referencia para supervisar, auditar y monitorear los sistemas de ADM para la supervisión regulatoria y la responsabilidad legal en el sector privado y público.
Directrices de adquisiciones con perspectiva de género: las organizaciones y todos los niveles de gobierno deben desarrollar directrices de adquisiciones de igualdad de género de ADM con objetivos estrictos; y describir los roles y responsabilidades de aquellas organizaciones requeridas para aplicar estos principios.
Mejorar los conjuntos de datos: datos abiertos desagregados por género, recopilación de datos y conjuntos de datos de calidad inclusivos: producir activamente conjuntos de datos abiertos desagregados por género; Esto permite comprender mejor las fuentes de sesgo en la IA y, en última instancia, mejorar el rendimiento de los sistemas de aprendizaje automático. Invertir en controles para supervisar los procesos de recopilación de datos y la verificación humana en el circuito, de modo que los datos no se recopilen a expensas de las mujeres y otros grupos tradicionalmente excluidos. Participar en procesos de recopilación de datos más inclusivos que se centren no solo en la cantidad sino también en la calidad de los conjuntos de datos.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Gekko, Nomura et al., show that Drp1 elimination in zygotes using the Trim-Away technique leads to mitochondrial clustering and uneven mitochondrial partitioning during the first embryonic cleavage, resulting in embryonic arrest. They monitor organellar localization and partitioning using specific targeted fluorophores. They also describe the effects of mitochondrial clustering in spindle formation and the detrimental effect of uneven mitochondrial partitioning to daughter cells.
Strengths:
The authors have gathered solid evidence for the uneven segregation of mitochondria upon Drp1 depletion through different means: mitochondrial labelling, ATP labelling and mtDNA copy number assessment in each daughter cell. Authors have also characterised the defects in cleavage mitotic spindles upon Drp1 loss
Weaknesses:
While this study convincingly describes the phenotype seen upon Drp1 loss, my major concern is that the mechanism underlying these defects in zygotes remains unclear. The authors refer to mitochondrial fragmentation as the mechanism ensuring organelle positioning and partitioning into functional daughters during the first embryonic cleavage. However, could Drp1 have a role beyond mitochondrial fission in zygotes? I raise these concerns because, as opposed to other Drp1 KO models (including those in oocytes) which lead to hyperfused/tubular mitochondria, Drp1 loss in zygotes appears to generate enlarged yet not tubular mitochondria. Lastly, while the authors discard the role of mitochondrial transport in the clustering observed, more refined experiments should be performed to reach that conclusion.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
This paper examines the recruitment of the inflammasome seeding pattern recognition receptor NLRP3 to the Golgi. Previously, electrostatic interactions between the polybasic region of NLRP3 and negatively charged lipids were implicated in membrane association. The current study concludes that reversible S-acylation of the conserved Cys-130 residue, in conjunction with upstream hydrophobic residues plus the polybasic region, act together to promote Golgi localization of NLRP3, although additional parts of the protein are needed for full Golgi localization. Treatment with the bacterial ionophore nigericin inhibits membrane traffic and apparently prevents Golgi-associated thioesterases from removing the acyl chain, causing NLRP3 to become immobilized at the Golgi. This mechanism is put forth as an explanation for how NLRP3 is activated in response to nigericin.
The experiments are generally well presented. It seems likely that Cys-130 does indeed play a previously unappreciated role in Golgi association of NLRP3. However, the evidence for S-acylation at Cys-130 is largely indirect, and the process by which nigericin enhances membrane association is not yet fully understood. Therefore, this interesting study points the way for further analysis.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors address cellular mechanisms underlying the early stages of Sjogren's syndrome, using a mouse model in which 5,6-Dimethyl-9-oxo-9H-xanthene-4-acetic acid (DMXAA) is applied to stimulate the interferon gene (STING) pathway. They show that in this model salivary secretion in response to neural stimulation is greatly reduced, even though calcium responses of individual secretory cells was enhanced. They attribute the secretion defect to reduced activation of Ca2+ -activated Cl- channels (TMEM16a), due to an increased distance between Ca2+ release channels (IP3 receptors) and TMEM16a which is expected to reduce the [Ca2+] sensed by TMEM16a. A variety of disruptions in mitochondria were also observed after DMXAA treatment, including reduced abundance, altered morphology, depolarization and reduced oxygen consumption rate. The results of this study shed new light on some of the early events leading to the loss of secretory function in Sjogren's syndrome, at a time before inflammatory responses cause the death of secretory cells.
Strengths:
Two-photon microscopy enabled Ca2+ measurements in the salivary glands of intact animals in response to physiological stimuli (nerve stimulation. This approach has been shown previously by the authors as necessary to preserve the normal spatiotemporal organization of calcium signals that lead to secretion under physiological conditions.
Superresolution (STED) microscopy allowed precise measurements of the spacing of IP3R and TMEM16a and the cell membranes that would otherwise be prevented by the diffraction limit. The measured increase of distance (from 84 to 155 nm) would be expected to reduce [Ca2+] at the TMEM16a channel.
The authors effectively ruled out a variety of alternative explanations for reduced secretion, including changes in AQP5 expression, and TMEM16a expression, localization and Ca2+ sensitivity as indicated by Cl- current in response to defined levels of Ca2+. Suppression of Cl- currents by a fast buffer (BAPTA) but not a slow one (EGTA) supports the idea that increased distance between IP3R and TMEM16A contributes to the secretory defect in DMXAA-treated cells.
Weaknesses:
While the Ca2+ distribution in the cells was less restricted to the apical region in DMXAA-treated cells, it is not clear that this is relevant to the reduced activation of TMEM16a or to pathophysiological changes associated with Sjogren's syndrome.
Despite the decreased level of secretion, Ca2+ signal amplitudes were higher in the treated cells, raising the question of how much this might compensate for the increased distance between IP3R and TMEM16a. The authors assume that the increased separation of IP3R and TMEM16a (and the resulting decrease in local [Ca2+]) outweighed the effect of higher global [Ca2+], but this point was not addressed directly.
The description of mitochondrial changes in abundance, morphology, membrane potential, and oxygen consumption rate were not well integrated into the rest of the paper. While they may be a facet of the multiple effects of STING activation and may occur during Sjogren's syndrome, their possible role in reducing secretion was not examined. As it stands, the mitochondrial results are largely descriptive and more studies are needed to connect them to the secretory deficits in SJogren's syndrome.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this manuscript, Leikina et al. investigate the role of redox changes in the ubiquitous protein La in promotion of osteoclast fusion. In a recently published manuscript, the investigators found that osteoclast multinucleation and resorptive activity are regulated by a de-phosphorylated and proteolytically cleaved form of the La protein that is present on the cell surface of differentiating osteoclasts. In the present work, the authors build upon these findings to determine the physiologic signals that regulate La trafficking to the cell membrane and ultimately, the ability of this protein to promote fusion. Building upon other published studies that show 1) that intracellular redox signaling can elicit changes in the confirmation and localization of La, and 2) that osteoclast formation is dependent on ROS signaling, the authors hypothesize that oxidation of La in response to intracellular ROS underlies the re-localization of La to the cell membrane and that this is necessary for its pro-fusion activity. The authors test this hypothesis in a rigorous manner using antioxidant treatments, recombinant La protein, and modification of cysteine residues predicted to be key sites of oxidation. Osteoclast fusion is then monitored in each condition using fluorescence microscopy. These data strongly support the conclusion that oxidized La is de-phosphorylated, increases in abundance at the cell surface of differentiating osteoclasts, and promotes cell-cell fusion. A strength of this manuscript is the use of multiple complementary approaches to test the hypothesis, especially the use of Cys mutant forms of La to directly tie the observed phenotypes to changes in residues that are key targets for oxidation. The manuscript is also well written and describes a clearly articulated hypothesis based on a precise summation of the existing literature. The findings of this manuscript will be of interest to researchers in the field of bone biology, but also more generally to cell biologists. The data in this manuscript may also lead to future studies that target La for bone diseases in which there is increased osteoclast activity. Weaknesses of the first version of the manuscript were minor and predominantly related to data presentation choices and some statistical analyses. These weaknesses were comprehensively addressed in the revised manuscript, and therefore the study has increased clarity and rigor.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript the authors investigate the contributions of the long noncoding RNA snhg3 in liver metabolism and MAFLD. The authors conclude that liver-specific loss or overexpression of Snhg3 impacts hepatic lipid content and obesity through epigenetic mechanisms. More specifically, the authors invoke that nuclear activity of Snhg3 aggravates hepatic steatosis by altering the balance of activating and repressive chromatin marks at the Pparg gene locus. This regulatory circuit is dependent on a transcriptional regulator SNG1.
Strengths:
The authors developed a tissue specific lncRNA knockout and KI models. This effort is certainly appreciated as few lncRNA knockouts have been generated in the context of metabolism. Furthermore, lncRNA effects can be compensated in a whole organism or show subtle effects in acute versus chronic perturbation, rendering the focus on in vivo function important and highly relevant. In addition, Snhg3 was identified through a screening strategy and as a general rule the authors the authors attempt to follow unbiased approaches to decipher the mechanisms of Snhg3.
Weaknesses:
Despite efforts at generating a liver-specific knockout, the phenotypic characterization is not focused on the key readouts. Notably missing are rigorous lipid flux studies and targeted gene expression/protein measurement that would underpin why loss of Snhg3 protects from lipid accumulation. Along those lines, claims linking the Snhg3 to MAFLD would be better supported with careful interrogation of markers of fibrosis and advanced liver disease. In other areas, significance is limited since the presented data is either not clear or rigorous enough. Finally, there is an important conceptual limitation to the work since PPARG is not established to play a major role in the liver.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This study presents a valuable finding on the expression levels of circHMGCS1 regulating arginase-1 by sponging miR-4521observed in diabetes-induced vascular endothelial dysfunction, leading to decrease in vascular nitric oxide secretion and inhibition of endothelial nitric oxide synthase activity. Further, increase in the expression of adhesion molecules and generation of cellular reactive oxygen species reduced vasodilation and accelerated the impairment of vascular endothelial function.<br /> Modulating circHMGCS1/miR-4521/ARG1 axis could serve as a potential strategy to prevent diabetes-associated cardiovascular diseases.
Comments on revised version:
The authors answered all questions satisfactorily.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this work, the authors continue their investigations on the key role of glycosylation to modulate the function of a therapeutic antibody. As a follow-up to their previous demonstration on how ADCC was heavily affected by the glycans at the Fc gamma receptor (FcγR)IIIa, they now dissect the contributions of the different glycans that decorate the diverse glycosylation sites. Using a well-designed mutation strategy, accompanied by exhaustive biophysical measurements, with extensive use of NMR, using both standard and newly developed methodologies, they demonstrate that there is one specific locus, N162, which is heavily involved in the stabilization of (FcγR)IIIa and that the concomitant NK function is regulated by the glycan at this site.
Strengths:
The methodological aspects are carried out at the maximum level.
Weaknesses:
The exact (or the best possible assessment) of the glycan composition at the N162 site is not defined.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors report an inability to reproduce a transgenerational memory of avoidance of the pathogen PA14 in C. elegans. Instead, the authors demonstrate intergenerational inheritance for a single F1 generation, in embryos of mothers exposed to OP50 and PA14, where embryos isolated from these mothers by bleaching are capable of remembering to avoid PA14 in a manner that is dependent on systemic RNAi proteins sid-1 and sid-2. This could reflect systemic sRNAs generated by neuronal daf-7 signaling that are transmitted to F1 embryos. The authors note that transgenerational memory of PA14 was reported by the Murphy group at Princeton, but that environmental or strain variation (worms or bacteria) might explain the single generation of inheritance observed at Harvard. The Hunter group tried different bacterial growth conditions and different worm growth temperatures for independent PA14 strains, which they showed to be strongly pathogenic. However, the authors could not reproduce a transgenerational effect at Harvard. This important data will allow members of the scientific community to focus on the robust and reproducible inheritance of PA14 avoidance transmitted to F1 embryos of mothers exposed to PA14, which the authors demonstrate depends on small RNAs in a manner that is downstream of or in parallel to daf-7. This paper honestly and importantly alters expectations and questions the model that avoidance of PA14 is mediated by a bacterial ncRNA whose siRNAs target a C. elegans gene. Instead, endogenous C. elegans sRNAs that affect pathogen response may be the culprit that explains sRNA-mediated avoidance.
Overall, this is an important paper that demonstrates that one model for transgenerational inheritance in C. elegans is not reproducible. This is important because it is not clear how many of the reported models of transgenerational inheritance reported in C. elegans are reproducible. The authors do demonstrate a memory for F1 embryos that could be a maternal effect, and the authors confirm that this is mediated by a systemic small RNA response. There are several points in the manuscript where a more positive tone might be helpful.
Strengths:
The authors note that the high copy number daf-7::GFP transgene used by the Murphy group displayed variable expression and evidence for somatic silencing or transgene breakdown in the Hunter lab, as confirmed by the Murphy group. The authors nicely use single copy daf-7::GFP to show that neuronal daf-7::GFP is elevated in F1 but not F2 progeny with regards to the memory of PA14 avoidance, speaking to an intergenerational phenotype.
The authors nicely confirm that sid-1 and sid-2 are generally required for intergenerational avoidance of F1 embryos of moms exposed to PA14. However, these small RNA proteins did not affect daf-7::GFP elevation in the F1 progeny. This result is unexpected given previous reports that single copy daf-7::GFP is not elevated in F1 progeny of sid mutants. Because the Murphy group reported that daf-7 mutation abolishes avoidance for F1 progeny, this means that the sid genes function downstream of daf-7 or in parallel, rather than upstream as previously suggested.
The authors studied antisense small RNAs that change in Murphy data sets, identifying 116 mRNAs that might be regulated by sRNAs in response to PA14. Importantly, the authors show that the maco-1 gene, putatively targeted by piRNAs according to the Kaletsky 2020 paper, displays few siRNAs that change in response to PA14. The authors conclude that the P11 ncRNA of PA14, which was proposed to promote interkingdom RNA communication by the Murphy group, is unlikely to affect maco-1 expression by generating sRNAs that target maco-1 in C. elegans. The authors define 8 genes based on their analysis of sRNAs and mRNAs that might promote resistance to PA14, but they do not further characterize these genes' role in pathogen avoidance. The Murphy group might wish to consider following up on these genes and their possible relationship with P11.
Weaknesses:
This very thorough and interesting manuscript is at times pugnacious.
Please explain more clearly what is High Growth media for E. coli in the text and methods, conveying why it was used by the Murphy lab, and if Normal Growth or High Growth is better for intergenerational heritability assays.
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www.researchsquare.com www.researchsquare.com
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Reviewer #3 (Public Review):
Summary:
In this work, the authors plate different type of cells on circular micropatterns and question how the organization and dynamics of the actin cytoskeleton correlate with particular actin chiral properties and rotational direction of the nucleus. The observe that cell spreading on large patterns correlates with the emergence of anti-clockwise rotations (ACW), while spreading on small patterns leads preferentially to clockwise rotations (CW). ACW originate, as previously demonstrated, from the polymerization of radial fibers, while clockwise rotations (CW) are observed when radial fibers are disorganized or absent and when transverse arcs take over to power CW rotations. These data are supported by a large number of observations and use of multiple drugs lead to observations that are consistent with the proposed model.
Strengths:
This is a beautiful work in which the authors rely on a large number of high-quality microscopic observations and use a full arsenal of drugs to test their model as thoroughly as possible.<br /> This study examines the influence of multiple actin networks. This is a challenging task in that the assembly and dynamics of different actin networks are interdependent, making it difficult to unambiguously analyze the importance of any specific network.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This paper uses single-molecule FRET to investigate the molecular basis for the distinct activation mechanisms between 2 GPCR responding to the chemokine CXCL12 : CXCR4, that couples to G-proteins, and ACKR3, which is G-protein independent and displays a higher basal activity.
Strengths:
It nicely combines the state-of-the-art techniques used in the studies of the structural dynamics of GPCR. The receptors are produced from eukaryotic cells, mutated, and labeled with single molecule compatible fluorescent dyes. They are reconstituted in nanodiscs, which maintain an environment as close as possible to the cell membrane, and immobilized through the nanodisc MSP protein, to avoid perturbing the receptor's structural dynamics by the use of an antibody for example.
The smFRET data are analysed using the HHMI technique, and the number of states to be taken into account is evaluated using a Bayesian Information Criterion, which constitutes the state-of-the-art for this task.
The data show convincingly that the activation of the CXCR4 and ACKR3 by an agonist leads to a shift from an ensemble of high FRET states to an ensemble of lower FRET states, consistent with an increase in distance between the TM4 and TM6. The two receptors also appear to explore a different conformational space. A wider distribution of states is observed for ACKR3 as compared to CXCR4, and it shifts in the presence of agonists toward the active states, which correlates well with ACKR3's tendency to be constitutively active. This interpretation is confirmed by the use of the mutation of Y254 to leucine (the corresponding residue in CXCR4), which leads to a conformational distribution that resembles the one observed with CXCR4. It is correlated with a decrease in constitutive activity of ACKR3.
Weaknesses:
Although the data overall support the claims of the authors, there are however some details in the data analysis and interpretation that should be modified, clarified, or discussed in my opinion.
Concerning the amplitude of the changes in FRET efficiency: the authors do not provide any structural information on the amplitude of the FRET changes that are expected. To me, it looks like a FRET change from ~0.9 to ~0.1 is very important, for a distance change that is expected to be only a few angstroms concerning the movement of the TM6. Can the authors give an explanation for that? How does this FRET change relate to those observed with other GPCRs modified at the same or equivalent positions on TM4 and TM6?
Concerning the intermediate states: the authors observe several intermediate states.
(1) First I am surprised, looking at the time traces, by the dwell times of the transitions between the states, which often last several seconds. Is such a long transition time compatible with what is known about the kinetic activation of these receptors?
(2) Second is it possible that these « intermediate » states correspond to differences in FRET efficiencies, that arise from different photophysical states of the dyes? Alexa555 and Cy5 are Cyanines, that are known to be very sensitive to their local environment. This could lead to different quantum yields and therefore different FRET efficiencies for a similar distance. In addition, the authors use statistical labeling of two cysteines, and have therefore in their experiment a mixture of receptors where the donor and acceptor are switched, and can therefore experience different environments. The authors do not speculate structurally on what these intermediate states could be, which is appreciated, but I think they should nevertheless discuss the potential issue of fluorophore photophysics effects.
(3) It would also have been nice to discuss whether these types of intermediate states have been observed in other studies by smFRET on GPCR labeled at similar positions.
On line 239: the authors talk about the R↔R' transitions that are more probable. In fact it is more striking that the R'↔R* transition appears in the plot. This transition is a signature of the behaviour observed in the presence of an agonist, although IT1t is supposed to be an inverse agonist. This observation is consistent with the unexpected (for an inverse agonist) shift in the FRET histogram distribution. In fact, it appears that all CXCR4 antagonists or inverse agonists have a similar (although smaller) effect than the agonist. Is this related to the fact that these (antagonist or inverse agonist) ligands lead to a conformation that is similar to the agonists, but cannot interact with the G-protein ?? Maybe a very interesting experiment would be here to repeat these measurements in the presence of purified G-protein. G-protein has been shown to lead to a shift of the conformational space explored by GPCR toward the active state (using smFRET on class A and class C GPCR). It would be interesting to explore its role on CXCR4 in the presence of these various ligands. Although I am aware that this experiment might go beyond the scope of this study, I think this point should be discussed nevertheless.
The authors also mentioned in Figure 6 that the energetic landscape of the receptors is relatively flat ... I do not really agree with this statement. For me, a flat conformational landscape would be one where the receptors are able to switch very rapidly between the states (typically in the submillisecond timescale, which is the timescale of protein domain dynamics). Here, the authors observed that the transition between states is in the second timescale, which for me implies that the transition barrier between the states is relatively high to preclude the fast transitions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper by Zhang, the authors build a physical framework to probe the mechanisms that underlie exchange of molecules between coexisting dense and dilute liquid-like phases of condensates. They first propose a continuum model, in the context of a FRAP-like experiment where the fluorescently labeled molecules inside the condensate are bleached at t=0 and the recovery of fluorescence is measured. Through this model, they identify how the key timescales of internal molecular mixing, replenishment from dilute phase, and interface transfer contribute to molecular exchange timescale. Motivated by a recent experiment reported by some of the co-authors previously (Brangwynne et al. in 2019) finding strong interfacial resistance in in vitro protein droplets of LAF-1, they seek to understand the microscopic features contributing to the interfacial conductance (inversely proportional to the resistance). To check, they perform coarse-grained MD-simulations of sticker-spacer self-associative polymers and report how conductance varies significantly even across the few explored sequences. Further, by looking at individual trajectories, they postulate the "bouncing" i.e., molecules that approach the interface but are not successfully absorbed is a strong contributor to this mass transfer limitation. Consistent with their predictions, sequences that have more free unbound stickers (i.e., for example through imbalance sequence sticker stoichiometries) have higher conductances and they show a simple linear scaling between number of unbound stickers and conductance. Finally, they predict that an droplet-size dependent transition in recovery time behavior.
Strengths:
(1) This paper is overall well-written and clear to understand.<br /> (2) By combining coarse-grained simulations, continuum modeling, and comparison to published data, the authors provide a solid picture of how their proposed framework relates to molecular exchange mechanisms that are dominated by interface resistance and LAF-1 droplets.<br /> (3) The choice of different ways to estimate conductance from simulation and reported data are thoughtful and convincing on their near-agreement (although a little discussion of why and when they differ would be merited as well).
Updated re-review:
This revised update by Zhang et al. is improved and addresses many of the concerns raised by myself and the other reviewer, especially with the expanded discussion, contextualized text in model description, and the addition of a nice example case-study in revised Fig. 4. I believe the paper provides solid evidence of how "bouncing" may contribute to interfacial resistance/exchange dynamics in biomolecular condensates and is a useful study for the community.
Note:<br /> In their response, the authors bring up an important point in references for LAF1 mutant FRAP data. While I found a few papers, for example https://www.pnas.org/doi/abs/10.1073/pnas.2000223117 and https://www.cell.com/biophysj/fulltext/S0006-3495(23)00464-2 , these are likely to be not whole droplet bleaches. I wonder whether it may be possible to approximately predict the conductance from other parameters (such as from effective expressions in eq 14) to roughly estimate what the effect maybe since LAF-1 has fairly "known" stickers and spacers. Note that this is not required at all, but I just bring this up in case it may be of interest to authors!
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, the authors describe the construction of an extremely large-scale anatomical model of juvenile rat somatosensory cortex (excluding the barrel region), which extends earlier iterations of these models by expanding across multiple interconnected cortical areas. The models are constructed in such a way as to maintain biological detail from a granular scale - for example, individual cell morphologies are maintained, and synaptic connectivity is founded on anatomical contacts. The authors use this model to investigate a variety of properties, from cell-type specific targeting (where the model results are compared to findings from recent large-scale electron microscopy studies) to network metrics. The model is also intended to serve as a platform and resource for the community by being a foundation for simulations of neuronal circuit activity and for additional anatomical studies that rely on the detailed knowledge of cellular identity and connectivity.
Strengths:
As the authors point out, the combination of scale and granularity of their model is what makes this study valuable and unique. The comparisons with recent electron microscopy findings are some of the most compelling results presented in the study, showing that certain connectivity patterns can arise directly from the anatomical configuration, while other discrepancies highlight where more selective targeting rules (perhaps based on molecular cues) are likely employed. They also describe intriguing effects of cortical thickness and curvature on circuit connectivity and characterize the magnitude of those effects on different cortical layers.
The detailed construction of the model is drawn on a wide range of data sources (cellular and synaptic density measures, neuronal morphologies, cellular composition measures, brain geometry, etc.) that are integrated together; other data sources are used for comparison and validation. This consolidation and comparison also represent a valuable contribution to the overall understanding of the modeled system.
Weaknesses:
The scale of the model, which is a primary strength, also can carry some drawbacks. In order to integrate all the diverse data sources together, many specific decisions must be made about, for example, translating findings from different species or regions to the modeled system, or deciding which aspects of the system can be assumed to be the same and which should vary. All these decisions will have effects on the predicted results from the model, which could limit the types of conclusions that can be made (both by the others and by others in the community who may wish to use the model for their own work).
As an example, while it is interesting that broad brain geometry has effects on network structure (Figure 7), it is not clear how those effects are actually manifested. I am not sure if some of the effects could be due to the way the model is constructed - perhaps there may be limited sets of morphologies that fit into columns of particular thicknesses, and those morphologies may have certain idiosyncrasies that could produce different statistics of connectivities where they are heavily used. That may be true to biology, but it may also be somewhat artifactual if, for example, the only neurons in the library that fit into that particular part of the cortex differ from the typical neurons that are actually found in that region (but may not have been part of the morphological sampling). I also wonder how much the assumption that the layers have the same relative thicknesses everywhere in the cortex affects these findings, since layer thicknesses do in fact vary across the cortex.
In addition, the complexity of the model means that some complicated analyses and decisions are only presented in this manuscript with perhaps a single panel and not much textual explanation. I find, for example, that the panels of Figure S2 seem to abstract or simplify many details to the point where I am not clear about what they are actually illustrating - how does Figure S2D represent the results of "the process illustrated in B"? Why are there abrupt changes in connectivity at region borders (shown as discontinuous colors), when dendrites and axons span those borders and so would imply interconnectivity across the borders? What do the histograms in E1 and E2 portray, and how are they related to each other?
Overall, the model presented in this study represents an enormous amount of work and stands as a unique resource for the community, but also is made somewhat unwieldy for the community to employ due to the weight of its manifold specific construction decisions, size, and complexity.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors propose that the energy landscape of animals can be thought of in the same way as the fundamental versus realized niche concept in ecology. Namely, animals will use a subset of the fundamental energy landscape due to a variety of factors. The authors then show that the realized energy landscape of eagles increases with age as the animals are better able to use the energy landscape.
Strengths:
This is a very interesting idea and that adds significantly to the energy landscape framework. They provide convincing evidence that the available regions used by birds increase with size.
Review of revised version:
The authors have addressed all my comments and concerns. This is a really nice and important manuscript. I have one minor suggestion: Line 74-85: when discussing the effect of ontogeny, the authors give examples of how these may change due to improved cognition and memory. I would recommend they also give examples of how these may change with morphology (e.g. change in wing or fin relative area, buoyancy in sharks etc) should also be included. Most growth in fish for example is allometric so the relative measures of area of fins to body size should also change.
This is of course up to the authors but it would highlight how their study is applicable to many other systems beyond just birds (even though morphology is of little importance for their eagles).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Ren et al developed a novel computational method to investigate cell evolutionary trajectory for scRNA-seq samples. This method, MGPfact, estimates pseudotime and potential branches in the evolutionary path by explicitly modeling the bifurcations in a Gaussian process. They benchmarked this method using synthetic as well as real-world samples and showed superior performance for some of the tasks in cell trajectory analysis. They further demonstrated the utilities of MGPfact using single-cell RNA-seq samples derived from microglia or T cells and showed that it can accurately identify the differentiation timepoint and uncover biologically relevant gene signatures.
Strengths:
Overall I think this is a useful new tool that could deliver novel insights for the large body of scRNA-seq data generated in the public domain. The manuscript is written in a logical way and most parts of the method are well described.
Weaknesses:
Some parts of the methods are not clear.
It should be outlined in detail how pseudo time T is updated in Methods. It is currently unclear either in the description or Algorithm 1.
There should be a brief description in the main text of how synthetic data were generated, under what hypothesis, and specifically how bifurcation is embedded in the simulation.
Please explain what the abbreviations mean at their first occurrence.
In the benchmark analysis (Figures 2/3), it would be helpful to include a few trajectory plots of the real-world data to visualize the results and to evaluate the accuracy.
It is not clear how this method selects important genes/features at bifurcation. This should be elaborated on in the main text.
It is not clear how survival analysis was performed in Figure 5. Specifically, were critical confounders, such as age, clinical stage, and tumor purity controlled?
I recommend that the authors perform some sort of 'robustness' analysis for the consensus tree built from the bifurcation Gaussian process. For example, subsample 80% of the cells to see if the bifurcations are similar between each bootstrap.
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arxiv.org arxiv.org
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Reviewer #1 (Public Review):
The authors proposed a framework to estimate the posterior distribution of parameters in biophysical models. The framework has two modules: the first MLP module is used to reduce data dimensionality and the second NPE module is used to approximate the desired posterior distribution. The results show that the MLP module can capture additional information compared to manually defined summary statistics. By using the NPE module, the repetitive evaluation of the forward model is avoided, thus making the framework computationally efficient. The results show the framework has promise in identifying degeneracy. This is an interesting work.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In their manuscript, Gan and colleagues identified a functional critical residue, Tyr404, which when mutated to W or A results in GOF and LOF of TRPML1 activity, respectively. In addition, the authors provide a high-resolution structure of TRPML1 with PI(4,5)P2 inhibitor. This high-resolution structure also revealed a bound phospholipid likely sphingomyelin at the agonist/antagonist site, providing a plausible explanation for sphingomyelin inhibition of TRPML1.
This is an interesting study, revealing valuable additional information on TRPML1 gating mechanisms including effects on endogenous phospholipids on channel activity. The provided data are convincing. Some major open questions remain. The work will be of interest to a wide audience including industry researchers occupied with TRPML1 exploration as a drug target.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The overall goal of the manuscript is to delineate pathways that are conditionally essential with the Bam complex and associated chaperones. The Bam complex is made of several proteins, including BamA and BamD, which are essential. The protein complex works to insert proteins in the asymmetric outer membrane. Substrates are translated in the cytoplasm prior to transport across the cell envelope to the Bam complex. Transport includes non-essential periplasmic chaperones, SurA, Skp, and DegP. According to the authors, the pathways were assumed to be redundant. The Bam complex also includes non-essential components, BamBCE. These were thought to be accessory components that interact with BamA and BamD to coordinate optimal activity. While some roles have been assigned to BamE and BamB, a detailed understanding of the role of each accessory Bam protein is lacking. In this study, more specific roles for each non-essential Bam component are proposed.
Strengths:
The overall findings are intriguing and could advance our understanding as to how the Gram-negative cell envelope is assembled. These studies could provide new targets for antimicrobial treatment. In general, the manuscript was well-written.
Weaknesses:
While the overall findings are interesting, I had some concerns with the data analysis, presentation, and conclusions. Not all the conclusions are supported by data. The proposed revisions include experimental and editorial work. The manuscript is generally well-written and could provide impactful data to advance the field if the concerns are addressed.
Major concerns:
Overall Comments:
(1) The cutoffs the authors used to define "conditionally essential" mutants are not reported. The results also lack validation for lethality using a titratable system. It would be ideal to validate several genes in each dataset to determine cutoffs (i.e. 5-fold decrease in insertion mutants) for conditional lethality. It was not done (or described) here.
(2) Also, two mutations that both make the cells sick could provide an additive effect (i.e. dapF and BamB), which doesn't necessarily mean the pathways are linked. The authors should revise their wording. They have not shown genetic linkage in some cases.
(3) Mutations throughout the manuscript are not complemented. It would be ideal to add complementation data to show the gene-phenotype relationship is specific.
(4) Also, I would argue the term "conditionally essential genes" should be replaced with "synthetically lethal". Strains were compared in the same conditions but with different genetic backgrounds.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Sun et al. generated germline-specific cKO mice for the Znhit1 gene and examined its effect on male meiosis. The authors found that the loss of Znhit1 affects the transcriptional activation of pachytene. Znhit1 is a subunit of the SRCAP chromatin remodeling complex and a depositor of H2AZ, and in cKO spermatocytes, H2AZ is not deposited into the gene region. The authors claim that this is why the PGA was not activated. These findings provide important insights into the mechanisms of transcriptional regulation during the meiotic prophase.
Strengths:
The authors used samples from their original mouse model, analyzing both the epigenome and the transcriptome in detail using diverse NGS analyses to gain new insights into PGA. The quality of the results appeared excellent.
Weaknesses:
Overall, the data is inconsistent with the authors' claims and does not support their final conclusions. In addition, the sample used may not be the most suitable for the analysis, but a more suitable sample would dramatically improve the overall quality of the paper.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This work introduces a new imaging tool for profiling tumor microenvironments through glucose conversion kinetics. Using GL261 and CT2A intracranial mouse models, the authors demonstrated that tumor lactate turnover mimicked the glioblastoma phenotype, and differences in peritumoral glutamate-glutamine recycling correlated with tumor invasion capacity, aligning with histopathological characterization. This paper presents a novel method to image and quantify glucose metabolites, reducing background noise and improving the predictability of multiple tumor features. It is, therefore, a valuable tool for studying glioblastoma in mouse models and enhances the understanding of the metabolic heterogeneity of glioblastoma.
Strengths:
By combining novel spectroscopic imaging modalities and recent advances in noise attenuation, Simões et al. improve upon their previously published Dynamic Glucose-Enhanced deuterium metabolic imaging (DGE-DMI) method to resolve spatiotemporal glucose flux rates in two commonly used syngeneic GBM mouse models, CT2A and GL261. This method can be standardized and further enhanced by using tensor PCA for spectral denoising, which improves kinetic modeling performance. It enables the glioblastoma mouse model to be assessed and quantified with higher accuracy using imaging methods.
The study also demonstrated the potential of DGE-DMI by providing spectroscopic imaging of glucose metabolic fluxes in both the tumor and tumor border regions. By comparing these results with histopathological characterization, the authors showed that DGE-DMI could be a powerful tool for analyzing multiple aspects of mouse glioblastoma, such as cell density and proliferation, peritumoral infiltration, and distant migration.
Weaknesses:
Although the paper provides clear evidence that DGE-DMI is a potentially powerful tool for the mouse glioblastoma model, it fails to use this new method to discover novel features of tumors. The data presented mainly confirm tumor features that have been previously reported. While this demonstrates that DGE-DMI is a reliable imaging tool in such circumstances, it also diminishes the novelty of the study.
When using DGE-DMI to quantitatively map glycolysis and mitochondrial oxidation fluxes, there is no comparison with other methods to directly identify the changes. This makes it difficult to assess how sensitive DGE-DMI is in detecting differences in glycolysis and mitochondrial oxidation fluxes, which undermines the claim of its potential for in vivo GBM phenotyping.
The study only used intracranial injections of two mouse glioblastoma cell lines, which limits the application of DGE-DMI in detecting and characterizing de novo glioblastomas. A de novo mouse model can show tumor growth progression and is more heterogeneous than a cell line injection model. Demonstrating that DGE-DMI performs well in a more clinically relevant model would better support its claimed potential usage in patients.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Previous work has shown that the evolutionarily-conserved division-orienting protein LGN/Pins (vertebrates/flies) participates in division orientation across a variety of cell types, perhaps most importantly those that undergo asymmetric divisions. Micromere formation in echinoids relies on asymmetric cell division at the 16-cell stage, and these authors previously demonstrated a role for the LGN/Pins homolog AGS in that ACD process. Here they extend that work by investigating and exploiting the question of why echinoids but not other echinoderms form micromeres. Starting with a phylogenetics approach, they determine that much of the difference in ACD and micromere formation in echinoids can be attributed to differences in the AGS C-terminus, in particular a GoLoco domain (GL1) that is missing in most other echinoderms.
Strengths:
There is a lot to like about this paper. It represents a superlative match of the problem with the model system and the findings it reports are a valuable addition to the literature. It is also an impressively thorough study; the authors should be commended for using a combination of experimental approaches (and consequently generating a mountain of data).
Weaknesses:
There is an intriguing finding described in Figure 1. AGS in sea cucumbers looks identical to AGS in the pencil urchin, at least at the C terminus (including the GL1 domain). Nevertheless, there are no micromeres in sea cucumbers. Therefore another mechanism besides GL motif organization has arisen to support micromere formation. It is a consequential finding and an important consideration in interpreting the data, but I could not find any mention of it in the text. That is a missed opportunity and should be remedied, ideally not only through discussion but also experimentation. Specifically: does sea cucumber AGS (SbAGS) ever localize to the vegetal cortex in sea cucumbers? Can it do so in echinoids? Will that support micromere formation?
The authors point out that AGS-PmGL demonstrates enrichment at the vegetal cortex (arrow in 5G, quantifications in 5H), unlike PmAGS. AGS-PmGL does not however support ACD. They interpret this result to indicate "that other elements of SpAGS outside of its C-terminus can drive its vegetal cortical localization but not function." This is a critical finding and deserves more attention. Put succinctly: Vegetal cortical localization of AGS is insufficient to promote ACD, even in echinoids. Why should this be?
The authors did perform experiments to address this problem, hypothesizing that the difference might be explained by the linker region, which includes a conserved phosphorylation site that mediates binding to Dlg. They write "To test if this serine is essential for SpAGS localization, we mutated it to alanine (AGS-S389A in Fig. S3A). Compared to the Full AGS control, the mutant AGS-S389A showed reduced vegetal cortical localization (Fig. S3B-C) and function (Fig. S3D-E). Furthermore, we replaced the linker region of PmAGS with that of SpAGS (PmAGS-SpLinker in Fig. S4A-B). However, this mutant did not show any cortical localization nor proper function in ACD (Fig. S4C-F). Therefore, the SpAGS C-terminus is the primary element that drives ACD, while the linker region serves as the secondary element to help cortical localization of AGS."
The experiments performed only make sense if the AGS-PmGL chimeric protein used in Figure 5 starts the PmGL sequence only after the Sp linker, or at least after the Sp phosphorylation site. I can't tell from the paper (Figure S3 indicates that it does, whereas S5 suggests otherwise), but it's a critical piece of information for the argument. Another piece of missing information is whether the PmAGS can be phosphorylated at its own conserved phosphorylation site. The authors don't test this, which they could at least try using a phosphosite prediction algorithm, but they do show that the candidate phosphorylation site has a slightly different sequence in Pm than in Et and Sp (Fig. S4A). With impressive rigor, the authors go on to mutate the PmAGS phosphorylation site to make it identical to Sp. Nothing happens. Vegetal cortical localization does not increase over AGS-PmGL alone. Micromere formation is unrescued.
There is therefore a logic problem in the text, or at least in the way the text is written. The paragraph begins "Additionally, AGS-PmGL unexpectedly showed cortical localization (Figure 5G), while PmAGS showed no cortical localization (Figure 5B)." We want to understand why this is true, but the explanation provided in the remainder of the paragraph doesn't match the question: according to quite a bit of their own data, the phosphorylation site in the linker does not explain the difference. It might explain why AGS-PmGL fails to promote micromere formation, but only if the AGS-PmGL chimeric protein uses the Pm linker domain (see above).
Another concern that is potentially related is the measurement of cortical signal. For example, in the control panel of Figure 5C, there is certainly a substantial amount of "non-cortical" signal that I believe is nuclear. I did not see a discussion of this signal or its implications. My impression of the pictures generally is that the nuclear signal and cortical signal are inversely correlated, which makes sense if they are derived from the same pool of total protein at different points of the cell cycle. If that's the case (and it might not be) I would expect some quantifications to be impacted. For example, the authors show in Figure S3B that AGS-S389A mutant does not localize to the cortex. However, this mutant shows a radically different localization pattern to the accompanying control picture (AGS), namely strong enrichment in what I assume to be the nucleus. Is the S389 mutant preventing AGS from making it to the cortex? Or are these pictures instead temporally distinct, meaning that AGS hasn't yet made it out of the nucleus? Notably, the work of Johnston et al. (Cell 2009), cited in the text, does not show or claim that the linker domain impacts Pins localization. Their model is rather that Pins is anchored at the cortex by Gαi, not Dlg, and that is the same model described in this manuscript. In agreement with that model and the results of Johnston et al., a later study (Neville et al. EMBO Reports 2023) failed to find a role for Dlg or the conserved phosphorylation site in Pins localization.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors identified nanobodies that were specific for the trypanosomal enzyme pyruvate kinase in previous work seeking diagnostic tools. They have shown that a site involved in the allosteric regulation of the enzyme is targeted by the nanobody and using elegant structural approaches to pinpoint where binding occurs, opening the way to the design of small molecules that could also target this site.
Strengths:
The structural work shows the binding of a nanobody to a specific site on Trypanosoma congolense pyruvate kinase and provides a good explanation as to how binding inhibits enzyme activity. The authors go on to show that by expressing the nanobodies within the parasites they can get some inhibition of growth, which albeit rather weak, they provide a case on how this could point to targeting the same site with small molecules as potential trypanocidal drugs.
Weaknesses:
The impact on growth is rather marginal. Although explanations are offered on the reasons for that, including the high turnover rate of the expressed nanobody and the difficulty in achieving the high levels of inhibition of pyruvate kinase required to impact energy production sufficiently to kill parasites, this aspect of the work doesn't offer great support to developing small molecule inhibitors of the same site.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Bloomington Stock Center
DOI: 10.1007/978-1-4939-8772-6_3
Resource: Bloomington Stock Center
Curator: @maulamb
SciCrunch record: Bloomington Stock Center
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chiselapp.com chiselapp.com
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Mapa mental
El mapa mental debería tener ramas más detalladas que permitan recuperar y justificar información incluso meses después de lo que estamos haciendo
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1. Cargué tres documentos, incluidos 2 PDF y un archivo de audio.
Me gustaría saber como lograste procesar el documento de audio, ¿estaba descargado previamente en el computador o copiaste el link?
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El ejercicio esta muy bien hecho, quizá lo que falta es interiorizar mejor algunos conceptos. Pero la manera en la que desarrolla el ejercicio y como lo explica deja claro la manera en la que Felipe se relaciona con la herramienta
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Con las preguntas realizadas, la herramienta brindó respuestas acertadas y precisas uniendo la información de los diferentes documentos cargados. En este caso fue verosimil, pero con un gran volumen de información puede que no acierte de la misma forma.
Sería conveniente agregar el hecho de que las respuestas dicen que apelan a más fuentes de las que realmente usan. Para ello es bueno tener la respuesta textual fuera de la captura de pantalla
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Buena presentación visual acompañada por capturas de pantalla. Sugeriría colocar respuestas textuales también, transcritas desde NucliaDB de manera que se puedan revisar en detalle fuera de la captura.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In the manuscript entitled "SARS-CoV-2 NSP13 interacts with TEAD to suppress Hippo-YAP signaling", Meng et al. report that SARS-CoV-2 infection disrupts YAP downstream gene transcription in both patient lung samples and the iPSC-cardiomyocytes. Among the tested SARS-CoV-2 proteins, the helicase nonstructural protein 13 (NSP13) was identified to target YAP transcriptional activity both in vitro and in vivo, independent of the Hippo pathway. Mechanistically, NSP13 inhibits YAP transcriptional activity through its interaction with TEAD4 and a group of nuclear repressor proteins, a process that requires its helicase activity. Overall, this study uncovers a novel regulation of the YAP/TEAD complex by SARS-CoV-2 infection, highlighting its impact on cellular signaling events. The manuscript is well-written and easy to follow. Here are some suggestions for the authors to further improve their work.
Major points
(1) The authors discovered a novel regulation of the Hippo-YAP pathway by SARS-CoV-2 infection but did not address the pathological significance of this finding. It remains unclear why YAP downstream gene transcription needs to be inhibited in response to SARS-CoV-2 infection. Is this inhibition crucial for the innate immune response to SARS-CoV-2? The authors should re-analyze their snRNA-seq and bulk RNA-seq data described in Figure 1 to determine whether any of the affected YAP downstream genes are involved in this process.
(2) The authors concluded that helicase activity is required for NSP13-induced inhibition of YAP transcriptional activity based on mutation studies (Figure 3B). This finding is somewhat confusing, as K131, K345/K347, and R567 are all essential residues for NSP13 helicase activity while mutating K131 did not affect NSP13's ability to inhibit YAP (Figure 3B). Additionally, there are no data showing exactly how NSP13 inhibits the YAP/TEAD complex through its helicase function. This point was also not reflected in their proposed working model (Figure 4H).
(3) The proposed model that NSP13 binds TEAD4 to recruit repressor proteins and inhibits YAP/TEAD downstream gene transcription (Figure 4H) needs further characterization. First, it is notable that the provided NSP13 IP-MS data did not reveal any TEAD family members as binding proteins for NSP13 (Supplement Figure 4C and the tables), suggesting that NSP13 may modulate the YAP/TEAD complex through other mechanisms, possibly involving other binding proteins. Second, NSP13 is a DNA-binding protein, and its nucleic acid-binding mutant K345A/K347A failed to inhibit YAP transcriptional activity (Figure 3B). The authors should investigate whether NSP13 could bind to the TEAD binding sequence or the nearby sequence on the genome to modulate TEAD's DNA binding ability. Third, regarding the identified nuclear repressors, the authors should validate the interaction of NSP13 with the ones whose loss activates YAP transcriptional activity (Figure 4G). Lastly, why can't NSP13 bind TEAD4 in the cytoplasmic fractionation if both NSP13 and TEAD4 are detected there (Figure 3B)? This finding indicates their interaction is not a direct protein-protein interaction but is mediated by something in the nucleus, such as genomic DNA.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Yun et al. examined the molecular and neuronal underpinnings of changes in Drosophila female reproductive behaviors in response to social cues. Specifically, the authors measure the ejaculate-holding period, which is the amount of time females retain male ejaculate after mating (typically 90 min in flies). They find that female fruit flies, Drosophila melanogaster, display shorter holding periods in the presence of a native male or male-associated cues, including 2-Methyltetracosane (2MC) and 7-Tricosene (7-T). They further show that 2MC functions through Or47b olfactory receptor neurons (ORNs) and the Or47b channel, while 7-T functions through ppk23 expressing neurons. Interestingly, their data also indicates that two other olfactory ligands for Or47b (methyl laurate and palmitoleic acid) do not have the same effects on the ejaculate-holding period. By performing a series of behavioral and imaging experiments, the authors reveal that an increase in cAMP activity in pC1 neurons is required for this shortening of the ejaculate-holding period and may be involved in the likelihood of remating. This work lays the foundation for future studies on sexual plasticity in female Drosophila.
The conclusions of this paper are supported by the data and the authors have revised the manuscript in accordance with comments of the reviewers. This revised version also contains the expression pattern of the lines used for modulating individual pC1 subtypes. These data and reagents open interesting avenues for future studies on female receptivity and mate choice.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The process of EMT is a major contributor of metastasis and chemoresistance in breast cancer. By using a modified PyMT model that allows identification of cells undergoing EMT and their decedents via S100A4-Cre mediated recombination of the mTmG allele, Ban et al. tackle a very important question of how tumor metastasis and therapy resistance by EMT can be blocked. They identified that pathways associated with ribosome biogenesis (RiBi) are activated during transition cell states. This finding represents a promising therapeutic target to block any transition from E to M (activated during cell dissemination and invasion) as well as from M to E (activated during metastatic colonization). Inhibition of RiBi-blocked EMT also reduced the establishment of chemoresistance that is associated with an EMT phenotype. Hence, RiBi blockage together with standard chemotherapy showed synergistic effects, resulting in impaired colonization/metastatic outgrowth in an animal model. The study is of great interest and of high clinical relevance as the authors show that blocking the transition from E to M or vice versa targets both aspects of metastasis, dissemination form the primary tumor and colonization in distant organs.
The study is done with high skill using state of the art technology and the conclusions are convincing and solid, but some aspects require some additional experimental support and clarification. It remains elusive whether blocking of EMT/MET is necessary for the synergistic effect of standard chemotherapy together with RiBi blockage or whether a general growth disadvantage of RiBi treated cells independent of blocking transition is responsible. How can specific effect on state transition by RiBI block be seperated from global effects attributed to overall reduced protein biosynthesis, proliferation etc.? Some other aspects are misleading or need extension:
In the revised version, the authors appropriately addressed all my comments. I'd like to congratulate the authors for this wonderful work!
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
This study reports a physical interaction between the kinase DYRK1A and the Tuberous Sclerosis Complex (TSC) protein complex (TSC1, TSC2, TBC1D7). Furthermore, this study demonstrates that DYRK1A, upon interaction with the TSC proteins, regulates mTORC1 activity and cell size. Additionally, this study identifies T1462 on TSC2 as a phosphorylation target of DYRK1A. Finally, the authors demonstrate that DYRK1A impacts cell size using human, mouse and Drosophila cells.
The interaction described here is highly impactful to the field of mTORC1-regulated cell growth and uncovers a previously unrecognized TSC-associated interacting protein. DYRK1A and its regulation of mTORC1 activation may have an impact for multiple diseases in which mTORC1 is hyperactivated.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Working memory is imperfect - memories accrue error over time and are biased towards certain identities. For example, previous work has shown memory for orientation is more accurate near the cardinal directions (i.e., variance in responses is smaller for horizontal and vertical stimuli) while being biased towards diagonal orientations (i.e., there is a repulsive bias away from horizontal and vertical stimuli). The magnitude of errors and biases increase the longer an item is held in working memory and when more items are held in working memory (i.e., working memory load is higher). Previous work has argued that biases and errors could be explained by increased perceptual acuity at cardinal directions. However, these models are constrained to sensory perception and do not explain how biases and errors increase over time in memory. The current manuscript builds on this work to show how a two-layer neural network could integrate errors and biases over a memory delay. In brief, the model includes a 'sensory' layer with heterogenous connections that lead to the repulsive bias and decreased error at the cardinal directions. This layer is then reciprocally connected with a classic ring attractor layer. Through their reciprocal interactions, the biases in the sensory layer are constantly integrated into the representation in memory. In this way, the model captures the distribution of biases and errors for different orientations that has been seen in behavior and their increasing magnitude with time. The authors compare the two-layer network to a simpler one-network model, showing that the one model network is harder to tune and shows an attractive bias for memories that have lower error (which is incompatible with empirical results).
Strengths:
The manuscript provides a nice review of the dynamics of items in working memory, showing how errors and biases differ across stimulus space. The two-layer neural network model is able to capture the behavioral effects as well as relate to neurophysiological observations that memory representations are distributed across sensory cortex and prefrontal cortex.
The authors use multiple approaches to understand how the network produces the observed results. For example, analyzing the dynamics of memories in the low-dimensional representational space of the networks provides the reader with an intuition for the observed effects.
As a point of comparison with the two-layer network, the authors construct a heterogenous one-layer network (analogous to a single memory network with embedded biases). They argue that such a network is incapable of capturing the observed behavioral effects but could potentially explain biases and noise levels in other sensory domains where attractive biases have lower errors (e.g., color).
The authors show how changes in the strength of Hebbian learning of excitatory and inhibitory synapses can change network behavior. This argues for relatively stronger learning in inhibitory synapses, an interesting prediction.
The manuscript is well-written. In particular, the figures are well done and nicely schematize the model and the results.
Weaknesses:
Despite its strengths, the manuscript does have some weaknesses. These weaknesses are adequately discussed in the manuscript and motivate future research.
One weakness is that the model is not directly fit to behavioral data, but rather compared to a schematic of behavioral data. As noted above, the model provides insight into the general phenomenon of biases in working memory. However, because the models are not fit directly to data, they may miss some aspects of the data.
In addition, directly fitting the models to behavioral data could allow for a broader exploration of parameter space for both the one-layer and two-layer models (and their alternatives). Such an approach would provide stronger support for the papers claims (such as "....these evolving errors...require network interaction between two distinct modules."). That being said, the manuscript does explore several alternative models and also acknowledges the limitation of not directly fitting behavior, due to difficulties in fitting complex neural network models to data.
One important behavioral observation is that both diffusive noise and biases increase with the number of items in working memory. The current model does not capture these effects and it isn't clear how the model architecture could be extended to capture these effects. That being said, the authors note this limitation in the Discussion and present it as a future direction.
Overall:
Overall, the manuscript was successful in building a model that captured the biases and noise observed in working memory. This work complements previous studies that have viewed these effects through the lens of optimal coding, extending these models to explain the effects of time in memory. In addition, the two-layer network architecture extends previous work with similar architectures, adding further support to the distributed nature of working memory representations.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This work by Stauber et al., is focused on understanding the signaling mechanisms that are associated with tendinopathy development, and by screening a panel of human tendinopathy samples, identified IL-6/JAK/STAT as a potential mediator of this pathology. Using an innovate explant model they delineated the requirement for IL-6 in the main body of the tendon to alter the dynamics of extrinsic fibroblasts. These studies are complemented by in vivo studies that include a Scx-GFP reporter. This approach facilitates examination of the effects of IL6-/- on Scx+ cells, and the differences observed between ex vivo and in vivo contexts.
The use of a publicly available existing dataset is considered a strength, since this dataset includes expression data from several different human tendons experiencing tendinopathy. The revised analysis that includes only non-sheathed tendons facilitates the identification of potentially conserved regulators of the tendinopathy phenotype, with immunostaining for CD90, IL-6R, and IL-6 expression in human tendinopathy samples providing important validation of the transcriptomic studies.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In their paper, Hou and co-workers explored the use of a FRET sensor for endogenous g-sec activity in vivo in the mouse brain. They used AAV to deliver the sensor to the brain for neuron specific expression and applied NIR in cranial windows to assess FRET activity; optimizing as well an imaging and segmentation protocol. In brief they observe clustered g-sec activity in neighboring cells arguing for a cell non-autonomous regulation of endogenous g-sec activity in vivo.
Strengths:
Mone.
Weaknesses:
Overall the authors provide a very limited data set and in fact only a proof of concept that their sensor can be applied in vivo. This is not really a research paper, but a technical note. With respect to their observation of clustered activity, they now provide an overview image, next to zoomed details. However, from these images one cannot conclude 'by eye' any clustering event. This aligns with the very low r values. All neurons in the field show variable activity and a clustering is not really evident from these examples. Even within a cluster, there is variability. The authors now confirm that expression levels are indeed variable but are independent from the ratio measurements. Further, they controlled for specificity by including DAPT treatments, but opposite to their own in vitro data (in primary neurons) the ratios increased. The authors argue that both distance and orientation can either decrease or increase ratios and that the use of this biosensor should be explored model-by-model. This doesn't really confer high confidence and may hinder other groups in using this sensor reliably.
Secondly, there is still no physiological relevance for this observation. The experiments are performed in wild-type mice, but it would be more relevant to compare this with a fadPSEN1 KI or a PSEN1cKO model to investigate the contribution of a gain of toxic function or LOF to the claimed cell non-autonomous activations. The authors acknowledge this shortcoming but argue that this is for a follow-up study.
For instance, they only monitor activity in cell bodies, and miss all info on g-sec activity in neurites and synapses: what is the relevance of the cell body associated g-sec and can it be used as a proxy for neuronal g-sec activity? If cells 'communicate' g-sec activities, I would expect to see hot spots of activity at synapses between neurons.
Without some more validation and physiologically relevant studies, it remains a single observation and rather a technical note paper, instead of a true research paper.
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Reviewer #1 (Public Review):
Summary:
This paper suggests to apply intrinsically-motivated exploration for the discovery of robust goal states in gene regulatory networks.
Strengths:
The paper is well written. The biological motivation and the need for such methods are formulated extraordinarily well. The battery of experimental models is impressive.
Weaknesses:
(1) The proposed method is compared to the random search. That says little about the performance with regard to the true steady-state goal sets. The latter could be calculated at least for a few simple ODE (e.g., BIOMD0000000454, `Metabolic Control Analysis: Rereading Reder'). The experiment with 'oscillator circuits' may not be directly interpolated to the other models.
The lack of comparison to the ground truth goal set (attractors of ODE) from arbitrary initial conditions makes it hard to evaluate the true performance/contribution of the method. A part of the used models can be analyzed numerically using JAX, while there are models that can be analyzed analytically.
"...The true versatility of the GRN is unknown and can only be inferred through empirical exploration and proxy metrics....": one could perform a sensitivity analysis of the ODEs, identifying stable equilibria. That could provide a proxy for the ground truth 'versatility'.
(2) The proposed method is based on `Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning', which assumes state action trajectories [s_{t_0:t}, a_{t_0:t}], (2.1 Notations and Assumptions' in the IMGEP paper). However, the models used in the current work do not include external control actions, but rather only the initial conditions can be set. It is not clear from the methods whether IMGEP was adapted to this setting, and how the exploration policy was designed w/o actual time-dependent actions. What does "...generates candidate intervention parameters to achieve the current goal...."<br /> mean considering that interventions 'Sets the initial state...' as explained in Table 2?
(3) Fig 2 shows the phase space for (ERK, RKIPP_RP) without mentioning the typical full scale of ERK, RKIPP_RP. It is unclear whether the path from (0, 0) to (~0.575, ~3.75) at t=1000 is significant on the typical scale of this phase space. is it significant on the typical scale of this phase space?
(4) Table 2:<br /> (a) Where is 'effective intervention' used in the method?<br /> (b) In my opinion 'controllability', 'trainability', and 'versatility' are different terms. If there correspondence is important I would suggest to extend/enhance the column "Proposed Isomorphism". otherwise, it may be confusing. I don't see how this table generalizes generalizes "concepts from dynamical complex systems and behavioral sciences under a common navigation task perspective".
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The manuscript by Wang et al is, like its companion paper, very unusual in the opinion of this reviewer. It builds off of the companion theory paper's exploration of the "Wright-Fisher Haldane" model but applies it to the specific problem of diversity in ribosomal RNA arrays. The authors argue that polymorphism and divergence among rRNA arrays are inconsistent with neutral evolution, primarily stating that the amount of polymorphism suggests a high effective size and thus a slow fixation rate, while we, in fact, observe relatively fast fixation between species, even in putatively non-functional regions. They frame this as a paradox in need of solving, and invoke the WFH model.
The same critiques apply to this paper as to the presentation of the WFH model and the lack of engagement with the literature, particularly concerning Cannings models and non-diffusive limits. However, I have additional concerns about this manuscript, which I found particularly difficult to follow.
My first, and most major, concern is that I can never tell when the authors are referring to diversity in a single copy of an rRNA gene compared to when they are discussing diversity across the entire array of rRNA genes. I admit that I am not at all an expert in studies of rRNA diversity, so perhaps this is a standard understanding in the field, but in order for this manuscript to be read and understood by a larger number of people, these issues must be clarified.
The authors frame the number of rRNA genes as roughly equivalent to expanding the population size, but this seems to be wrong: the way that a mutation can spread among rRNA gene copies is fundamentally different than how mutations spread within a single copy gene. In particular, a mutation in a single copy gene can spread through vertical transmission, but a mutation spreading from one copy to another is fundamentally horizontal: it has to occur because some molecular mechanism, such as slippage, gene conversion, or recombination resulted in its spread to another copy. Moreover, by collapsing diversity across genes in an rRNA array, the authors are massively increasing the mutational target size.
For example, it's difficult for me to tell if the discussion of heterozygosity at rRNA genes in mice starting on line 277 is collapsed or not. The authors point out that Hs per kb is ~5x larger in rRNA than the rest of the genome, but I can't tell based on the authors' description if this is diversity per single copy locus or after collapsing loci together. If it's the first one, I have concerns about diversity estimation in highly repetitive regions that would need to be addressed, and if it's the second one, an elevated rate of polymorphism is not surprising, because the mutational target size is in fact significantly larger.
Even if these issues were sorted out, I'm not sure that the authors framing, in terms of variance in reproductive success is a useful way to understand what is going on in rRNA arrays. The authors explicitly highlight homogenizing forces such as gene conversion and replication slippage but then seem to just want to incorporate those as accounting for variance in reproductive success. However, don't we usually want to dissect these things in terms of their underlying mechanism? Why build a model based on variance in reproductive success when you could instead explicitly model these homogenizing processes? That seems more informative about the mechanism, and it would also serve significantly better as a null model, since the parameters would be able to be related to in vitro or in vivo measurements of the rates of slippage, gene conversion, etc.
In the end, I find the paper in its current state somewhat difficult to review in more detail, because I have a hard time understanding some of the more technical aspects of the manuscript while so confused about high-level features of the manuscript. I think that a revision would need to be substantially clarified in the ways I highlighted above.
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Reviewer #1 (Public Review):
In this manuscript, Lee et al. compared encoding of odor identity and value by calcium signaling from neurons in the ventral pallidum (VP) in comparison to D1 and D2 neurons in the olfactory tubercle (OT).
Strengths:
They utilize a strong comparative approach, which allows the comparison of signals in two directly connected regions. First, they demonstrate that both D1 and D2 OT neurons project strongly to the VP, but not the VTA or other examined regions, in contrast to accumbal D1 neurons which project strongly to the VTA as well as the VP. They examine single unit calcium activity in a robust olfactory cue conditioning paradigm that allows them to differentiate encoding of olfactory identity versus value, by incorporating two different sucrose, neutral and air puff cues with different chemical characteristics. They then use multiple analytical approaches to demonstrate strong, low-dimensional encoding of cue value in the VP, and more robust, high-dimensional encoding of odor identity by both D1 and D2 OT neurons, though D1 OT neurons are still somewhat modulated by reward contingency/value. Finally, they utilize a modified conditioning paradigm that dissociates reward probability and lick vigor to demonstrate that VP encoding of cue value is not dependent on encoding of lick vigor during sucrose cues, and that separable populations of VP neuros encode cue value/sucrose probability and lick vigor. Direct comparisons of single unit responses between the two regions now utilize linear mixed effects models with random effects for subject,
Weaknesses:
The manuscript still includes mention of differences in effect size or differing "levels" of significance between VP and OT D1 neurons without reports of a direct comparisons between the two populations. This is somewhat mitigated by the comprehensive statistical reporting in the supplemental information, but interpretation of some of these results is clouded by the inclusion of OT D2 neurons in these analyses, and the limited description or contextualization in the main text.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This work explored intra and interspecific niche partitioning along spatial, temporal, and dietary niche partitioning between apex carnivores and mesocarnivores in the Qilian Mountain National Park of China, using camera trapping data and DNA metabarcoding sequencing data. They conclude that spatial niche partitioning plays a key role in facilitating the coexistence of apex carnivore species, spatial and temporal niche partitioning facilitate the coexistence of mesocarnivore species, and spatial and dietary niche partitioning facilitate the coexistence between apex and mesocarnivore species. The information presented in this study is important for wildlife conservation and will contribute substantially to the current understanding of carnivore guilds and effective conservation management in fragile alpine ecosystems.
Strengths:
Extensive fieldwork is evident in the study. Aiming to cover a large percentage of the Qilian Mountain National Park, the study area was subdivided into squares, as a geographical reference to distribute the sampling points where the camera traps were placed and the excreta samples were collected.
They were able to obtain many records in their camera traps and collected many samples of excreta. This diversity of data allowed them to conduct robust analyses. The data analyses carried out were adequate to obtain clear and meaningful results that enabled them to answer the research questions posed. The conclusions of this paper are mostly well supported by data.
The study has demonstrated the coexistence of carnivore species in the landscapes of the Qilian Mountains National Park, complementing the findings of previous studies. The information presented in this study is important for wildlife conservation and will contribute substantially to the current understanding of carnivore guilds and effective conservation management in fragile alpine ecosystems.
Weaknesses:
It is necessary to better explain the methodology because it is not clear what is the total sampling effort. In methodology, they only claim to have used 280 camera traps, and in the results, they mention that there are 319 sampling sites. However, the total sampling effort (e.g. total time of active camera traps) carried out in the study and at each site is not specified.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Kainate receptors play various important roles in synaptic transmission. The receptors can be divided into low affinity kainate receptors (GluK1-3) and high affinity kainate receptos (GluK4-5). The receptors can assemble as homomers (GluK1-3) or low-high affinity heteromers (GluK4-5). The functional diversity is further increased by RNA splicing. Previous studies have investigated C-terminal splice variants of GluK1, but GluK1 N-terminal (exon 9) insertions have not been previously characterized. In this study Dhingra et al investigate the functional implications of a GluK1 splice variant that inserts a 15 amino acid segment into the extracellular N-terminal region of the protein using whole-cell and excised outside-out electrophysiology.<br /> The authors convincingly show that the insertion profoundly impacts the function of GluK1-1a - the channels that have the insertion are slower to desensitize. The data also shows that the insertion changes the modulatory effects of Neto proteins, resulting in altered rates of desensitization and recovery from desensitization. To determine the mechanism by which the insertion exerts these functional effects, the authors perform pull-down assays of Neto proteins, and extensive mutagenesis on the insert.<br /> The electrophysiological part of the study is very rigorous and meticulous.
The biggest weakness of the manuscript is the structural work. Due to issues with preferred orientation (a common problem in cryo-EM), the 3D reconstructions are at a low resolution (in the 5-8 Å range) and cannot offer much mechanistic insight into the effects of the insertion. Based on the available data, the authors posit that the insertion does not change the arrangement of the subunits in the desensitized state. However, there is no comparison with a structure that does not contain the insertion, so while the statement may well be true, no data is shown to support it.
Overall, the cryo-EM contributes little and distracts from the good parts of the manuscript.
Another part that does not contribute much is the RNAseq data that has been pulled from a database and analyzed for the paper. It is being used to show that the exon 9 insertion variant is predominantly expressed in the cerebellar cortex at early stages of brain development. The methods do not describe in detail how the data has been analyzed (e.g., is the data scaled per sample/gene or globally?) so it is hard to know what we can compare in the heat plots. In Figure 1- supplement 1 there aren't striking differences in expression (at least not obviously visible in the current illustration).
Despite these weaknesses, the study is a valuable contribution to the field because it characterizes a GluK1 variant that has not been studied before and highlights the functional diversity that exists within the kainate receptor family.
Revised manuscript:
The authors have clarified some of the issues raised by the reviewers, but no new data has been added to strengthen the manuscript. The structural part of the manuscript remains its weakest point, and the extent of mechanistic insight remains low.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
This study examines lipid profiles in cancer patients treated with the neurotoxic chemotherapy paclitaxel. Multiple methods, including machine learning as well as more conventional statistical modelling, were used to classify lipid patterns before and after paclitaxel treatment and in conjunction with neuropathy status. Lipid profiles before and after paclitaxel therapy were analysed from 31 patients. The study aimed to characterize from the lipid profile if plasma samples were collected pre paclitaxel or post paclitaxel and their relevance to neuropathy status. Sphingolipids including sphinganine-1-phosphate (SA1P) differed between patients with and without neuropathy. To examine the potential role of SA1P, it was applied to murine primary sensory neuron cultures, and produced calcium transients in a proportion of neurons. This response was abolished by application of a TRPV1 antagonist. The number of neurons responding to SA1P was partially reduced by the sphingosine 1-phosphate receptor (S1PR1) modulator fingolimod.
Strengths:
The strengths of this study include the use of multiple methods to classify lipid patterns and the attempt to validate findings from the clinical cohort in a preclinical model using primary sensory neurons.
Weaknesses:
These still stand from the original review and are repeated here:
There are a number of weaknesses in the study. The small sample size is a significant limitation of the study. Out of 31 patients, only 17 patients were reported to develop neuropathy, with significant neuropathy (grade 2/3) in only 5 patients. The authors acknowledge this limitation in the results and discussion sections of the manuscript, but it limits the interpretation of the results. Also acknowledged is the limited method used to assess neuropathy.
Potentially due to this small number of patients with neuropathy, the machine learning algorithms could not distinguish between samples with and without neuropathy. Only selected univariate analyses identified differences in lipid profiles potentially related to neuropathy.
Three sphingolipid mediators including SA1P differed between patients with and without neuropathy at the end of treatment. These sphingolipids were elevated at end of treatment in the cohort with neuropathy, relative to those without neuropathy. However, across all samples from pre to pos- paclitaxel treatment, there was a significant reduction in SA1P levels. It is unclear from the data presented what the underlying mechanism for this result would be. If elevated SA1P is associated with neuropathy development, it would be expected to increase in those who develop neuropathy from pre to post-treatment timepoints.
Primary sensory neuron cultures were used to examine the effects of SA1P application. SA1P application produced calcium transients in a small proportion of sensory neurons. It is not clear how this experimental model assists in validating the role of SA1P in neuropathy development as there is no assessment of sensory neuron damage or other hallmarks of peripheral neuropathy. These results demonstrate that some sensory neurons respond to SA1P and that this activity is linked to TRPV1 receptors. However, further studies will be required to determine if this is mechanistically related to neuropathy.
Impact:
Taken in total, the data presented do not provide sufficient evidence to support the contention that SA1P has an important role in paclitaxel induced peripheral neuropathy. Further, the results do not provide evidence to support the use of S1PR1 receptor antagonists as a therapeutic strategy. It is important to be careful with language use in the discussion, as the significance of the present results are overstated.
However, based on the results of previous studies, it is likely that sphingolipid metabolism plays a role in chemotherapy induced peripheral neuropathy. Based on this existing evidence, the S1PR1 receptor antagonist fingolimod has already been examined in experimental models and in clinical trials. Further work is needed to examine the links between lipid mediators and neuropathy development and identify additional strategies for intervention.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
The authors performed a Multi-Omics Factor Analysis (MOFA) on analysis of two published MDS patient cohorts-1 from bone marrow mononuclear cells (BMMNCs) and CD34 cells (ref 17) and another from CD34+ cells (ref 15) --with three data modalities (clinical, genotype, and transcriptomics). Seven different views, including immune profile, inflammation/aging, Retrotransposon (RTE) expression, and cell- type composition, were derived from these modalities to attempt to identify the latent factors with significant impact on MDS prognosis.
SF3B1 was found to be the only mutation among 13 mutations in the BMMNC cohort that indicated a significant association with high inflammation. This trend was also observed to a lesser extent in the CD34+ cohort. The MOFA factor representing inflammation showed a good prognosis for MDS patients with high inflammation. In contrast, SRSF2 mutant cases showed a granulocyte-monocyte progenitor (GMP) pattern and high levels of senescence, immunosenescence, and malignant myeloid cells, consistent with their poor prognosis. Also, MOFA identified RTE expression as a risk factor for MDS. They proposed that this work showed the efficacy of their integrative approach to assess MDS prognostic risk that 'goes beyond all the scoring systems described thus far for MDS'.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):<br /> The authors present the cryo-EM structure of of PSI-fucoxanthin chlorophyll a/c-binding proteins (FCPs) supercomplex from the diatom Thalassiosira pseudonana CCMP1335 at a global resolution of 2.3 Å. This exceptional resolution allows the authors to construct a near-atomic model of the entire supercomplex and elucidate the molecular details of FCPs arrangement. The high-resolution structure reveals subunits not previously identified in earlier reconstructions and models, as well as sequence analysis of PSI-FCPIs from other diatoms and red algae. Additionally, the authors use their model in conjunction with a phylogenetic analysis to compare and contrast the structural features of the T. pseudonana supercomplex with those of Chaetoceros gracilis, uncovering key structural features that contribute to the efficiency of light energy conversion in diatoms.
The study employs the advanced technique of single particle cryo-electron microscopy to visualize the complex architecture of the PSI supercomplex at near-atomic resolution and analyze the specific roles of FCPs in enhancing photosynthetic performance in diatoms.
Overall, the approach and data are both compelling and of high quality. The paper is well written and will be of wide interest for comprehending the molecular mechanisms of photosynthesis in diatoms. This work provides valuable insights for applications in bioenergy, environmental conservation, plant physiology, and membrane protein structural biology.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The study by Wu et al presents interesting data on bacterial cell organization, a field that is progressing now, mainly due to the advances in microscopy. Based mainly on fluorescence microscopy images, the authors aim to demonstrate that the two structures that account for bacterial motility, the chemotaxis complex and the flagella, colocalize to the same pole in Pseudomonas aeruginosa cells and to expose the regulation underlying their spatial organization and functioning.
Strengths:
The subject is of importance.
Weaknesses:
The conclusions are too strong for the presented data. The lack of statistical analysis makes this paper incomplete. The novelty of the findings is not clear.
Major issues:
(1) The novelty is in question since in the Abstract the authors highlight their main finding, which is that both the chemotaxis complex and the flagella localize to the same pole, as surprising. However, in the Introduction they state that "pathway-related receptors that mediate chemotaxis, as well as the flagellum are localized at the same cell pole17,18". I am not a pseudomonas researcher and from my short glance at these references, I could not tell whether they report colocalization of the two structures to the same pole. However, I trust the authors that they know the literature on the localization of the chemotaxis complex and flagella in their organism. See also major issue number 5 on the novelty regarding the involvement of c-di-GMP.
(2) Statistics for the microscopy images, on which most conclusions in this manuscript are based, are completely missing. Given that most micrographs present one or very few cells, together with the fact that almost all conclusions depend on whether certain macromolecules are at one or two poles and whether different complexes are in the same pole, proper statistics, based on hundreds of cells in several fields, are absolutely required. Without this information, the results are anecdotal and do not support the conclusions. Due to the importance of statistics for this manuscript, strict statistical tests should be used and reported. Moreover, representative large fields with many cells should be added as supportive information.
The problem is more pronounced when the authors make strong statements, as in lines 157-158: "The results revealed that the chemoreceptor arrays no longer grow robustly at the cell pole (Figure 2A)". Looking at the seven cells shown in Figure 2A, five of them show polar localization of the chemoreceptors. The question is then: what is the percentage of cells that show precise polar, near-polar, or mid cell localization (the three patterns shown here) in the mutant and in the wild type? Since I know that these three patterns can also be observed in WT cells, what counts is the difference, and whether it is statistically significant.
Even for the graphs shown in Figures 3C and 3D, where the proportion of cells with obvious chemoreceptor arrays and absolute fluorescence brightness of the chemosensory array are shown, respectively, the questions that arise are: for how many individual cells these values hold and what is the significance of the difference between each two strains?
(3) The authors conclude that "Motor structural integrity is a prerequisite for chemoreceptor self-assembly" based on the reduction in cells with chemoreceptor clusters in mutants deleted for flagellar genes, despite the proper polar localization of the chemotaxis protein CheY. They show that the level of CheY in the WT and the mutant strains is similar, based on Western blot, which in my opinion is over-exposed. "To ascertain whether it is motor integrity rather than functionality that influences the efficiency of chemosensory array assembly", they constructed a mutant deleted for the flagella stator and found that the motor is stalled while CheY behaves like in WT cells. The authors further "quantified the proportion of cells with receptor clusters and the absolute fluorescence intensity of individual clusters (Figures 3C-D)". While Figure 3DC suggests that, indeed, the flagella mutants show fewer cells with a chemotaxis complex, Figure 3D suggests that the differences in fluorescence intensity are not statistically significant.
Since it is obvious that the regulation of both structures' production and localization is codependent, I think that it takes more than a Western blot to make such a decision.
(4) I wonder why the authors chose to label CheY, which is the only component of the chemotaxis complex that shuttles back and forth to the base of the flagella. In any case, I think that they should strengthen their results by repeating some key experiments with labeled CheW or CheA.
(5) The last section of the results is very problematic, regarding the rationale, the conclusions, and the novelty. As far as the rationale is concerned, I do not understand why the authors assume that "a spatial separation between the chemoreceptors and flagellar motors should not significantly impact the temporal comparison in bacterial chemotaxis". Is there any proof for that? More surprising for me was to read that "The signal transduction pathways in E. coli are relatively simple, and the chemotaxis response regulator CheY-P affects only the regulation of motor switching". There are degrees of complexity among signal transduction pathways in E. coli, but the chemotaxis seems to be ranked at the top. CheY is part of the adaptation. Perfect adaptation, as many other issues related to the chemotaxis pathway, which include the wide dynamic range, the robustness, the sensitivity, and the signal amplification (gain), are still largely unexplained. Hence, such assumptions are not justified.
More perplexing is the novelty of the authors' documentation of the effect of the chemotaxis proteins on the c-di-GMP level. In 2013, Kulasekara et al. published a paper in eLife entitled "c-di-GMP heterogeneity is generated by the chemotaxis machinery to regulate flagellar motility". In the same year, Kulasekara published a paper entitled "Insight into a Mechanism Generating Cyclic di-GMP Heterogeneity in Pseudomonas aeruginosa". The authors did not cite these works and I wonder why.
(6) Throughout the manuscript, the authors refer to foci of fluorescent CheY as "chemoreceptor arrays". If anything, these foci signify the chemotaxis complex, not the membrane-traversing chemoreceptors.
Conclusions:
The manuscript addresses an interesting subject and contains interesting, but incomplete, data.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this manuscript, the authors employ a combined proteomic and genetic approach to identify the glycoprotein QC factor malectin as an important protein involved in promoting coronavirus infection. Using proteomic approaches, they show that the non-structural protein NSP2 and malectin interact in the absence of viral infection, but not in the presence of viral infection. However, both NSP2 and malectin engage the OST complex during viral infection, with malectin also showing reduced interactions with other glycoprotein QC proteins. Malectin KD reduce replication of coronaviruses, including SARS-COV2. Collectively, these results identify Malectin as a glycoprotein QC protein involved in regulating coronavirus replication that could potentially be targeted to mitigate coronavirus replication.
Overall, the experiments described appear well performed and the interpretations generally reflect the results. Moreover, this work identifies Malectin as an important pro-viral protein whose activity could potentially be therapeutically targeted for the broad treatment of coronavirus infection. However, there are some weaknesses in the work that, if addressed, would improve the impact of the manuscript.
Notably, the mechanism by which malectin regulates viral replication is not well described. It is clear from the work that malectin is a pro-viral protein in the work presented, but the mechanistic basis of this activity is not pursued. Some potential mechanisms are proposed in the discussion, but the manuscript would be strengthened if additional insight was included. For example, does the UPR activated to higher levels in infected cells depleted of malectin? Do glycosylation patterns of viral (or non-viral) proteins change in malectin-depleted cells? Additional insight into this specific question would significantly improve the manuscript.
Further, the evidence for increased interactions between OST and malectin during viral infection is fairly weak, despite being a major talking point throughout the manuscript. The reduced interactions between malectin and other glycoproteostasis QC factors is evident, but the increased interactions with OST are not well supported. I'd recommend backing off on this point throughout the text, instead, continuing to highlight the reduced interactions.
I was also curious as to why non-structural proteins, nsp2 and nsp4, showed robust interactions with host proteins localized to both the ER and mitochondria? Do these proteins localize to different organelles or do these interactions reflect some other type of dysregulation? It would be useful to provide a bit of speculation on this point.
Again, the overall identification of malectin as a pro-viral protein involved in the replication of multiple different coronaviruses is interesting and important, but additional insights into the mechanism of this activity would strengthen the overall impact of this work.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
EnvA-pseudotyped glycoprotein-deleted rabies virus has emerged as an essential tool for tracing monosynaptic inputs to genetically defined neuron populations in the mammalian brain. Recently, in addition to the SAD B19 rabies virus strain first described by Callaway and colleagues in 2007, the CVS N2c rabies virus strain has become popular due to its low toxicity and high trans-synaptic transfer efficiency. However, despite its widespread use in the mammalian brain, particularly in mice, the application of this cell-type-specific monosynaptic rabies tracing system in zebrafish has been limited by low labeling efficiency and high toxicity. In this manuscript, the authors aimed to develop an efficient retrograde monosynaptic rabies-mediated circuit mapping tool for larval zebrafish. Given the translucent nature of larval zebrafish, whole-brain neuronal activities can be monitored, perturbed, and recorded over time. Introducing a robust circuit mapping tool for larval zebrafish would enable researchers to simultaneously investigate the structure and function of neural circuits, which would be of significant interest to the neural circuit research community. Furthermore, the ability to track rabies-labeled cells over time in the transparent brain could enhance our understanding of the trans-synaptic retrograde tracing mechanism of the rabies virus.
To establish an efficient rabies virus tracing system in the larval zebrafish brain, the authors conducted meticulous side-by-side experiments to determine the optimal combination of trans-expressed rabies G proteins, TVA receptors, and recombinant rabies virus strains. Consistent with observations in the mouse brain, the CVS N2c strain trans-complemented with N2cG was found to be superior to the SAD B19 combination, offering lower toxicity and higher efficiency in labeling presynaptic neurons. Additionally, the authors tested various temperatures for the larvae post-virus injection and identified 36{degree sign}C as the optimal temperature for improved virus labeling. They then validated the system in the cerebellar circuits, noting evolutionary conservation in the cerebellar structure between zebrafish and mammals. The monosynaptic inputs to Purkinje cells from granule cells were neatly confirmed through ablation experiments.
However, there are a couple of issues that this study should address. Additionally, conducting some extra experiments could provide valuable information to the broader research field utilizing recombinant rabies viruses as retrograde tracers.
(1) It was observed that many radial glia were labeled, which casts doubt on the specificity of trans-synaptic spread between neurons. The issues of transneuronal labeling of glial cells should be addressed and discussed in more detail. In this manuscript, the authors used a transgenic zebrafish line carrying a neuron-specific Cre-dependent reporter and EnvA-CVS N2c(dG)-Cre virus to avoid the visualization of virally infected glial cells. However, this does not solve the real issue of glial cell labeling and the possibility of a non-synaptic spread mechanism.
In addition, wrong citations in Line 307 were made when referring to previous studies discovering the same issue of RVdG-based transneuronal labeling radial glial cells.
"The RVdG-based transneuronal labeling of radial glial cells was commonly observed in larval zebrafish29,30".
The cited work was conducted using vesicular stomatitis virus (VSV). A more thorough analysis and/or discussion on this topic should be included. Several key questions should be addressed:
Does the number of labeled glial cells increase over time?<br /> Do they increase at the same rate over time as labeled neurons?<br /> Are the labeled glial cells only present around the injection site?<br /> Can the phenomenon of transneuronal labeling of radial glial cells be mitigated if the tracing is done in slightly older larvae?<br /> What is the survival rate of the infected glial cells over time?<br /> If an infected glial cell dies due to infection or gets ablated, does the rabies virus spread from the dead glial cells?<br /> If TVA and rabies G are delivered to glial cells, followed by rabies virus injection, will it lead to the infection of other glial cells or neurons?
Answers to any of these questions could greatly benefit the broader research community.
(2) The optimal virus tracing effect has to be achieved by raising the injected larvae at 36C. Since the routine temperature of zebrafish culture is around 28C, a more thorough characterization of the effect on the health of zebrafish should be conducted.
(3) Given the ability of time-lapse imaging of the infected larval zebrafish brain, the system can be taken advantage of to tackle important issues of rabies virus tracing tools.<br /> a) Toxicity.<br /> The toxicity of rabies viruses is an important issue that limits their application and affects the interpretation of traced circuits. For example, if a significant proportion of starter cells die before analysis, the traced presynaptic networks cannot be reliably assigned to a "defined" population of starter cells. In this manuscript, the authors did an excellent job of characterizing the effects of different rabies strains, G proteins derived from various strains, and levels of G protein expression on starter cell survival. However, an additional parameter that should be tested is the dose of rabies virus injection. The current method section states that all rabies virus preparations were diluted to 2x10^8 infection units per ml, and 2-5 nl of virus suspension was injected near the target cells. It would be interesting to know the impact of the dose/volume of virus injection on retrograde tracing efficiency and toxicity. Would higher titers of the virus lead to more efficient labeling but stronger toxicities? What would be the optimal dose/volume to balance efficiency and toxicity? Addressing these questions would provide valuable insights and help optimize the use of rabies viruses for circuit tracing.
b) Primary starters and secondary starters:<br /> Given that the trans-expression of TVA and G is widespread, there is the possibility of coexistence of starter cells from the initial infection (primary starters) and starter cells generated by rabies virus spreading from the primary starters to presynaptic neurons expressing G. This means that the labeled input cells could be a mixed population connected with either the primary or secondary starter cells.
It would be immensely interesting if time-lapse imaging could be utilized to observe the appearance of such primary and secondary starter cells. Assuming there is a time difference between the initial appearance of these two populations, it may be possible to differentiate the input cells wired to these populations based on a similar temporal difference in their initial appearance. This approach could provide valuable insights into the dynamics of rabies virus spread and the connectivity of neural circuits.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Wang, Y. et al. used a silicone wire embolus to definitively and acutely clot the pterygopalatine ophthalmic artery in addition to carotid artery ligation to completely block blood supply to the mouse inner retina, which mimic clinical acute retinal artery occlusion. A detailed characterization of this mouse model determined the time course of inner retina degeneration and associated functional deficits, which closely mimic human patients. Whole retina transcriptome profiling and comparison revealed distinct features associated with ischemia, reperfusion, and different model mechanisms. Interestingly and importantly, this team found a sequential event including reperfusion-induced leukocyte infiltration from blood vessels, residual microglial activation, and neuroinflammation that may lead to neuronal cell death.
Strengths:
Clear demonstration of the surgery procedure with informative illustrations, images, and superb surgical videos.<br /> Two time points of ischemia and reperfusion were studied with convincing histological and in vivo data to demonstrate the time course of various changes in retinal neuronal cell survivals, ERG functions, and inner/outer retina thickness.<br /> The transcriptome comparison among different retinal artery occlusion models provides informative evidence to differentiate these models.<br /> The potential applications of the in vivo retinal ischemia-reperfusion model and relevant readouts demonstrated by this study will certainly inspire further investigation of the dynamic morphological and functional changes of retinal neurons and glial cell responses during disease progression and before and after treatments.
Weaknesses:
It would be beneficial to the manuscript and the readers if the authors could improve the English of this manuscript by correcting obvious grammar errors, eliminating many of the acronyms that are not commonly used by the field, and providing a reason why this complicated but clever surgery procedure was designed and a summary table with time course of all the morphological, functional, cellular, and transcriptome changes associated with this model.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Satoshi Yamashita et al., investigate the physical mechanisms driving tissue bending using the cellular Potts Model, starting from a planar cellular monolayer. They argue that apical length-independent tension control alone cannot explain bending phenomena in the cellular Potts Model, contrasting with previous works, particularly Vertex Models. They conclude that an apical elastic term, with zero rest value (due to endocytosis/exocytosis), is necessary to achieve apical constriction, and that tissue bending can be enhanced by adding a supracellular myosin cable. Additionally, a very high apical elastic constant promotes planar tissue configurations, opposing bending.
Strengths:
- The finding of the required mechanisms for tissue bending in the cellular Potts Model provides a natural alternative for studying bending processes in situations with highly curved cells.<br /> - Despite viewing cellular delamination as an undesired outcome in this particular manuscript, the model's capability to naturally allow T1 events might prove useful for studying cell mechanics during out-of-plane extrusion.
Weaknesses:
- The authors claim that the cellular Potts Model (CPM) is unable to achieve the results of the vertex model (VM) simulations due to naturally non-straight cellular junctions in the CPM versus the VM. The lack of a substantial comparison undermines this assertion. None of the references mentioned in the manuscript are from a work using vertex model with straight cellular junctions, simulating apical constriction purely by a enhancing a length-independent apical tension. Sherrard et al and Pérez-González et al. use 2D and 3D Vertex Models, respectively, with a "contractility" force driving apical constriction. However, their models allow cell curvature. Both references suggest that the cell side flexibility of the CPM shouldn't be the main issue of the "contractility model" for apical constriction.<br /> - The myosin cable is assumed to encircle the invaginated cells. Therefore, it is not clear why the force acts over the entire system (even when decreasing towards the center), and not locally in the contour of the group of cells under constriction. The specific form of the associated potential is missing. It is unclear how dependent the results of the manuscript are on these not-well-motivated and model-specific rules for the myosin cable.<br /> - The authors are using different names than the conventional ones for the energy terms. Their current attempt to clarify what is usually done in other works might lead to further confusion.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
As adult-born granule neurons have been shown to play diverse roles, both positive and negative, to modulate hippocampal circuitry and function in epilepsy, understanding the mechanisms by which altered neurogenesis contribute to seizures is important for future therapeutic strategies. The work by Jain et al., demonstrates that increasing adult-born neurons (not increasing adult neurogenesis because BrdU birthdating was not performed in this study) before status epilepticus (SE) leads to a suppression in chronic seizures in the pilocarpine model of temporal lobe epilepsy. This work is potentially interesting because previous studies showed suppressing adult-born neurons led to reduced chronic seizures.
To increase adult-born neurons, the authors conditionally delete the pro-apoptotic gene Bax using a tamoxifen inducible Nestin-CreERT2 which has been previously published to increase proliferation and survival of adult-born neurons by Sahay et al. (although this was not shown in this study). After 6 weeks of tamoxifen injection, the authors subject male and female mice to pilocarpine induced SE. In the first study, at 2 hours after pilocarpine, the authors examine latency to the first seizure, severity and total number of acute seizures, and power during SE. In the second study in a separate group of mice, the authors examine chronic seizure number and frequency, seizure duration, postictal depression, and seizure distribution/cluster seizures for 3 weeks after pilocarpine. Overall, the study concludes that increasing adult-born neurons in the normal adult brain can reduce epilepsy in females specifically.
Strengths:
(1) The study is sex matched and reveals differences in response to increasing adult-born neurons in chronic seizures between male and females.
(2) The EEG recording parameters are stringent, and analysis of chronic seizures is comprehensive. In two separate experiments, the electrodes were implanted to record EEG from cortex as well as hippocampus. The recording is done for 10 hours post pilocarpine to analyze acute seizures, and for 3 weeks continuous video EEG recording was done to analyze chronic seizures.
Weaknesses:
(1) Increased DCX alone (without birthdating with BrdU) could indicate increased survival of adult-born neurons, not proliferation or birth of newborn neurons per se. While prior work has demonstrated that tamoxifen injection in adult mice showed an increase in dentate gyrus neurogenesis based on studies of BrdU, Ki67, and DCX (Sahay et al., 2011), the dynamics of adult-born neurons (proliferation, differentiation, and/or survival) could be different in epileptic (pilocarpine-treated) animals. Other stages, e.g., proliferation of neural precursors or maturation of adult-born dentate granule cells, was not examined. Analysis of additional stages of adult neurogenesis may reveal additional cellular understanding and add impact of the work on the field.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Wang et al., present a paper aiming to identify NALCN and TRPC6 channels as key mechanisms regulating VTA dopaminergic neuron spontaneous firing and investigating whether these mechanisms are disrupted in a chronic unpredictable stress model mouse.
Major strengths:
This paper uses multiple approaches to investigate the role of NALCN and TRPC6 channels in VTA dopaminergic neurons.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This paper reports an intracranial SEEG study of speech coordination, where participants synchronize their speech output with a virtual partner that is designed to vary its synchronization behavior. This allows the authors to identify electrodes throughout the left hemisphere of the brain that have activity (both power and phase) that correlates with the degree of synchronization behavior. They find that high-frequency activity in the secondary auditory cortex (superior temporal gyrus) is correlated to synchronization, in contrast to primary auditory regions. Furthermore, activity in the inferior frontal gyrus shows a significant phase-amplitude coupling relationship that is interpreted as compensation for deviation from synchronized behavior with the virtual partner.
Strengths:
(1) The development of a virtual partner model trained for each individual participant, which can dynamically vary its synchronization to the participant's behavior in real-time, is novel and exciting.
(2) Understanding real-time temporal coordination for behaviors like speech is a critical and understudied area.
(3) The use of SEEG provides the spatial and temporal resolution necessary to address the complex dynamics associated with the behavior.
(4) The paper provides some results that suggest a role for regions like IFG and STG in the dynamic temporal coordination of behavior both within an individual speaker and across speakers performing a coordination task.
Weaknesses:
(1) The main weakness of the paper is that the results are presented in a largely descriptive and vague manner. For instance, while the interpretation of predictive coding and error correction is interesting, it is not clear how the experimental design or analyses specifically support such a model, or how they differentiate that model from the alternatives. It's possible that some greater specificity could be achieved by a more detailed examination of this rich dataset, for example by characterizing the specific phase relationships (e.g., positive vs negative lags) in areas that show correlations with synchronization behavior. However, as written, it is difficult to understand what these results tell us about how coordination behavior arises.
(2) In the results section, there's a general lack of quantification. While some of the statistics reported in the figures are helpful, there are also claims that are stated without any statistical test. For example, in the paragraph starting on line 342, it is claimed that there is an inverse relationship between rho-value and frequency band, "possibly due to the reversed desynchronization/synchronization process in low and high frequency bands". Based on Figure 3, the first part of this statement appears to be true qualitatively, but is not quantified, and is therefore impossible to assess in relation to the second part of the claim. Similarly, the next paragraph on line 348 describes optimal clustering, but statistics of the clustering algorithm and silhouette metric are not provided. More importantly, it's not entirely clear what is being clustered - is the point to identify activity patterns that are similar within/across brain regions? Or to interpret the meaning of the specific patterns? If the latter, this is not explained or explored in the paper.
(3) Given the design of the stimuli, it would be useful to know more about how coordination relates to specific speech units. The authors focus on the syllabic level, which is understandable. But as far as the results relate to speech planning (an explicit point in the paper), the claims could be strengthened by determining whether the coordination signal (whether error correction or otherwise) is specifically timed to e.g., the consonant vs the vowel. If the mechanism is a phase reset, does it tend to occur on one part of the syllable?
(4) In the discussion the results are related to a previously-described speech-induced suppression effect. However, it's not clear what the current results have to do with SIS, since the speaker's own voice is present and predictable from the forward model on every trial. Statements such as "Moreover, when the two speech signals come close enough in time, the patient possibly perceives them as its own voice" are highly speculative and apparently not supported by the data.
(5) There are some seemingly arbitrary decisions made in the design and analysis that, while likely justified, need to be explained. For example, how were the cutoffs for moderate coupling vs phase-shifted coupling (k ~0.09) determined? This is noted as "rather weak" (line 212), but it's not clear where this comes from. Similarly, the ROI-based analyses are only done on regions "recorded in at least 7 patients" - how was this number chosen? How many electrodes total does this correspond to? Is there heterogeneity within each ROI?
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Reviewer #1 (Public Review):
Summary:
Johnston and Smith used linear electrode arrays to record from small populations of neurons in the superior colliculus (SC) of monkeys performing a memory-guided saccade (MGS) task. Dimensionality reduction (PCA) was used to reveal low-dimensional subspaces of population activity reflecting the slow drift of neuronal signals during the delay period across a recording session (similar to what they reported for parts of the cortex: Cowley et al., 2020). This SC drift was correlated with a similar slow-drift subspace recorded from the prefrontal cortex, and both slow-drift subspaces tended to be associated with changes in arousal (pupil size). These relationships were driven primarily by neurons in superficial layers of the SC, where saccade sensitivity/selectivity is typically reduced. Accordingly, delay-period modulations of both spiking activity and pupil size were independent of saccade-related activity, which was most prevalent in deeper layers of the SC. The authors suggest that these findings provide evidence of a separation of arousal- and motor-related signals. The analysis techniques expand upon the group's previous work and provide useful insight into the power of large-scale neural recordings paired with dimensionality reduction. This is particularly important with the advent of recording technologies which allow for the measurement of spiking activity across hundreds of neurons simultaneously. Together, these results provide a useful framework for comparing how different populations encode signals related to cognition, arousal, and motor output in potentially different subspaces.
The conclusions drawn by this paper, however, are only partially supported by the data. Additional statistical comparisons and clarifications are needed.
Comments:
(1) The authors make fairly strong claims that "arousal-related fluctuations are isolated from neurons in the deep layers of the SC" (emphasis added). This conclusion is based on comparisons between a "slow drift axis", a low-dimensional representation of neuronal drift, and other measures of arousal (Figures 2C, 3) and motor output sensitivity (Figures 2B, 3B). However, the metrics used to compare the slow-drift axis and motor activity were computed during separate task epochs: the delay period (600-1100 ms) and a peri-saccade epoch (25 ms before and after saccade initiation), respectively. As the authors reference, deep-layer SC neurons are typically active only around the time of a saccade. Therefore, it is not clear if the lack of arousal-related modulations reported for deep-layer SC neurons is because those neurons are truly insensitive to those modulations, or if the modulations were not apparent because they were assessed in an epoch in which the neurons were not active. A potentially more valuable comparison would be to calculate a slow-drift axis aligned to saccade onset.
(2) More generally, arousal-related signals may persist throughout multiple different epochs of the task. It would be worthwhile to determine whether similar "slow-drift" dynamics are observed for baseline, sensory-evoked, and saccade-related activity. Although it may not be possible to examine pupil responses during a saccade, there may be systematic relationships between baseline and evoked responses.
(3) The relationships between changes in SC activity and pupil size are quite small (Figures 2C & 5C). Although the distribution across sessions (Figure 2C) is greater than chance, they are nearly 1/4 of the size compared to the PFC-SC axis comparisons. Likewise, the distribution of r2 values relating pupil size and spiking activity directly (Figure 5) is quite low. We remain skeptical that these drifts are truly due to arousal and cannot be accounted for by other factors. For example, does the relationship persist if accounting for a very simple, monotonic (e.g., linear) drift in pupil size and overall firing rate over the course of an individual session?
(4) It is not clear how the final analysis (Figure 6) contributes to the authors' conclusions. The authors perform PCA on: (i) residual spiking responses during the delay period binned according to pupil size, and (ii) spiking responses in the saccade epoch binned according to target location (i.e., the saccade tuning curve). The corresponding PCs are the spike-pupil axis and the saccade tuning axis, respectively. Unsurprisingly, the spike-pupil axis that captures variance associated with arousal (and removes variance associated with saccade direction) was not correlated with a saccade-tuning axis that captures variance associated with saccade direction and omits arousal. Had these measures been related it would imply a unique association between a neuron's preferred saccade direction and pupil control- which seems unlikely. The separation of these axes thus seems trivial and does not provide evidence of a "mechanism...in the SC to prevent arousal-related signals interfering with the motor output." It remains unknown whether, for example, arousal-related signals may impact trial-by-trial changes in neuronal gain near the time of a saccade, or alter saccade dynamics such as acceleration, precision, and reaction time.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In the retina, parallel processing of cone photoreceptor output under bright light conditions dissects critical features of our visual environment and is fundamental to visual function. Cone photoreceptor signals are sampled by several types of bipolar cells and passed onto the ganglion cells. At the output of retinal processing, retinal ganglion cells send about 40 different codes of the visual scene to the brain for further processing. In this study, the authors focus on whether subtype-specific differences in the size of synaptic ribbon-associated vesicle pools of bipolar cells contribute to different retinal ganglion cell (RGC) responses. Specifically, inputs to ON alpha RGCs producing transient versus sustained kinetics (ON-S vs. ON-T, respectively) are compared. The authors first demonstrate that ON-S vs. ON-T RGCs are readily identifiable in a whole mount preparation and respond differently to both static and to a spatially uniform, randomly fluctuating (Gaussian noise) light stimulus. Liner-nonlinear (LN) models were used to estimate the transformation between visual input and excitatory synaptic input for each RGCs; these models suggested the presence of transient versus sustained kinetics already in the excitatory inputs to ON-T and ON-S RGCs. Indeed, the authors show that (glutamatergic) excitatory inputs to ON-S vs. ON-T RGCs are of distinct kinetics. The subtypes of bipolar cells providing input to ON-S are known (i.e., type 6 and 7), but the source of excitatory bipolar inputs to ON-T RGCs needed to be determined. In a tedious process, it is elegantly shown here that ON-T RGCs receive most of their excitatory inputs from type 5 and 6 bipolars. Interestingly, the temporal properties of light-evoked responses of type 5, 6, and 7 bipolars recorded from the somas were indistinguishable and rather sustained, suggesting that the origin of transient kinetics of excitatory inputs to ON-T RGCs suggested by the LN model might be found in the processing of visual signals at the bipolar cell axon terminal. Blocking GABA- or glycinergic inhibitory inputs did not alter the light-evoked excitatory input kinetics to ON-T and ON-S RGCs. Two-photon glutamate sensor imaging revealed significantly faster kinetics of light-evoked glutamate signals at ON-T versus ON-S RGCs. Detailed EM analysis of bipolar cell ribbon synapses onto ON-T and ON-S RGCs revealed fewer ribbon-associated vesicles at ON-T synapses, which is consistent with stronger paired-flash depression of light-evoked excitatory currents in ON-T RGCS versus ON-S RGCs. This study suggests that bipolar subtype-specific differences in the size of synaptic ribbon-associated vesicle pools contribute to transient versus sustained kinetics in RGCs.
Strengths:
The use of multiple, state-of-the-art tools and approaches to address the kinetics of bipolar to ganglion cell synapse in an identified circuit.
Weaknesses:
For the most part, the data in the paper support the conclusions, and the authors were careful to try to address questions in multiple ways. Two-photon glutamate sensor imaging experiment showing that blocking GABA- and glycinergic inhibition does not change the kinetics of light-evoked glutamate signals at ON-T RGCs would strengthen the conclusion that bipolar subtype-specific differences in the size of synaptic ribbon-associated vesicle pools contribute to transient versus sustained kinetics in RGCs.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In the study "Re-focusing visual working memory during expected and unexpected memory tests" by Sisi Wang and Freek van Ede, the authors investigate the dynamics of attentional re-orienting within visual working memory (VWM). Utilizing a robust combination of behavioral measures, electroencephalography (EEG), and eye tracking, the research presents a compelling exploration of how attention is redirected within VWM under varying conditions. The research question addresses a significant gap in our understanding of cognitive processes, particularly how expected and unexpected memory tests influence the focus and re-focus of attention. The experimental design is meticulously crafted, enabling a thorough investigation of these dynamics. The figures presented are clear and effectively illustrate the findings, while the writing is concise and accessible, making the complex concepts understandable. Overall, this study provides valuable insights into the mechanisms of visual working memory and attentional re-orienting, contributing meaningfully to the field of cognitive neuroscience. Despite the strengths of the manuscript, there are several areas where improvements could be made.
Microsaccades or Saccades?
In the manuscript, the terms "microsaccades" and "saccades" are used interchangeably. For instance, "microsaccades" are mentioned in the keywords, whereas "saccades" appear in the results section. It is crucial to differentiate between these two concepts. Saccades are large, often deliberate eye movements used for scanning and shifting attention, while microsaccades are small, involuntary movements that maintain visual perception during fixation. The authors note the connection between microsaccades and attention, but it is not well-recognized that saccades are directly linked to attention. Despite the paradigm involving a fixation point, it remains unclear whether large eye movements (saccades) were removed from the analysis. The authors mention the relationship between microsaccades and attention but do not clarify whether large eye movements (saccades) were excluded from the analysis. If large eye movements were removed during data processing, this should be documented in the manuscript, including clear definitions of "microsaccades" and "saccades." If such trials were not removed, the contribution of large eye movements to the results should be shown, and an explanation provided as to why they should be considered.
Alpha Lateralization in Attentional Re-orienting
In the attentional orienting section of the results (Figure 2), the authors effectively present EEG alpha lateralization results with time-frequency plots and topographic maps. However, in the attentional re-orienting section (Figure 3), these visualizations are absent. It is important to note that the time period in attentional orienting differs from attentional re-orienting, and consequently, the time-frequency plots and topographic maps may also differ. Therefore, it may be invalid to compute alpha lateralization without a clear alpha activity difference. The authors should consider including time-frequency plots and topographic maps for the attentional re-orienting period to validate their findings.
Onset and Offset Latency of Saccade Bias
The use of the 50% peak to determine the onset and offset latency of the saccade bias is problematic. For example, if one condition has a higher peak amplitude than another, the standard for saccade bias onset would be higher, making the observed differences between the onset/offset latencies potentially driven by amplitude rather than the latencies themselves. The authors should consider a more robust method for determining saccade bias onset and offset that accounts for these amplitude differences.
Control Analysis for Trials Not Using the Initial Cue
The control analysis for trials where participants did not use the initial cue raises several questions:
(1) The authors claim that "unlike continuous alpha activity, saccades are events that can be classified on a single-trial level." However, alpha activity can also be analyzed at the single-trial level, as demonstrated by studies like "Alpha Oscillations in the Human Brain Implement Distractor Suppression Independent of Target Selection" by Wöstmann et al. (2019). If single-trial alpha activity can be used, it should be included in additional control analyses.
(2) The authors aimed to test whether the re-orienting signal observed after the test is not driven exclusively by trials where participants did not use the initial cue. They hypothesized that "in such a scenario, we should only observe attention deployment after the test stimulus in trials in which participants did not use the preceding retro cue." However, if the saccade bias is the index for attentional deployment, the authors should conduct a statistical test for significant saccade bias rather than only comparing toward-saccade after-cue trials with no-toward-saccade after-cue trials. The null results between the two conditions do not immediately suggest that there is attention deployment in both conditions.
(3) Even if attention deployment occurs in both conditions, the prolonged re-orienting effect could also be caused by trials where participants did not use the initial cue. Unexpected trials usually involve larger and longer brain activity. The authors should perform the same analysis on the time after the removal of trials without toward-saccade after the cue to address this potential confound.
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Reviewer #1 (Public Review):
Summary:
Mosshammer et al. studied the oxygenic photosynthetic productivity of beachrock samples containing cyanobacteria with different pigment compositions. The use of longer wavelength absorbing chlorophylls in some cyanobacteria (chlorophylls d and f) allows their photosystems to use light further in the red than canonical chlorophyll a photosystems. As such, their distribution in visible light-shaded environments, such as the beachrock studied by Mosshammer et al., allows them to perform oxygenic photosynthesis using wavelengths not capable of driving photosynthesis in most cyanobacteria, algae, or plants.
By adapting measuring systems they have previously used to study these types of beachrock samples, the authors attempt to mimic a more natural light penetration through the beachrock in order to measure oxygen production. By doing so with different wavelengths and intensities, the authors are able to show that far-red light-driven oxygen production is potentially capable of driving high levels of gross primary production.
Strengths:
The manuscript builds on previous measurement techniques used by the authors while focussing on illumination from the top of a sample rather than the specific microbial layers themselves. This provides a more environmentally realistic understanding of the beachrock community, as well as far-red light-driven photosynthesis.
The manuscript benefits from using previously defined methods to further characterize complex environmental samples.
Weaknesses:
The manuscript suffers from a lack of discussion and interpretation of the findings, and as such is more of a report.
Using the envionmental beachrock samples has inherent complications, from the variation in rock morphology, to the microbial community composition of different samples as well as within a single sample. It would benefit the authors to discuss these technical difficulties in more detail, as the light penetration through the beachrock is likely greatly limiting measurements of chlorophyll f and/or chlorophyll d-driven photosynthesis in the beachrock.
This can be seen in the different luminescence measurements (Figure 2 and supplements), that the different samples have clear differences in far-red light-driven oxygen production. While the BLACK sample produces oxygen with 740nm LED filtered with a NIR-75N filter, neither of the other two samples produce measureable oxygen under this condition. Conversely, this sample results in the lowest level of gross photosynthesis when measuring dissolved oxygen. A more detailed discussion of the variation between and within samples and measurements would benefit the overall results of the manuscript.
The PINK beachrock sample has the highest level of chlorophyll d per chlorophyll a. As FaRLiP cyanobacteria only incorporate 1 chlorophyll d per photosystem II, and none in photosytem I, is there a (relatively) high composition of Acaryochloris species in the PINK sample? If normalized to the reflectance minima can more distinct populations be identified?
For Figure 1, multiple points should be clarified. The first is that the HPLC methods are estimates of concentrations, as the extinction coefficients are not correct for the solvent solution for which the pigments elute, and are likely to be differently incorrect for each pigment. This results in quantitatively incorrect data, but qualitative comparisons between samples likely remain valid. Secondly, the pigment concentrations can also be misleading. Within the cyanobacterial cells, photosystem I harbors approximately 3 times as many chlorophylls as photosystem II. While the community numbers and photosystem stoichiometry are not necessarily relevant to the current study, the red shift in absorbance between photosystem II and photosystem I is of importance for the measurements performed. How cyanobacterial cells with differing concentrations of photosystems will absorb the red tail of the far-red LEDs, as well as impact the light penetration would be a useful discussion point.
The different samples used are from varying beachrock zonations but have the same chlorophyll f per chlorophyll a concentrations. A discussion of why this might be would be useful.
For the luminescence measurements (Figure 2 and supplements), no oxygen production is seen in the BROWN or PINK beachrock samples when the 740nm LED is filtered with a NIR-75N filter. This is likely due to multiple factors (low initial intensity compounded by penetration depth, community composition, etc.) but should be discussed. While the authors say that Chrooccidiopsis species dominate the samples, variation of absorbance between different chlorophyll f containing cyanobacteria has also been measured (see Tros et al. 2021, Chem), and the extent to which even chlorophyll f species extend into the far-red varies. Discussions about these implications would help with their characterization of the luminescence data. While the authors discuss that based on their respiration measurements the oxygen may be being consumed, resulting in an inability to measure it (lines 147-150), other explanations are clearly viable.
For the luminescence measurements, no oxygen production is discernable in the endolithic region when excited with visible light, which is at a much stronger intensity than the near-infrared light used. However, both Acaryochloris and chlorophyll f cyanobacteria are capable of driving photosynthesis with visible light. As the intensities used are much brighter than for the NIR measurements, presumably generated oxygen would be higher than what could be immediately consumed by respiration. It is important that the authors address this.
A highlighted point by the authors is the >20% of photosynthesis driven by NIR in the beachrock at comparable irradiation. However, this statement is deceiving for multiple reasons.<br /> (1) The irradiation is likely not comparable for what is reaching the cells. This is not a problem per se as illumination from above is the point, but does skew the interpretation.<br /> (2) The >20% value comes from the maximum amount of gross photosynthesis driven by NIR at ~1400 umol photons m-2s-1, whereas at other comparable illuminations the value is much, much lower (<1%). A likely interpretation of such data is that while the chlorophyll f endolithic layer is capable of producing a relatively large amount of oxygen, it is likely far less productive under most illuminations, though not zero.
The authors have the difficult task of weaving in results from laboratory, uniculture or isolated photosystem measurements with their environmental-based results. This is especially clear in lines 172-183. While the authors are correct that measurements of trapping times in chlorophyll f containing photosystems have been measured and are slower in chlorophyll f photosystem II and photosystem I relative to all chlorophyll a photosystems, the quantum yield for trapping remains high in chlorophyll f photosystem I (Tros et al. 2021, Chem). The quantum yield of trapping for chlorophyll f photosystem II is much lower for chlorophyll f than chlorophyll a complex, though improved by the attachment of phycobilisomes. However, these are intrinsic physical properties of the complexes that are not modulated in response to the environments. This could be interpreted that at low photon flux densities as measured in these experiments, the endolithic near infrared-driven oxygen production could be limited by an overall lower quantum efficiency of trapping the captured light and thus minimizing photosynthetic productivity relative to a theoretical level based on the efficiency of the chlorophyll a photosystem II. How the variations in intensity and spectral composition impact the cyanobacterial community likely involves many other factors and has not been addressed (though see Nurnberg et al. 2018, Science and Viola et al. 2022 eLife for further discussions).
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Reviewer #1 (Public Review):
Summary:
In this work, the authors study whether the human brain uses long term priors (acquired during our lifetime) regarding the statistics of auditory stimuli to make predictions respecting auditory stimuli. This is an important open question in the field of predictive processing.
To address this question, the authors cleverly profit from the naturally existing differences in two linguistic groups. While speakers of Spanish use phrases in which function-words (short words like, articles and prepositions) are followed by content-words (longer words like nouns, adjectives and verbs), speakers of Basque use phrases with the opposite order. Because of this, speakers of Spanish usually hear phrases in which short words are followed by longer words, and speakers of Basque experience the opposite. This difference in the order of short and longer words is hypothesized to result in a long term duration prior that is used to make predictions regarding the likely durations of incoming sounds, even if they are not linguistic in nature.
To test this, the authors used MEG to measure the mismatch responses (MMN) elicited by the omission of short and long tones that were presented in alternation. The authors report an interaction between the language background of the participants (Spanish, Basque) and the type of omission MMN (short, long), which goes in line with their predictions. They supplement these results with a source level analysis.
Strengths:
This work has many strengths. To test the main question, the authors profit from naturally occurring differences in the everyday auditory experiences of two linguistic groups, which allows to test the effect of putative auditory priors consolidated over the years. This is a direct way of testing the effect of long term priors.
The fact that the priors in question are linguistic and that the experiment was conducted using non-linguistic stimuli (i.e. simple tones), allows to test if these long term priors generalize across auditory domains.
The experimental design is elegant and the analysis pipeline appropriate. This work is very well written. In particular the introduction and discussion sections are clear and engaging. The literature review is complete.
Weaknesses:
The authors report a widespread omission response, which resembles the classical mismatch response (in MEG planar gradiometers) with strong activations in sensors over temporal regions. However the interaction reported is circumscribed to four sensors that do not overlap with the peaks of activation of the omission response.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In Drosophila melanogaster, expression of Sex-lethal (Sxl) protein determines sexual identity and drives female development. Functional Sxl protein is absent from males where splicing includes a termination codon-containing "poison" exon. Early during development, in the soma of female individuals, Sxl expression is initiated by an X chromosome counting mechanism that activates the Sxl establishment promoter (SxlPE) to produce an initial amount of Sxl protein. This then suppresses the inclusion of the "poison" exon, directing the constructive splicing of Sxl transcripts emerging from the Sxl maintenance promotor (SxlPM) which is activated at a later stage during development irrespective of sex. This autoregulatory loop maintains Sxl expression and commits to female development.
Sxl also determines the sexual identity of the germline. Here Sxl expression generally follows the same principles as in somatic tissues, but the way expression is initiated differs from the soma. This regulation has so far remained elusive.
In the presented manuscript, Goyal et al. show that activation of Sxl expression in the germline depends on additional regulatory DNA sequences, or sequences different from the ones driving initial Sxl expression in the soma. They further demonstrate that sisterless A (sisA), a transcription factor that is required for activation of Sxl expression in the soma, is also necessary, but not sufficient, to initiate the expression of functional Sxl protein in female germ cells. sisA expression precedes Sxl induction in the germline and its ablation by RNAi results in impaired expression of Sxl, formation of ovarian tumors, and germline loss, phenocopying the loss of Sxl. Intriguingly, this phenotype can be rescued by the forced expression of Sxl, demonstrating that the primary function of sisA in the germline is the induction of Sxl expression.
Strengths:
The clever design of probes (for RNA FISH) and reporters allowed the authors to dissect Sxl expression from different promoters to get novel insight into sex-specific gene regulation in the germline. All experiments are carefully controlled. Since Sxl regulation differs between the soma and the germline, somatic tissues provide elegant internal controls in many experiments, ensuring e.g. functionality of the reporters. Similarly, animals carrying newly generated alleles (e.g. genomic tagging of the Sxl locus) are fertile and viable, demonstrating that the genetic manipulation does not interfere with protein function. The conclusions drawn from the experimental data are sound and advance our understanding of how Sxl expression is induced in the female germline.
Weaknesses:
The assays employed by the authors provide valuable information on when Sxl promoters become active. However, since no information on the stability of the gene products (i.e. RNA and protein) is available, it remains unclear when the SxlPE promoter is switched off in the germline (conceptually it only needs to be active for a short time period to initiate production of functional Sxl protein). As correctly stated by the authors, the persisting signals observed in the germline might therefore not reflect the continuous activity of the SxlPE promoter.
Mapping of regulatory elements and their function: SxlPE with 1.5 kb of flanking upstream sequence is sufficient to recapitulate early Sxl expression in the soma. The authors now provide evidence that beyond that, additional DNA sequences flanking the SxlPE promoter are required for germline expression. However, a more precise mapping was not performed. Also, due to technical limitations, the authors could not precisely map the sisA binding sites. Since this protein is also involved in the somatic induction of Sxl, its binding sites likely reside in the region 1.5kb upstream of the SxlPE promoter, which has been reported to be sufficient for somatic regulation. The regulatory role of the sequences beyond SxlPE-1.5kb therefore remains unaddressed and it remains to be investigated which trans-acting factor(s) exert(s) its/their function(s) via this region.
The central question of how Sxl expression is initiated and controlled in the germline still remains unanswered. Since sisA is zygotically expressed in both the male and the female germline (Figure 4D), it is unlikely the factor that restricts Sxl expression to the female germline.
How does weak expression of Sxl in male tissues or expression above background after knockdown of sisA reconcile with the model that an autoregulatory feedback loop enforces constant and clonally inheritable Sxl expression once Sxl is induced? Is the current model for Sxl expression too simple or are we missing additional factors that modulate Sxl expression (such as e.g. Sister of Sex-lethal)? While I do not expect the authors to answer these questions, I would expect them to appropriately address these intriguing aspects in the discussion.
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Reviewer #1 (Public Review):
In this manuscript, Liu et al. used scRNA-seq to characterize cell type-specific responses during allergic contact dermatitis (ACD) in a mouse model, specifically the hapten-induced DNFB model. Using the scRNA-seq data, they deconvolved the cell types responsible for the expression of major inflammatory cytokines such as IFNG (from CD4 and CD8 T cells), IL4/13 (from basophils), IL17A (from gd T cells), and IL1B from neutrophils and macrophages. They found the highest upregulation of a type 1 inflammatory response, centering around IFNG produced by CD4 and CD8 T cells. They further identified a subpopulation of dermal fibroblasts (pre-adipocytes found in the dermal white adipose tissue layer) that upregulate CXCL9/10 during ACD and provide functional genetic evidence in their mouse model that disrupting IFNG signaling in fibroblasts decreases CD8 T cell infiltration and overall inflammation. They identify an increase in IFNG-expressing CD8 T cells in human patient samples of ACD vs. healthy control skin and co-localization of CD8 T cells with PDGFRA+ fibroblasts, which suggests this mechanism is relevant to human ACD. This mechanism is reminiscent of recent work showing that IFNG signaling in dermal fibroblasts upregulates CXCL9/10 to recruit CD8 T cells in a mouse model of vitiligo. Overall, this is a well-presented, clear, and comprehensive manuscript. The conclusions of the study are well supported by the data, with thoughtful discussion on study limitations by the authors. One such limitation was the use of one ACD model (DNFB), which prevents an assessment of how broadly relevant this axis is. The human sample validation is limited by the multiplexing capacity of immunofluorescence markers but shows a predominance of CD8+/IFNG+ cells and PDGFRA+/CXCL10+ cells in ACD (which are virtually absent in healthy control), along with co-localization of CD8+ cells with PDGFRA+ cells. Thus, this mechanism is likely active in human ACD.
Strengths:<br /> Through deep characterization of the in vivo ACD model using scRNA-seq, the authors were able to determine which cell types were expressing the major cytokines involved in ACD inflammation, such as IFNG, IL4/13, IL17A, and IL1B. These analyses are well-presented and thoughtful, showing first that the response is IFNG-dominant, then focusing on deeper characterization of lymphocytes, myeloid cells, and fibroblasts, which are also validated and complemented by FACS experiments using canonical markers of these cell types as well as IF staining. Crosstalk analyses from the scRNA-seq data led the authors to focus on IFNG signaling fibroblasts, and in vitro experiments demonstrate that CXCL9 and CXCL10 are expressed by fibroblasts stimulated by IFNG. In vivo functional genetic evidence demonstrates an important role for IFNG signaling in fibroblasts, as KO of Ifngr1 using Pdgfra-Cre Ifngr1 fl/fl mice, showed a reduction in inflammation and CD8 T cell recruitment. Human ACD sample staining demonstrates the likely activity of the CD8 T cell IFNG-driven fibroblast response in human disease.
Weaknesses:<br /> The use of one model limits an understanding of how broad this fibroblast-T cell axis is during ACD. However, the authors chose the most commonly employed model and compared their data to work in a vitiligo model (another type 1 immune response) to demonstrate similar mechanisms at play. Human patient samples of ACD were co-stained with two markers at a time, demonstrating the presence of CD8+IFNG+ T cells, PDGFRA+CXCL10+ fibroblasts, and co-localization of PDGFRA+ fibroblasts and CD8+ T cells. However, no IF staining demonstrates co-expression of all 4 markers at once; thus, the human validation of co-localization of CD8+IFNG+ T cells and PDGFRA+CXCL10+ fibroblasts is ultimately indirect, although more likely than not to be true.
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Reviewer #1 (Public Review):
Review after revision
Of note the main results of this article are very similar to the results present in the previous manuscript (same Figures 1 to 9, addition of Figure 10 with no quantification).<br /> Unfortunately, the main weaknesses of the article have not been addressed:
(1) The main findings have been obtained in clones of Jurkat cells. They have not been confirmed in primary T cells. The only experiment performed in primary cells is shown in Figure S7 (primary human T lymphoblasts) for which only the distribution of FMNL1 is shown without quantification. No results presenting the effect of FMNL1 KO and expression of mutants in primary T cells are shown.
(2) Analysis in- depth of the defect in actin remodeling (quantification of the images, analysis of some key actors of actin remodeling) is still lacking. Only F-actin is shown, no attempt to look more precisely at actors of actin remodeling has been done.
(3) The defect in the secretion of extracellular vesicles is still very preliminary. Examples of STED images given by the authors are nice, yet no quantification is performed.
(4) Results shown in Figure S12 on the colocalization of proteins phosphorylated on Ser/Thr are still not convincing. It seems indeed that "phospho-PKC" is labeling more preferentially the CMAC positive cells (Raji) than the Jurkat T cells. It is thus particularly difficult to conclude on the co-localization and even more on the recruitment of phosphorylated-FMNL1 at the IS. Thus, these experiments are not conclusive and cannot be the basis even for their cautious conclusion: "Although all these data did not allow us to infer that FMNL1b is phosphorylated at the IS due to the resolution limit of confocal and STED microscopes, the results are compatible with the idea that both endogenous FMNL1 and YFP-FMNL1bWT are specifically phosphorylated at the cIS".
The study would benefit from a more careful statistical analysis. The dot plots showing polarity are presented for one experiment. Yet, the distribution of the polarity is broad. Results of the 3 independent experiments should be shown and a statistical analysis performed on the independent experiments.
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Reviewer #1 (Public Review):
Summary:
This paper presents valuable findings that gustation and feeding state influence the preferred environmental temperature preference in flies. Interestingly, the authors showed that by refeeding starved animals with non-nutritive sugar sucralose, they are able to tune their preference towards a higher temperature in addition to nutrient-dependent warm preference. The authors show that temperature sensing and sweet sensing gustatory neurons (SGNs) are involved in the former but not the latter. In addition, their data indicate that peptidergic signals involved in internal state and clock genes are required for taste-dependent warm preference behavior.
The authors made an analogy of their results to the cephalic phase response (CPR) in mammals where the thought, sight and taste of food prepares the animal for the consumption of food and nutrients. The authors showed that taste triggers CPR-induced temperature preference behaviors in flies. The authors also briefly covered that the combined modalities of smell and taste induced CPR responses, showing that starved orco mutant flies failed to recover temperature preference after refeeding with sucralose.
The findings of this work hold promising future research prospects, for example, whether the sight of food influences temperature preference behavior in hungry flies, or whether taste, smell and sight work together or independently in promoting CPR responses.
Futhermore, these valuable behavioral results can be further investigated in flies with the advantage of being able to dissect the neural circuitry underlying CPR and nutrient homeostasis.
Strengths:
(1) The authors convincingly showed that tasting is sufficient to drive warm temperature preference behavior in starved flies and show that it is independent of nutrient-driven warm preference.<br /> (2) By using the genetic manipulation of key internal sensors and genes controlling internal feeding and sleep state such as DH44 neurons and the per genes for eg the authors linked gustation and temperature preference behavior control to the internal state of the animal.
Weaknesses:
Most of the weaknesses of the paper have been addressed in the revision. The points mentioned below are meant to improve readability of the paper and to promote understanding of the significance of the work.<br /> (1) Supplementary fig 1 could replace Figure 1A. The purpose of Figure 1F is not clear to me as the comparison between the different food substances is not separately addressed anywhere in the text.<br /> (2) The data for the orco receptor mutant could be placed in the main figures to justify the discussion emphasising CPR-like responses.
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Reviewer #1 (Public Review):
Summary:
This paper uses a model of binge alcohol consumption in mice to examine how the behaviour and its control by a pathway between the anterior insular cortex (AIC) to the dorsolateral striatum (DLS) may differ between males and females. Photometry is used to measure the activity of AIC terminals in the DLS when animals are drinking and this activity seems to correspond to drink bouts in males but not females. The effects appear to be lateralized with inputs to the left DLS being of particular interest.
Strengths:
Increasing alcohol intake in females is of concern and the consequences for substance use disorder and brain health are not fully understood, so this is an area that needs further study. The attempt to link fine-grained drinking behaviour with neural activity has the potential to enrich our understanding of the neural basis of behaviour, beyond what can be gleaned from coarser measures of volumes consumed etc.
Weaknesses:
The introduction to the drinking in the dark (DID) paradigm is rather narrow in scope (starting line 47). This would be improved if the authors framed this in the context of other common intermittent access paradigms and gave due credit to important studies and authors that were responsible for the innovation in this area (particularly studies by Wise, 1973 and returned to popular use by Simms et al 2010 and related papers; e.g., Wise RA (1973). Voluntary ethanol intake in rats following exposure to ethanol on various schedules. Psychopharmacologia 29: 203-210; Simms, J., Bito-Onon, J., Chatterjee, S. et al. Long-Evans Rats Acquire Operant Self-Administration of 20% Ethanol Without Sucrose Fading. Neuropsychopharmacol 35, 1453-1463 (2010).) The original drinking in the dark demonstrations should also be referenced (Rhodes et al., 2005). Line 154 Theile & Navarro 2014 is a review and not the original demonstration.
When sex differences in alcohol intake are described, more care should be taken to be clear about whether this is in terms of volume (e.g. ml) or blood alcohol levels (BAC, or at least g/kg as a proxy measure). This distinction was often lost when lick responses were being considered. If licking is similar (assuming a single lick from a male and female brings in a similar volume?), this might mean males and females consume similar volumes, but females due to their smaller size would become more intoxicated so the implications of these details need far closer consideration. What is described as identical in one measure, is not in another.
While the authors have some previous data on the AIC to DLS pathway, there are many brain regions and pathways impacted by alcohol and so the focus on this one in particular was not strongly justified. Since photometry is really an observational method, it's important to note that no causal link between activity in the pathway and drinking has been established here.
It would be helpful if the authors could further explain whether their modified lickometers actually measure individual licks. While in some systems contact with the tongue closes a circuit which is recorded, the interruption of a photobeam was used here. It's not clear to me whether the nose close to the spout would be sufficient to interrupt that beam, or whether a tongue protrusion is required. This detail is important for understanding how the photometry data is linked to behaviour. The temporal resolution of the GCaMP signal is likely not good enough to capture individual links but I think more caution or detail in the discussion of the correspondence of these events is required.
Even if the pattern of drinking differs between males and females, the use of the word "strategy" implies a cognitive process that was never described or measured.
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Reviewer #1 (Public Review):
Summary:
This paper introduces an efficient approach to infer properties of receptive-field subunits from the ensemble of spike-triggered stimuli. This is an important general problem in sensory coding. The results introduced in the paper make a solid contribution to both how subunits can be identified and how subunits of different types are coordinated in space.
Strengths:
A primary strength of the paper is the development of approaches that substantially speed non-negative matrix factorization and by doing so create an opportunity for a more systematic exploration of how the procedure depends on various control parameters. The improved procedure is well documented and the direct comparisons with previous procedures are helpful. The improved efficiency enabled several improvements in the procedure - notably tests of good procedures for initializing NNMF and tests of the dependence of the results on the sparsity regularization parameter.
A second strength of the paper is the exploration of the spatial relationship between different subunits. This, to my knowledge, is new and is an interesting direction. There are some concerns about this analysis (see weaknesses below), but if this analysis can be strengthened it will provide new information that will be important both functionally and developmentally.
Weaknesses:
A primary concern is that choices made about parameters for several aspects of the analysis appear to be made subjectively. Much of this centers around how much of the structure in the extracted subunits is imposed by the procedure itself, and how much reflects the underlying neural circuitry. Some specific issues related to this concern are:
- Sparsity: the use of the autocorrelation function to differentiate real vs spurious subunits should be documented and validated. For example, can the authors split data in half and show that the real subunits are stable?
- Choice of regularization: the impact of the regularization parameter on subunit properties is nicely documented. However, the choice of an appropriate regularization parameter seems somewhat arbitrary. Line 253-256 is an example of this problem: this sentence sounds circular - as if the sparsity factor was turned up until the authors obtained what they expected to obtain. Could the choice of this parameter significantly impact the properties of the extracted subunits? How sensitive are the subunit properties to that parameter? Some additional control analyses are needed to validate the parameter choice (see the crossvalidation comment below).
- Crossvalidation was not used to identify the regularization constraint value because the weight matrix from NNMF does not generalize beyond the data it was fit to. Could the authors instead hold the components matrix fixed and recompute the weight matrix, and use that approach for cross-validation (especially since it is really the components matrix that needs validating)?
The paper would benefit from a more complete comparison with known anatomy. For example, can the authors estimate the number of cones within each subunit? This is well-constrained both anatomically (at least in macaque) and, especially for midget ganglion cell subunits, functionally. In macaque, most midget bipolar cells get input from single cones, so the number of extracted subunits should be close to the number of cones. This would be a useful point of comparison for the current work.
Is the analysis of the spatial relationship between different subunit mosaics robust to the incompleteness of those mosaics? The argument on lines 496-503 should be backed up by more analysis. For example, if subunits are removed from regions where the mosaic is pretty complete, do the authors change the spatial dependence? Alternatively, could they use synthetic mosaics with properties like those measured to check the sensitivity to missing cells?
NNMF relies on accounting for each spike-triggered stimulus with a linear combination of components. Would nonlinearities - e.g. those in the bipolar cell outputs - substantially change the results?
Does the approach work for cells that receive input from multiple bipolar types? Some ganglion cells, e.g. in mice, receive input from multiple bipolar types, each accounting for a sizable percentage of the total input. There is similar anatomical work indicating that parasol cells may receive input from multiple diffuse bipolar types. It is not clear whether the current approach works in cases where the subunits of a single ganglion cell overlap. Some discussion of this would be useful.
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Gating of Kv10 channels is unique because it involves coupling between non-domain swapped voltage sensing domains, a domain-swapped cytoplasmic ring assembly formed by the N- and C-termini, and the pore domain. Recent structural data suggests that activation of the voltage sensing domain relieves a steric hindrance to pore opening, but the contribution of the cytoplasmic domain to gating is still not well understood. This aspect is of particular importance because proteins like calmodulin interact with the cytoplasmic domain to regulate channel activity. The effects of calmodulin (CaM) in WT and mutant channels with disrupted cytoplasmic gating ring assemblies are contradictory, resulting in inhibition or activation, respectively. The underlying mechanism for these discrepancies is not understood. In the present manuscript, Reham Abdelaziz and collaborators use electrophysiology, biochemistry and mathematical modeling to describe how mutations and deletions that disrupt inter-subunit interactions at the cytoplasmic gating ring assembly affect Kv10.1 channel gating and modulation by CaM. In the revised manuscript, additional information is provided to allow readers to identify within the Kv10.1 channel structure the location of E600R, one of the key channel mutants analyzed in this study. However, the mechanistic role of the cytoplasmic domains that this study focuses on, as well as the location of the ΔPASCap deletion and other perturbations investigated in the study remain difficult to visualize without additional graphical information.
The authors focused mainly on two structural perturbations that disrupt interactions within the cytoplasmic domain, the E600R mutant and the ΔPASCap deletion. By expressing mutants in oocytes and recording currents using Two Electrode Voltage-Clamp (TEV), it is found that both ΔPASCap and E600R mutants have biphasic conductance-voltage (G-V) relations and exhibit activation and deactivation kinetics with multiple voltage-dependent components. Importantly, the mutant-specific component in the G-V relations is observed at negative voltages where WT channels remain closed. The authors argue that the biphasic behavior in the G-V relations is unlikely to result from two different populations of channels in the oocytes, because they found that the relative amplitude between the two components in the G-V relations was highly reproducible across individual oocytes that otherwise tend to show high variability in expression levels. Instead, the G-V relations for all mutant channels could be well described by an equation that considers two open states O1 and O2, and a transition between them; O1 appeared to be unaffected by any of the structural manipulations tested (i.e. E600R, ΔPASCap, and other deletions) whereas the parameters for O2 and the transition between the two open states were different between constructs. The O1 state is not observed in WT channels and is hypothesized to be associated with voltage sensor activation. O2 represents the open state that is normally observed in WT channels and is speculated to be associated with conformational changes within the cytoplasmic gating ring that follow voltage sensor activation, which could explain why the mutations and deletions disrupting cytoplasmic interactions affect primarily O2.
Severing the covalent link between the voltage sensor and pore reduced O1 occupancy in one of the deletion constructs. Although this observation is consistent with the hypothesis that voltage-sensor activation drives entry into O1, this result is not conclusive. Structural as well as functional data has established that the coupling of the voltage sensor and pore does not entirely rely on the S4-S5 covalent linker between the sensor and the pore, and thus the severed construct could still retain coupling through other mechanisms, which is consistent with the prominent voltage dependence that is observed. If both states O1 and O2 require voltage sensor activation, it is unclear why the severed construct would affect state O1 primarily, as suggested in the manuscript, as opposed to decreasing occupancy of both open states. In line with this argument, the presence of Mg2+ in the extracellular solution affected both O1 and O2. This finding suggests that entry into both O1 and O2 requires voltage-sensor activation because Mg2+ ions are known to stabilize the voltage sensor in its most deactivated conformations.
Activation towards and closure from O1 is slow, whereas channels close rapidly from O2. A rapid alternating pulse protocol was used to take advantage of the difference in activation and deactivation kinetics between the two open components in the mutants and thus drive an increasing number of channels towards state O1. Currents activated by the alternating protocol reached larger amplitudes than those elicited by a long depolarization to the same voltage. This finding is interpreted as an indication that O1 has a larger macroscopic conductance than O2. In the revised manuscript, the authors performed single-channel recordings to determine why O1 and O2 have different macroscopic conductance. The results show that at voltages where the state O1 predominates, channels exhibited longer open times and overall higher open probability, whereas at more depolarized voltages where occupancy of O2 increases, channels exhibited more flickery gating behavior and decreased open probability. These results are informative but not conclusive since single-channel amplitudes could not be resolved at strong depolarizations, limiting the extent to which the data could be analyzed. In the last revision, the authors have included one representative example showing inhibition of single channel activity by the Kv10-specific inhibitor astemizole. Group data analysis would be needed to conclusively establish that the currents that were recorded indeed correspond to Kv10 channels.
It is shown that conditioning pulses to very negative voltages result in mutant channel currents that are larger and activate more slowly than those elicited at the same voltage but starting from less negative conditioning pulses. In voltage-activated curves, O1 occupancy is shown to be favored by increasingly negative conditioning voltages. This is interpreted as indicating that O1 is primarily accessed from deeply closed states in which voltage sensors are in their most deactivated position. Consistently, a mutation that destabilizes these deactivated states is shown to largely suppress the first component in voltage-activation curves for both ΔPASCap and E600R channels.
The authors then address the role of the hidden O1 state in channel regulation by calcium-calmodulin (CaM). Stimulating calcium entry into oocytes with ionomycin and thapsigargin, assumed to enhance CaM-dependent modulation, resulted in preferential potentiation of the first component in ΔPASCap and E600R channels. This potentiation was attenuated by including an additional mutation that disfavors deeply closed states. Together, these results are interpreted as an indication that calcium-CaM preferentially stabilizes deeply closed states from which O1 can be readily accessed in mutant channels, thus favoring current activation. In WT channels lacking a conducting O1 state, CaM stabilizes deeply closed states and is therefore inhibitory. It is found that the potentiation of ΔPASCap and E600R by CaM is more strongly attenuated by mutations in the channel that are assumed to disrupt interaction with the C-terminal lobe of CaM than mutations assumed to affect interaction with the N-terminal lobe. These results are intriguing but difficult to interpret in mechanistic terms. The strong effect that calcium-CaM had on the occupancy of the O1 state in the mutants raises the possibility that O1 can be only observed in channels that are constitutively associated with CaM. To address this, a biochemical pull-down assay was carried out to establish that only a small fraction of channels are associated with CaM under baseline conditions. These CaM experiments are potentially very interesting and could have wide physiological relevance. However, the approach utilized to activate CaM is indirect and could result in additional non-specific effects on the oocytes that could affect the results.
Finally, a mathematical model is proposed consisting of two layers involving two activation steps for the voltage sensor, and one conformational change in the cytoplasmic gating ring - completion of both sets of conformational changes is required to access state O2, but accessing state O1 only requires completion of the first voltage-sensor activation step in the four subunits. The model qualitatively reproduces most major findings on the mutants. Although the model used is highly symmetric and appears simple, the mathematical form used for the rate constants in the model adds a layer of complexity to the model that makes mechanistic interpretations difficult. In addition, many transitions that from a mechanistic standpoint should not depend on voltage were assigned a voltage dependence in the model. These limitations diminish the mechanistic insight that can be reliably extracted from the model.
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Reviewer #1 (Public Review):
In this manuscript, Yang et al. conduct a comprehensive investigation to demonstrate the role of adipose tissue miR-802 in obesity-associated inflammation and metabolic dysfunction. Using multiple models and techniques, they propose a mechanism where elevated levels of miR-802 in adipose tissue (both in mouse models and humans) trigger fat accumulation and inflammation, leading to increased adiposity and insulin resistance. They suggest that increased miR-802 levels in adipocytes during obesity result in the downregulation of TRAF3, a negative regulator of canonical and non-canonical NF-κB pathways. This downregulation induces inflammation through the production of cytokines/chemokines that attract and polarize macrophages. Concurrently, the NF-κB pathway induces the lipogenic transcriptional factor SREBP1, which promotes fat accumulation and further recruits pro-inflammatory macrophages. While the proposed model is supported by multiple experiments and consistent data, there are areas where the manuscript could be improved. Some improvements can be addressed in the text, while others require additional controls, experiments, or analyses.
(1) The manuscript should provide measurements of lipid droplet/adipocyte size for all models, both in vitro and in vivo. In vivo studies should also include fat weight measurements. This is crucial to determine whether miR-802, TRAF3, and SREBP1 promote adiposity/fat accumulation across all models.<br /> (2) The rationale for co-culture experiments using WAT SVF is unclear, given that miR-802 is upregulated by obesity in adipocytes, not in the stromal-vascular fraction. These experiments would be more relevant if performed using isolated adipocytes or differentiated WAT SVF.<br /> (3) Figures 1G and 1H lack a control group (time 0 or NCD). Without this control, it is impossible to determine if inflammation precedes miR-802 upregulation.<br /> (4) The statement, "The knockout of miR-802 in adipose tissue did not alter food intake, body weight, glucose level, and adiposity (data not shown)," needs more detail regarding the age and sex of the animals. These data are important and should be reported, perhaps in a supplementary figure.<br /> (5) The terms "KO" (knockout) and "KI" (knock-in) are misleading for AAV models, as they do not modify the genome. "KD" (knockdown) and "OE" (overexpression) are more accurate.<br /> (6) The statement, "miR-802 expression was unaffected in other organs (Figure S3O)," should clarify that this is except for BAT.
By addressing these points, the manuscript would present a more robust and clear demonstration of the role of miR-802 in obesity-associated inflammation and metabolic dysfunction.
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Reviewer #1 (Public Review):
In this paper, Tompary & Davachi present work looking at how memories become integrated over time in the brain, and relating those mechanisms to responses on a priming task as a behavioral measure of memory linkage. They find that remotely but not recently formed memories are behaviorally linked and that this is associated with a change in the neural representation in mPFC. They also find that the same behavioral outcomes are associated with the increased coupling of the posterior hippocampus with category-sensitive parts of the neocortex (LOC) during a post-learning rest period-again only for remotely learned information. There was also correspondence in rest connectivity (posterior hippocampus-LOC) and representational change (mPFC) such that for remote memories specifically, the initial post-learning connectivity enhancement during rest related to longer-term mPFC representational change.
This work has many strengths. The topic of this paper is very interesting, and the data provide a really nice package in terms of providing a mechanistic account of how memories become integrated over a delay. The paper is also exceptionally well-written and a pleasure to read. There are two studies, including one large behavioral study, and the findings replicate in the smaller fMRI sample. I do however have two fairly substantive concerns about the analytic approach, where more data will be required before we can know whether the interpretations are an appropriate reflection of the findings. These and other concerns are described below.
(1) One major concern relates to the lack of a pre-encoding baseline scan prior to recent learning.
a) First, I think it would be helpful if the authors could clarify why there was no pre-learning rest scan dedicated to the recent condition. Was this simply a feasibility consideration, or were there theoretical reasons why this would be less "clean"? Including this information in the paper would be helpful for context. Apologies if I missed this detail in the paper.
b) Second, I was hoping the authors could speak to what they think is reflected in the post-encoding "recent" scan. Is it possible that these data could also reflect the processing of the remote memories? I think, though am not positive, that the authors may be alluding to this in the penultimate paragraph of the discussion (p. 33) when noting the LOC-mPFC connectivity findings. Could there be the reinstatement of the old memories due to being back in the same experimental context and so forth? I wonder the extent to which the authors think the data from this scan can be reflected as strictly reflecting recent memories, particularly given it is relative to the pre-encoding baseline from before the remote memories, as well (and therefore in theory could reflect both the remote + recent). (I should also acknowledge that, if it is the case that the authors think there might be some remote memory processing during the recent learning session in general, a pre-learning rest scan might not have been "clean" either, in that it could have reflected some processing of the remote memories-i.e., perhaps a clean pre-learning scan for the recent learning session related to point 1a is simply not possible.)
c) Third, I am thinking about how both of the above issues might relate to the authors' findings, and would love to see more added to the paper to address this point. Specifically, I assume there are fluctuations in baseline connectivity profile across days within a person, such that the pre-learning connectivity on day 1 might be different from on day 2. Given that, and the lack of a pre-learning connectivity measure on day 2, it would logically follow that the measure of connectivity change from pre- to post-learning is going to be cleaner for the remote memories. In other words, could the lack of connectivity change observed for the recent scan simply be due to the lack of a within-day baseline? Given that otherwise, the post-learning rest should be the same in that it is an immediate reflection of how connectivity changes as a function of learning (depending on whether the authors think that the "recent" scan is actually reflecting "recent + remote"), it seems odd that they both don't show the same corresponding increase in connectivity-which makes me think it may be a baseline difference. I am not sure if this is what the authors are implying when they talk about how day 1 is most similar to prior investigation on p. 20, but if so it might be helpful to state that directly.
d) Fourth and very related to my point 1c, I wonder if the lack of correlations for the recent scan with behavior is interpretable, or if it might just be that this is a noisy measure due to imperfect baseline correction. Do the authors have any data or logic they might be able to provide that could speak to these points? One thing that comes to mind is seeing whether the raw post-learning connectivity values (separately for both recent and remote) show the same pattern as the different scores. However, the authors may come up with other clever ways to address this point. If not, it might be worth acknowledging this interpretive challenge in the Discussion.
(2) My second major concern is how the authors have operationalized integration and differentiation. The pattern similarity analysis uses an overall correspondence between the neural similarity and a predicted model as the main metric. In the predicted model, C items that are indirectly associated are more similar to one another than they are C items that are entirely unrelated. The authors are then looking at a change in correspondence (correlation) between the neural data and that prediction model from pre- to post-learning. However, a change in the degree of correspondence with the predicted matrix could be driven by either the unrelated items becoming less similar or the related ones becoming more similar (or both!). Since the interpretation in the paper focuses on change to indirectly related C items, it would be important to report those values directly. For instance, as evidence of differentiation, it would be important to show that there is a greater decrease in similarity for indirectly associated C items than it is for unrelated C items (or even a smaller increase) from pre to post, or that C items that are indirectly related are less similar than are unrelated C items post but not pre-learning. Performing this analysis would confirm that the pattern of results matches the authors' interpretation. This would also impact the interpretation of the subsequent analyses that involve the neural integration measures (e.g., correlation analyses like those on p. 16, which may or may not be driven by increased similarity among overlapping C pairs). I should add that given the specificity to the remote learning in mPFC versus recent in LOC and anterior hippocampus, it is clearly the case that something interesting is going on. However, I think we need more data to understand fully what that "something" is.
(3) The priming task occurred before the post-learning exposure phase and could have impacted the representations. More consideration of this in the paper would be useful. Most critically, since the priming task involves seeing the related C items back-to-back, it would be important to consider whether this experience could have conceivably impacted the neural integration indices. I believe it never would have been the case that unrelated C items were presented sequentially during the priming task, i.e., that related C items always appeared together in this task. I think again the specificity of the remote condition is key and perhaps the authors can leverage this to support their interpretation. Can the authors consider this possibility in the Discussion?
(4) For the priming task, based on the Figure 2A caption it seems as though every sequence contributes to both the control and primed conditions, but (I believe) this means that the control transition always happens first (and they are always back-to-back). Is this a concern? If RTs are changing over time (getting faster), it would be helpful to know whether the priming effects hold after controlling for trial numbers. I do not think this is a big issue because if it were, you would not expect to see the specificity of the remotely learned information. However, it would be helpful to know given the order of these conditions has to be fixed in their design.
(5) The authors should be cautious about the general conclusion that memories with overlapping temporal regularities become neurally integrated - given their findings in MPFC are more consistent with overall differentiation (though as noted above, I think we need more data on this to know for sure what is going on).
(6) It would be worth stating a few more details and perhaps providing additional logic or justification in the main text about the pre and post-exposure phases were set up and why. How many times each object was presented pre and post, and how the sequencing was determined (were any constraints put in place e.g., such that C1 and C2 did not appear close in time?). What was the cover task (I think this is important to the interpretation & so belongs in the main paper)? Were there considerations involving the fact that this is a different sequence of the same objects the participants would later be learning - e.g., interference, etc.?
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Reviewer #1 (Public Review):
In this study, Girardello et al. use proteomics to reveal the membrane tension sensitive caveolin-1 interactome in migrating cells. The authors use EM and surface rendering to demonstrate that caveolae formed at the rear of migrating cells are complex membrane-linked multilobed structures, and they devise a robust strategy to identify caveolin-1 associated proteins using APEX2-mediated proximity biotinylation. This important dataset is further validated using proximity ligation assays to confirm key interactions, and follows up with an interrogation of a surprising relationship between caveolae and RhoGTPase signalling, where caveolin-1 recruits ROCK1 under high membrane tension conditions, and ROCK1 activity is required to reform caveolae upon reversion to isotonic solution. However, caveolin-1 recruits the RhoA inactivator ARHGAP29 when membrane tension is low and ARHGAP29 overexpression leads to disassembly of caveolae and reduced cell motility. This study builds on previous findings linking caveolae to positive feedback regulation of RhoA signalling, and provides further evidence that caveolae serve to drive rear retraction in migration but also possess an intrinsic brake to limit RhoA activation, leading the authors to suggest that cycles of caveolae assembly and disassembly could thereby be central to establish a stable cell rear for persistent cell migration
A major strength of the manuscript is the robust proteomic dataset. The experimental set up is well defined and mostly well controlled, and there is good internal validation in that the high abundance of core caveolar proteins in low membrane tension (isotonic) conditions, and absence under high membrane tension (brief hypo-osmotic shock) conditions, correlating very well with previous finding. The data could however be better presented to show where statically robust changes occur, and supplementary information should include a table of showing abundance. It's very good to see a link to PRIDE, providing a useful resource for the community.
The authors detail several known interactions and their mechanosensitivty, but also report new interactors of caveolin-1. Several mechanosensitive interactions of caveolin-1 take place at the cell rear, but others are more diffuse across the cell looking at the PLA data (e.g FLN1, CTTN, HSPB1; Figure 4A-F and Figure 4 supplement 1). It is interesting to speculate that those at the cell rear are involved in caveolae, whilst others are linked specifically to caveolin-1 (e.g. dolines). PLA or localisation analysis with Cavin1/PTRF may be able to resolve this and further specify caveolae versus non-caveolae mechanosensitive interactions.
The Cav1/ARHGAP29 influence on YAP signalling is interesting, but appear to be quite isolated from the rest of the manuscript. Does overexpression of ARHGAP29 influence YAP signalling and/or caveolar protein expression/Cav1pY14?<br /> ARHGAP29 and RhoA/ROCK1 related observations are very interesting and potentially really important. However, the link between ARHGAP29 and caveolae is not well established (other than in proteomic data). PLA or FRET could help establish this.<br /> The relationship between ARHGAP29 and RhoA signalling is not well defined. Is GAP activity important in determining the effect on migration and caveolae formation? What is the effect on RhoA activity? Alternatively, the authors could investigate YAP dependent transcriptional regulation downstream of overexpression.
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Reviewer #3 (Public Review):
Although the authors findings are interesting, they do little to demonstrate new scientific information or advancements in producing genetically modified livestock with improved production characteristics. While the MSTNDel273 sheep exhibited an increased number of muscle fibers, the data provided did not demonstrate a significant improvement in meat production, quality or quantity in the MSTNDel273 sheep vs WT.
The manuscript is very long, complicated and difficult to read, given the minimum amount of significant information that is provided. It reads more like a graduate student thesis than a scientific manuscript ready for publication. Given the significant findings are so minimal, the amount of text provided, figures and tables are excessive. A large number of different molecular techniques are employed to try and decipher the mechanism(s) that result in the observed phenotype = double muscling. The authors focus on the MEK-ERK-FOSL1 pathway and suggest this is the key pathway/mechanism resulting in the phenotype observed in MSTNDel273sheep. However, they provide very little "significant" evidence to support this. RNA-Seq data demonstrated that hundreds of different genes were either upregulated or down-regulated, but the authors chose to only focus on FOSL1 and associated genes. The findings do not support the idea that FOSL1 is not involved, but neither do they strongly support FOSL1 involvement. The observations made by the authors could be co-incidental and not causative in nature.
The authors indicate that sgRNA design changes in addition to changing the molar ratio of Cas9MRNA:sgRNA improved the ability to generate biallelic homozygous mutant sheep; however, the data provided to not demonstrate any significant difference. Given the small number of sheep that were actually produced and evaluated, it is extremely difficult to demonstrate anything that was analyzed to be significantly (statistically) different between MSTNDel273 sheep and WT, yet the authors seem to ignore this in much of their discussion. There is no explanation as to why the authors started with sheep that were FGF5 knockouts. The reviewer assumes that this was simply a line of sheep available from previous studies and the goal was to produce sheep with both improved hair/wool characteristics in addition to improved muscle development. However, the use of FGF5 knockout sheep complicates the ability to accurately decipher the unique aspects associated with targeting only myostatin for knock-out. At minimum, this is a variable that has to be considered in the statistical analysis. No information is provided on the methods used to produce the MSTNDel273 sheep, which seems fundamentally important. It is assumed they were produced by injecting one-cell zygotes then transferring these into surrogate females, but given the information provided, it is impossible to know. Certainly, the methods employed could have a profound effect on the outcome. There is no information provided on the sex of the animals produced and then analyzed.
Comments on revised version:
The manuscript by Chen et al. is improved and demonstrates successful gene editing in sheep embryos to obtain biallelic mutation of Mstn and FGF5. Despite the improvements in the revised manuscript, the cellular and molecular mechanism remain inadequate to conclude whether Fosl1 indeed acts downstream of myostatin. In addition, there is little that is new direction versus confirmatory for what is already well know regarding Mstn and FGF5
There are also a number of editorial mistakes e.g. the authors refer to tables S1-S4 in the materials and methods and results section, but there is no table S1-S4 provided.
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Reviewer #1 (Public Review):
Summary:
The data clearly demonstrate that arpin is important for vessel barrier function, yet its genetic loss via a CRISPR strategy was not lethality, but led to viable animals in C57Blk strain at 12 weeks of age, albeit with leaky blood vessels. Pharmacological approaches were employed to demonstrate that loss of arpin led to ROCK1-dependent stress fiber formation that promoted increased permeability.
Strengths:
The results clearly demonstrate that arpin is expressed in the endothelium of blood vessels and its deficiency leads to leaky blood vessels in in vivo and in vitro models.
Weaknesses:
They conclude vessel leak was not related to enhanced Arp2/3 function through arpin deficiency, but no direct evidence of Arp2/3 activity is provided to support this conclusion. Instead, the authors concluded that ROCK1 activity was elevated in arpin knockdown cells and caused robust stress fiber formation. This idea could be strengthened by testing if ROCK1 inhibition by pharmacological block in arpin KO mice leads to less vascular leakage while pharmacological inhibition of Arp2/3 does not attenuate increased vessel permeability.
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Reviewer #1 (Public Review):
Summary:
BMP signaling is, arguably, best known for its role in the dorsoventral patterning, but not in nematodes, where it regulates body size. In their paper, Vora et al. analyze ChIP-Seq and RNA-Seq data to identify direct transcriptional targets of SMA-3 (Smad) and SMA-9 (Schnurri) and understand the respective roles of SMA-3 and SMA-9 in the nematode model Caenorhabditis elegans. The authors use publicly available SMA-3 and SMA-9 ChIP-Seq data, own RNA-Seq data from SMA-3 and SMA-9 mutants, and bioinformatic analyses to identify the genes directly controlled by these two transcription factors (TFs) and find approximately 350 such targets for each. They show that all SMA-3-controlled targets are positively controlled by SMA-3 binding, while SMA-9-controlled targets can be either up or downregulated by SMA-9. 129 direct targets were shared by SMA-3 and SMA-9, and, curiously, the expression of 15 of them was activated by SMA-3 but repressed by SMA-9. Since genes responsible for cuticle collagen production were eminent among the SMA-3 targets, the authors focused on trying to understand the body size defect known to be elicited by the modulation of BMP signaling. Vora et al. provide compelling evidence that this defect is likely to be due to problems with the BMP signaling-dependent collagen secretion necessary for cuticle formation.
Strengths:
Vora et al. provide a valuable analysis of ChIP-Seq and RNA-Seq datasets, which will be very useful for the community. They also shed light on the mechanism of the BMP-dependent body size control by identifying SMA-3 target genes regulating cuticle collagen synthesis and by showing that downregulation of these genes affects body size in C. elegans.
Weaknesses:
(1) Although the analysis of the SMA-3 and SMA-9 ChIP-Seq and RNA-Seq data is extremely useful, the goal "to untangle the roles of Smad and Schnurri transcription factors in the developing C. elegans larva", has not been reached. While the role of SMA-3 as a transcriptional activator appears to be quite straightforward, the function of SMA-9 in the BMP signaling remains obscure. The authors write that in SMA-9 mutants, body size is affected, but they do not show any data on the mechanism of this effect.
(2) The authors clearly show that both TFs can bind independently of each other, however, by using distances between SMA-3 and SMA-9 ChIP peaks, they claim that when the peaks are close these two TFs act as complexes. In the absence of proof that SMA-3 and SMA-9 physically interact (e.g. that they co-immunoprecipitate - as they do in Drosophila), this is an unfounded claim, which should either be experimentally substantiated or toned down.
(3) The second part of the paper (the collagen story) is very loosely connected to the first part. dpy-11 encodes an enzyme important for cuticle development, and it is a differentially expressed direct target of SMA-3. dpy-11 can be bound by SMA-9, but it is not affected by this binding according to RNA-Seq. Thus, technically, this part of the paper does not require any information about SMA-9. However, this can likely be improved by addressing the function of the 15 genes, with the opposing mode of regulation by SMA-3 and SMA-9.
(4) The Discussion does not add much to the paper - it simply repeats the results in a more streamlined fashion.
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Reviewer #1 (Public Review):
Summary:
This manuscript by Aybar-Torres et al investigated the effect of common human STING1 variants on STING-mediated T cell phenotypes in mice. The authors previously made knock-in mice expressing human STING1 alleles HAQ or AQ, and here they established a new knock-in line Q293. The authors stimulated cells isolated from these mice with STING agonists and found that all three human mutant alleles resist cell death, leading to the conclusion that R293 residue is essential for STING-mediated cell death (there are several caveats with this conclusion, more below). The authors also bred HAQ and AQ alleles to the mouse Sting1-N153S SAVI mouse and observed varying levels of rescue of disease phenotypes with the AQ allele showing more complete rescue than the HAQ allele. The Q293 allele was not tested in the SAVI model. They conclude that the human common variants such as HAQ and AQ have a dominant negative effect over the gain-of-function SAVI mutants.
Strengths:
The authors and Dr. Jin's group previously made important observations of common human STING1 variants, and these knock-in mouse models are essential for understanding the physiological function of these alleles.
Weaknesses:
However, although some of the observations reported here are interesting, the data collectively does not support a unified model. The authors seem to be drawing two sets of conclusions from in vitro and in vivo experiments, and neither mechanism is clear. Several experiments need better controls, and these knock-in mice need more comprehensive functional characterization.
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www.biorxiv.org www.biorxiv.org
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Summary:
This paper described the dynamics of the nuclear substructure called PML Nucleolar Association (PNA) in response to DNA damage on ribosomal DNA (rDNA) repeats. The authors showed that the PNA with rDNA repeats is induced by the inhibition of topoisomerases and RNA polymerase I and that the PNA formation is modulated by RAD51, thus homologous recombination. Artificially induced DNA double-strand breaks (DSBs) in rDNA repeats stimulate the formation of PNA with DSB markers. This DSB-triggered PNA formation is regulated by DSB repair pathways.
Strengths:
This paper illustrates a unique DNA damage-induced sub-nuclear structure containing the PML body, which is specifically associated with the nucleolus. Moreover, the dynamics of this PML Nucleolar Association (PNA) require topoisomerases and RNA polymerase I and are modulated by RAD51-mediated homologous recombination and non-homologous end-joining. This study provides a unique regulation of DSB repair at rDNA repeats associated with the unique-membrane-less subnuclear structure.
Weaknesses:
Although the PNA formation on rDNA repeat is nicely shown by cytological analysis, the biological significance of PNA in DSB repair is not fully addressed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> 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 nose poke 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 nose poke. 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:<br /> 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:<br /> One weakness to me is the impact of identifying whether D1 and D2 had similar or different activity patterns. Does observing increasing/decreasing activity in D2 versus D1, or different activity patterns in D1 and D2, support one model of interval timing over another, or does it further support a more specific idea of how DMS contributes to interval timing?
I found the results presented in Figures 2 and 3 to be a little confusing or misleading. In Figure 2, the authors appear to claim that D1 neurons decrease their activity over the time interval while D2 neurons increase activity. The authors use this result to suggest that D1/D2 activity patterns are different. In Figure 3, a different analysis is done, and this time D2 neurons do not significantly increase their activity with time, conflicting with Figure 2. While in both figures, there is a significant difference between the mean slopes across the population, the secondary effect of positive/negative slope for D2/D1 neurons changes. I find this especially confusing as the authors refer back to the positive/negative slope for D2/D1 neurons result throughout the rest of the text.
It is a bit unclear to me how the authors chose the parameters for the model, and how well the model explains behavior is quantified. It seems that the authors didn't perform cross-validation across trials (i.e., they chose parameters that explained behavior across all trials combined, rather than choosing parameters from a subset of trials and determining whether those parameters are robust enough to explain behavior on held-out trials). I think this would increase the robustness of the result.
In addition, it remains a bit unclear to me how the authors changed the specific parameters they did to model the optogenetic manipulation. It seems these parameters were chosen because they fit the manipulation data. This makes me wonder if this model is flexible enough that there is almost always a set of parameters that would explain any experimental result; in other words, I'm not sure this model has high explanatory power.
Lastly, the results are based on a relatively small dataset (tens of cells).
Impact:<br /> 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. However, the significance of the key finding -- that D1 and D2 activity is distinct across time -- remains somewhat ambiguous to me.
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Reviewer #1 (Public Review):
Summary:
This review evaluates the SCellBOW framework, which applies phenotype algebra to obtain vectors from cancer subclusters or user-defined subclusters.
Strengths:
SCellBOW employs an innovative application of NLP-inspired techniques to analyze scRNA-seq data, facilitating the identification and visualization of phenotypically divergent cell subpopulations.
The framework demonstrates robustness in accurately representing various cell types across multiple datasets, highlighting its versatility and utility in different biological contexts.
By simulating the impact of specific malignant subpopulations on disease prognosis, SCellBOW provides valuable insights into the relative risk and aggressiveness of cancer subpopulations, which is crucial for personalized therapeutic strategies.
The identification of a previously unknown and aggressive AR−/NElow subpopulation in metastatic prostate cancer underscores the potential of SCellBOW in uncovering clinically significant findings.
Weaknesses:
The reliance on bulk RNA-seq data as a reference raises concerns about potentially misleading results due to the presence of RNA expression from immune cells in the TME. It is unclear if SCellBOW adequately addresses this issue, which could affect the accuracy of the cancer subcluster vectors.
The method of extracting vectors in phenotype algebra appears to be a straightforward subtraction operation. This simplicity might limit its efficiency in excluding associations with phenotypes from specific subpopulations, potentially leading to inaccurate interpretations of the data.
The review would benefit from additional validation studies to assess the effectiveness of SCellBOW in distinguishing between cancerous and non-cancerous signals, particularly in heterogeneous tumor environments.
Further clarification on how SCellBOW handles mixed-cell populations within bulk RNA-seq data would strengthen the evaluation of its applicability and reliability in diverse research settings.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This study unveils a novel role for ferritin in Drosophila larval brain development. Furthermore, it pinpoints that the observed defects in larval brain development resulting from ferritin knockdown are attributed to impaired Fe-S cluster activity and ATP production. Overall this is a well-conducted and novel study.
The author have adequately addressed the concerns.
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In this study, the authors confirm that one of the genes classified as essential in a Tn-mutagenesis study in A. baumannii, Aeg1, is, in fact, an essential gene. The strength of the work is that it discovered that the depletion of Aeg1 leads to cell filamentation and that activation mutations in various cell division genes can suppress the requirement for Aeg1. These results suggest that Aeg1 plays an important role in cell division. The work's weakness is that it lacks convincing evidence to define Aeg1's place or role in the divisome assembly pathway. It is unclear whether proteins are at the division site under the wildtype condition and when Aeg1 is depleted, and whether Aeg1 is indeed required for a set of division proteins to the division site.
Reviewer comments:
The revised manuscript partially addressed two of the three major concerns from the previous assessment: (1) the functionality test of fluorescent fusion proteins using a spotting assay, and (2) membrane protein topology in the bacterial two-hybrid assays by constructing a C-terminal T25 fusion.
(1) In the spotting assay, all fluorescent fusion proteins rescued the growth of the corresponding deletion strain, which suggests these fusion proteins are functional. However, fluorescent images of these fusion proteins were diffusive, and only a few cells showed the expected midcell/membrane localization pattern for cell division proteins. This observation raised the concern that these fusion proteins may be cleaved in the middle, leading to the separation of the untagged fusion partner and diffusive fluorescent protein in the cytoplasm, which would explain the positive spotting rescue results. This phenomenon is commonly observed in other bacterial species. A western blot using an antibody targeting either the fluorescent protein or the fusion partner is widely used to examine whether the fusion protein is expressed at its full length.
(2) The authors constructed a C-terminal fusion of Aeg1 and showed that it still interacted with ZipA and FtsN. This result supports the authors' suggestion that the N-terminus of Aeg1 may not be the predicated membrane-targeting domain. Along the same line, the membrane topology of ZipA should also be considered. ZipA's N terminus is in the membrane facing the periplasm, and its C terminal domain is in the cytoplasm. Therefore, the PUT18C fusion will place the T18 domain of ZipA in the periplasm. All other division proteins' N termini are in the cytoplasm.
(3) Colocalization images did not show significant midcell localizations for each fluorescent protein; most cells showed diffusive cytoplasmic fluorescence. In all other species, midcell localization of cell division proteins is prominent in dividing cells, especially for early division proteins such as ZipA (at least 40-50% of cells show midcell bands). In A. baumannii, divisome localization timing may differ from other species, but this possibility needs to be established before the colocalization pattern is examined. Compounding this issue is that in Aeg1 depletion strains, some cells expressing ZipA, FtsB, FtsL, and FtsN fusions showed roughly regularly spaced puncta in long filamentous cells. It is hard to explain why this was observed if, under the WT condition, these fusions do not localize to the midcell. These results again raised concerns that these fusion proteins may not be functional and the observations are protein aggregates.
Besides these major issues, experimental observations did not support some claims in the main text. For example: (1) In the two-hybrid assay, only ZipA and FtsN showed significant interactions with Aeg1, as judged by the darkness of the blue spots. FtsL and FtsB showed pale spots. The quantified values accompanying this figure did not appear to agree with the image. (2) The spotting rescue assay showed that only FtsB-E56A and FtsA-E202K was able to bypass Aeg1 depletion (full dilution set comparable to that of Aeg1 complementation), but the main text claimed that FtsA-D124A and V144L, and FtsW-M254I and S274G also rescued the growth. These claims could be misleading.
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Reviewer #1 (Public Review):
Summary:
Understanding the mechanisms of how organisms respond to environmental stresses is a key goal of biological research. Assessment of transcriptional responses to stress can provide some insights into those underlying mechanisms. The researchers quantified traits, fitness, and gene expression (transcriptional) response to salinity stress (control vs stress treatments) for 130 accessions of rice (three replicates for each accession), which were grown in the field in the Philippines. This experimental design allowed for many different types of downstream analyses to better understand the biology of the system. These analyses included estimating the strength of selection imposed on transcription in each environment, evaluating possible trade-offs in gene expression, testing whether salinity induces transcriptional decoherence, and conducting various eQTL-type analyses.
Strengths:
The study provides an extensive analysis of gene expression responses to stress in rice and offers some insights into underlying mechanisms of salinity responses in this important crop system. The fact that the study was conducted under field conditions is a major plus, as the gene expression responses to soil salinity are more realistic than if the study was conducted in a greenhouse or growth chamber. The preprint is generally well-written and the methods and results are mostly well-described.
Weaknesses:
While the study makes good use of analyzing the dataset, it is not clear how the current work advances our understanding of gene regulatory evolution or plant responses to soil salinity generally. Overall, the results are consistent with other prior studies of gene expression and studies of selection across environmental conditions. Some of the framing of the paper suggests that there is more novelty to this study than there is in reality. That said, the results will certainly be useful for those working in rice and should be interesting to scientists interested in how gene expression responses to stress occur under field conditions. I detail other concerns I had about the preprint below:
The abstract on lines 33-35 illustrates some of my concerns about the overstatement of the novelty of the current study. For example, is it really true that the role of gene expression in mediating stress response and adaptation is largely unexplored? There have been numerous studies that have evaluated gene expression responses to stresses in a wide range of organisms. Perhaps, I am missing something critically different about this study. If so, I would recommend that the authors reword this sentence to clarify what gap is being filled by this study. Further, is it really the case that none of them have evaluated how the correlational structure of gene expression changes in response to stresses in plants, as implied in lines 263-265? Don't the various modules and PC analyses of gene expression get at this question?
There were some places in the methods of the preprint that required more information to properly evaluate. For example, more information should be provided on lines 664-668 about how G, E, and GxE effects were established, especially since this is so central to this study. What programs/software (R? SAS? Other?) were used for these analyses? If R, how were the ANOVAs/models fit? What type of ANOVA was used? How exactly was significance determined for each term? Which effects were considered fixed and which were random? If the goal was to fit mixed models, why not use an approach like voom-limma (Law et al. 2014 Genome Biology)? More details should also be added to lines 688-709 about these analyses, including what software/programs were used for these analyses.
One thing that I found a bit confusing throughout was the intermixing of different terms and types of selection. In particular, there seemed to be some inconsistencies with the usage of quantitative genetics terms for selection (e.g. directional, stabilizing) vs molecular evolution terms for selection (e.g. positive, purifying). I would encourage the authors to think carefully about what they mean by each of these terms and make sure that those definitions are consistently applied here.
It would be useful to clarify the reasons for the inherent bias in the detection of conditional neutrality (CN) and antagonistic pleiotropy (AP; Lines 187-196). It is also not clear to me what the authors did to deal with the bias in terms of adjusting P-value thresholds for CN and AP the way it is currently written. Further, I found the discussion of antagonistic pleiotropy and conditional neutrality to be a bit confusing for a couple of reasons, especially around lines 489-491. First of all, does it really make sense to contrast gene expression versus local adaptation, when lots of local adaptation likely involves changes in gene expression? Second, the implication that antagonistic pleiotropy is more common for local adaptation than the results found in this study seems questionable. Conditional neutrality appears to be more common for local adaptation as well: see Table 2 of Wadgymar et al. 2017 Methods in Ecology and Evolution. That all said, it is always difficult to conclude that there are no trade-offs (antagonistic pleiotropy) for a particular locus, as the detecting trade-offs may only manifest in some years and not others and can require large sample sizes if they are subtle in effect.
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Reviewer #1 (Public Review):
The study starts with the notion that in an AD-like disease model, ILC2s in the Rag1 knock-out were expanded and contained relatively more IL-5+ and IL-13+ ILC2s. This was confirmed in the Rag2 knock-out mouse model.
By using a chimeric mouse model in which wild-type knock-out splenocytes were injected into irradiated Rag1 knock-out mice, it was shown that even though the adaptive lymphocyte compartment was restored, there were increased AD-like symptoms and increased ILC2 expansion and activity. Moreover, in the reverse chimeric model, i.e. injecting a mix of wild-type and Rag1 knock-out splenocytes into irradiated wild-type animals, it was shown that the Rag1 knock-out ILC2s expanded more and were more active. Therefore, the authors could conclude that the RAG1 mediated effects were ILC2 cell-intrinsic.
Subsequent fate-mapping experiments using the Rag1Cre;reporter mouse model showed that there were indeed RAGnaïve and RAGexp ILC2 populations within naïve mice. Lastly, the authors performed multi-omic profiling, using single-cell RNA sequencing and ATAC-sequencing, in which a specific gene expression profile was associated with ILC2. These included well-known genes but the authors notably also found expression of Ccl1 and Ccr8 within the ILC2. The authors confirmed their earlier observations that in the RAGexp ILC2 population, the Th2 regulome was more suppressed, i.e. more closed, compared to the RAGnaïve population, indicative of the suppressive function of RAG on ILC2 activity. I do agree with the authors' notion that the main weakness was that this study lacks the mechanism by which RAG regulates these changes in ILC2s.
The manuscript is very well written and easy to follow, and the compelling conclusions are well supported by the data. The experiments are meticulously designed and presented. I wish to commend the authors for the study's quality.
Even though the study is compelling and well supported by the presented data, some additional context could increase the significance:
(1) The presence of the RAGnaïve and RAGexp ILC2 populations raises some questions on the (different?) origin of these populations. It is known that there are different waves of ILC2 origin (most notably shown in the Schneider et al Immunity 2019 publication, PMID 31128962). I believe it would be very interesting to further discuss or possibly show if there are different origins for these two ILC populations.
Several publications describe the presence and origin of ILC2s in/from the thymus (PMIDs 33432227 24155745). Could the authors discuss whether there might be a common origin for the RAGexp ILC2 and Th2 cells from a thymic lineage? If true that the two populations would be derived from different populations, e.g. being the embryonic (possibly RAGnaïve) vs. adult bone marrow/thymus (possibly RAGexp), this would show a unique functional difference between the embryonic derived ILC2 vs. adult ILC2.
(2) On line 104 & Figures 1C/G etc. the authors describe that in the RAG knock-out ILC2 are relatively more abundant in the lineage negative fraction. On line 108 they further briefly mentioned that this observation is an indication of enhanced ILC2 expansion. Since the study includes an extensive multi-omics analysis, could the authors discuss whether they have seen a correlation of RAG expression in ILC2 with regulation of genes associated with proliferation, which could explain this phenomenon?
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Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors experimentally demonstrated the heterogeneous behavior of sarcomeres in cardiomyocytes and that a stochastic component exists in their contractile activity, which cancels out at the level of myofibrils.
Strengths:
The experiments and data analysis are robust and valid. With very good statistics and unbiased methods, they show cellular activity at the individual level and highlight the heterogeneity between biological networks. The similarity of the results to the study cited in [24] demonstrates the validity of the in vitro setup for answering these questions and the feasibility of such in-vitro systems to extend our knowledge of physiology.
Weaknesses:
Compared to the current literature ([24]), the study does not show a high degree of innovation. It mainly confirms what has been established in the past. The authors complemented the published experiments by developing an in vitro setup with stem cells and by changing the stiffness of the substrate to simulate pathological conditions. However, the experiments they performed do not allow them to explain more than the study in [24], and the conclusions of their study are based on interpretation and speculation about the possible mechanism underlying the observations.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Yang et al report a novel regulatory role of SIRT4 in the progression of kidney fibrosis. The authors showed that in the fibrotic kidney, SIRT4 exhibited an increased nuclear localization. Deletion of Sirt4 in renal tubule epithelium attenuated the extent of kidney fibrosis following injury, while overexpression of SIRT4 aggravates kidney fibrosis. Employing a battery of in vitro and in vivo experiments, the authors demonstrated that SIRT4 interacts with U2AF2 in the nucleus upon TGF-β1 stimulation or kidney injury and deacetylates U2AF2 at K413, resulting in elevated CCN2 expression through alternative splicing of Ccn2 gene to promote kidney fibrosis. The authors further showed that the translocation of SIRT4 is through the BAX/BAK pore complex and is dependent on the ERK1/2-mediated phosphorylation of SIRT4 at S36, and consequently the binding of SIRT4 to importin α1. This fundamental work substantially advances our understanding of the progression of kidney fibrosis and uncovers a novel SIRT4-U2AF2-CCN2 axis as a potential therapeutic target for kidney fibrosis.
Strengths:
Overall, this is an extensive, well-performed study. The results are convincing, and the conclusions are mostly well supported by the data. The message is interesting to a wider community working on kidney fibrosis, protein acetylation, and SIRT4 biology.
Weaknesses:
The manuscript could be further strengthened if the authors could address a few points listed below:
(1) In the results part 3.9, an in vitro deacetylation assay employing recombinant SIRT4 and U2AF2 should be included to support the conclusion that SIRT4 is a deacetylase of U2AF2. Similarly, an in vitro binding assay can be included to confirm whether SIRT4 and U2AF2 are directly interacted.
(2) In Figure 6D, the Western Blot data using U2AF2-K453Q is confusing and is quite disconnected from the rest of the data and not explained. This data can be removed or explained why U2AF2-K453Q is employed here.
(3) Although ERK inhibitor U0126 blocked the nuclear translocation of SIRT4 in vivo, have the authors checked whether treatment with U0126 could affect the expression of kidney fibrosis markers in UUO mice?
(4) The format of gene and protein abbreviations in the manuscript should be standardized.
(5) There are a few grammar issues throughout the manuscript. The English/grammar could be stronger, thus improving the overall accessibility of the science to readers.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Zhao et al. used the human forebrain organoid model, transgenic mice model, and embryonic neural progenitor cells to investigate the mutation previously identified in Williams Syndrome. They found abnormal proliferation and differentiation induced by this mutation, as well as altered expression profiles corresponding with aberrant cell clusters. This is regulated through the binding of GTF2IRD1 to transthyretin (TTR) promoter regions and tested on three models mentioned above on neurodevelopmental deficits.
Strengths:
Authors have applied both cell culture, organoid culture and in vivo model to test the previously reported mutation found in Williams Syndrome. They investigated cell behavior including proliferation and differentiation, while using the NGS technique to identify potential signaling pathways that are highly involved and can serve as a candidate to save the phenotype.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Young (2.5 mo [adolescent]) rats were tasked to either press one lever for immediate reward or another for delayed reward. The task had a complex structure in which (1) the number of pellets provided on the immediate reward lever changed as a function of the decisions made, (2) rats were prevented from pressing the same lever three times in a row. Importantly, this task is very different from most intertemporal choice tasks which adjust delay (to the delayed lever), whereas this task held the delay constant and adjusted the number of 20 mg sucrose pellets provided on the immediate value lever.
Analyses are based on separating sessions into groups, but group membership includes arbitrary requirements and many sessions have been dropped from the analyses. Computational modeling is based on an overly simple reinforcement learning model, as evidenced by fit parameters pegging to the extremes. The neural analysis is overly complex and does not contain the necessary statistics to assess the validity of their claims.
Strengthes:
The task is interesting.
Weaknesses:
Behavior:
The basic behavioral results from this task are not presented. For example, "each recording session consisted of 40 choice trials or 45 minutes". What was the distribution of choices over sessions? Did that change between rats? Did that change between delays? Were there any sequence effects? (I recommend looking at reaction times.) Were there any effects of pressing a lever twice vs after a forced trial? This task has a very complicated sequential structure that I think I would be hard pressed to follow if I were performing this task. Before diving into the complex analyses assuming reinforcement learning paradigms or cognitive control, I would have liked to have understood the basic behaviors the rats were taking. For example, what was the typical rate of lever pressing? If the rats are pressing 40 times in 45 minutes, does waiting 8s make a large difference?
For that matter, the reaction time from lever appearance to lever pressing would be very interesting (and important). Are they making a choice as soon as the levers appear? Are they leaning towards the delay side, but then give in and choose the immediate lever? What are the reaction time hazard distributions?
It is not clear that the animals on this task were actually using cognitive control strategies on this task. One cannot assume from the task that cognitive control is key. The authors only consider a very limited number of potential behaviors (an overly simple RL model). On this task, there are a lot of potential behavioral strategies: "win-stay/lose-shift", "perseveration", "alternation", even "random choices" should be considered.
The delay lever was assigned to the "non-preferred side". How did side bias affect the decisions made?
The analyses based on "group" are unjustified. The authors compare the proportion of delayed to immediate lever press choices on the non-forced trials and then did k-means clustering on this distribution. But the distribution itself was not shown, so it is unclear whether the "groups" were actually different. They used k=3, but do not describe how this arbitrary number was chosen. (Is 3 the optimal number of clusters to describe this distribution?) Moreover, they removed three group 1 sessions with an 8s delay and two group 2 sessions with a 4s delay, making all the group 1 sessions 4s delay sessions and all group 2 sessions 8s delay sessions. They then ignore group 3 completely. These analyses seem arbitrary and unnecessarily complex. I think they need to analyze the data by delay. (How do rats handle 4s delay sessions? How do rats handle 6s delay sessions? How do rats handle 8s delay sessions?). If they decide to analyze the data by strategy, then they should identify specific strategies, model those strategies, and do model comparison to identify the best explanatory strategy. Importantly, the groups were session-based, not rat based, suggesting that rats used different strategies based on the delay to the delayed lever.
The reinforcement learning model used was overly simple. In particular, the RL model assumes that the subjects understand the task structure, but we know that even humans have trouble following complex task structures. Moreover, we know that rodent decision-making depends on much more complex strategies (model-based decisions, multi-state decisions, rate-based decisions, etc). There are lots of other ways to encode these decision variables, such as softmax with an inverse temperature rather than epsilon-greedy. The RL model was stated as a given and not justified. As one critical example, the RL model fit to the data assumed a constant exponential discounting function, but it is well-established that all animals, including rodents, use hyperbolic discounting in intertemporal choice tasks. Presumably this changes dramatically the effect of 4s and 8s. As evidence that the RL model is incomplete, the parameters found for the two groups were extreme. (Alpha=1 implies no history and only reacting to the most recent event. Epsilon=0.4 in an epsilon-greedy algorithm is a 40% chance of responding randomly.)
The authors do add a "dbias" (which is a preference for the delayed lever) term to the RL model, but note that it has to be maximal in the 4s condition to reproduce group 2 behavior, which means they are not doing reinforcement learning anymore, just choosing the delayed lever.
Neurophysiology:
The neurophysiology figures are unclear and mostly uninterpretable; they do not show variability, statistics or conclusive results.
As with the behavior, I would have liked to have seen more traditional neurophysiological analyses first. What do the cells respond to? How do the manifolds change aligned to the lever presses? Are those different between lever presses? Are there changes in cellular information (both at the individual and ensemble level) over time in the session? How do cellular responses differ during that delay while both levers are out, but the rats are not choosing the immediate lever?
Figure 3, for example, claims that some of the principal components tracked the number of pellets on the immediate lever ("ival"), but they are just two curves. No statistics, controls, or justification for this is shown. BTW, on Figure 3, what is the event at 200s?
I'm confused. On Figure 4, the number of trials seems to go up to 50, but in the methods, they say that rats received 40 trials or 45 minutes of experience.
At the end of page 14, the authors state that the strength of the correlation did not differ by group and that this was "predicted" by the RL modeling, but this statement is nonsensical, given that the RL modeling did not fit the data well, depended on extreme values. Moreover, this claim is dependent on "not statistically detectable", which is, of course, not interpretable as "not different".
There is an interesting result on page 16 that the increases in theta power were observed before a delayed lever press but not an immediate lever press, and then that the theta power declined after an immediate lever press. These data are separated by session group (again group 1 is a subset of the 4s sessions, group 2 is a subset of the 8s sessions, and group 3 is ignored). I would much rather see these data analyzed by delay itself or by some sort of strategy fit across delays. That being said, I don't see how this description shows up in Figure 6. What does Figure 6 look like if you just separate the sessions by delay?
Discussion:
Finally, it is unclear to what extent this task actually gets at the questions originally laid out in the goals and returned to in the discussion. The idea of cognitive effort is interesting, but there is no data presented that this task is cognitive at all. The idea of a resourced cognitive effort and a resistance cognitive effort is interesting, but presumably the way one overcomes resistance is through resource-limited components, so it is unclear that these two cognitive effort strategies are different.
The authors state that "ival-tracking" (neurons and ensembles that presumably track the number of pellets being delivered on the immediate lever - a fancy name for "expectations") "taps into a resourced-based form of cognitive effort", but no evidence is actually provided that keeping track of the expectation of reward on the immediate lever depends on attention or mnemonic resources. They also state that a "dLP-biased strategy" (waiting out the delay) is a "resistance-based form of cognitive effort" but no evidence is made that going to the delayed side takes effort.
The authors talk about theta synchrony, but never actually measure theta synchrony, particularly across structures such as amygdala or ventral hippocampus. The authors try to connect this to "the unpleasantness of the delay", but provide no measures of pleasantness or unpleasantness. They have no evidence that waiting out an 8s delay is unpleasant.
The authors hypothesize that the "ival-tracking signal" (the expectation of number of pellets on the immediate lever) "could simply reflect the emotional or autonomic response". Aside from the fact that no evidence for this is provided, if this were to be true, then, in what sense would any of these signals be related to cognitive control?
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www.medrxiv.org www.medrxiv.org
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Joint Public Review:
Summary:
This study retrospectively analyzed clinical data to develop a risk prediction model for pulmonary hypertension in high-altitude populations. This finding holds clinical significance as it can be used for intuitive and individualized prediction of pulmonary hypertension risk in these populations. The strength of evidence is high, utilizing a large cohort of 6,603 patients and employing statistical methods such as LASSO regression. The model demonstrates satisfactory performance metrics, including AUC values and calibration curves, enhancing its clinical applicability.
Strengths:
(1) Large Sample Size: The study utilizes a substantial cohort of 6,603 subjects, enhancing the reliability and generalizability of the findings.
(2) Robust Methodology: The use of advanced statistical techniques, including least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression, ensures the selection of optimal predictive features.
(3) Clinical Utility: The developed nomograms are user-friendly and can be easily implemented in clinical settings, particularly in resource-limited high-altitude regions.
(4) Performance Metrics: The models demonstrate satisfactory performance, with strong AUC values and well-calibrated curves, indicating accurate predictions.
Weaknesses:
(1) Lack of External Validation: The models were validated internally, but external validation with cohorts from other high-altitude regions is necessary to confirm their generalizability.
(2) Simplistic Predictors: The reliance on ECG and basic demographic data may overlook other potential predictors that could improve the models' accuracy and predictive power.
(3) Regional Specificity: The study's cohort is limited to Tibet, and the findings may not be directly applicable to other high-altitude populations without further validation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors describe a comprehensive analysis of sex-biased expression across multiple tissues and species of mouse. Their results are broadly consistent with previous work, and their methods are robust, as the large volume of work in this area has converged toward a standardized approach.
I have a few quibbles with the findings, and the main novelty here is the rapid evolution of sex-biased expression over shorter evolutionary intervals than previously documented, although this is not statistically supported. The other main findings, detailed below, are somewhat overstated.
(1) In the introduction, the authors conflate gametic sex, which is indeed largely binary (with small sperm, large eggs, no intermediate gametic form, and no overlap in size) with somatic sexual dimorphism, which can be bimodal (though sometimes is even more complicated), with a large variance in either sex and generally with a great deal of overlap between males and females. A good appraisal of this distinction is at https://doi.org/10.1093/icb/icad113. This distinction in gene expression has been recognized for at least 20 years, with observations that sex-biased expression in the soma is far less than in the gonad.
For example, the authors frame their work with the following statement:<br /> "The different organs show a large individual variation in sex-biased gene expression, making it impossible to classify individuals in simple binary terms. Hence, the seemingly strong conservation of binary sex-states does not find an equivalent underpinning when one looks at the gene-expression makeup of the sexes"
The authors use this conflation to set up a straw man argument, perhaps in part due to recent political discussions on this topic. They seem to be implying one of two things. a) That previous studies of sex-biased expression of the soma claim a binary classification. I know of no such claim, and many have clearly shown quite the opposite, particularly studies of intra-sexual variation, which are common - see https://doi.org/10.1093/molbev/msx293, https://doi.org/10.1371/journal.pgen.1003697, https://doi.org/10.1111/mec.14408, https://doi.org/10.1111/mec.13919, https://doi.org/10.1111/j.1558-5646.2010.01106.x for just a few examples. Or b) They are the first to observe this non-binary pattern for the soma, but again, many have observed this. For example, many have noted that reproductive or gonad transcriptome data cluster first by sex, but somatic tissue clusters first by species or tissue, then by sex (https://doi.org/10.1073/pnas.1501339112, https://doi.org/10.7554/eLife.67485)<br /> Figure 4 illustrates the conceptual difference between bimodal and binary sexual conceptions. This figure makes it clear that males and females have different means, but in all cases the distributions are bimodal.
I would suggest that the authors heavily revise the paper with this more nuanced understanding of the literature and sex differences in their paper, and place their findings in the context of previous work.
(2) The authors also claim that "sexual conflict is one of the major drivers of evolutionary divergence already at the early species divergence level." However, making the connection between sex-biased genes and sexual conflict remains fraught. Although it is tempting to use sex-biased gene expression (or any form of phenotypic dimorphism) as an indicator of sexual conflict, resolved or not, as many have pointed out, one needs measures of sex-specific selection, ideally fitness, to make this case (https://doi.org/10.1086/595841, 10.1101/cshperspect.a017632). In many cases, sexual dimorphism can arise in one sex only without conflict (e.g. 10.1098/rspb.2010.2220). As such, sex-biased genes alone are not sufficient to discriminate between ongoing and resolved conflict.
(3) To make the case that sex-biased genes are under selection, the authors report alpha values in Figure 3B. Alpha value comparisons like this over large numbers of genes often have high variance. Are any of the values for male- female- and un-biased genes significantly different from one another? This is needed to make the claim of positive selection.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The title states "IL-2 enhances effector function but suppresses follicular localization of CD8+ T cells in chronic infection" which data from the paper show but does not seem to be the major goal of the authors. As stated in the short assessment above, the goal of this work seems to connect IL-2 signals, mostly given exogenously, to the differentiation of progenitor T cells (TPEX) that will help sustain effector T cell responses against chronic viral infection (TEX/TEFF). The authors mostly use chronic LCMV infection in mice as their model of choice, Flow cytometry, fluorescent microscopy, and some in vitro assays to explore how IL2 regulates TPEX and TEX/TEFF differentiation. Gain and loss of functions experiments are also conducted to explore the roles of L2 signaling and BLIMP-1 in regulating these processes. Lastly, a loose connection of their mouse findings on TPEX/TEX cells to a clinical study using low-dose IL-2 treatment in SLE patients is attempted.
Strengths:
(1) The impact of IL-2 treatment of TPEX/TEX differentiation is very clear.
(2) The flow cytometry data are convincing and state-of-the-art.
Weaknesses:
(1) The title appears disconnected from the major focus of the work.
(2) The number of TPEX cells is not changed. IL2 treatment increases the number of TEFF and the proportion of TPEX is lower suggesting it does not target TPEX formation. The conclusion about an inhibitory role of IL2 treatment on TPEX formation seems therefore largely overstated.
(3) Are the expanded TEX/TEFF cells really effectors? Only GrB and some cell surface markers are monitored (44, 62L). Other functions should be included, e.g., CD107a, IFNg, TNF, chemokines - Tbet?
(4) The rationale for IL2 treatment timing is unclear. Seems that this is given at the T cell contraction time and this is interesting compared to the early treatment that ablate TPEX generation. Maybe this should really be explored further?
(5) The TGFb/IL6/IL2 in vitro experiment does not bring much to the paper.
(6) The Figure 2 data try to provide an explanation for a prior lack of difference in viral titers after IL2 treatment. It is hard to be convinced by these tissue section data as presented. It also begs the question of how the host would benefit from the low dose IL-2 treatment if IL-2 TEFF are not contributing to viral control as a result of their inappropriate localization to viral reservoirs.
(7) It is unclear what the STA5CA and BLIMP-1 KO experiments in Figure 3 add to the story that is not already expected/known.
(8) The connection to the low-dose IL2 treatment in SLE patients is very loose and weak. This version is likely not the ligand that preferentially signals to CD122 either. SLE is different from a chronic viral infection and the question of timing seems critical from all the data shown in this manuscript. So it is very difficult to make any robust link to the mechanistic data.
(9) It is really unclear what the take-home message is. IL-2 is signaling via STAT5 and BLIMP1 is also a known target as published by many groups including this one, and these results are more than expected. The observation that TEFF may be differentially localized in the WP area is interesting but no mechanisms are really provided (guessing CXCR5 but again expected). Also, all these observations are highly dependent on the timing of IL2 administration which is fascinating but not explored at all. It also limits significance since underlying mechanisms are unknown and we do not know when such treatment would have to be given.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
In this manuscript, Ghazi et reported that inhibition of KRASG12C signaling increases autophagy in KRASG12C expressing lung cancer cells. Moreover, the combination of DCC 3116, a selective ULK1/2 inhibitor, plus sotorasib displays cooperative/synergistic suppression of human KRASG12C driven lung cancer cell proliferation in vitro and tumor growth in vivo. Additionally, in genetically engineered mouse models of KRASG12C driven NSCLC, inhibition of either KRASG12C or ULK1/2 decreases tumor burden and increases mouse survival. Additionally, this study found that LKB1 deficiency diminishes the sensitivity of KRASG12C/LKB1Null-driven lung cancer to the combination treatment, perhaps through the emergence of mixed adeno/squamous cell carcinomas and mucinous adenocarcinomas.
Strengths:
Both human cancer cells and mouse models were employed in this study to illustrate that inhibiting ULK1/2 could enhance the responsiveness of KRASG12C lung cancer to sotorasib. This research holds translational importance.
Weaknesses:
The revised manuscript has addressed most of my previous concerns. However, I still have one issue: the sample size (n) for the GEMM study in Figures 4E and 4F is too small, despite the authors' explanation. The data do not support the conclusion due to the lack of significant difference in tumor burden. Additionally, the significance labels in Figure 4E are not clearly explained.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors profile gene expression, chromatin accessibility and chromosomal architecture (by Hi-C) in activated CD4 T cells and use this information to link non-coding variants associated with autoimmune diseases with putative target genes. They find over a 1000 genes physically linked with autoimmune disease loci in these cells, many of which are upregulated upon T cell activation. Focusing on IL2, they dissect the regulatory architecture of this locus, including the allelic effects of GWAS variants. They also intersect their variant-to-gene lists with data from CRISPR screens for genes involved in CD4 T cell activation and expression of inflammatory genes, finding enrichments for regulators. Finally, they showed that pharmacological inhibition of some of these genes impacts T cell activation.
This is a solid study that follows a well-established canvas for variant-to-gene prioritisation using 3D genomics, applying it to activated T cells. The authors go some way in validating the lists of candidate genes, as well as explore the regulatory architecture of a candidate GWAS locus. Jointly with data from previous studies performing variant-to-gene assignment in activated CD4 T cells (and other immune cells), this work provides a useful additional resource for interpreting autoimmune disease-associated genetic variation.
Autoimmune disease variants were already linked with genes in CD28-stimulated CD4 T cells using chromosome conformation capture, specifically Promoter CHi-C and the COGS pipeline (Javierre et al., Cell 2016; Burren et al., Genome Biol 2017; Yang et al., Nat Comms 2020). The authors cite these papers and present a comparative analysis of their variant-to-gene assignments (in addition to scRNA-seq eQTL-based assignments). Furthermore, they find that the Burren analysis yields a higher enrichment for gold standard genes.
I thank the authors for their revisions in response to my initial review. The revised version now includes a more comprehensive comparative analysis of different datasets and V2G approaches and discusses the potential sources of differences in the results. Most significantly, the authors have now included an interesting comparison of their methodology with the popular ABC technique and outlined the key limitations of ABC relative to their method and other (Capture) Hi-C-based V2G approaches.
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public Review):
Summary:
The authors used structural and biophysical methods to provide insight into Parkin regulation. The breadth of data supporting their findings was impressive and generally well-orchestrated.
Strengths:
(1) They have done a better job explaining the rationale for their experiments thought-out.
(2) The use of molecular scissors in their construct represents a creative approach to examine inter-domain interactions. Appropriate controls were included.
(3) From my assessment, the experiments are well-conceived and executed.
(4) The authors do a better job of highlighting the question being addressed experimentally.
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URL
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
This is an exciting paper that explores the in vitro assembly of recombinant alpha-synuclein into amyloid filaments. The authors changed the pH and the composition of the assembly buffers, as well as the presence of different types of seeds, and analysed the resulting structures by cryo-EM.
Strengths:
By doing experiments at different pHs, the authors found that so-called type 2 and type-3 polymorphs form in a pH dependent manner. In addition, they find that type-1 filaments form in the presence of phosphate ions. One of their in vitro assembled type-1 polymorphs is similar to the alpha-synuclein filaments that were extracted from the brain of an individual with juvenile-onset synucleinopathy (JOS). They hypothesize that additional densities in a similar place as additional densities in the JOS fold correspond to phosphate ions.
Comments on the revised version:
This is OK now. I thank the authors for their constructive engagement with my comments.
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