Reviewer #1 (Public review):

Summary:

The study by Deng et al reports single cell expression analysis of developing mouse hearts and examines the requirements for cardiac fibroblasts in heart maturation. The work includes extensive gene expression profiling and bioinformatic analysis. The prenatal fibroblast ablation studies show new information on the requirement of these cells on heart maturation before birth.

The strengths of the manuscript are the new single cell datasets and comprehensive approach to ablating cardiac fibroblasts in pre and postnatal development in mice. Extensive data are presented on mouse embryo fibroblast diversity and morphology in response to fibroblast ablation. Histological data support localization of major cardiac cell types and effects of fibroblast ablation on cardiac gene expression at different times of development.

A weakness of the study is that the major conclusions regarding collagen signaling and heart maturation are based on gene expression patterns and are not functionally validated.

Reviewer #1 (Public review):

The authors, Zhang et al., demonstrate the beneficial effects of treating degenerate human primary intervertebral disc (IVD) cells with recombinant human PDGF-AB/BB on the senescence transcriptomic signatures. Utilizing a combination of degenerate cells from elderly humans and experimentally induced senescence in young, healthy IVD cells, the authors show the therapeutic effects on mRNA transcription as well as cellular processes through informatics approaches.

One notable strength of this study is the use of human primary cells and recombinant forms of human PDGF-AB/BB proteins, which increases the translational potential of these in vitro studies. The manuscript is well-written, and the informatics analyses are thorough and clearly presented.

Comments on revisions:

The revised manuscript adds greater clarity, and the impact of the study is greatly enhanced.

Reviewer #1 (Public review):

Summary:

Zhao and colleagues employ Drosophila nephrocytes as a model to investigate the effects of a high-fat diet on these podocyte-like cells. Through a highly focused analysis, they initially confirm previous research in their hands demonstrating impaired nephrocyte function and move on to observe the mislocalization of a slit diaphragm-associated protein (pyd) and a knock-in into the locus of the Drosophila nephrin (sns). Employing another reporter construct, they identify activation of the JAK/STAT signaling pathway in nephrocytes. Subsequently, the authors demonstrate the involvement of this pathway in nephrocyte function from multiple angles, using a gain-of-function construct, silencing of an inhibitor, and ectopic overexpression of a ligand. Silencing the effector Stat92E via RNAi or inhibiting JAK/STAT with Methotrexate effectively restored impaired nephrocyte function and slit diaphragm architecture induced by a high-fat diet, while showing no impact under normal dietary conditions.

Strengths:

The findings establish a link between JAK/STAT activity and the impact of a high-fat diet on nephrocytes. This nicely underscores the importance of organ crosstalk for nephrocytes and supports a potential role for JAK/STAT in diabetic nephropathy, as previously suggested by other models.

Weaknesses:

While the analysis provides valuable insights, it appears somewhat over-reliant on tracer uptake in certain instances. Clinical inferences based on a Drosophila model should be interpreted with caution.

Reviewer #1 (Public review):

Summary:

The authors use microscopy experiments to track the gliding motion of filaments of the cyanobacteria Fluctiforma draycotensis. They find that filament motion consists of back and forth trajectories along a "track", interspersed with reversals of movement direction, with no clear dependence between filament speed and length. It is also observed that longer filaments can buckle and form plectonemes. A computational model is used to rationalize these findings.

Strengths:

Much work in this field focuses on molecular mechanisms of motility; by tracking filament dynamics this work helps to connect molecular mechanisms to environmentally and industrially relevant ecological behavior such as aggregate formation.

The observation that filaments move on tracks is interesting and potentially ecologically signifiant.

The observation of rotating membrane-bound protein complexes and tubular arrangement of slime around the filament provide important clues to the mechanism of motion.

The observation that long filaments buckle has potential to shed light on the nature of mechanical forces in the filaments, e.g. through study of the length dependence of buckling.

The comparison between motility on agar and on glass is interesting since it shows that filaments have both intrinsic propensity to reverse (that is seen on glass) and mechanically triggered reversal (that is seen on agar when the filament reaches the end of a track).

Weaknesses:

The manuscript makes the interesting statement that the distribution of speed vs filament length is uniform, which would constrain the possibilities for mechanical coupling between the filaments. However Fig 2C does not show a uniform distribution but rather an apparent lack of correlation between speed and filament length, although the statistical degree of correlation is not given. In my view, Fig 2C should not be described as a uniform distribution since mathematically that means something very different than what is shown here. Instead the figure should be described quantitatively with the use of a measured correlation coefficient. This also applies to Fig. S3A.

The statement "since filament speed results from a balance between propulsive forces and drag, these observations of no or positive correlation between filament speed and length show that all (or a fixed proportion of) cells in a filament contribute to propulsive force generation" helps to clarify the important link between Fig 2C and the concept that all cells contribute, but I think this statement is not obvious for many readers, and could be made clearer, e.g. by the use of a simple mathematical model for a chain of bacterial that accounts for drag forces and propulsion forces for each bacterium.

The authors have now clarified that the computational model is 1D and cannot explain the coupling between rotation, slime generation and motion. I find it encouraging and important that model predictions for the dwell time distributions (Fig S12 and S13) are similar to experimental measurements, but I think it would be better to put these results in the main text, together also with Fig S4. If these important results are in the supplement it is harder for the reader to assess the match between model and experiments.

Filament buckling is not analysed in quantitative detail, but the authors have now clarified that this will be the topic of future work with a 2D or 3D computational model.

Reviewer #1 (Public review):

Summary:

The manuscript by Yamamoto et al. presents a model by which the four main axes of the limb are required for limb regeneration to occur in the axolotl. A longstanding question in regeneration biology is how existing positional information is used to regenerate the correct missing elements. The limb provides an accessible experimental system by which to study the involvement of the anteroposterior, dorsoventral, and proximodistal axes in the regenerating limb. Extensive experimentation has been performed in this area using grafting experiments. Yamamoto et al. use the accessory limb model and some molecular tools to address this question. There are some interesting observations in the study. In particular, one strength is the potent induction of accessory limbs in the dorsal axis with BMP2+Fgf2+Fgf8, which is very interesting.

Strengths:

The manuscript presents some novel phenotypes generated in axolotl limbs due to Wnt signaling. This is generally the first example in which Wnt signaling has provided a gain-of-function in the axolotl limb model. They also present a potent way of inducing limb patterning in the dorsal axis by the addition of just beads loaded with Bmp2+Fgf8+Fgf2.

Weaknesses:

Although interesting, the study makes bold claims about determining the molecular basis of DV positional cues, but the experimental evidence is not definitive and does not take into account the previous work on DV patterning in the amniote limb. Also, testing the hypothesis on blastemas after limb amputation would be needed to support the strong claims in the study. There are several examples of very strong claims, but the evidence lacks support for these claims.

Joint Public Review:

Summary:

The authors investigate how stochastic and deterministic factors are integrated in cell fate decisions, using Dictyostelium discoideum as a model system. They show that cells in different cell cycle phases (a deterministic factor) are predisposed to different fates, albeit with deviations, when exposed to the same environmental stimulus. However, gene expression variability (a stochastic factor) enhances the robustness of cellular responses to environmental cues that disrupt the cell cycle.

Using a simple, tractable mathematical model, the authors demonstrate that cell fate decisions in D. discoideum depend on a combination of deterministic and stochastic factors, i.e., cell cycle phase and gene expression variability, respectively. They then identify Set1 - a key regulator of gene expression variability - indicate the mechanism through which it modulates this variability, and link it to a phenotype in D. discoideum development. Finally, they confirm that gene expression variability contributes to the robustness of the cell's response to environmental disruptions that interfere with the cell cycle.

Strengths:

The authors are careful in the choice of their experiments and in measuring gene expression variability, using methods that account for expected trends with average gene expression.

Weaknesses:

However, in terms of mathematical modelling, it would be important to rule out sources of stochasticity (other than gene expression variability), and also to consider cases where stochastic factors are not necessarily completely independent of the deterministic ones.

Reviewer #1 (Public review):

Summary:

These authors have asked how lytic phage predation impacts antibiotic resistance and virulence phenotypes in methicillin-resistant Staphylococcus aureus (MRSA). They report that staphylococcal phages cause MRSA strains to become sensitized to b-lactams and to display reduced virulence. Moreover, they identify mutations in a set of genes required for phage infection that may impact antibiotic resistance and virulence phenotypes.

Strengths:

Phage-mediated re-sensitization to antibiotics has been reported previously but the underlying mutational analyses have not been described. These studies suggest that phages and antibiotics may target similar pathways in bacteria.

Weaknesses:

One limitation is the lack of mechanistic investigations linking particular mutations to the phenotypes reported here. This limits the impact of the work.

Another limitation of this work is the use of lab strains and a single pair of phages. However, while incorporation of clinical isolates would increase the translational relevance of this work it is unlikely to change the conclusions.

Comments on revisions:

The authors have addressed my concerns.

Reviewer #1 (Public review):

Summary:

These authors have asked how lytic phage predation impacts antibiotic resistance and virulence phenotypes in methicillin-resistant Staphylococcus aureus (MRSA). They report that staphylococcal phages cause MRSA strains to become sensitized to b-lactams and to display reduced virulence. Moreover, they identify mutations in a set of genes required for phage infection that may impact antibiotic resistance and virulence phenotypes.

Strengths:

Phage-mediated re-sensitization to antibiotics has been reported previously but the underlying mutational analyses have not been described. These studies suggest that phages and antibiotics may target similar pathways in bacteria.

Weaknesses:

One limitation is the lack of mechanistic investigations linking particular mutations to the phenotypes reported here. This limits the impact of the work.

Another limitation of this work is the use of lab strains and a single pair of phages. However, while incorporation of clinical isolates would increase the translational relevance of this work it is unlikely to change the conclusions.

Reviewer #2 (Public review):

Summary:

This study uses in vivo multimodal high-resolution imaging to track how microglia and neutrophils respond to light-induced retinal injury from soon after injury to 2 months post-injury. The in vivo imaging finding was subsequently verified by ex vivo study. The results suggest that despite the highly active microglia at the injury site, neutrophils were not recruited in response to acute light-induced retinal injury.

Strengths:

An extremely thorough examination of the cellular-level immune activity at the injury site. In vivo imaging observations being verified using ex vivo techniques is a strong plus.

Reviewer #1 (Public review):

Summary:

In this study, authors explored how galanin affects whole-brain activity in larval zebrafish using wide-field Ca2+ imaging, genetic modifications, and drugs that increase brain activity. The authors conclude that galanin has a sedative effect on the brain under normal conditions and during seizures, mainly through the galanin receptor 1a (galr1a). However, acute "stressors(?)" like pentylenetetrazole (PTZ) reduce galanin's effects, leading to increased brain activity and more seizures. Authors claim that galanin can reduce seizure severity while increasing seizure occurrence, speculated to occur through different receptor subtypes. This study confirms galanin's complex role in brain activity, supporting its potential impact on epilepsy.

Strengths:

The overall strength of the study lies primarily in its methodological approach using whole-brain Calcium imaging facilitated by the transparency of zebrafish larvae. Additionally, the use of transgenic zebrafish models is an advantage, as it enables genetic manipulations to investigate specific aspects of galanin signaling. This combination of advanced imaging and genetic tools allows for addressing galanin's role in regulating brain activity.

Weaknesses:

The weaknesses of the study also stem from the methodological approach, particularly the use of whole-brain Calcium imaging as a measure of brain activity. While epilepsy and seizures involve network interactions, they typically do not originate across the entire brain simultaneously. Seizures often begin in specific regions or even within specific populations of neurons within those regions. Therefore, a whole-brain approach, especially with Calcium imaging with inherited limitations, may not fully capture the localized nature of seizure initiation and propagation, potentially limiting the understanding of Galanin's role in epilepsy.

Furthermore, Galanin's effects may vary across different brain areas, likely influenced by the predominant receptor types expressed in those regions. Additionally, the use of PTZ as a "stressor" is questionable since PTZ induces seizures rather than conventional stress. Referring to seizures induced by PTZ as "stress" might be a misinterpretation intended to fit the proposed model of stress regulation by receptors other than Galanin receptor 1 (GalR1).

The description of the EAAT2 mutants is missing crucial details. EAAT2 plays a significant role in the uptake of glutamate from the synaptic cleft, thereby regulating excitatory neurotransmission and preventing excitotoxicity. Authors suggest that in EAAT2 knockout (KO) mice galanin expression is upregulated 15-fold compared to wild-type (WT) mice, which could be interpreted as galanin playing a role in the hypoactivity observed in these animals.

However, the study does not explore the misregulation of other genes that could be contributing to the observed phenotype. For instance, if AMPA receptors are significantly downregulated, or if there are alterations in other genes critical for brain activity, these changes could be more important than the upregulation of galanin. The lack of wider gene expression analysis leaves open the possibility that the observed hypoactivity could be due to factors other than, or in addition to, galanin upregulation.

Moreover, the observation that in double KO mice for both EAAT2 and galanin there was little difference in seizure susceptibility compared to EAAT2 KO mice alone further supports the idea that galanin upregulation might not be the reason to the observed phenotype. This indicates that other regulatory mechanisms or gene expressions might be playing a more pivotal role in the manifestation of hypoactivity in EAAT2 mutants.

These methodological shortcomings and conceptual inconsistencies undermine the perceived strengths of the study, and hinders understanding of Galanin's role in epilepsy and stress regulation.

Comments on revisions:

The revised manuscript and the answers of the authors is appreciated. However, the criticisms were addressed only partially and main weaknesses of the manuscript are still remaining.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors addressed the previous comments from reviewers.

Strengths:

This study identified that NOLC1 could bind to p53 and decrease its nuclear transcriptional activity, then inhibit p53-mediated ferroptosis in gastric cancer.

Weaknesses:

There are a few Western blot images that were processed with excessive contrast adjustment, such as Figure 2I (Caspase-3 in MKN-45 group), Figure 4H (GPX4 in MKN-45 group), and Figure 5G/5I.

Reviewer #1 (Public review):

Summary:

Gene transfer agent (GTA) from Bartonella is a fascinating chimeric GTA that evolved from the domestication of two phages. Not much is known about how the expression of the BaGTA is regulated. In this manuscript, Korotaev et al noted the structural similarity between BrrG (a protein encoded by the ror locus of BaGTA) to a well-known transcriptional anti-termination factor, 21Q, from phage P21. This sparked the investigation into the possibility that BaGTA cluster is also regulated by anti-termination. Using a suite of cell biology, genetics, and genome-wide techniques (ChIP-seq), Korotaev et al convincingly showed that this is most likely the case. The findings offer the first insight into the regulation of GTA cluster (and GTA-mediated gene transfer) particularly in this pathogen Bartonella. Note that anti-termination is a well-known/studied mechanism of transcriptional control. Anti-termination is a very common mechanism for gene expression control of prophages, phages, bacterial gene clusters, and other GTAs, so in this sense, the impact of the findings in this study here is limited to Bartonella.

Strengths:

convincing results that overall support the main claim of the manuscript.

Weaknesses:

A few important controls are missing.

Comments on revisions:

I am happy with this revised version except for one point, that is a single replicate for ChIP-seq, I don't think that is appropriate.

Reviewer #1 (Public review):

Koesters and colleagues investigated the role of the small GTPase Rab3A in homeostatic scaling of miniature synaptic transmission in primary mouse cortical cultures using electrophysiology and immunohistochemistry. The major finding is that TTX incubation for 48 hours does not induce an increase in the amplitude of excitatory synaptic miniature events in neuronal cortical cultures derived from Rab3A KO and Rab3A Earlybird mutant mice. NASPM application had comparable effects on mEPSC amplitude in control and after TTX, implying that Ca2+-permeable glutamate receptors are unlikely modulated during synaptic scaling. Immunohistochemical analysis revealed no significant changes in GluA2 puncta size, intensity, and integral after TTX treatment in control and Rab3A KO cultures. Finally, they provide evidence that loss of Rab3A in neurons, but not astrocytes, blocks homeostatic scaling. Based on these data, the authors propose a model in which neuronal Rab3A is required for homeostatic scaling of synaptic transmission, potentially through GluA2-independent mechanisms.

The major finding - impaired homeostatic up-scaling after TTX treatment in Rab3A KO and Rab3 earlybird mutant neurons - is supported by data of high quality. However, the paper falls short of providing any evidence or direction regarding potential mechanisms. The data on GluA2 modulation after TTX incubation are likely statistically underpowered and do not allow drawing solid conclusions, such as GluA2-independent mechanisms of up-scaling.

The study should be of interest to the field because it implicates a presynaptic molecule in homeostatic scaling, which is generally thought to involve postsynaptic neurotransmitter receptor modulation. However, it remains unclear how Rab3A participates in homeostatic plasticity.

Major (remaining) point:

(1) The current version of the abstract only includes the results on GluA2 immunofluorescence and mEPSC amplitude modulation after TTX treatment in control cultures, and a requirement for Rab3A in neurons instead of astrocytes. The major findings, including the block of the mEPSC amplitude increase upon TTX treatment in Rab3KO/EB mutants, are not mentioned. The abstract should be revised so that it reflects all major findings, potentially at the expense of citing previous work by the authors.

Reviewer #1 (Public review):

The authors of this study use electron microscopy and 3D reconstruction techniques to study the morphology of distinct classes of Drosophila sensory neurons *across many neurons of the same class.* This is a comprehensive study attempting to look at nearly all the sensory neurons across multiple sensilla to determine a) how much morphological variability exists between and within neurons of different and similar sensory classes, and 2) identify dendritic features that may have evolved to support particular sensory functions. This study builds upon the authors' previous work, which allowed them to identify and distinguish sensory neuron subtypes in the EM volumes without additional staining so that reconstructed neurons could reliably be placed in the appropriate class. This work is unique in looking at a large number of individual neurons of the same class to determine what is consistent and what is variable about their class-specific morphologies.

This means that in addition to providing specific structural information about these particular cells, the authors explore broader questions of how much morphological diversity exists between sensory neurons of the same class and how different dendritic morphologies might affect sensory and physiological properties of neurons.

The authors found that CO2-sensing neurons have an unusual, sheet-like morphology in contrast to the thin branches of odor-sensing neurons. They show that this morphology greatly increases the surface area to volume ratio above what could be achieved by modest branching of thin dendrites, and posit that this might be important for their sensory function, though this was not directly tested in their study. The study is mainly descriptive in nature, but thorough, and provides a nice jumping-off point for future functional studies. One interesting future analysis could be to examine all four cell types within a single sensilla together to see if there are any general correlations that could reveal insights about how morphology is determined and the relative contributions of intrinsic mechanisms vs interactions with neighboring cells. For example, if higher than average branching in one cell type correlated with higher than average branching in another type, if in the same sensilla. This might suggest higher extracellular growth or branching cues within a sensilla. Conversely, if higher branching in one cell type consistently leads to reduced length or branching in another, this might point to dendrite-dendrite interactions between cells undergoing competitive or repulsive interactions to define territories within each sensilla as a major determinant of the variability.

Reviewer #1 (Public review):

In this study, Marocco and colleagues perform a deep characterization of the complex molecular mechanism guiding the recognition of a particular CELLmotif previously identified in hepatocytes in another publication. Having miR-155-3p with or without this CELLmotif as initial focus, the authors identify 21 proteins differentially binding to these two miRNA versions. From these, they decided to focus on PCBP2. They elegantly demonstrate PCBP2 binding to miR-155-3p WT version but not to the CELLmotif-mutated version. miR-155-3p contains a hEXOmotif identified in a different report, whose recognition is largely mediated by another RNA-binding protein called SYNCRIP. Interestingly, mutation of the hEXOmotif contained in miR-155-3p did not only blunt SYNCRIP binding, but also PCBP2 binding despite the maintenance of the CELLmotif. This indicates that somehow SYNCRIP binding is a prerequisite for PCBP2 binding. EMSA assay confirms that SYNCRIP is necessary for PCBP2 binding to miR-155-3p, while PCBP2 is not needed for SYNCRIP binding. The authors aim to extend these findings to other miRNAs containing both motifs. For that, they perform a small-RNA-Seq of EVs released from cells knockdown for PCBP2 versus control cells, identifying a subset of miRNAs whose expression either increases or decreases. The assumption is that those miRNAs containing PCBP2-binding CELLmotif should now be less retained in the cell and go more to extracellular vesicles, thus reflecting a higher EV expression. The specific subset of miRNAs having both the CELLmotif and hEXOmotif (9 miRNAs) whose expressions increase in EVs due to PCBP2 reduction is also affected by knocking down SYNCRIP in the sense that reduction of SYNCRIP leads to lower EV sorting. Further experiments confirm that PCBP2 and SYNCRIP bind to these 9 miRNAs and that knocking down SYNCRIP impairs their EV sorting.

Reviewer #1 (Public review):

Summary:

This study uncovers a protective role of the ubiquitin-conjugating enzyme variant Uev1A in mitigating cell death caused by over-expressed oncogenic Ras in polyploid Drosophila nurse cells and by RasK12 in diploid human tumor cell lines. The authors previously showed that overexpression of oncogenic Ras induces death in nurse cells, and now they perform a deficiency screen for modifiers. They identified Uev1A as a suppressor of this Ras-induced cell death. Using genetics and biochemistry, the authors found that Uev1A collaborates with the APC/C E3 ubiquitin ligase complex to promote proteasomal degradation of Cyclin A. This function of Uev1A appears to extend to diploid cells, where its human homologs UBE2V1 and UBE2V2 suppress oncogenic Ras-dependent phenotypes in human colorectal cancer cells in vitro and in xenografts in mice.

Strengths:

(1) Most of the data is supported by a sufficient sample size and appropriate statistics.<br /> (2) Good mix of genetics and biochemistry.<br /> (3) Generation of new transgenes and Drosophila alleles that will be beneficial for the community.

Weaknesses:

(1) Phenotypes are based on artificial overexpression. It is not clear whether these results are relevant to normal physiology.

(2) The phenotype of "degenerating ovaries" is very broad, and the study is not focused on phenotypes at the cellular level. Furthermore, no information is provided in the Materials and Methods on how degenerating ovaries are scored, despite this being the most important assay in the study.

(3) In Figure 5, the authors want to conclude that uev1a is a tumor-suppressor, and so they over-express ubev1/2 in human cancer cell lines that have RasK12 and find reduced proliferation, colony formation, and xenograft size. However, genes that act as tumor suppressors have loss-of-function phenotypes that allow for increased cell division. The Drosophila uev1a mutant is viable and fertile, suggesting that it is not a tumor suppressor in flies. Additionally, they do not deplete human ubev1/2 from human cancer cell lines and assess whether this increases cell division, colony formation, and xenograph growth.

(4) A critical part of the model does not make sense. CycA is a key part of their model, but they do not show CycA protein expression in WT egg chambers or in their over-expression models (nos.RasV12 or bam>RasV12). Based on Lilly and Spradling 1996, Cyclin A is not expressed in germ cells in region 2-3 of the germarium; whether CycA is expressed in nurse cells in later egg chambers is not shown but is critical to document comprehensively.

(5) The authors should provide more information about the knowledge base of uev1a and its homologs in the introduction.

Reviewer #1 (Public review):

Summary:

The authors confirmed earlier findings that AVP influences α and β cells differently, depending on glucose concentrations. At substimulatory glucose levels, AVP combined with forskolin - an activator of cAMP -did not significantly stimulate β cells, although it did activate α cells. Once glucose was raised to stimulatory levels, β cells became active, and α cell activity declined, indicating glucose's suppressive effect on α cells and permissive effect on β cells. Under physiological glucose levels (8-9 mM), forskolin enhanced β-cell calcium oscillations, and AVP further modulated this activity. However, AVP's effect on β cells was variable across islets and did not significantly alter AUC measurements (a combined indicator of oscillation frequency and duration). In α cells, forskolin and AVP led to increased activity even at high glucose levels, suggesting that α cells remain responsive despite expected suppression by insulin and glucose.

Experiments with physiological concentrations of epinephrine suggest that AVP does not operate via Gs-coupled V2 receptors in β cells, as AVP could not counteract epinephrine's inhibitory effects. Instead, epinephrine reduced β cell activity while increasing α cell activity through different G-protein-coupled mechanisms. These results emphasize that AVP can potentiate α-cell activation and has a nuanced, context-dependent effect on β cells.

The most robust activation of both α and β cells by AVP occurred within its physiological osmo-regulatory range (~10-100 pM), confirming that AVP exerts bell-shaped concentration-dependent effects on β cells. At low concentrations, AVP increased β cell calcium oscillation frequency and reduced "halfwidths"; high concentrations eventually suppressed β cell activity, mimicking the muscarinic signaling. In α cells, higher AVP concentrations were required for peak activation, which was not blunted by receptor inactivation within physiological ranges.

Attempting to further dissect the role of specific AVP receptors, the authors designed and tested peptide ligands selective for V1b receptors. These included a selective V1b agonist; a V1b agonist with antagonist properties at V1a and oxytocin receptors; and a selective V1a antagonist. In pancreatic slices, these peptides seem to replicate AVP's effects on Ca²⁺ signaling, although responses were highly variable, with some islets showing increased activity and others no change or suppression. The variability was partly attributed to islet-specific baseline activity, and the authors conclude that AVP and V1b receptor agonists can modulate β cell activity in a state-dependent manner, stimulating insulin secretion in quiescent cells and inhibiting it in already active cells.

Strengths:

Overall, the study is technically advanced and provides useful pharmacological tools. However, the conclusions are limited by a lack of direct mechanistic and functional data. Addressing these gaps through a combination of signaling pathway interrogation, functional hormone output, genetic validation, and receptor localization would strengthen the conclusions and reduce the current (interpretive) ambiguity.

Weaknesses:

(1) The study is entirely based on pharmacological tools. Without genetic models, off-target effects or incomplete specificity of the peptides cannot be fully ruled out.

(2) Despite multiple claims about β cell activation or inhibition, the functional output - insulin secretion - is weakly assessed, and only in limited conditions. This aspect makes it very hard to correlate calcium dynamics with physiological outcomes.

(3) Insulin and glucagon secretion assays should be provided; the authors should measure hormone release in parallel with Ca2+ imaging, using perifusion assays, especially during AVP ramp and peptide ligand applications.

Additionally, there is no standardization of the metabolic state of islets. The authors should consider measuring islet NAD(P)H autofluorescence or mitochondrial potential (e.g., using TMRE) to control for metabolic variability that may affect responsiveness.

(4) There is a high degree of variability in response to AVP and V1b agonists across islets (activation, no effect, inhibition). Surprisingly, the authors do not fully explore the cause of this heterogeneity (whether it is due to receptor expression differences, metabolic state, experimental variability, or other conditions).

(5) There is no validation of V1b receptor expression at the protein or mRNA level in α or β cells using in situ hybridization, immunohistochemistry, or spatial transcriptomics.

(6) AVP effects are described in terms of permissive or antagonistic effects on cAMP (especially in relation to epinephrine), but direct measurements of cAMP in α and β cells are not shown, weakening these conclusions. The authors should use Epac-based cAMP FRET sensors in α and β cells to monitor the interaction between AVP, forskolin, and epinephrine more conclusively.

(7) Single-islet transcriptomics or proteomics (also to clarify variability) should be provided to analyze receptor expression variability across islets to correlate with response phenotypes (activation vs inhibition). Alternatively, the authors could perform calcium imaging with simultaneous insulin granule tracking or ATP levels to assess islet functional states.

(8) While the study implies AVP acts through V1b receptors on β cells, the signaling downstream (e.g., PLC activation, IP3R isoforms involved) is simply inferred but not directly shown.

(9) The interpretation that IP3R inactivation (mentioned in the title!) underlies the bell-shaped AVP effect is just hypothetical, without direct measurements. Assays in β (and/or α)-cell-specific V1b KO mice and IP3R KO mice must be provided to support these speculations.

Reviewer #1 (Public review):

Summary

In this manuscript, the authors introduce Gcoupler, a Python-based computational pipeline designed to identify endogenous intracellular metabolites that function as allosteric modulators at the G protein-coupled receptor (GPCR) - Gα protein interface. Gcoupler is comprised of four modules:

I. Synthesizer - identifies protein cavities and generates synthetic ligands using LigBuilder3

II. Authenticator - classifies ligands into high-affinity binders (HABs) and low-affinity binders (LABs) based on AutoDock Vina binding energies

III. Generator - trains graph neural network (GNN) models (GCM, GCN, AFP, GAT) to predict binding affinity using synthetic ligands

IV. BioRanker - prioritizes ligands based on statistical and bioactivity data

The authors apply Gcoupler to study the Ste2p-Gpa1p interface in yeast, identifying sterols such as zymosterol (ZST) and lanosterol (LST) as modulators of GPCR signaling. Our review will focus on the computational aspects of the work. Overall, we found the Gcoupler approach interesting and potentially valuable, but we have several concerns with the methods and validation that need to be addressed prior to publication/dissemination.

(1) The exact algorithmic advancement of the Synthesizer beyond being some type of application wrapper around LigBuilder is unclear. Is the grow-link approach mentioned in the methods already a component of LigBuilder, or is it custom? If it is custom, what does it do? Is the API for custom optimization routines new with the Synthesizer, or is this a component of LigBuilder? Is the genetic algorithm novel or already an existing software implementation? Is the cavity detection tool a component of LigBuilder or novel in some way? Is the fragment library utilized in the Synthesizer the default fragment library in LigBuilder, or has it been customized? Are there rules that dictate how molecule growth can occur? The scientific contribution of the Synthesizer is unclear. If there has not been any new methodological development, then it may be more appropriate to just refer to this part of the algorithm as an application layer for LigBuilder.

(2) The use of AutoDock Vina binding energy scores to classify ligands into HABs and LABs is problematic. AutoDock Vina's energy function is primarily tuned for pose prediction and displays highly system-dependent affinity ranking capabilities. Moreover, the HAB/LAB thresholds of -7 kcal/mol or -8 kcal/mol lack justification. Were these arbitrarily selected cutoffs, or was benchmarking performed to identify appropriate cutoffs? It seems like these thresholds should be determined by calibrating the docking scores with experimental binding data (e.g., known binders with measured affinities) or through re-scoring molecules with a rigorous alchemical free energy approach.

(3) Neither the Results nor Methods sections provide information on how the GNNs were trained in this study. Details such as node features, edge attributes, standardization, pooling, activation functions, layers, dropout, etc., should all be described in detail. The training protocol should also be described, including loss functions, independent monitoring and early stopping criteria, learning rate adjustments, etc.

(4) GNN model training seems to occur on at most 500 molecules per training run? This is unclear from the manuscript. That is a very small number of training samples if true. Please clarify. How was upsampling performed? What were the HAB/LAB class distributions? In addition, it seems as though only synthetically generated molecules are used for training, and the task is to discriminate synthetic molecules based on their docking scores. Synthetic ligands generated by LigBuilder may occupy distinct chemical space, making classification trivial, particularly in the setting of a random split k-folds validation approach. In the absence of a leave-class-out validation, it is unclear if the model learns generalizable features or exploits clear chemical differences. Historically, it was inappropriate to evaluate ligand-based QSAR models on synthetic decoys such as the DUD-E sets - synthetic ligands can be much more easily distinguished by heavily parameterized ligand-based machine learning models than by physically constrained single-point docking score functions.

(5) Training QSAR models on docking scores to accelerate virtual screening is not in itself novel (see here for a nice recent example: https://www.nature.com/articles/s43588-025-00777-x), but can be highly useful to focus structure-based analysis on the most promising areas of ligand chemical space; however, we are perplexed by the motivation here. If only a few hundred or a few thousand molecules are being sampled, why not just use AutoDock Vina? The models are trained to try to discriminate molecules by AutoDock Vina score rather than experimental affinity, so it seems like we would ideally just run Vina? Perhaps we are misunderstanding the scale of the screening that was done here. Please clarify the manuscript methods to help justify the approach.

(6) The brevity of the MD simulations raises some concerns that the results may be over-interpreted. RMSD plots do not reliably compare the affinity behavior in this context because of the short timescales coupled with the dramatic topological differences between the ligands being compared; CoQ6 is long and highly flexible compared to ZST and LST. Convergence metrics, such as block averaging and time-dependent MM/GBSA energies, should be included over much longer timescales. For CoQ6, the authors may need to run multiple simulations of several microseconds, identify the longest-lived metastable states of CoQ6, and perform MM/GBSA energies for each state weighted by each state's probability.

Reviewer #1 (Public review):

Summary:

In this study, Tittelmeier et al. explored the role of sphingolipid metabolism in maintaining endolysosomal membrane integrity and its downstream effects on tau aggregation and toxicity, using both worms and human cell models. The authors showed that knockdown of sphingolipid metabolism genes reduced endolysosomal membrane fluidity, as revealed by FRAP and C-Laurdan imaging, leading to increased vesicle rupture. Furthermore, tau aggregates accumulated in endolysosomes and exacerbated membrane rigidity and damage, promoting seeded tau aggregation, likely by enabling tau seed escape into the cytosol. Importantly, unsaturated fatty acid supplementation restored membrane fluidity, suppressed tau propagation, and alleviated neurotoxicity in C. elegans. These findings provide insight into how lipid dysregulation contributes to tau pathology and highlight membrane fluidity restoration as a potential therapeutic avenue for Alzheimer's disease.

Strengths:

The study addresses the connection between sphingolipid metabolism, endolysosomal membrane integrity, and tau pathology, which is a relevant topic in the context of Alzheimer's disease and related tauopathies.

The use of both C. elegans and human cell models provides cross-species perspectives that help frame the findings in a broader biological context.

The combination of FRAP and C-Laurdan dye imaging offers a biophysical approach to investigate changes in membrane properties, which is a technically interesting aspect of the study.

The observation that unsaturated fatty acid supplementation can modulate membrane fluidity and influence tau-related phenotypes adds an element of potential therapeutic interest.

The study presents multiple experimental approaches to address the proposed mechanism, and efforts were made to examine both membrane behavior and tau aggregation dynamics.

Weaknesses:

In Figure 3, the authors used C-Laurdan imaging to assess membrane fluidity and showed that knockdown of SPHK2, the human ortholog of sphk-1, led to increased membrane rigidity. However, the authors did not co-stain with a lysosomal marker, making it unclear whether the observed effect is specific to lysosomal membranes or reflects general membrane changes. Co-staining with LysoTracker or applying segmentation masks to isolate lysosomal signals would significantly improve interpretation.

Line 173 states that Lipofectamine 2000 increases membrane fluidity based on GP index changes, but this is incorrect. A higher GP index indicates increased membrane order (i.e., reduced fluidity), so the statement should be revised. Additionally, Lipofectamine 2000 can itself alter membrane rigidity, posing a risk of false-positive interpretations. To confirm the role of SPHK2 in this phenotype, the authors should use a CRISPR/Cas9 knockout model instead of relying solely on siRNA transfection, which may be confounded by the delivery reagent. Without lysosomal co-staining and SPHK2 KO validation, the authors cannot conclusively claim that SPHK2 loss affects endolysosomal membrane integrity.

The section titled "Fibrillar tau increases membrane rigidity and exacerbates endolysosomal damage" (lines 177-215) requires substantial revision. The narrative jumps abruptly between worms and cell models, making it hard to follow the logic. The use of the F3ΔK281::mCherry strain is introduced without explanation or context. It is unclear whether this strain is relevant to lysosomal membrane rupture, as no reference or justification is provided. The authors should clarify whether this reporter is intended to detect lysosomal membrane permeabilization (LMP). If so, it would be more appropriate to use established LMP reporters, such as lysosome-targeted fluorescent sensors, galectin-based reporters, or dextran leakage assays. Based on the current data in Figure 3G, it is difficult to draw firm conclusions regarding membrane rupture levels.

To support the conclusion that sphingolipid metabolism gene knockdown alters membrane properties, the study would benefit from direct lipidomic analysis. Measuring changes in sphingolipid profiles in both C. elegans and cell models would provide biochemical evidence for the proposed disruption of lipid homeostasis. Given the availability of lipidomics platforms, this type of analysis should be feasible in both worms and human cells and would significantly strengthen the mechanistic claims regarding membrane fluidity and integrity.

The conclusions of the study rely heavily on imaging-based assays, including FRAP, C-Laurdan, and fluorescence microscopy. While these approaches provide valuable spatial and qualitative insights, they are inherently indirect and subject to interpretive limitations. To strengthen the mechanistic claims, the authors should incorporate additional biochemical or quantitative approaches. For example, lipidomics would allow direct measurement of membrane lipid composition changes, and western blotting or quantitative proteomics could assess levels of membrane-associated proteins involved in endolysosomal function or stress responses. Including such data would significantly improve the robustness and reproducibility of the study's conclusions.

The human cell experiments were performed exclusively in HEK293T cells, which are not physiologically relevant for modeling Alzheimer's disease or lysosomal function in neurons. Given that the study aims to draw conclusions related to tau aggregation and lysosomal membrane integrity, the use of a more disease-relevant cellular model is essential. There are several established AD-relevant cell models, including iPSC-derived neurons, neuroblastoma lines expressing tau, or microglial models, which would better reflect the cellular context of tauopathies. Validation of key findings in at least one of these systems would substantially enhance the biological relevance and translational impact of the study.

The authors reported that PUFA supplementation rescues neurotoxic phenotypes by increasing membrane fluidity. However, the data supporting this claim rely entirely on confocal imaging, shown in both the main and supplemental figures. To substantiate the mechanistic link between PUFA treatment and improved lysosomal membrane properties, the authors should include functional assays demonstrating that PUFAs are indeed incorporated into lysosomal membranes. Additionally, lipidomics analysis would be valuable to identify which lipid species are altered upon supplementation and correlate these changes with the observed phenotypic rescue. Furthermore, the conclusion that PUFAs rescue "neurotoxic phenotypes" is not appropriate based on data derived solely from HEK293T cells, which are not neuronal. To make claims about tau-related neurotoxicity, the authors should validate their findings in a more relevant neuronal model, such as SH-SY5Y neuroblastoma cells expressing tau or iPSC-derived neurons. This would better reflect the cellular environment of Alzheimer's disease and provide stronger support for the proposed therapeutic potential of PUFA supplementation.

While the authors demonstrate that ALA supplementation mitigates neurotoxicity in C. elegans expressing aggregated tau (F3ΔK281::mCherry), the current data are not sufficient to conclude that ALA directly rescues tau aggregation toxicity via a lysosome-specific mechanism. It remains unclear how lipid composition is altered upon ALA treatment and whether these changes correlate with functional improvement of lysosomal pathways. The manuscript does not provide mechanistic insight into how ALA enhances lysosomal health or attenuates endolysosomal damage. Moreover, supplementation with PUFAs like ALA can activate a wide range of cellular processes beyond lysosomal function, including alterations in membrane fluidity, signaling cascades, and oxidative stress responses. The authors should clarify how they distinguish the lysosome-related effects from these alternative pathways. For example, did they observe specific lysosomal markers or structural improvements in lysosomes upon ALA treatment? Additional data or controls would be necessary to support a lysosome-specific protective mechanism and to exclude the involvement of other PUFA-responsive pathways in the observed phenotypes.

Reviewer #1 (Public review):

Summary:

It is now increasingly becoming clear that macromolecules and their complexes can form larger structures such as filaments or cages in the cells under certain conditions. These can be beneficial for the cells to promote and coordinate metabolic activity or result in protection against stress. Reactive oxygen species (ROS) can be damaging to macromolecules in cells that grow both aerobically and anaerobically, and they have evolved different mechanisms to cope with ROS. Aerobic organisms have a number of enzymes to combat ROS, while anaerobic organisms have evolved other means, and one such mechanism is described by Song et al in the article.<br /> In Pyrococcus furiosus, a hyperthermophilic anaerobic bacterium, Song et al describe the formation of Oxidative stress-induced tubular structures (OSITs). Using proteomics and electron cryomicroscopy (CryoEM), the authors find that the protein Rubrerythrin is upregulated upon exposure to oxygen, and the tetramer of this protein assembles to form these tubules that are varied in length with a consistent diameter of ~480 Å. They further observe that some of these tubules also have spherical viral-like particles. With enriched fraction of the OSITs from the cells and proteomics, it is shown that the predominant protein is encapsulin, which forms a caged structure and traps ferric iron. The combined structures of OSIT by rubreerythrin and the VLPs of encapsulin protect the cells from oxygen radicals by forming a complex.

Strengths:

The combination of proteomics and electron microscopy with the employment of both tomography of cellular sections and single particle cryoEM of enriched samples.

Weaknesses:

Some description of the methods, in particular the workflow of image processing, is not easy to follow and can be described with more clarity and be easier for non-experts to read/understand.

Reviewer #1 (Public review):

Summary:

This study shows a novel role for SCoR2 in regulating metabolic pathways in the heart to prevent injury following ischemia/reperfusion. It combines a new multi-omics method to determine SCoR2 mediated metabolic pathways in the heart. This paper would be of interest to cardiovascular researchers working on cardioprotective strategies following ischemic injury in the heart.

Strengths:

(1) Use of SCoR2KO mice subjected to I/R injury.

(2) Identification of multiple metabolic pathways in the heart by a novel multi-omics approach.

Weaknesses:

(1) Use of a global SCoR2KO mice is a limitation since the effects in the heart can be a combination of global loss of SCoR2.

(2) Lack of a cell type specific effect.

DOI: 10.1038/s41421-025-00804-1

Resource: (TKG Cat# TKG 0252, RRID:CVCL_1759)

Curator: @dhovakimyan1

SciCrunch record: RRID:CVCL_1759

What is this?

Reviewer #1 (Public review):

The authors present exciting new experimental data on the antigenic recognition of 78 H3N2 strains (from the beginning of the 2023 Northern Hemisphere season) against a set of 150 serum samples. The authors compare protection profiles of individual sera and find that the antigenic effect of amino acid substitutions at specific sites depends on the immune class of the sera, differentiating between children and adults. Person-to-person heterogeneity in the measured titers is strong, specifically in the group of children's sera. The authors find that the fraction of sera with low titers correlates with the inferred growth rate using maximum likelihood regression (MLR), a correlation that does not hold for pooled sera. The authors then measure the protection profile of the sera against historical vaccine strains and find that it can be explained by birth cohort for children. Finally, the authors present data comparing pre- and post- vaccination protection profiles for 39 (USA) and 8 (Australia) adults. The data shows a cohort-specific vaccination effect as measured by the average titer increase, and also a virus-specific vaccination effect for the historical vaccine strains. The generated data is shared by the authors and they also note that these methods can be applied to inform the bi-annual vaccine composition meetings, which could be highly valuable.

The following points could be addressed in a revision:

(1) The authors conclude that much of the person-to-person and strain-to-strain variation seems idiosyncratic to individual sera rather than age groups. This point is not yet fully convincing. While the mean titer of an individual may be idiosyncratic to the individual sera, the strain-to-strain variation still reveals some patterns that are consistent across individuals (the authors note the effects of substitutions at sites 145 and 275/276). A more detailed analysis, removing the individual-specific mean titer, could still show shared patterns in groups of individuals that are not necessarily defined by the birth cohort.

(2) The authors show that the fraction of sera with a titer below 138 correlates strongly with the inferred growth rate using MLR. However, the authors also note that there exists a strong correlation between the MLR growth rate and the number of HA1 mutations. This analysis does not yet show that the titers provide substantially more information about the evolutionary success. The actual relation between the measured titers and fitness is certainly more subtle than suggested by the correlation plot in Figure 5. For example, the clades A/Massachusetts and A/Sydney both have a positive fitness at the beginning of 2023, but A/Massachusetts has substantially higher relative fitness than A/Sydney. The growth inference in Figure 5b does not appear to map that difference, and the antigenic data would give the opposite ranking. Similarly, the clades A/Massachusetts and A/Ontario have both positive relative fitness, as correctly identified by the antigenic ranking, but at quite different times (i.e., in different contexts of competing clades). Other clades, like A/St. Petersburg are assigned high growth and high escape but remain at low frequency throughout. Some mention of these effects not mapped by the analysis may be appropriate.

(3) For the protection profile against the vaccine strains, the authors find for the adult cohort that the highest titer is always against the oldest vaccine strain tested, which is A/Texas/50/2012. However, the adult sera do not show an increase in titer towards older strains, but only a peak at A/Texas. Therefore, it could be that this is a virus-specific effect, rather than a property of the protection profile. Could the authors test with one older vaccine virus (A/Perth/16/2009?) whether this really can be a general property?

Reviewer #1 (Public review):

Summary:

In this manuscript, Uphoff et al. propose a structural and mechanistic model in which the multidomain ECM protein SVEP1 enables Angiopoietin (ANG) binding to the orphan receptor TIE1, thereby promoting downstream receptor phosphorylation and signaling. Using AlphaFold-based modeling, the authors predict that the CCP20 domain of SVEP1 binds to TIE1, creating a composite surface that facilitates Angiopoietin association and TIE1 activation. The resulting ternary model (SVEP1-TIE1-ANG) offers a structural rationale for how SVEP1 converts TIE1 into a functional, ligand-responsive receptor. Additional models and biological assays suggest roles for other domains of SVEP1, such as CCP5-EGF-L7, although these interactions are predicted with low confidence. The authors interpret these findings as the first structural framework for how SVEP1 enables ANG-TIE1 signaling.

Strengths:

(1) The central hypothesis - that SVEP1 enables ANG binding to the orphan receptor TIE1 - is biologically compelling and addresses an important question in vascular biology.

(2) The AlphaFold-predicted ternary complex (SVEP1-TIE1-ANG) is plausible, high-confidence, and structurally consistent with prior functional data (e.g., poly-Ala scanning from Sato-Nishiuchi et al.).

(3) The authors' model offers a potential explanation for the previously observed role of SVEP1 in enhancing ANG signaling through TIE1, and may represent the first structural insight into TIE1's transition from orphan to ligand-activated receptor.

(4) The potential clinical implication - that a combinatorial ligand (ANG+SVEP1) can activate TIE1- could have translational relevance for vascular leak and inflammatory disease.

Weaknesses:

(1) Lack of structural validation and mechanistic follow-up:
Despite the promising AlphaFold model, there are no figures of the predicted interface, no residue-level interactions shown, no ipTM values reported, and no experimental follow-up to test the interface. PAE plots are incorrectly used as confidence justifications, which is not appropriate for complex predictions.

(2) Biophysical validation is missing:
No surface plasmon resonance (SPR), ITC, or biochemical assays are included to confirm ternary complex formation or quantify binding kinetics. Given the manuscript's structural focus, this is a major gap. For instance, an SPR experiment where ANG is immobilized, and TIE1 binding is measured {plus minus} SVEP1, would directly test the model. And allow direct comparison to ANG-TIE2.

(3) Missed opportunity for mutagenesis-driven validation:
 The manuscript does not include any interface-targeted mutations, despite clear opportunities. For example, mutating T2595 in SVEP1 (to R) or mutating the TIE1-specific residues (residues PL 202-203 to LF) could strongly test the model and potentially reveal dominant-negative behaviors. E.g. A T2595 mutant should block ANG binding but not TIE1 binding.

(4) Overinterpretation of weak models:
The additional AlphaFold model involving the CCP5-EGFL7 domains binding TIE1 has extremely low confidence (ipTM < 0.15) when reexamined by this reader and should not be emphasized. There is no biophysical evidence or binding data (SPR) to support this interaction, and its inclusion detracts from the much stronger CCP20 model.

(5) Language around modeling is overstated and potentially misleading:
Terms like "unequivocal," "high-affinity," or "affirms strong binding" in reference to AlphaFold predictions are inappropriate. These are hypotheses -not confirmations - and must be tested at the biochemical level. This should be clarified throughout the manuscript to ensure non-experts do not misinterpret modeling confidence as binding affinity.

(6) Negative stain EM data is not informative due to low resolution and lack of defined interfaces; unless replaced by higher-resolution Cryo-EM, this should be omitted. Better would be co-gel filtration, AUC, or SEC-MALLs with ANG-SVEP1-TIE1.

(7) Disjointed narrative:
The manuscript presents a compelling mechanism involving CCP20-driven ANG binding to TIE1, but then becomes fragmented by introducing the low-confidence CCP5-EGFL7 model and speculative higher-order polymerization models that are not experimentally supported.

Reviewer #1 (Public review):

Engineering of AAV replication proteins may provide new insights into Parvoviral replication and potentially enable improved recombinant AAV vector yield when incorporated into the manufacturing process. Silberg and colleagues report an AAV Rep library, that is an interesting and powerful approach, however, the screening design and subsequent experiments lack rigor and ultimately the results are premature. Overall, the manuscript does not accurately describe state-of-the-art in the field and has significant shortcomings with experimental design/data analysis. Key concerns are noted below:

The high enrichment of P19 variants in the library was likely an artifact of the fact they only transfected 20 ng of RepCap into their 5-plate preps. When such little Rep is provided, any boost in Rep expression levels will have a major on yield. When more RepCap is provided, 10 ug in their later evaluation, small changes in Rep expression are unlikely to have major impacts on yield. A more effective strategy would have been to transfect a normal amount of DNA and then utilize serial passaging through infectious cycling to account for cross packaging.

Introduction:<br /> - There are 7 FDA approved AAV gene therapies.<br /> - The description of "shuffling" when citing Mietsczh et al is misapplied. The cited paper discusses rationally designed hybrids.<br /> - The graphic represents a hybrid capsid, but the focus is rep. As such, this should be depicted differently.

Figures 1 and 2 are validation of previously published findings and general optimization of the experimental conditions. These do not provide the reader any new insight or information.

In Figure 3: The experimental approach is limited. It is unclear how the subpooling of different conditions was performed. As mentioned above, their library transfection strategy will significantly bias the results. The enriched variants have not been evaluated - specifically, the enriched non-synonymous mutations have not been shown to yield higher titers when tested individually.<br /> In Figure 4: The claim is made that "several synonymous mutations within the p19 promoter region increase Rep DNA packaging activity." However, Figure 4c does not show statistically significant differences in support of this claim. Additional supporting data is needed. Further, Authors state that the synonymous mutations are near the P19 promoter. However, looking at the sequence shown in figure 4, their annotation of the P19 promoter is not correct and the mutations are actually within the P19 promoter. Relatedly, the authors note that mutations enriched in the p19 region include additional tetranucleotide repeats. No synthetic variants with additional GCTCs have been generated to test this hypothesis. Further, these results would benefit from a Western blot and transcript analysis to confirm Rep52/40, expression levels of constructs.

Reviewer #1 (Public review):

Summary:

The authors test whether the archerfish can modulate the fast response to a falling target. By manipulating the trajectory of the target, they claim that the fish can modulate the fast response. While it is clear from the result that the fish can modulate the fast response, the experimental support for argument that the fish can do it for a reflex like behavior is inadequate.

Strengths:

Overall, the question that the authors raised in the manuscript is interesting.

Weaknesses:

Major comments:

(1) The argument that the fish can modulate reflex-like behavior relies on the claim that the archerfish makes the decision in 40 ms. There is little support for the 40 ms reaction time. The reaction time for the same behavior in Schlegel 2008, is 60-70 ms and in Tsvilling 2012 about 75 ms, if we take the half height of the maximum as estimated reaction time in both cases. If we take the peak (or average) of the distribution as an estimation of reaction time, the reaction time is even longer. This number is critical for the analysis the authors perform since if the reaction time is longer, maybe this is not a reflex as claimed. In addition, mentioning the 40 ms in the abstract is overselling the result. The title is also not supported by the results.

(2) A critical technical issue of the stimulus delivery is not clear. The frame rate is 120 FPS and the target horizontal speed can be up to 1.775 m/s. This produces target jumping on the screen 15 mm each frame. This is not a continuous motion. Thus, the similarity between the natural system where the target experience ballistic trajectory and the experiment here is not clear. Ideally, another type of stimulus delivery system is needed for a project of this kind that requires fast moving targets (e.g. Reiser, J. Neurosci.Meth. 2008). In addition, the screen is rectangular and not circular, so in some directions the target vanishes earlier than others. It must produce a bias in the fish response but there is no analysis of this type.

(3) The results here rely on the ability to measure the error of response in the case of virtual experiment. It is not clear how this is done since the virtual target does not fall. How do authors validate that the fish indeed perceives the virtual target as falling target? Since the deflection is at a later stage of the virtual trajectory, it is not clear what is the actual physics that governs the world of the experiment. Overall, the experimental setup is not well designed.

Comments on revisions:

The authors handled the comments, and the manuscript has improved accordingly. While some issues could still benefit from further clarification and depth, the current version meets the necessary standards.

Reviewer #1 (Public review):

In this study the authors aim to understand why decision formation during behavioural tasks is distributed across multiple brain areas. They hypothesize that multiple areas are used in order to implement an information bottleneck (IB). Using neural activity recorded from monkey DLPFC and PMd performing a 2-AFC task, they show that DLPFC represents various task variables (decision, color, target configuration), while downstream PMd primarily represents decision information. Since decision information is the only information needed to make a decision, the authors suggest that PMd has a minimal sufficient representation (as expected from an IB). They then train 3-area RNNs on the same task, and show that activity in the first and third areas resemble the neural representations of DLPFC and PMd, respectively. In order to propose a mechanism, they analyse the RNN and find that area 3 ends up with primarily decision information because feedforward connections between areas primarily propagate decision information.

Overall, the paper reads well and the data analysis and RNN modeling are well done and mostly correct. I agree with the authors that PMd has less information than DLPFC, meaning that some of the target and color information is attenuated. I also agree that this also happens in their multi-area RNN.

However, I find the use of the IB principle here muddles the water rather than clarifying anything. The key problem is that the authors evoke the information bottleneck in a mostly intuitive sense, but they do not actually use it (say, in their modelling). Rather, the IB is simply used to motivate why information will be or should be lost. Since the IB is a generic compressor, however, it does not make any statements about how a particular compression should be distributed or computed across brain areas.

If I ignore the reference to the information bottleneck, I still see a more mechanistic study that proposes a neural mechanism of how decisions are formed, in the tradition of RNN-modelling of neural activity as in Mante et al 2013. Seen through this more limited sense, the present study succeeds at pointing out a good model-data match.

Major points

(1) The IB is a formal, information-theoretic method to identify relevant information. However, in the paper, reference to the information bottleneck method (IB) is only used to motivate why (task-irrelevant) information should be lost in higher areas. The IB principle itself is actually never used. The RNNs are fitted using standard techniques, without reference to the IB. Without a formal link, I think the authors should describe their findings using words (e.g., task-irrelevant information is lost), rather than stating this as evidence for an information-theoretic principle.

(2) The advantage of employing a formal theory is that all assumptions have to be clarified. Since the authors only evoke the IB, but never employ it, they refrain from clarifying some of their assumptions. That is what creates unnecessary confusion.

For instance, the authors cite the following predictions of the IB principle: "(1) There exists a downstream area of cortex that has a minimal and sufficient representation to perform a task ... (2) there exists an upstream area of cortex that has more task information than the minimal sufficient area" - However, since the information bottleneck method is a generic compressor, it does not make any predictions about areas (or neurons). For a given sensory input p(x), a given task output p(y|x), and a given information loss, the IB generates exactly one optimal representation. In other words, the predictions made by the authors relie on other assumptions (e.g. feedforward processing, hierarchy, etc.) and these are not clearly stated.

(3) A corrollary to this problem is that the authors do not formally define task-irrelevant information. It seems the authors simply use the choice or decision as the thing that needs to be computed, and identify all other information as task-irrelevant. That's at least what I glean from the RNN model. However, I find that highly confusing because it suggests the conclusion that color information or target information are task-irrelevant. Surely, that cannot be true, since the decision is based on these quantities!

(4) If we define the output as the only task-relevant information, then any representation that is a pure motor representation would qualify as a minimal sufficient representation to carry out the correct actions. However, it is well-known that sensory information is lost in motor areas. It is not clear to me what exactly we gain by calling motor representations "minimal sufficient representations."

In summary, I think the authors should refrain from evoking the IB - which is a formal, mathematical principle - unless they actually use it formally as well.

Reviewer #1 (Public review):

Summary:

In this manuscript, Pakula et al. explore the impact of reactive oxygen species (ROS) on neonatal cerebellar regeneration, providing evidence that ROS activates regeneration through Nestin-expressing progenitors (NEPs). Using scRNA-seq analysis of FACS-isolated NEPs, the authors characterize injury-induced changes, including an enrichment in ROS metabolic processes within the cerebellar microenvironment. Biochemical analyses confirm a rapid increase in ROS levels following irradiation and forced catalase expression, which reduces ROS levels, and impairs external granule layer (EGL) replenishment post-injury.

Strengths:

Overall, the study robustly supports its main conclusion and provides valuable insights into ROS as a regenerative signal in the neonatal cerebellum.

Comments on revisions:

The authors have addressed most of the previous comments. However, they should clarify the following response:

*"For reasons we have not explored, the phenotype is most prominent in these lobules, that is why they were originally chosen. We edited the following sentence (lines 578-579):

First, we analyzed the replenishment of the EGL by BgL-NEPs in vermis lobules 3-5, since our previous work showed that these lobules have a prominent defect."*

It has been reported that the anterior part of the cerebellum may have a lower regenerative capacity compared to the posterior lobe. To avoid potential ambiguity, the authors should clarify that "the phenotype" and "prominent defect" refer to more severe EGL depletion at an earlier stage after IR rather than a poorer regenerative outcome. Additionally, they should provide a reference to support their statement or indicate if it is based on unpublished observations.

Reviewer #1 (Public review):

Summary:

Jin et al. investigated how the bacterial DNA damage (SOS) response and its regulator protein RecA affects the development of drug resistance under short-term exposure to beta-lactam antibiotics. Canonically, the SOS response is triggered by DNA damage, which results in the induction of error-prone DNA repair mechanisms. These error-prone repair pathways can increase mutagenesis in the cell, leading to the evolution of drug resistance. Thus, inhibiting the SOS regulator RecA has been proposed as means to delay the rise of resistance.

In this paper, the authors deleted the RecA protein from E. coli and exposed this ∆recA strain to selective levels of the beta-lactam antibiotic, ampicillin. After an 8h treatment, they washed the antibiotic away and allowed the surviving cells to recover in regular media. They then measured the minimum inhibitory concentration (MIC) of ampicillin against these treated strains. They note that after just 8 h treatment with ampicillin, the ∆recA had developed higher MICs towards ampicillin, while by contrast, wild-type cells exhibited unchanged MICs. This MIC increase was also observed in subsequent generations of bacteria, suggesting that the phenotype is driven by a genetic change.

The authors then used whole genome sequencing (WGS) to identify mutations that accounted for the resistance phenotype. Within resistant populations, they discovered key mutations in the promoter region of the beta-lactamase gene, ampC; in the penicillin-binding protein PBP3 which is the target of ampicillin; and in the AcrB subunit of the AcrAB-TolC efflux machinery. Importantly, mutations in the efflux machinery can impact the resistance towards other antibiotics, not just beta-lactams. To test this, they repeated the MIC experiments with other classes of antibiotics, including kanamycin, chloramphenicol, and rifampicin. Interestingly, they observed that the ∆recA strains pre-treated with ampicillin showed higher MICs towards all other antibiotics tested. This suggests that the mutations conferring resistance to ampicillin are also increasing resistance to other antibiotics.

The authors then performed an impressive series of genetic, microscopy, and transcriptomic experiments to show that this increase in resistance is not driven by the SOS response, but by independent DNA repair and stress response pathways. Specifically, they show that deletion of the recA reduces the bacterium's ability to process reactive oxygen species (ROS) and repair its DNA. These factors drive the accumulation of mutations that can confer resistance towards different classes of antibiotics. The conclusions are reasonably well-supported by the data, but some aspects of the data and the model need to be clarified and extended.

Strengths:

A major strength of the paper is the detailed bacterial genetics and transcriptomics that the authors performed to elucidate the molecular pathways responsible for this increased resistance. They systemically deleted or inactivated genes involved in the SOS response in E. coli. They then subjected these mutants to the same MIC assays as described previously. Surprisingly, none of the other SOS gene deletions resulted in an increase in drug resistance, suggesting that the SOS response is not involved in this phenotype. This led the authors to focus on the localization of DNA PolI, which also participates in DNA damage repair. Using microscopy, they discovered that in the RecA deletion background, PolI co-localizes with the bacterial chromosome at much lower rates than wild-type. This led the authors to conclude that deletion of RecA hinders PolI and DNA repair. Although the authors do not provide a mechanism, this observation is nonetheless valuable for the field and can stimulate further investigations in the future.

In order to understand how RecA deletion affects cellular physiology, the authors performed RNA-seq on ampicillin-treated strains. Crucially, they discovered that in the RecA deletion strain, genes associated with antioxidative activity (cysJ, cysI, cysH, soda, sufD) and Base Excision Repair repair (mutH, mutY, mutM), which repairs oxidized forms of guanine, were all downregulated. The authors conclude that down-regulation of these genes might result in elevated levels of reactive oxygen species in the cells, which in turn, might drive the rise of resistance. Experimentally, they further demonstrated that treating the ∆recA strain with an antioxidant GSH prevents the rise of MICs. These observations will be useful for more detailed mechanistic follow-ups in the future.

Weaknesses:

Throughout the paper, the authors use language suggesting that ampicillin treatment of the ∆recA strain induces higher levels of mutagenesis inside the cells, leading to the rapid rise of resistance mutations. However, as the authors note, the mutants enriched by ampicillin selection can play a role in efflux and can thus change a bacterium's sensitivity to a wide range of antibiotics, in what is known as cross-resistance. The current data is not clear on whether the elevated "mutagenesis" is driven by ampicillin selection or by a bona fide increase in mutation rate.

Furthermore, on a technical level, the authors employed WGS to identify resistance mutations in the ampicillin-treated wild-type and ∆recA strains. However, the WGS methodology described in the paper is inconsistent. Notably, wild-type WGS samples were picked from non-selective plates, while ΔrecA WGS isolates were picked from selective plates with 50 μg/mL ampicillin. Such an approach biases the frequency and identity of the mutations seen in the WGS and cannot be used to support the idea that ampicillin treatment induces higher levels of mutagenesis.

Finally, it is important to establish what the basal mutation rates of both the WT and ∆recA strains are. Currently, only the ampicillin-treated populations were reported. It is possible that the ∆recA strain has inherently higher mutagenesis than WT, with a larger subpopulation of resistant clones. Thus, ampicillin treatment might not, in fact, induce higher mutagenesis in ∆recA.

Summary of revised manuscript:

In their revisions, the authors have addressed my major concerns with additional experiments and changes to the text. Thank you!

Reviewer #1 (Public review):

Summary:

This paper shows that maternal high-fat diet during lactation changes microglia morphology in the PVN, potentially to acquire a more active state. Further, the authors reveal that PVN microglia engulf AgRP terminals in the PVN during postnatal development, a previously unrecognized behavior. A notable finding of this paper is that pharmacological reduction of microglial cells can reverse weight gain and terminal loss in the offspring under maternal high fat diet conditions, even though an increase in microglial engulfment of AgRP+ terminals was not observed, suggesting an alternative mechanism. The data support these findings, although questions remain regarding the efficacy and timing of the pharmacological microglial knockdown.

Strengths

(1) The impact of microglia on hypothalamic synaptic pruning is poorly characterized, and thus, the findings herein are especially of interest.

Weaknesses

(1) Most minor concerns were addressed during revisions, including additional details in the methods and results sections that help interpret the data as presented.

(2) The AgRP staining is unclear. For example, in Figure 2, the figure legend says "labeled AgRP terminals (red)" (Fig 2A-D) but then concludes no difference in the number of "AgRP neurons" (Fig 2J). Is this quantification of AgRP+ neurons, terminals, or both?

(3) The PLX experiments are critical to their conclusion that during lactation, microglia in the PVN sculpt AgRP inputs; however, there is no demonstration that PLX treatment effectively eliminated microglia during this postnatal window. Microglia depletion was only assessed at P55, a month past the PLX treatment window making it unclear when and by what percentage the microglia were eliminated.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors used a leucine/pantothenate auxotrophic strain of Mtb to screen a library of FDA-approved compounds for their antimycobacterial activity and found significant antibacterial activity of the inhibitor semapimod. In addition to alterations in pathways, including amino acid and lipid metabolism and transcriptional machinery, the authors demonstrate that semapimod treatment targets leucine uptake in Mtb. The work presents an interesting connection between nutrient uptake and cell wall composition in mycobacteria.

Strengths:

(1) The link between the leucine uptake pathway and PDIM is interesting but has not been characterized mechanistically. The authors discuss that PDIM presents a barrier to the uptake of nutrients and shows binding of the drug with PpsB. However it is unclear why only the leucine uptake pathway was affected. We still do not know what PpsB actually does for amino acid uptake - is it a transporter? Does semapimod binding affect its activity? Does the auxotrophic Mtb have lower PDIM levels compared to wild-type Mtb?

(2) The authors show an interesting result where they observed antibacterial activity of semapimod against H37Rv only in vivo and not in vitro. Why do the authors think this is the basis of this observation? It is possible semapimod has an immunomodulatory effect on the host since leucine is an essential amino acid in mice. The authors could check pro-inflammatory cytokine levels in infected mouse lungs with and without drug treatment.

(3) The authors show that the semapimod-resistant auxotroph lacks PDIM. The conclusions would be further strengthened by including validations using PDIM mutants, including del-ppsB Mtb and other genes of the PDIM locus, whether in vivo this mutant would be more susceptible (or resistant) to semapimod treatment.

(4) Prolonged subculturing can introduce mutations in PDIM, which can be overcome by supplementing with propionate (Mullholland et al, Nat Microbiol, 2024). Did the authors also supplement their cultures with propionate? It would be interesting to see what mutations would result in Semr strains with propionate supplementation along with prolonged semapimod treatment.

Weaknesses:

I have summarized the limitations above in my comments. Overall, it would be helpful to provide more mechanistic details to study the connection between leucine uptake and PDIM.

Reviewer #1 (Public review):

Summary:

The manuscript finds a negative relationship between tuberculin skin test-induced type I interferon activity with chest X-ray tuberculosis severity in humans. This evidence is between incomplete and solid. It needs a bioinfomatics/transcriptomics reviewer to make a more insightful judgement. The manuscript demonstrates a convincing role for Stat2 in controlling Mycobacterium marinum infection in zebrafish embryos, incomplete data are presented linking reduced leukocyte recruitment to the infection susceptibility phenotype.

Strengths:

(1) An interesting analysis of TST response correlated with chest X-ray pathology.

(2) Novel data on a protective role for Stat2 in a natural host-mycobacterial species infection pairing.

Weaknesses:

(1) The transcriptional modules are very large sets of genes that do not present a clear picture of what is actually being measured relative to other biological pathways.

(2) The link between infection-Stat2-leukocyte recruitment and containment of infection is plausible, but lacks a specific link to the first part of the manuscript.

Major concerns

(1) Line 158: The two transcriptional modules should be placed in the context of other DEG patterns. The macrophage type I interferon module, in particular, is quite large (361 genes). Can this be made more granular in terms of type I IFN ligands and STAT2-dependent genes?

(2) The ifnphi1 injection into mxa:mCherry stat2 crispants is a nice experiment to demonstrate loss of type I IFN responsiveness. Further data is required to demonstrate if important mycobacterial control pathways (IFNy, TNF, il6?, etc) are intact in stat2 crispants before being able to conclude that these phenotypes are specific to type I IFN.

Reviewer #1 (Public review):

Summary:

A fundamental technique for the identification of peptide-specific CD8 T cells is the use of fluorophore-conjugated and peptide loaded MHC tetramers. Classically, refolding of specific peptides with MHC monomers can be labour intensive, and not optimal for screening large numbers of different peptides. Hence, UV-exchanged tetramers have been developed to upscale this, however, still has some associated challenges such as UV-mediated damage to peptide complexes. Here, Pothast, C.R. et al demonstrate the efficacy of using temperature exchanged tetramers for the prevalent alleles HLA-A*03:01, A*11:01, B*07:02, and C*07:02. Building upon their previous work with HLA-A*02:01, H-2Kb, and HLA-E. They first demonstrate the complex stability of tetramers with different affinity peptides at high temperature, showing complex destabilisation can be rescued with higher affinity peptides. This is followed by an optimisation of peptide exchange temperatures, tailored for each allele. The authors then demonstrate successful binding to clonal T cell lines, and then a step further with viral peptides against PBMCs from individuals with confirmed infection history. For the latter they compare to conventional tetramers and demonstrate comparable signal.<br /> Due to the prevalence of these 4 alleles, the ease-of-handling, and short time requirements, these tetramers are likely to show high utility.

Strengths:

The manuscript is well-written and the results are solid, although more detail may add clarity to some of the results, in particular Figures 1 and 2. Other than the points reported below, the study uses accurate controls to demonstrate the specificity of the tetramers, and the data are convincing.

Overall, the interpretation of the results is accurate, and the discussion is thorough. Additional comments may be included to cover potential tetramer batch variability and differences in the stability of different alleles. Specifically, whether certain alleles require higher-affinity peptides to be stable, compared to others.

Weaknesses:

The authors demonstrate the equivalence of temperature-exchanged tetramers to conventional ones, however, as they are an advancement on UV-exchange, it would be useful to show data on how their stability, exchange efficacy, and binding to T cell lines compare to UV-based tetramers. It would be supportive to show that temperature does not impact fluorophore intensity as well.

Reviewer #1 (Public review):

Summary:

This study focuses on the bacterial metabolite TMA, generated from dietary choline. These authors and others have previously generated foundational knowledge about the TMA metabolite TMAO, and its role in metabolic disease. This study extends those findings to test whether TMAO's precursor, TMA, and its receptor TAAR5 are also involved and necessary for some of these metabolic phenotypes. They find that mice lacking the host TMA receptor (Taar5-/-) have altered circadian rhythms in gene expression, metabolic hormones, gut microbiome composition, and olfactory and innate behavior. In parallel, mice lacking bacterial TMA production or host TMA oxidation have altered circadian rhythms.

Strengths:

These authors use state-of-the-art bacterial and murine genetics to dissect the roles of TMA, TMAO, and their receptor in various metabolic outcomes (primarily measuring plasma and tissue cytokine/gene expression). They also follow a unique and unexpected behavioral/olfactory phenotype. Statistics are impeccable.

Weaknesses:

Enthusiasm for the manuscript is dampened by some ambiguous writing and the presentation of ideas in the introduction, both of which could easily be improved upon revision.

Reviewer #1 (Public review):

Summary:

This manuscript analyses primarily the effects of deleting the TgfbR1 and TgfbR2 receptors from endothelial cells at postnatal stages of vascular development and blood-retina barrier maturation in the retina. The authors find that deletion of these receptors affects vascular development in the retina, but importantly, it affects the infiltration of immune cells across the vessels in the retina. The findings demonstrate that Tgfb signaling through TgfbR1/R2 heterodimers regulates primarily the immune phenotypes of endothelial cells in addition to regulating vascular development. The data provided by the authors provide a solid support for their conclusions.

Strengths:

(1) The manuscript uses a variety of elegant genetic studies in mice to analyze the role of TgfbR1 and TgfbR2 receptors in endothelial cells at postnatal stages of vascular development and blood-retina barrier maturation in the retina.

(2) The authors provide a nice comparison of the vascular phenotypes in endothelial-specific knockout of TgfbR1 and TgfbR2 in the retina (and to a lesser degree in the brain) with those from Npd KO mice (loss of Ndp/Fzd signaling) or loss of VEGF-A signaling to dissect the specific roles of Tgf signaling for vascular development in the retina.

(3) The snRNAseq data of vessel segments from the brains of WT versus TgfbR1 -iECKO mice provides a nice analysis of pathways and transcripts that are regulated by Tgfb signaling in endothelial cells.

Weaknesses:

(1) The authors claim that choroidal neovascular tuft phenotypes are similar in TgfbrR1 KO and TgfbrR2 KO mice. However, the phenotypes look more severe in the TgfbrR1 KO rather than TgfbrR2 KO mice. Can the authors show a quantitative comparison of the number of choroidal neovascular tufts per whole eye cross-section in both genotypes?

(2) In the analysis of Sulfo-NHS-Biotin leakage in the retina to assess blood-retina barrier maturation. The authors claim that there is increased vascular leakage in the TgfbR1 KO mice. However, it does not seem like Sulfo-NHS-biotin is leaking outside the vessels. Therefore, it cannot be increased vascular permeability. Can the authors provide a detailed quantification of the leakage phenotype?

(3) The immune cell phenotyping by snRNAseq is premature, as the number of cells is very small. The authors should sort for CD45+ cells and perform single-cell RNA sequencing.

(4) The analysis of BBB leakage phenotype in TgfbR1 KO mice needs to be more detailed and include tracers as well as serum IgG leakage.

(5) A previous study (Zarkada et al., 2021, Developmental Cell) showed that EC-deletion of Alk5 affects the D tip cells. The phenotypes of those mice look very similar to those shown for TgfbrR1 KO mice. Are D-tip cells lost in these mutants by snRNAseq?

Reviewer #1 (Public review):

Summary:

This paper examines how geometric regularities in abstract shapes (e.g., parallelograms, kites) are perceived and processed in the human brain. The manuscript contains multimodal data (behavior, fMRI, MEG) from adults and additional fMRI data from 6-year-old children. The key findings show that (1) processing geometric shapes lead to reduced activity in ventral areas in comparison to complex stimuli and increased activity in intraparietal and inferior temporal regions, (2) the degree of geometric regularity modulates activity in intraparietal and inferior temporal regions, (3) similarity in neural representation of geometric shapes can be captured early by using CNN models and later by models of geometric regularity. In addition to these novel findings, the paper also includes a replication of behavioral data, showing that the perceptual similarity structure amongst the geometric stimuli used can be explained by a combination of visual similarities (as indexed by a feedforward CNN model of the ventral visual pathway) and geometric features.

Strengths:

(1) The study incorporates multi-modal data that uses more than one task and different populations of participants (adults and children).

(2) It replicates behavioral findings of an earlier study in a larger cohort.

(3) The paper comes with openly accessible code in a well-documented GitHub repository, and the data will be published with the paper on OpenNeuro.

Weaknesses:

I wonder how task difficulty and linguistic labels interact with the current findings. Based on the behavioral data, shapes with more geometric regularities are easier to detect when surrounded by other shapes. Do shape labels that are readily available (e.g., "square") help in making accurate and speedy decisions? Can the sensitivity to geometric regularity in intraparietal and inferior temporal regions be attributed to differences in task difficulty? Similarly, are the MEG oddball detection effects that are modulated by geometric regularity also affected by task difficulty?

Reviewer #1 (Public review):

Lipid transfer proteins (LTPs) play a crucial role in the intramembrane lipid exchange within cells. However, the molecular mechanisms that govern this activity remain largely unclear. Specifically, the way in which LTPs surmount the energy barrier to extract a single lipid molecule from a lipid bilayer is not yet fully understood. This manuscript investigates the influence of membrane properties on the binding of Ups1 to the membrane and the transfer of phosphatidic acid (PA) by the LTP. The findings reveal that Ups1 shows a preference for binding to membranes with positive curvature. Moreover, coarse-grained molecular dynamics simulations indicate that positive curvature decreases the energy barrier associated with PA extraction from the membrane. Additionally, lipid transfer assays conducted with purified proteins and liposomes in vitro demonstrate that the size of the donor membrane significantly impacts lipid transfer efficiency by Ups1-Mdm35 complexes, with smaller liposomes (characterized by high positive curvature) promoting rapid lipid transfer.

This study offers significant new insights into the reaction cycle of phosphatidic acid (PA) transfer by Ups1 in mitochondria. Notably, the authors present compelling evidence that, alongside negatively charged phospholipids, positive membrane curvature enhances lipid transfer - an effect that is particularly relevant at the mitochondrial outer membrane. The experiments are technically robust, and my primary feedback pertains to the interpretation of specific results.

(1) The authors conclude from the lipid transfer assays (Figure 5) that lipid extraction is the rate-limiting step in the transfer cycle. While this conclusion seems plausible, it should be noted that the authors employed high concentrations of Ups1-Mdm35 along with less negatively charged phospholipids in these reactions. This combination may lead to binding becoming the rate-limiting factor. The authors should take this point into consideration. In this type of assay, it is challenging to clearly distinguish between binding, lipid extraction, and membrane dissociation as separate processes.

(2) The authors should discuss that variations in the size of liposomes will also affect the distance between them at a constant concentration, which may affect the rate of lipid transfer. Therefore, the authors should determine the average size and size distribution of liposomes after sonication (by DLS or nanoparticle analyzer, etc.).

(3) The authors use NBD-PA in the lipid transfer assays. Does the size of the donor liposomes affect the transfer of NBD-PA and DOPA similarly? Since NBD-labeled lipids are somewhat unstable within lipid bilayers (as shown by spontaneous desorption in Figure 5B), monitoring the transfer of unlabeled PA in at least one setting would strengthen the conclusion of the swap experiments.

(4) The present study suggests that membrane domains with positive curvature at the outer membrane may serve as starting points for lipid transport by Ups1-Mdm35. Is anything known about the mechanisms that form such structures? This should be discussed in the text.

Reviewer #1 (Public review):

Summary:

The nuclear protein SATB1 was originally identified as a protein of the 'nuclear matrix', an aggregate of nuclear components that arose upon extracting nuclei with high salt. While the protein was assumed to have a global function in chromatin organization, it has subsequently been linked to a variety of pathological conditions, notably cancer. The mapping of the factor by conventional ChIP procedures showed strong enrichment in active, accessible chromatin, suggesting a direct role in gene regulation, perhaps in enhancer-promoter communication. These findings did not explain why SATB1-chromatin interaction resisted the 2 M salt extraction during early biochemical fractionation of nuclei.

The authors, who have studied SATB1 for many years, now developed an unusual variation of the ChIP procedure, in which they purify crosslinked chromatin by centrifugation through 8 M urea. Remarkably, while they lose all previously mapped signals for SATB1 in active chromatin, they now gain many binding events in silent regions of the genome, represented by lamin-associated domains (LADs).

SATB1 had previously been shown by the authors and others to bind to DNA with special properties, termed BUR for 'base-unpairing regions'). BURs are AT-rich and apparently enriched in equally AT-rich LADs. The 'urea-ChIP' pattern is essentially complementary to the classical ChIP pattern. The authors now speculate that the previously known SATB1 binding pattern determined by standard ChIP, which does not overlap BURs particularly well, is due to indirect chromatin binding, whereas they consider the urea-ChIP profile, which fits better to the BUR distribution on the chromosome, to be due to direct binding.

Building on the success with urea-ChIP the authors adapted the 4C-procedure of chromosome conformation mapping to work with urea-purified chromatin. The data suggest a model according to which BUR-bound SATB1 mediates long-distance interaction between active loci and some kind of scaffold structure formed by SATB1. Because cell type-specific differences are observed, they suggest that the SATB1 interactions are functionally relevant.

Strengths:

Given the unusual findings of essentially mutually exclusive 'standard ChIP' and 'urea-ChIP' profiles, the authors conducted many appropriate controls. They showed that all SATB1 peaks in urea-ChIP and 96% of peaks in standard-ChIP represent true signals, as they are not observed in a SATB1 knockout cell line. They also show that the urea-ChIP and standard ChIP yield similar profiles for CTCF and polycomb complex subunits. The data appear reproducible judged by at least two replicates and triangulation. The SATB1 KO cells provide a nice control for the specificity of signals, including those that arise from their elaborately modified 4C protocol.

In their revised manuscript the authors provide relevant background information concerning the effect of urea on the denaturation of macromolecules. Importantly, they argue convincingly that urea does not denature DNA under their conditions.

Weaknesses:

Despite the authors' efforts to explain their findings along with a lot of background information, some readers may be left confused due to the complexity of the system. BURs are found enriched in LADs, but are also present in active chromatin. SATB1 binds a subset of BURs, but the reason for discrimination remains unclear. SATB1 appears to bind chromatin in at least two modes with differing diffusion properties and exactly how this relates to the indirect and direct chromatin binding modes is mechanistically unclear.

The authors resort to the term 'SATB1-enriched subnuclear structure' to describe the profile gained through denaturing ChIP, thus avoiding strong statements about involvement of known nuclear structures (such as LADs or heterochromatin) and about functional implications.

The authors acknowledge a potential for RNA to be involved in modulating SATB1 interactions with chromatin, but leave this for future investigation.

Comment on revised version:

The authors revised their manuscript to my satisfaction.

Reviewer #1 (Public review):

Summary:

This work studies representations in a network with one recurrent layer and one output layer that needs to path-integrate so that its position can be accurately decoded from its output. To formalise this problem, the authors define a cost function consisting of the decoding error and a regularisation term. They specify a decoding procedure that, at a given time, averages the output unit center locations, weighted by the activity of the unit at that time. The network is initialised without position information, and only receives a velocity signal (and a context signal to index the environment) at each timestep, so to achieve low decoding error it needs to infer its position and keep it updated with respect to its velocity by path integration.

The authors take the trained network and let it explore a series of environments with different geometries while collecting unit activities to probe learned representations. They find localised responses in the output units (resembling place fields) and border responses in the recurrent units. Across environments, the output units show global remapping and the recurrent units show rate remapping. Stretching the environment generally produces stretched responses in output and recurrent units. Ratemaps remain stable within environments and stabilise after noise injection. Low-dimensional projections of the recurrent population activity forms environment-specific clusters that reflect the environment's geometry, which suggests independent rather than generalised representations. Finally, the authors discover that the centers of the output unit ratemaps cluster together on a triangular lattice (like the receptive fields of a single grid cell), and find significant clustering of place cell centers in empirical data as well.

The model setup and simulations are clearly described, and are an interesting exploration of the consequences of a particular set of training requirements - here: path integration and decodability. But it is not obvious to what extent the modelling choices are a realistic reflection of how the brain solves navigation. Therefore, it is not clear whether the results generalize beyond the specifics of the setup here.

Strengths:

The authors introduce a very minimal set of model requirements, assumptions, and constraints. In that sense, the model can function as a useful 'baseline', that shows how spatial representations and remapping properties can emerge from the requirement of path integration and decodability alone. Moreover, the authors use the same formalism to relate their setup to existing spatial navigation models, which is informative.

The global remapping that the authors show is convincing and well-supported by their analyses. The geometric manipulations and the resulting stretching of place responses, without additional training, are interesting. They seem to suggest that the recurrent network may scale the velocity input by the environment dimensions so that the exact same path integrator-output mappings remain valid (but maybe there are other mechanisms too that achieve the same).

The simulations and analyses in the appendices serve as insightful controls for the main results.

The clustering of place cell peaks on a triangular lattice is intriguing, given there is no grid cell input. It could have something to do with the fact that a triangular lattice provides optimal coverage of 2d space? The included comparison with empirical data is valuable as a first exploration, showing a promising example, but doesn't robustly support the modelling results.

Weaknesses:

The navigation problem that needs to be solved by the model is a bit of an odd one. Without any initial position information, the network needs to figure out where it is, and then path-integrate with respect to a velocity signal. As the authors remark in Methods 4.2, without additional input, the only way to infer location is from border interactions. It is like navigating in absolute darkness. Therefore, it seems likely that the salient wall representations found in the recurrent units are just a consequence of the specific navigation task here; it is unclear if the same would apply in natural navigation. In natural navigation, there are many more sensory cues that help inferring location, most importantly vision, but also smell and whiskers/touch (which provides a more direct wall interaction; here, wall interactions are indirect by constraining velocity vectors). There is a similar but weaker concern about whether the (place cell like) localised firing fields of the output units are a direct consequence of the decoding procedure that only considers activity center locations.

The conclusion that 'representations are attractive' (heading of section 2) is not entirely supported. The authors show 'attractor-like behaviour' within a single context, but there could be alternative explanations for the recovery of stable ratemaps after noise injection. For example, the noise injection could scramble the network's currently inferred position, so that it would need to re-infer its position from boundary interactions along the trajectory. In that case the stabilisation would be driven by the input, not just internal attractor dynamics. Indeed, the useful control analysis in Appendix D suggests such a mechanism: without a velocity signal, only for small noise injections the network returns to a high correlation state. Correlated representations are recovered for larger noise injections due to the same mechanism that allow the network to determine its position upon from an uninformative initial hidden state upon entering a new environment, i.e. boundary interactions.

The authors report empirical data that shows clustering of place cell centers like they find for their output units. They report that 'there appears to be a tendency for the clusters to arrange in hexagonal fashion, similar to our computational findings'. This is an interesting observation on the distribution of place field centres which seems justified based on the example animal shown, but not across the population of animals included.

Reviewer #1 (Public review):

Summary:

In this study, authors explored how galanin affects whole-brain activity in larval zebrafish using wide-field Ca2+ imaging, genetic modifications, and drugs that increase brain activity. The authors conclude that galanin has a sedative effect on the brain under normal conditions and during seizures, mainly through the galanin receptor 1a (galr1a). However, acute "stressors(?)" like pentylenetetrazole (PTZ) reduce galanin's effects, leading to increased brain activity and more seizures. Authors claim that galanin can reduce seizure severity while increasing seizure occurrence, speculated to occur through different receptor subtypes. This study confirms galanin's complex role in brain activity, supporting its potential impact on epilepsy.

Strengths:

The overall strength of the study lies primarily in its methodological approach using whole-brain Calcium imaging facilitated by the transparency of zebrafish larvae. Additionally, the use of transgenic zebrafish models is an advantage, as it enables genetic manipulations to investigate specific aspects of galanin signaling. This combination of advanced imaging and genetic tools allows for addressing galanin's role in regulating brain activity.

Weaknesses:

We have carefully reviewed the revised manuscript and the authors' responses. While the authors have attempted to address the points raised, I find that the revisions and rebuttals are insufficient and not entirely adequate. The authors seem not to have modified the manuscript in any way to take our comments into account.

In particular, many of the methodological and conceptual issues I initially raised remain unresolved. For example, the fundamental concern regarding the use of whole-brain calcium imaging - a method that may not effectively capture the localized and network-specific nature of seizure initiation and propagation - has not been adequately addressed. The authors acknowledge some limitations but do not sufficiently discuss how these affect the interpretation of their findings or propose mitigations. This could be added to the discussion section.

Additionally, the characterization of PTZ as a "stressor" remains problematic. Although the authors have retained this terminology, PTZ is widely understood to act primarily as a proconvulsant agent rather than a general stressor, and framing it otherwise continues to appear like a model-fitting rather than evidence-driven decision. The authors should consider changing the terminology throughout the manuscript and address these concerns when discussing their choice of PTZ as "stressor".

The discussion of the EAAT2 mutant model also remains incomplete. Although the authors mention preliminary transcriptome analyses, no new data were included, and it is stated that the evaluation is ongoing. Without thorough gene expression data, alternative explanations for the hypoactivity phenotype (such as changes in AMPA receptor or other critical neurotransmission-related genes) remain plausible and unaddressed. Moreover, the authors' acknowledgement that galanin upregulation is "at best one of a suite of regulatory mechanisms" further diminishes the centrality of their conclusions without sufficiently reworking the narrative of the study.

Finally, the finding that double knockout animals for EAAT2 and galanin showed little difference in seizure susceptibility compared to EAAT2 knockouts alone suggests that galanin upregulation may not play a dominant functional role, yet this important implication is not adequately reflected in the interpretation of the results.

Conclusion:

In summary, although the authors have made some efforts to respond to the critiques, I do not believe the manuscript has been substantially improved in response in R2, and I do not see reason to change my original assessment made after R1. The major conceptual and methodological concerns remain largely unaddressed, limiting the impact and validity of the study's conclusions. These concerns should be addressed not only in the rebuttal letter but also in the manuscript.

Reviewer #1 (Public review):

Summary:

In this manuscript, Ru and colleagues investigated regulatory gene interactions during osteogenic differentiation. By profiling transcriptomic changes during mesenchymal stem cell differentiation, they identified KLF16 as a key transcription factor that inhibits osteogenic differentiation and mineralization. It was found that overexpression of KLF16 suppressed osteogenesis in vitro, while KLF16⁺/⁻ mice exhibited enhanced bone density, underscoring its regulatory role in bone formation.

Strengths:

(1) Bioinformatics is strong and comprehensive.

(2) Identification of KLF16 in osteoblast differentiation is exciting and innovative.

Weaknesses:

(1) The mechanism of KLF16 function is not studied.

(2) Studies of KLF16 in bone development, from both in vitro and in vivo perspectives, are descriptive.

(3) Findings in bioinformatics analysis are mostly redundant with previous studies in the field, and can be simplified.

Reviewer #1 (Public review):

The authors have developed a contextual fear learning (CFC) paradigm in head-fixed mice that produces freezing as the conditioned response. Typically, lick suppression is the conditioned response in such designs, but this 1) introduces a potential confounding influence of reward learning on neural assessments of aversion learning and 2) does not easily allow comparison of head-fixed studies with extensive previous work in freely moving animals, which use freezing as the primary conditioned response. This report describes 3 versions of this virtual reality CFC paradigm, its validation using place-cell remapping, and provides suggestions for further refinement and application.

The first part of this study is a report on the development and outcomes of 3 variations of the CFC paradigm in a virtual reality environment. The fundamental design is strong, with head-fixed mice required to run down a linear virtual track to obtain a water reward. Once trained, the water reward is no longer necessary and mice will navigate virtual reality environments. There are rigorous performance criteria to ensure that mice that make it to the experimental stage show very low levels of inactivity prior to fear conditioning. These criteria do result in only 40% of the mice making it to the experimental stage, but high rates of activity in the VR environment is crucial for detecting learning-related freezing. It is possible that further adjustments to the procedure could improve attrition rates.

Paradigm versions 1 and 2 vary the familiarity of the control context while paradigm versions 2 and 3 vary the inter-shock interval. Version 1 is the most promising, showing the greatest increase in conditioned freezing (~40%) and good discrimination between contexts (delta ~15-20%). Version 2 showed no clear evidence of learning - average freezing at recall day 1 was not different than pre-shock freezing. First lap freezing showed a difference, but this single lap effect is not useful for many of the neural circuit questions for which this paradigm is meant to facilitate. Version 3 produces greater freezing and slower extinction than version 2. While the magnitude of the context discrimination is less than that in version 1, further optimization of the VR CFC is likely to produce robust learning and extinction. The authors discuss several options for further optimization.

The second part of the study is a validation of the head-fixed CFC VR protocol through demonstration that fear conditioning leads to remapping of dorsal CA1 place fields, similar to that observed in freely moving subjects. The results support this aim and largely replicate previous findings in freely moving subjects. One difference from previous work of note is that VR CFC led to remapping of the control environment, not just the conditioning context. The authors present several possible explanations for this lack of specificity to the shock context. While this experiment examined place cell remapping after fear conditioning, it did not attempt to link neural activity to the learned association or freezing behavior.

In summary, this is an important methodological innovation and this study sets the initial parameters and neuronal validation needed to further optimize a head-fixed CFC paradigm that produces freezing. In the discussion, the authors note the limitations of this study, suggest next steps in refinement, and point to several future directions using this protocol to significantly advance our understanding of the neural circuits of threat-related learning and behavior.

Comments on revisions:

The manuscript is much stronger with the additions and revisions the authors provided in their revised submission.

Reviewer #1 (Public review):

Summary:

In this manuscript, Guo and colleagues used a cell rounding assay to screen a library of compounds for inhibition of TcdB, an important toxin produced by Clostridioides difficile. Caffeic acid and derivatives were identified as promising leads, and caffeic acid phenethyl ester (CAPE) was further investigated.

Strengths:

Considering the high morbidity rate associated with C. difficile infections (CDI), this manuscript presents valuable research in the investigation of novel therapeutics to combat this pressing issue. Given the rising antibiotic resistance in CDI, the significance of this work is particularly noteworthy. The authors employed a robust set of methods and confirmatory tests, which strengthen the validity of the findings. The explanations provided are clear, and the scientific rationale behind the results is well-articulated. The manuscript is extremely well written and organized. There is a clear flow in the description of the experiments performed. Also, the authors have investigated the effects of CAPE on TcdB in careful detail, and reported compelling evidence that this is a meaningful and potentially useful metabolite for further studies.

Weaknesses:

Although the authors have made changes to the manuscript to address some of my comments, many of the comments were not satisfactorily addressed. Many of the changes are still superficial, and some concerns still need to be addressed. Important details are still missing from the description of some experiments. Authors should carefully revise the manuscript to ascertain that all details that could affect interpretation of their results are presented clearly.

There is still very little discussion (none, really) in the manuscript about the fact that, because the authors observed a significant effect of CAPE on both bacterial growth and spore production, some of the phenotypes observed can no longer be attributed solely to toxin inhibition.

The details about mass spectrometry are still insufficient. It is still unclear whether metabolite identifications were always based on MS1 or MS2. Instead, several details that are really secondary were included. Authors should be unequivocally clear as to how metabolite identities were obtained. They should also indicate which mass spectrometer was used, and there should be a section in the Materials and Methods describing these experiments.

About the removal of carry-over compounds, the authors stated that ultrafiltration centrifugal partition was used. However, although the authors explained this in detail in their response to reviewers file, the details were omitted from the main text. Authors should clearly state in the manuscript text that "Due to the large molecular weight of TcdB, approximately 270 kDa, we selected a 100 kDa molecular weight cutoff ultrafiltration membrane. The centrifugation was performed at 4000 g for 5 min to eliminate the compounds that did not bind to TcdB."

These are important details which need to be included.

Reviewer #1 (Public review):

Summary:

Brdar, Osterburg, Munick, et al. present an interesting cellular and biochemical investigation of different p53 isoforms. The authors investigate the impact of different isoforms on the in-vivo transcriptional activity, protein stability, induction of the stress response, and hetero-oligomerization with WT p53. The results are logically presented and clearly explained. Indeed, the large volume of data on different p53 isoforms will provide a rich resource for researchers in the field to begin to understand the biochemical effects of different truncations or sequence alterations.

Strengths:

The authors achieved their aims to better understand the impact/activity of different p53 is-forms, and their data well support their statements. Indeed, the major strengths of the paper lie in its comprehensive characterization of different p53 isoforms and the different assays that are measured. Notably, this includes p53 transcriptional activity, protein degradation, induction of the chaperone machinery, and hetero-oligomerization with wtp53. This will provide a valuable dataset where p53 researchers can evaluate the biological impact of different isoforms in different cell lines. The authors went to great lengths to control and test for the effect of (1) p53 expression level, (2) promotor type, and (3) cell type. I applaud their careful experiments in this regard.

Comments on revised version:

The authors have addressed all of my concerns convincingly, including with a new mass spectrometry experiment to quantify p53 peptides specifically.

Reviewer #1 (Public review):

Batra, Cabrera and Spence et al. present a model which integrates histone posttranslational modification (PTM) data across cell models to predict gene expression with the goal of using this model to better understand epigenetic editing. This gene expression prediction model approach is useful if a) it predicts gene expression in specific cell lines b) it predicts expression values rather than a rank or bin, c) if it helps us to better understand the biology of gene expression or d) it helps us to understand epigenome editing activity. Problematically for points a) and b) it is easier to directly measure gene expression than to measure multiple PTMs and so the real usefulness of this approach mostly relates to c) and d).

Other approaches have been published that use histone PTM to predict expression (e.g. PMID 27587684, 36588793). Is this model better in some way? No comparisons are made, although a claim is made that direct comparisons are difficult. I appreciate that the authors have not used the histone PTM data to predict gene expression levels of an "average cell" but rather that they are predicting expression within specific cell types or for unseen cell types. Approaches that predict expression levels are much more useful, whereas some previous approaches have only predicted expressed or not expressed or a rank order or bin-based ranking. The paper does not seem to have substantial novel insights into understanding the biology of gene expression.

The approach of using this model to predict epigenetic editor activity on transcription is interesting and to my knowledge novel although only examined in the context of a p300 editor. As the author point out the interpretation of the epigenetic editing data is convoluted by things like sgRNA activity scoring and to fully understand the results likely would require histone PTM profiling and maybe dCas9 ChIP-seq for each sgRNA which would be a substantial amount of work.

Furthermore from the model evaluation of H3K9me3 is seems the model is performing modestly for other forms of epigenetic or transcriptional editing- e.g. we know for the best studied transcriptional editor which is CRISPRi (dCas9-KRAB) that recruitment to a locus is associated with robust gene repression across the genome and is associated with H3K9me3 deposition by recruitment of KAP1/HP1/SETDB1 (PMID: 35688146, 31980609, 27980086, 26501517).

One concern overall with this approach is that dCas9-p300 has been observed to induce sgRNA independent off target H3K27Ac (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349887/ see Figure S5D) which could convolute interpretation of this type of experiment for the model.

Comments on revisions: This resubmission adds a comparison to existing gene prediction methods, but add no new confirmation experiments with predicting epigenome editing efficiency and had only one minor text edit.

Reviewer #1 (Public review):

Summary:

In the present study, the authors examined the possibility of using phosphatidyl-inositol kinase 3-kinase alpha (PI3Ka) inhibitors for heterotopic ossification in fibrodysplasia ossificans progressiva. Administration of BYL719, a chemical inhibitor of PI3Ka, prevented heterotopic ossification in a mouse model of FOP that expressed a mutated ACVR1 receptor. Genetic ablation of PI3Ka also suppressed heterotopic ossification in mice. BYL719 blocked osteo/chondroprogenitor specification and reduced inflammatory responses by reducing the number of fibro-adipogenic progenitors (FAPs) and promoting muscle fibre regeneration in vivo. The authors claimed that inhibition of PI3Ka is a safe and effective therapeutic strategy for heterotopic ossification.

Strengths:

Taking together previous reports on the specificity of BY718 in PI3K, it was suggested that BYL719 inhibits heterotopic ossification by reducing FAPs and promoting muscle regeneration through the PI3K pathway in vivo.

Weaknesses:

In the original manuscript, there was the possibility that BYL719 inhibited heterotopic ossification through non-specific and toxic effects rather than the PI3k pathway.

However, the authors added new data and explanations in the revision to solve the possibility. The findings of the authors would be useful and would provide an additional direction to develop a therapeutic strategy for heterotopic ossification.

Reviewer #1 (Public review):

Summary:

In a previous work Prut and colleagues had shown that during reaching, high frequency stimulation of the cerebellar outputs resulted in reduced reach velocity. Moreover, they showed that the stimulation produced reaches that deviated from a straight line, with the shoulder and elbow movements becoming less coordinated. In this report they extend their previous work by addition of modeling results that investigate the relationship between the kinematic changes and torques produced at the joints. The results show that the slowing is not due to reductions in interaction torques alone, as the reductions in velocity occur even for movements that are single joint. More interestingly, the experiment revealed evidence for decomposition of the reaching movement, as well as an increase in the variance of the trajectory.

Strengths:

This is a rare experiment in a non-human primate that assessed the importance of cerebellar input to the motor cortex during reaching.

Weaknesses:

None

Reviewer #2 (Public review):

Summary:

The study characterized the dependence of spike timing-dependent long-term depression (tLTD) on presynaptic NMDA receptors and the intracellular cascade after NMDAR activation possibly involved in the observed decrease in glutamate probability release at L5-L5 synapses of the visual cortex in mouse brain slices.

Strengths:

The genetic and electrophysiological experiments are thorough. The experiments are well reported and mainly support the conclusions. This study confirms and extends current knowledge by elucidating additional plasticity mechanisms at cortical synapses, complementing existing literature.

Weaknesses:

No direct testing for ions passing trough standard NMDAR, mainly sodium and calcium is shown.

Reviewer #1 (Public review):

Summary:

The paper by Graff et al. investigates the function of foxf2 in zebrafish to understand the progression of cerebral small vessel disease. The authors use a partial loss of foxf2 (zebrafish possess two foxf2 genes, foxf2a and foxf2b, and the authors mainly analyze homozygous mutants in foxf2a) to investigate the role of foxf2 signaling in regulating pericyte biology. They find that the number of pericytes is reduced in foxf2a mutants and that the remaining pericytes display alterations in their morphologies. The authors further find that mutant animals can develop to adulthood, but that in adult animals, both endothelial and pericyte morphologies are affected. They also show that mutant pericytes can partially repopulate the brain after genetic ablation.

Strengths:

The paper is well written and easy to follow.

Weaknesses:

The results are mainly descriptive, and it is not clear how they will advance the field at their current state, given that a publication on mice has already examined the loss of foxf2 phenotype on pericyte biology (Reyahi, 2015, Dev. Cell).

(1) Reyahi et al. showed that loss of foxf2 in mice leads to a marked downregulation of pdgfrb expression in perivascular cells. In contrast to expectation, perivascular cell numbers were higher in mutant animals, but these cells did not differentiate properly. The authors use a transgenic driver line expressing gal4 under the control of the pdgfrb promoter and observe a reduction in pericyte (pdgfrb-expressing) cells in foxf2a mutants. In light of the mouse data, this result might be due to a similar downregulation of pdgfrb expression in fish, which would lead to a downregulation of gal4 expression and hence reduced labelling of pericytes. The authors show a reduction of pdgfrb expression also in zebrafish in foxf2b mutants (Chauhan et al., The Lancet Neurology 2016). It would be important to clarify whether, also in zebrafish, foxf2a/foxf2b mutants have reduced or augmented numbers of perivascular cells and how this compares to the data in the mouse. The authors should perform additional characterization of perivascular cells using marker gene expression (for a list of markers, see e.g., Shih et al. Development 2021) and/or genetic lineage tracing.

(2) The authors motivate using foxf2a mutants as a model of reduced foxf2 dosage, "similar to human heterozygous loss of FOXF2". However, it is not clear how the different foxf2 genes in zebrafish interact with each other transcriptionally. Is there upregulation of foxf2b in foxf2a mutants and vice versa? This is important to consider, as Reyahi et al. showed that foxf2 gene dosage in mice appears to be important, with an increase in foxf2 gene dosage (through transgene expression) leading to a reduction in perivascular cell numbers.

(3) Figures 3 and 4 lack data quantification. The authors describe the existence of vascular defects in adult fish, but no quantifiable parameters or quantifications are provided. This needs to be added.

(4) The analysis of pericyte phenotypes and morphologies is not clear. On page 6, the authors state: "In the wildtype brain, adult pericytes have a clear oblong cell body with long, slender primary processes that extend from the cytoplasm with secondary processes that wrap around the circumference of the blood vessel." Further down on the same page, the authors note: "In wildtype adult brains, we identified three subtypes of pericytes, ensheathing, mesh and thin-strand, previously characterized in murine models." In conclusion, not all pericytes have long, slender primary processes, but there are at least three different sub-types? Did the authors analyze how they might be distributed along different branch orders of the vasculature, as they are in the mouse? Which type of pericyte is affected in foxf2a mutant animals? Can the authors identify the branch order of the vasculature for both wildtype and mutant animals and compare which subtype of pericyte might be most affected? Are all subtypes of pericytes similarly affected in mutant animals? There also seems to be a reduction in smooth muscle cell coverage.

(5) Regarding pericyte regeneration data (Figure 7): Are the values in Figure 7D not significantly different from each other (no significance given)?

(6) In the discussion, the authors state that "pericyte processes have not been studied in zebrafish". Ando et al. (Development 2016) studied pericyte processes in early zebrafish embryos, and Leonard et al. (Development 2022) studied zebrafish pericytes and their processes in the developing fin.

Reviewer #1 (Public review):

In this manuscript, Pagano and colleagues test the idea that the protein GMCL1 functions as a substrate receptor for a Cullin RING 3 E3 ubiquitin ligase (CUL3) complex. Using a pulldown approach, they identify GMCL1 binding proteins, including the DNA damage scaffolding protein 53BP1. They then focus on the idea that GMCL1 recruits 53BP1 for CUL3-dependent ubiquitination, triggering subsequent proteasomal degradation of ubiquitinated 53BP1.

In addition to its DNA damage signalling function, in mitosis, 53BP1 is reported to form a stopwatch complex with the deubiquitinating enzyme USP28 and the transcription factor p53 (PMID: 38547292). These 53BP1-stopwatch complexes generated in mitosis are inherited by G1 daughter cells and help promote p53-dependent cell cycle arrest independent from DNA damage (PMID: 38547292). Several studies show that knockout of 53BP1 overcomes G1 cell cycle arrest after mitotic delays caused by anti-mitotic drugs or centrosome ablation (PMID: 27432897, 27432896). In this model, it is crucial that 53BP1 remains stable in mitosis and more stopwatch complex is formed after delayed mitosis.

Pagano and coworkers suggest that 53BP1 levels can sometimes be suppressed in mitosis if the cells overexpress GMCL1. They carry out a bioinformatic analysis of available public data for p53 wild-type cancer cell lines resistant to the anti-mitotic drug paclitaxel and related compounds. Stratifying GMCL1 into low and high expression groups reveals a weak (p = 0.05 or ns) correlation with sensitivity to taxanes. It is unclear on what basis the authors claim paclitaxel-resistant and p53 wild-type cancer cell lines bypass the mitotic surveillance/timer pathway. They have not tested this. Figure 3 is a correlation assembled from public databases but has no experimental tests. Figure 4 looks at proliferation but not cell cycle progression or the length of mitosis. The main conclusions relating to cell cycle progression and specifically the link to mitotic delays are therefore not supported by experimental data. There is no imaging of the cell cycle or cell fate after mitotic delays, or analysis of where the cells arrest in the cell cycle. Most of the cell lines used have been reported to lack a functional mitotic surveillance pathway in the recent work by Meitinger. To support these conclusions, the stability of endogenous 53BP1 under different conditions in cells known to have a functional mitotic surveillance pathway needs to be examined. A key suggestion in the work is that the level of GMCL1 expression correlates with resistance to taxanes. For the mitotic surveillance pathway, the type of drug (nocodazole, taxol, etc) used to induce a delay isn't thought to be relevant, only the length of the delay. Do GMCL1-overexpressing cells show resistance to anti-mitotics in general?

Importantly, if GMCL1 specifically degrades 53BP1 during prolonged mitotic arrests, the authors should show what happens during normal cell divisions without any delays or drug treatments. How much 53BP1 is destroyed in mitosis under those conditions? Does 53BP1 destruction depend on the length of mitosis, drug treatment, or does 53BP1 get degraded every mitosis regardless of length? Testing the contribution of key mitotic E3 ligase activities on mitotic 53BP1 stability, such as the anaphase-promoting complex/cyclosome (APC/C) is important in this regard. One previous study reported an analysis of putative APC/C KEN-box degron motifs in 53BP1 and concluded these play a role in 53BP1 stability in anaphase (PMID: 28228263).

There is no direct test of the proposed mechanism, and it is therefore unclear if 53BP1 is ubiquitinated by a GMCL1-CUL3 ligase in cells, and how efficient this process would be at different cell cycle stages. A key issue is the lack of experimental data explaining why the proposed mechanism would be restricted to mitosis. Indirect effects, such as loss of 53BP1 from the chromatin fraction during M phase upon GMCL1 overexpression, do not necessarily mean that 53BP1 is degraded. PLK1-dependent chromatin-cytoplasmic shuttling of 53BP1 during mitotic delays has been described previously (PMID: 38547292, 37888778). These papers are cited in the text, but the main conclusions of those papers on 53BP1 incorporation into a stopwatch complex during mitotic delays have been ignored. Are the authors sure that 53BP1 is destroyed in mitosis and not simply re-localised between chromatin and non-chromatin fractions? At the very least, these reported findings should be discussed in the text.

The authors use a variety of cancer cell line models throughout their study, most of which have been reported to lack a functional mitotic surveillance pathway. U2OS and HCT116 cells do not respond normally to mitotic delays, despite being annotated as p53 WT. Other studies have used p53 wild-type hTERT RPE-1 cells to study the mitotic surveillance pathway. If the model is correct, then over-expressing GMCL1 in hTERT-RPE1 cells should suppress cell cycle arrest after mitotic delays, and GMCL1 KO should make the cells more sensitive to delays. These experiments are needed to provide an adequate test of the proposed model.

To conclude, while the authors propose a potentially interesting model on how GMCL1 overexpression could regulate 53BP1 stability to limit p53-dependent cell cycle arrest, it is unclear what triggers this pathway or when it is relevant. 53BP1 is known to function in DNA damage signalling, and GMCL1 might be relevant in that context. The manuscript contains the initial description of GMCL1-53BP1 interaction but lacks a proper analysis of the function of this interaction and is therefore a preliminary report.

Reviewer #1 (Public review):

Strengths:

Sarpaning et al. provide a thorough characterization of putative Rnt1 cleavage of mRNA in S. cerevisiae. Previous studies have discovered Rnt1 mRNA substrates anecdotally, and this global characterization expands the known collection of putative Rnt1 cleavage sites. The study is comprehensive, with several types of controls to show that Rnt1 is required for several of these cleavages.

Weaknesses:

Formally speaking, the authors do not show a direct role of Rnt1 in mRNA cleavage - no studies were done (e.g., CLIP-seq or similar) to define direct binding sites. Is the mutant Rnt1 expected to trap substrates? Without direct binding studies, the authors rely on genetics and structure predictions for their argument, and it remains possible that a subset of these sites is an indirect consequence of rnt1. This aspect should be addressed in the discussion.

The comprehensive list of putative Rnt1 mRNA cleavage sites is interesting insofar as it expands the repertoire of Rnt1 on mRNAs, but the functional relevance of the majority of these sites remains unknown. Along these lines, the authors should present a more thorough characterization of putative Rnt1 sites recovered from in vitro Rnt1 cleavage.

The authors need to corroborate the rRNA 3'-ETS tetraloop mutations with a northern analysis of 3'-ETS processing to confirm an ETS processing defect (which might need to be done in decay mutants to stabilize the liberated ETS fragment). They state that the tetraloop mutation does not yield a growth defect and use this as the basis for concluding that rRNA cleavage is not the major role of Rnt1 in vivo, which is a surprising finding. But it remains possible that tetraloop mutations did not have the expected disruptive effect in vivo; if the ETS is processed normally in the presence of tetraloop mutations, it would undermine this interpretation. This needs to be more carefully examined.

To support the assertion that YDR514C cleavage is required for normal "homeostasis," and more specifically that it is the major contributor to the rnt1∆ growth defect, the authors should express the YDR514C-G220S mutant in the rDNA∆ strains with mutations in the 3'-ETS (assuming they disrupt ETS processing, see above). This simple experiment should provide a relative sense of "importance" for one or the other cleavage being responsible for the rnt1∆ defect. Given the accepted role of Rnt1 cleavage in rRNA processing and a dogmatic view that this is the reason for the rnt1∆ growth defect, such a result would be surprising and elevate the functional relevance and significance of Rnt1 mRNA cleavage.

Given that some Rnt1 mRNA cleavage is likely nuclear, it is possible that some of these targets are nascent mRNA transcripts, as opposed to mature but unexported mRNA transcripts, as proposed in the manuscript. A role for Rnt1 in co-transcriptional mRNA cleavage would be conceptually similar to Rnt1 cleavage of the rRNA 3'-ETS to enable RNA Pol I "torpedo" termination by Rat1, described by Proudfoot et al (PMID 20972219). To further delineate this point, the authors could e.g., examine the poly-A tails on abundant Rnt1 targets to establish whether they are mature, polyadenylated mRNAs (e.g., northern analysis of oligo-dT purified material). A more direct test would be PARE analysis of oligo-dT enriched or depleted material to determine the poly-A status of the cleavage products. Alternatively, their association with chromatin could be examined.

While laboratory strains of budding yeast have a single RNase III ortholog Rnt1, several other budding yeast have a functional RNAi system with Dcr and Ago (PMID 19745116), and laboratory yeast strains are a derived state due to pressure from the killer virus to lose the RNAi system (PMID 21921191). The current study could provide new insight into the relative substrate preferences of Rnt1 and budding yeast Dicer, which could be experimentally confirmed by expressing Dcr in RNT1 and rnt1∆ strains. In lieu of experiments, discussion of the relevance of Rnt1 cleavage compared to yeast RNAi should be included in the discussion before the "human implications" section.

For SNR84 in Figure S3D, it appears that the TSS may be upstream of the annotated gene model. Does RNA-seq coverage (from external datasets) extend upstream to these additional mapped cleavages? The assertion that the mRNA is uncapped is concerning; an alternative explanation is that the nascent mRNA has a cap initially but is subsequently cleaved by Rnt1. This point should be clarified or reworded for accuracy.

Reviewer #1 (Public review):

Summary:

Genome-wide association studies have been an important approach to identifying the genetic basis of human traits and diseases. Despite their successes, for many traits, a substantial amount of variation cannot be explained by genetic factors, indicating that environmental variation and individual 'noise' (stochastic differences as well as unaccounted for environmental variation) also play important roles. The authors' goal was to address whether gene expression variation in genetically identical individuals, driven by historical environmental differences and 'noise', could be used to predict reproductive trait differences.

Strengths:

To address this question, the authors took advantage of genetically identical C. elegans individuals to transcriptionally profile 180 adult hermaphrodite individuals that were also measured for two reproductive traits. A major strength of the paper is its experimental design. While experimenters aim to control the environment that each worm experiences, it is known that there are small differences that each worm experiences even when they are grown together on the same agar plate - e.g. the age of their mother, their temperature, the amount of food they eat, and the oxygen and carbon dioxide levels depending on where they roam on the plate. Instead of neglecting this unknown variation, the authors design the experiment up front to create two differences in the historical environment experienced by each worm: 1) the age of its mother and 2) 8 8-hour temperature difference, either 20 or 25 {degree sign}C. This helped the authors interpret the gene expression differences and trait expression differences that they observed.

Using two statistical models, the authors measured the association of gene expression for 8824 genes with the two reproductive traits, considering both the level of expression and the historical environment experienced by each worm. Their data supports several conclusions. They convincingly show that gene expression differences are useful for predicting reproductive trait differences, predicting ~25-50% of the trait differences depending on the trait. Using RNAi, they also show that the genes they identify play a causal role in trait differences. Finally, they demonstrate an association with trait variation and the H3K27 trimethylation mark, suggesting that chromatin structure can be an important causal determinant of gene expression and trait variation.

Overall, this work supports the use of gene expression data as an important intermediate for understanding complex traits. This approach is also useful as a starting point for other labs in studying their trait of interest.

Weaknesses:

There are no major weaknesses that I have noted. Some important limitations of the work (that I believe the authors would agree with) are worth highlighting, however:

(1) A large remaining question in the field of complex traits remains in splitting the role of non-genetic factors between environmental variation and stochastic noise. It is still an open question which role each of these factors plays in controlling the gene expression differences they measured between the individual worms.

(2) The ability of the authors to use gene expression to predict trait variation was strikingly different between the two traits they measured. For the early brood trait, 448 genes were statistically linked to the trait difference, while for egg-laying onset, only 11 genes were found. Similarly, the total R2 in the test set was ~50% vs. 25%. It is unclear why the differences occur, but this somewhat limits the generalizability of this approach to other traits.

(3) For technical reasons, this approach was limited to whole worm transcription. The role of tissue and cell-type expression differences is important to the field, so this limitation is important.

Reviewer #1 (Public review):

Summary:

Even though mutations in LRRK2 and GBA1 (which encodes the protein GCase) increase the risk of developing Parkinson's disease (PD), the specific mechanisms driving neurodegeneration remain unclear. Given their known roles in lysosomal function, the authors investigate how LRRK2 and GCase activity influence the exocytosis of the lysosomal lipid BMP via extracellular vesicles (EVs). They use fibroblasts carrying the PD-associated LRRK2-R1441G mutation and pharmacologically modulate LRRK2 and GCase activity.

Strengths:

The authors examine both proteins at endogenous levels, using MEFs instead of cancer cells. The study's scope is potentially interesting and could yield relevant insights into PD disease mechanisms.

Weaknesses:

Many of the authors' conclusions are overstated and not sufficiently supported by the data. Several statistical errors undermine their claims. Pharmacological treatment is very long, leading to potential off-target effects. Additionally, the authors should be more rigorous when using EV markers.

Reviewer #1 (Public review):

Summary:

This paper seeks to understand the upstream regulation and downstream effectors of glycolysis in retinal progenitor cells, using mouse retinal explants as the main model system. The paper presents evidence that high glycolysis in retinal progenitor cells is required for their proliferation and timely differentiation into photoreceptors. Retinal glycolysis increases after deletion of Pten. The authors suggest that high glycolysis controls cell proliferation and differentiation by promoting intracellular alkalinization, beta-catenin acetylation and stabilization and consequent activation of the canonical Wnt pathway.

Strengths:

- The experiments showing that PFKFB3 overexpression is sufficient to increase proliferation of retinal progenitors (which are already highly dividing cells) and photoreceptor differentiation are striking and the result unanticipated. It suggests that glycolytic flux is normally limiting for proliferation in embryos.<br /> - Likewise the result that an increase in pH from 7.4 to 8.0 is sufficient to increase proliferation implies that pH regulation may have instructive roles in setting the tempo of retinal development and embryonic cell proliferation. Similarly for the results showing that acetate supplementation increases proliferation (I think this result should be moved to the main figures).

Weaknesses:

- Epistatic experiments to test if changes in pH mediate the effects of glycolysis on photoreceptor differentiation, or if Wnt activation is the main downstream effector of glycolysis in controlling differentiation are not presented.<br /> - It is likely that metabolism changes ex vivo vs in vivo, and therefore stable isotope tracing experiments in the explants may not reflect in vivo metabolism.<br /> - The retina at P0 is composed of both progenitors and differentiated cells. It is not clear if the results of the RNA-seq and metabolic analysis reflect changes in the metabolism of progenitors, or of mature cells, or changes in cell type composition rather than direct metabolic changes in a specific cell type.<br /> - The biochemical links between elevated glycolysis and pH and beta-catenin stability are unclear. White et al found that higher pH decreased beta-catenin stability (JCB 217: 3965) in contrast to the results here. Oginuma et al found that inhibition of glycolysis or beta-catenin acetylation does not affect beta-catenin stability (Nature 584:98), again in contrast to these results. Another paper showed that acidification inhibits Wnt signaling by promoting the expression of a transcriptional repressor and not via beta-catenin stability (Cell Discovery 4:37). There are also additional papers showing increased pH can promote cell proliferation via other mechanisms (e.g. Nat Metab 2:1212). It is possible that there is organ-specificity in these signaling pathways however some clarification of these divergent results is warranted.<br /> - The gene expression analysis is not completely convincing. E.g. expression of additional glycolytic genes should be shown in Fig. 1. It is not clear why Hk1 and Pgk1 are specifically shown, and conclusions about changes in glycolysis are difficult to draw from expression of these two genes. The increase in glycolytic gene expression in the Pten-deficient retina is generally small.<br /> - Is it possible that glycolytic inhibition with 2DG slows down development and production of most new differentiated cells rather than specifically affecting photoreceptor differentiation?<br /> - Are the prematurely-born cells caused by PFKFB3 overexpression photoreceptors as assessed by morphology or markers (in addition to position)?

Reviewer #1 (Public review):

Summary:

The paper describes the cryoEM structure of RAD51 filament on the recombination intermediate. In the RAD51 filament, the insertion of a DNA-binding loop called the L2 loop stabilizes the separation of the complementary strand for the base-pairing with an incoming ssDNA and the non-complementary strand, which is captured by the second DNA-binding channel called the site II. The molecular structure of the RAD51 filament with a recombination intermediate provides a new insight into the mechanism of homology search and strand exchange between ssDNA and dsDNA.

Strengths:

This is the first human RAD51 filament structure with a recombination intermediate called the D-loop. The work has been done with great care, and the results shown in the paper are compelling based on cryo-EM and biochemical analyses. The paper is really nice and important for researchers in the field of homologous recombination, which gives a new view on the molecular mechanism of RAD51-mediated homology search and strand exchange.

Weaknesses:

The authors need more careful text writing. Without page and line numbers, it is hard to give comments.

Reviewer #1 (Public review):

Summary:

This work contributes several important and interesting observations regarding the heterotolerance of non-growing Escherichia coli and Pseudomonas aeruginosa to the antimicrobial peptide tachyplesin. The primary mechanism of action of tachyplesin is thought to be disruption of the bacterial cell envelope, leading to leakage of cellular contents after a threshold level of accumulation. Although the MIC for tachyplesin in exponentially growing E. coli is just 1 ug/ml, the authors observe that a substantial fraction of a stationary phase population of bacteria survives much higher concentrations, up to 64 ug/ml. By using a fluorescently labelled analogue of tachyplesin, the authors show that the amount of per-cell intracellular accumulation of tachyplesin displays a bimodal distribution, and that the fraction of "low accumulators" correlates with the fraction of survivors. Using a microfluidic device, they show that low accumulators exclude propidium iodide, suggesting that their cell envelopes remain largely intact, while high accumulators of tachyplesin also stain with propidium iodide. They show that this phenomenon holds for several clinical isolates of E. coli with different genetic determinants of antibiotic resistance, and for a strain of Pseudomonas aeruginosa. However, the bimodal distribution does not occur in these organisms for several other antimicrobial peptides, or for tachyplesin in Klebsiella pneumoniae or Staphylococcus aureus, indicating some degree of specificity in the interaction between AMP and bacterial cell envelope. They next explore the dynamics of the fluorescent tachyplesin accumulation and show interestingly that a high degree of accumulation is initially seen in all cells, but that the "low accumulator" subpopulation manages to decrease the amount of intracellular fluorescence over time, while the "high accumulator"subpopulation continues to increase its intracellular fluorescence. Focusing on increased efflux as a hypothesised mechanism for the "low accumulator" phenotype, based on transcriptomic analysis of the two subpopulations, the authors screen putative efflux inhibitors to see if they can block the formation of the low accumulator subpopulation. They find that both the protonophore CCCP and the SSRI sertraline can block the formation of this subpopulation and that a combination of sertraline plus tachyplesin kills a greater fraction of the stationary phase cells than either agent alone, similar to the killing observed when growing cells are treated with tachyplesin.

Strengths:

This study provides new insight into the heterogeneous behaviours of non-growing bacteria when exposed to an antimicrobial peptide, and into the dynamics of their response. The single-cell analysis by FACS and microscopy is compelling. The results provide a much-needed single cell perspective on the phenomenon of tolerance to AMPs and a good starting point for further exploration.

Weaknesses:

The authors have substantially improved the clarity of the manuscript and have added additional experiments to probe further the location of the AMP relative to low and high accumulators, and the physiological states of these sub-populations. These experiments strengthen the assertion that low accumulators keep the AMP at the cell surface while high accumulators permit intracellular access to the AMP.

However, many questions still remain about the physiological characterisation of the "low accumulator" cells. While the evidence presented does support an induced response that removes the AMP from the interior of the cell, no clear mechanism for this is favoured by the experiments presented.

A double deletion of acrA and tolC (two out of the three components of the major constitutive RND efflux pump) reduces the appearance of the low accumulator phenotype, but interestingly, the single deletions have no effect, and a well-characterised inhibitor of RND efflux pumps also has no effect. The authors identify a two-component system, qseCB, that appears necessary for the appearance of low accumulators, but this system has pleiotropic effects on many cellular systems, with only tenuous connections to efflux. The selected pharmacological agents that could prevent the appearance of low accumulators do not offer clear insight into the mechanism by which low accumulators arise, because they have diverse modes of action.

The transcriptomics data collected for low and high accumulator sub-populations are interesting, but in my opinion, the conclusions that can be drawn from these data remain overstated. It is not possible to make any claims about the total amount of "protein synthesis, energy production, and gene expression" on the basis of RNA-Seq data. The reads from each sample are normalised, so there is no information about the total amount of transcript. Many elements of total cellular activity are post-transcriptionally regulated, so it is impossible to assess from transcriptomics alone. Finally, the transcriptomic data are analysed in aggregated clusters of genes that are enriched for biological processes, for example: "Cluster 2 included processes involved in protein synthesis, energy production, and gene expression that were downregulated to a greater extent in low accumulators than high accumulators". However, this obscures the fact that these clusters include genes that are generally inhibitory of the process named, as well as genes that facilitate the process.

The authors have added an experiment to attempt to assess overall metabolic activity in the low accumulator and high accumulator populations, which is a welcome addition. They apply the redox dye resazurin and observe lower resorufin (reduced form) fluorescence in the low accumulator population, which they take to indicate a lower respiration rate. This seems possible, however, an important caveat is that they have shown the low accumulator population to retain substantially lower amounts of multiple different fluorescent molecules (tachyplesin-NBD, propidium iodide, ethidium bromide) intracellularly compared to the high accumulator population. It seems possible that the low accumulator population is also capable of removing resazurin or resorufin from the intracellular space, regardless of metabolic rate. Indeed, it has previously been shown that efflux by RND efflux pumps influences resazurin reduction to resorufin in both P. aeruginosa and E. coli. By measuring only the retained redox dye using flow cytometry, the results may be confounded by the demonstrated ability of the low accumulator population to remove various fluorescent dyes. More work is needed to strongly support broad conclusions about the physiological states of the low and high accumulator populations.

The phenomenon of the emergence of low accumulators, which are phenotypically tolerant to the antimicrobial peptide tachyplesin, is interesting and important even if there is still work to be done to understand the mechanism by which it occurs.

Reviewer #1 (Public review):

Summary:

This is a very well-written paper presenting interesting findings related to the recovery following the end-Permian event in continental settings, from N China. The finding is timely as the topic is actively discussed in the scientific community. The data provides additional insights into the faunal, and partly, floral global recovery following the EPE, adding to the global picture.

Strengths:

The conclusions are supported by an impressive amount of sedimentological and paleontological data (mainly trace fossils) and illustrations.

Reviewer #1 (Public review):

Summary:

The authors found that IL-1b signaling is pivotal for hypoxemia development and can modulate NETs formation in LPS+HVV ALI model.

Strengths:

They used IL1R1 ko mice and proved that IL1R1 is involved in ALI model proving that IL1b signalling leads towards ARDS. In addition, hypothermia reduces this effect, suggesting a therapeutic option.

Comments on revised version:

The authors have addressed this Reviewer's concerns. The manuscript is much stronger in the current form and can be published.

Reviewer #1 (Public review):

Summary:

The manuscript presents a significant and rigorous investigation into the role of CHMP5 in regulating bone formation and cellular senescence. The study provides compelling evidence that CHMP5 is essential for maintaining endolysosomal function and controlling mitochondrial ROS levels, thereby preventing the senescence of skeletal progenitor cells.

Strengths:

The authors demonstrate that the deletion of Chmp5 results in endolysosomal dysfunction, elevated mitochondrial ROS, and ultimately enhanced bone formation through both autonomous and paracrine mechanisms. The innovative use of senolytic drugs to ameliorate musculoskeletal abnormalities in Chmp5-deficient mice is a novel and critical finding, suggesting potential therapeutic strategies for musculoskeletal disorders linked to endolysosomal dysfunction.

Comments on the latest version:

My concerns were addressed.

Reviewer #1 (Public review):

Summary:

Ferreiro et al. present a method to simulate protein sequence evolution under a birth-death model where sequence evolution is constrained by structural constraints on protein stability. The authors then use this model to explore the predictability of sequence evolution in several viral structural proteins. In principle, this work is of great interest to molecular evolution and phylodynamics, which have struggled to couple non-neutral models of sequence evolution to phylodynamic models like birth-death. Unfortunately, though, the model shows little improvement over neutral models in predicting protein evolution, and this ultimately appears to be due to fundamental conceptual problems with how fitness is modeled and linked to the phylodynamic birth-death model.

Major concerns:

(1) Fitness model: All lineages have the same growth rate r = b-d because the authors assume b+d=1. But under a birth-death model, the growth r is equivalent to fitness, so this is essentially assuming all lineages have the same absolute fitness since increases in reproductive fitness (b) will simply trade off with decreases in survival (d). Thus, even if the SCS model constrains sequence evolution, the birth-death model does not really allow for non-neutral evolution such that mutations can feed back and alter the structure of the phylogeny.

(2) Predictive performance: Similar performance in predicting amino acid frequencies is observed under both the SCS model and the neutral model. I suspect that this rather disappointing result owes to the fact that the absolute fitness of different viral variants could not actually change during the simulations (see comment #1).

(3) Model assessment: It would be interesting to know how much the predictions were informed by the structurally constrained sequence evolution model versus the birth-death model. To explore this, the authors could consider three different models: 1) neutral, 2) SCS, and 3) SCS + BD. Simulations under the SCS model could be performed by simulating molecular evolution along just one hypothetical lineage. Seeing if the SCS + BD model improves over the SCS model alone would be another way of testing whether mutations could actually impact the evolutionary dynamics of lineages in the phylogeny.

(4) Background fitness effects: The model ignores background genetic variation in fitness. I think this is particularly important as the fitness effects of mutations in any one protein may be overshadowed by the fitness effects of mutations elsewhere in the genome. The model also ignores background changes in fitness due to the environment, but I acknowledge that might be beyond the scope of the current work.

(5) In contrast to the model explored here, recent work on multi-type birth-death processes has considered models where lineages have type-specific birth and/or death rates and therefore also type-specific growth rates and fitness (Stadler and Bonhoeffer, 2013; Kunhert et al., 2017; Barido-Sottani, 2023). Rasmussen & Stadler (eLife, 2019) even consider a multi-type birth-death model where the fitness effects of multiple mutations in a protein or viral genome collectively determine the overall fitness of a lineage. The key difference with this work presented here is that these models allow lineages to have different growth rates and fitness, so these models truly allow for non-neutral evolutionary dynamics. It would appear the authors might need to adopt a similar approach to successfully predict protein evolution.

Reviewer #1 (Public review):

Summary:

In this study, Ledamoisel et al. examined the evolution of visual and chemical signals in closely related Morpho butterfly species to understand their role in species coexistence. Using an integrative, state-of-the-art approach combining spectrophotometry, visual modeling, and behavioral mate choice experiments, they quantified differences in wing iridescence and assessed its influence on mate preference in allopatry and sympatry. They also performed chemical analyses to determine whether sympatric species exhibit divergent chemical cues that may facilitate species recognition and mate discrimination. The authors found iridescent coloration to be similar in sympatric Morpho species. Furthermore, male mate choice experiments revealed that in sympatry, males fail to discriminate conspecific females based on coloration, reinforcing the idea that visual signal convergence is primarily driven by predation pressure. In contrast, the divergence of chemical signals among sympatric species suggests their potential role in facilitating species recognition and mate discrimination. The authors conclude that interactions between ecological pressures and signal evolution may shape species coexistence.

Strengths:

The study is well-designed and integrates multiple methodological approaches to provide a thorough assessment of signal evolution in the studied species. I appreciate the authors' careful consideration of multiple selective pressures and their combined influence on signal divergence and convergence. Additionally, the inclusion of both visual and chemical signals adds an interesting and valuable dimension to the study, enhancing its importance. Beyond butterflies, this research broadens our understanding of multimodal communication and signal evolution in the context of species coexistence.

Weaknesses:

(1) The broader significance of the findings needs to be better articulated. While the authors emphasize that comparing adaptive traits in sympatry and allopatry provides insights into selective processes shaping reproductive isolation and coexistence, it is unclear what key conceptual or theoretical questions are being addressed. Are these patterns expected under certain evolutionary scenarios? Have they been empirically demonstrated in other systems? The authors should explicitly state the overarching research question, incorporate some predictions, and better contextualize their findings within the existing literature. If the results challenge or support previous work, that should be highlighted to strengthen the study's importance in a broader context.

(2) The motivation for studying visual signals and mate choice in allopatric populations (i.e., at the intraspecific level) is not well articulated, leaving their role in the broader narrative unclear. In particular, the rationale behind experiments 1, 2, and 3 is not well defined, as the authors have not made a strong case for the need for these intraspecific comparisons in the introduction. This issue is further compounded by the authors' primary focus on signal evolution in sympatry throughout both the results and the discussion. For instance, the divergence of iridescence in allopatry is a potentially interesting result. But the authors have not discussed its implications.

Overall, given that the primary conclusions are based on results and analyses in sympatry, the role of allopatric populations in shaping these conclusions needs to be better integrated and justified. Without a stronger link between the comparative framework and the study's key takeaways, the use of allopatric populations feels somewhat peripheral rather than central to the study's aim. Since the primary conclusions remain valid even without the allopatric comparisons, their inclusion requires a clearer rationale.

(3) While the authors demonstrate that iridescence is indistinguishable to predators in sympatry, they overstate the role of predation in driving convergence. The present study does not experimentally demonstrate that iridescence in this species has a confusion effect or contributes to evasive mimicry. Alternatively, convergence could result from other selective forces, such as signal efficacy due to environmental conditions, rather than being solely driven by predation.

Reviewer #1 (Public review):

Summary:

In this work, the authors have developed SPLASH+, a micro-assembly and biological interpretation framework that expands on their previously published reference-free statistical approach (SPLASH) for sequencing data analysis.

Strengths:

(1) The methodology developed by the authors seems like a promising approach to overcome many of the challenges posed by reference-based single-cell RNA-seq analysis methods.

(2) The analysis of the RNU6 repetitive small nuclear RNA provides a very compelling example of a type of transcript that is very challenging to analyze with standard reference-based methods (e.g., most reads from this gene fail to align with STAR, if I understood the result correctly).

Weaknesses:

(1) The manuscript presents a number of case studies from very diverse domains of single-cell RNA-seq analysis. As a result, the manuscript has been challenging to review, because it requires domain expertise in centromere biology, RNA splicing, RNA editing, V(D)J transcript diversity, and repeat polymorphisms.

(2) Although the paper focuses on SmartSeq2 full-length single-cell RNA-seq data analysis, the vast majority of single-cell RNA-seq data that is currently being generated comes from droplet-based methods (e.g., 10x Genomics) that sequence only the 3' or 5' ends of transcripts. As a result, it is unclear if SPLASH+ is also applicable to these types of data.

(3) The criteria used for the selection of the 10 'core genes' have not been sufficiently justified.

(4) It is currently unclear how the splicing diversity discovered in this paper relates to the concept of noisy splicing (i.e., there are likely many low-frequency transcripts and splice junctions that are unlikely to have a significant functional impact beyond triggering nonsense-mediated decay).

(5) The paper presents only a very superficial discussion of the potential weaknesses of the SPLASH+ method.

(6) The cursory mention of metatranscriptome in the conclusion of the paper is confusing, as it might suggest the presence of microbial cells in sterile human tissues (which has recently been discredited in cancer, see e.g. https://www.science.org/content/article/journal-retracts-influential-cancer-microbiome-paper).

Reviewer #1 (Public review):

Nielsen et al have identified a new disease mechanism underlying hypoplastic left heart syndrome due to variants in ribosomal protein genes that lead to impaired cardiomyocyte proliferation. This detailed study starts with an elegant screen in stem-cell-derived cardiomyocytes and whole genome sequencing of human patients and extends to careful functional analysis of RP gene variants in fly and fish models. Striking phenotypic rescue is seen by modulating known regulators of proliferation, including the p53 and Hippo pathways. Additional experiments suggest that the cell type specificity of the variants in these ubiquitously expressed genes may result from genetic interactions with cardiac transcription factors. This work positions RPs as important regulators of cardiomyocyte proliferation and differentiation involved in the etiology of HLHS, although the downstream mechanisms are unclear.

Reviewer #1 (Public review):

Summary:

This manuscript assesses the differences between young and aged chondrocytes. Through transcriptomic analysis and further assessments in chondrocytes, GATA4 was found to be increased in aged chondrocyte donors compared to young donors. Subsequent mechanistic analysis with lentiviral vectors, siRNAs, and a small molecule was used to study the role of GATA4 in young and old chondrocytes. Lastly, an in vivo study was used to assess the effect of GATA4 expression on osteoarthritis progression in a DMM mouse model.

Strengths:

This work linked the overexpression of GATA4 to NF-kB signaling pathway activation, alterations to the TGF-b signaling pathway, and found that GATA4 increased the progression of OA compared to the DMM control group. This indicates that GATA4 contributes to the onset and progression of OA in aged individuals.

Weaknesses:

(1) A couple of sentences should be added to the introduction, to emphasize the role GATA4 plays, such as the alterations to the TGF-b signaling pathway and the increased activation of the NF-kB pathway.

(2) Figure 1F, the GATA4 histology image should be bigger.

(3) Further discussion should be conducted regarding the reasoning as to why GATA4 increases the phosphorylation of SMAD1/5.

(4) More information should be included to clarify why GATA4 is thought to be linked to DNA damage and the pathway that is associated with that.

(5) Please add further information regarding the limitations of the animal study conducted in this work and future plans to assess this.

(6) In Figure 5, GATA4 should be changed to Gata4 in the graphed portions for consistency.

Reviewer #1 (Public review):

Summary:

This foundational study builds on prior work from this group to reveal the complexities underlying ligand-dependent RXRγ-Nur77 heterodimer formation, offering a compelling re-evaluation of their earlier conclusions. The authors examine how a library of RXR ligands influences the biophysical, structural, and functional properties of Nur77. They find that although the Nur77-RXRγ heterodimer shares notable functional similarities with the Nurr1-RXRα complex, it also exhibits unique features, notably, both dimer dissociation and classical agonist-driven activities. This work advances our understanding of the nuanced behaviors of nuclear receptor heterodimers, which have important implications for health and disease.

Strengths:

(1) Builds on previous work by providing a comprehensive analysis that examines whether Nur77-RXRγ heterodimer formation parallels that of the Nurr1-RXRα complex.

(2) Systematic evaluation of a library of RXR ligands provides a broad survey of functional outputs.

(3) Careful reanalysis of previous work sheds new light on how NR4A heterodimers function.

Weaknesses:

(1) Some conclusions appear overstated or are not well substantiated by the work presented. It's unclear how the data support a non-classical mode of agonism, for example, based on the data shown.

(2) Some assays have relatively few replicates, with only two in some cases.

Reviewer #1 (Public review):

Summary:

In this study, the authors take a closer look at whether AID-mediated SHM occurs at stalled RNA polII complexes. Through experimental and bioinformatic overlaps, authors observe that AID target sites really do not overlap with RNA polII stalling, convergent transcription, or H3K27Ac marks. Rather, AID target sites just exist around transcription start sites. The authors thus bring up an important argument, that RNA poll II stalling is not the driving mechanism for AID targeting. This is important since research groups work with the assumption that transcription stalling drives AID access to single-strand DNA. The authors are also clarifying their previous studies, where they suggested that stalled Spt5-associated RNA polII recruits AID DNA deamination activity.

Comments:

Transcription start sites (TSS) of promoter genes. Most AID mutations occur at the first 500 pbs to 1 kb from the TSS of promoters or enhancers, but not in the rest of the transcription module or gene body. To this end, existing literature (including work done by the author(s)) has suggested that transcription stalling or pausing of elongating RNA polymerase and/or chromatin modifications such as H3K27Ac (markers of promoters and enhancers) have something to do with helping AID see single-strand DNA substrates for SHM. These conclusions, initially being drawn from AID's functional interaction with Spt5 and RNA exosome -two factors involved in the resolution of stalled RNA polII - and further supported through co-relative data of AID SHM sites overlapping S2-P RNA polII. As with genomics data, these observations were drawn through the bioinformatic window of overlap by the respective authors of the previously published studies.

In this study, the authors take a closer look at these overlaps and observe that AID target sites really do not overlap with RNA polII stalling, convergent transcription, or H3K27Ac marks. Rather, AID target sites just exist around transcription start sites that accumulate promoter-proximal terminated transcripts. The authors thus bring up an important argument, that RNA poll II stalling is not the driving mechanism for AID targeting. This is important since research groups work with the assumption that transcription stalling drives AID access to single-strand DNA.

The authors are clarifying the models and literature that they themselves had set earlier, and are doing this with quite detailed analyses, with some well-done experiments. I feel they need to be heard. The experiments are well done, and the text is well written. Since the study is associative (versus being directly mechanistic) due to constant use of bioinformatics overlaps of SHM genomics data with ChIP data, some concerns will remain (and have been outlined by the authors), but that will be future work.

DOI: 10.7554/eLife.105802

Resource: RRID:ZFIN_ZDB-ALT-191023-1

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-191023-1

What is this?

Reviewer #1 (Public review):

This paper investigates the dynamics of excitatory synaptic weights under a calcium-based plasticity rule, in long (up to 10 minutes) simulations of a 211,000-neuron biophysically detailed model of a rat cortical network.

Strengths

(1) A very detailed network model, with a large number of neurons, connections, synapses, etc., and with a huge number of biological considerations implemented in the model.

(2) A carefully developed calcium-based plasticity rule, which operates with biologically relevant variables like calcium concentration and NMDA conductances.

(3) The study itself is detailed and thorough, covering many aspects of the cellular and network anatomy and properties and investigating their relationships to plasticity.

(4) The model remains stable over long periods of simulations, with the plasticity rule maintaining reasonable synaptic weights and not pushing the network to extremes.

(5) The variety of insights the authors derive in terms of relationships between the cellular and network properties and dynamics of the synaptic weights are potentially interesting for the field.

(6) Sharing the model and the associated methods and tools is a big plus.

Weaknesses

(1) Conceptually, there seems to be a missed opportunity here in that it is not clear what the network learns to do. The authors present 10 different input patterns, the network does some plasticity, which is then analyzed, but we do not know whether the learning resulted in anything functionally significant. Did the network learn to discriminate the patterns much better than at the beginning, to capture or anticipate the timing of pattern presentation, detect similarities between patterns, etc.? This is important to understand if one wants to assess the significance of synaptic changes due to plasticity. For example, if the network did not learn much new functionally, relative to its initial state, then the observed plasticity could be considered minor and possibly insufficient. In that case, were the network to learn something substantial, one would potentially observe much more extensive plasticity, and the results of the whole study could change, possibly including the stability of the network. While this could be a whole separate study, this issue is of central importance, and it is hard to judge the value of the results when we do not know what the network learned to do, if anything.

(2) In this study, plasticity occurs only at E-to-E connections but not at others. However, it is well known that inhibitory connections in the cortex exhibit at the very least a substantial short-term plasticity. One would expect that not including these phenomena would have substantial consequences on the results.

(3) Lines 134-135: "We calibrated layer-wise spontaneous firing rates and evoked activity to brief VPM inputs matching in vivo data from Reyes-Puerta et al. (2015)."

(4) Can the authors show these results? It is an important comparison, and so it would be great to see firing rates (ideally, their distributions) for all the cell types and layers vs. experimental data, for the evoked and spontaneous conditions.

(5) That being said, the Reyes-Puerta et al. paper reports firing rates for the barrel cortex, doesn't it? Whereas here, the authors are simulating a non-barrel cortex. Is such a comparison appropriate?

(6) Comparison with STDP on pages 5-7 and Figure 2: if I got this right, the authors applied STDP to already generated spikes, that is, did not run a simulation with STDP. That seems strange. The spikes they use here were generated by the system utilizing their calcium-based plasticity rule. Obviously, the spikes would be different if STDP was utilized instead. The traces of synaptic weights would then also be different. The comparison therefore is not quite appropriate, is it?

(7) Section 2.3 and Figure 5: I am not sure this analysis adds much. The main finding is that plasticity occurs more among cells in assemblies than among all cells. But isn't that expected given what was shown in the previous figures? Specifically, the authors showed that for cells that fire more, plasticity is more prominent. Obviously, cells that fire little or not at all won't belong to any assemblies. Therefore, we expect more plasticity in assemblies.

(8) Section 2.4 and Figure 6: It is not clear that the results truly support the formulation of the section's title ("Synapse clustering contributes to the emergence of cell assemblies, and facilitates plasticity across them") and some of the text in the section. What I can see is that the effect on rho is strong for non-clustered synapses (Figure 6C and Figure S8A). In some cases, it is substantially higher than what is seen for clustered synapses. Furthermore, the wording "synapse clustering contributes to the emergence of cell assemblies" suggests some kind of causal role of clustered synapses in determining which neurons form specific cell assemblies. I do not see how the data presented supports that. Overall, it appears that the story about clustered synapses is quite complicated, with both clustered and non-clustered synapses driving changes in rho across the board.

(9) Section 2.5 and Figure 7: Can we be certain that it is the edge participation that is a particularly good predictor of synaptic changes and/or strength, as opposed to something simpler? For example, could it be the overall number of synapses, excitatory synapses, or something along these lines, that the source and/or target neurons receive, that determine the rho dynamics? And then, I do not understand the claim that edge participation allows one to "delineate potentiation from depression". The only related data I can find is in Figure 7A3, about which the authors write "this effect was stronger for potentiation than depression". But I don't see what they mean. For both depression and facilitation, the changes observed are in the range of ~12% of probability values. And even if the effect is stronger, does it mean one can "delineate" potentiation from depression better? What does it mean, to "delineate"? If it is some kind of decoding based on the edge participation, then the authors did not show that.

(10) "test novel predictions in the MICrONS (2021) dataset, which while pushing the boundaries of big data neuroscience, was so far only analyzed with single cells in focus instead of the network as a whole (Ding et al., 2023; Wang et al., 2023)." That is incorrect. For example, the whole work of Ding et al. analyzes connectivity and its relation to the neuron's functional properties at the network level.

Comments on revisions:

The authors addressed all my concerns from the previous review, primarily via textual changes such as improved Discussion. Thus, most of the weaknesses raised in the original review are not eliminated - in particular, points 1, and 5-9 - but they are acknowledged and described better. This remains a useful study that should be of interest to researchers in the field.

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. Furthermore, they validate some of their findings using immunofluorescence. While the authors confirm key transcriptional signatures in external cohorts comparing HP infected and non-infected cases, the main conclusions drawn from their own patient cohort are based on the comparison between HPGC and healthy controls. This approach does not fully resolve which signatures and cell types are specifically driven by H. pylori infection. As the authors also acknowledge in the limitations of their studies, their conclusions would benefit from functional validation.

In summary, this study provides a valuable resource of 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 potential HP driven transcriptional signatures and how these might contribute to this increased risk. However, the study would highly benefit from a clearer and more systematic comparison between HPGC and non-HPGC to better delineate infection-specific effects.

Reviewer #1 (Public review):

Summary:

The manuscript entitled "Phosphodiesterase 1A Physically Interacts with YTHDF2 and Reinforces the Progression of Non-Small Cell Lung Cancer" explores the role of PDE1A in promoting NSCLC progression by binding to the m6A reader YTHDF2 and regulating the mRNA stability of several novel target genes, consequently activating the STAT3 pathway and leading to metastasis and drug resistance.

Strengths:

The study addresses a novel mechanism involving PDE1A and YTHDF2 interaction in NSCLC, contributing to our understanding of cancer progression.

Reviewer #1 (Public review):

IKK is the key signaling node for inflammatory signaling. Despite the availability of molecular structures, how the kinase achieves its specificity remains unclear. This paper describes a dynamic sequence of events in which autophosphorylation of a tyrosine near the activate site facilitates phosphorylation of the serine on the substrate via a phosphor-transfer reaction. The proposed mechanism is conceptually novel in several ways, suggesting that the kinase is dual specificity (tyrosine and serine) and that it mediates a phospho-transfer reaction. While bacteria contain phosphorylation-transfer enzymes, this is unheard of for mammalian kinases. However, what the functional significance of this enzymatic activity might remain unaddressed.

The revised manuscript adequately addresses all the points I suggested in the review of the first submission.

Reviewer #1 (Public review):

In this study, Brickwedde et al. leveraged a cross-modal task where visual cues indicated whether upcoming targets required visual or auditory discrimination. Visual and auditory targets were paired with auditory and visual distractors, respectively. The authors found that during the cue-to-target interval, posterior alpha activity increased along with auditory and visual frequency-tagged activity when subjects were anticipating auditory targets. The authors conclude that their results disprove the alpha inhibition hypothesis, and instead implies that alpha "regulates downstream information transfer." However, as I detail below, I do not think the presented data irrefutably disproves the alpha inhibition hypothesis. Moreover, the evidence for the alternative hypothesis of alpha as an orchestrator for downstream signal transmission is weak. Their data serves to refute only the most extreme and physiologically implausible version of the alpha inhibition hypothesis, which assumes that alpha completely disengages the entire brain area, inhibiting all neuronal activity.

(1) Authors assign specific meanings to specific frequencies (8-12 Hz alpha, 4 Hz intermodulation frequency, 36 Hz visual tagging activity, 40 Hz auditory tagging activity), but the results show that spectral power increases in all of these frequencies towards the end of the cue-to-target interval. This result is consistent with a broadband increase, which could simply be due to additional attention required when anticipating auditory target (since behavioral performance was lower with auditory targets, we can say auditory discrimination was more difficult). To rule this out, authors will need to show a power spectral density curve with specific increases around each frequency band of interest. In addition, it would be more convincing if there was a bump in the alpha band, and distinct bumps for 4 vs 36 vs 40 Hz band.<br /> (2) For visual target discrimination, behavioral performance with and without the distractor is not statistically different. Moreover, the reaction time is faster with distractor. Is there any evidence that the added auditory signal was actually distracting?<br /> (3) It is possible that alpha does suppress task-irrelevant stimuli, but only when it is distracting. In other words, perhaps alpha only suppresses distractors that are presented simultaneously with the target. Since the authors did not test this, they cannot irrefutably reject the alpha inhibition hypothesis.<br /> (4) In the abstract and Figure 1, the authors claim an alternative function for alpha oscillations; that alpha "orchestrates signal transmission to later stages of the processing stream." In support, the authors cite their result showing that increased alpha activity originating from early visual cortex is related to enhanced visual processing in higher visual areas and association areas. This does not constitute a strong support for the alternative hypothesis. The correlation between posterior alpha power and frequency-tagged activity was not specific in any way; Fig. 10 shows that the correlation appeared on both 1) anticipating-auditory and anticipating-visual trials, 2) the visual tagged frequency and the auditory tagged activity, and 3) was not specific to the visual processing stream. Thus, the data is more parsimonious with a correlation than a causal relationship between posterior alpha and visual processing.

Reviewer #1 (Public review):

Hearing and balance rely on specialized ribbon synapses that transmit sensory stimuli between hair cells and afferent neurons. Synaptic adhesion molecules that form and regulate transsynaptic interactions between inner hair cells (IHCs) and spiral ganglion neurons (SGNs) are crucial for maintaining auditory synaptic integrity and, consequently, for auditory signaling. Synaptic adhesion molecules such as neurexin-3 and neuroligin-1 and -3 have recently been shown to play vital roles in establishing and maintaining these synaptic connections ( doi: 10.1242/dev.202723 and DOI: 10.1016/j.isci.2022.104803). However, the full set of molecules required for synapse assembly remains unclear.

Karagulan et al. highlight the critical role of the synaptic adhesion molecule RTN4RL2 in the development and function of auditory afferent synapses between IHCs and SGNs, particularly regarding how RTN4RL2 may influence synaptic integrity and receptor localization. Their study shows that deletion of RTN4RL2 in mice leads to enlarged presynaptic ribbons and smaller postsynaptic densities (PSDs) in SGNs, indicating that RTN4RL2 is vital for synaptic structure. Additionally, the presence of "orphan" PSDs-those not directly associated with IHCs-in RTN4RL2 knockout mice suggests a developmental defect in which some SGN neurites fail to form appropriate synaptic contacts, highlighting potential issues in synaptic pruning or guidance. The study also observed a depolarized shift in the activation of CaV1.3 calcium channels in IHCs, indicating altered presynaptic functionality that may lead to impaired neurotransmitter release. Furthermore, postsynaptic SGNs exhibited a deficiency in GluA2/3 AMPA receptor subunits, despite normal Gria2 mRNA levels, pointing to a disruption in receptor localization that could compromise synaptic transmission. Auditory brainstem responses showed increased sound thresholds in RTN4RL2 knockout mice, indicating impaired hearing related to these synaptic dysfunctions.

The findings reported here significantly enhance our understanding of synaptic organization in the auditory system, particularly concerning the molecular mechanisms underlying IHC-SGN connectivity. The implications are far-reaching, as they not only inform auditory neuroscience but also provide insights into potential therapeutic targets for hearing loss related to synaptic dysfunction.

Comments on the Latest Version:

In the revised manuscript, the authors have addressed my previous comments and incorporated my recommendations by adding missing experimental details, using color-blind-friendly figure colors, and discussing the differences between GluA3 KO and RTN4RL2 KO phenotypes. They also clarified why the animals needed for additional experiments are no longer available. Although these specific animals are unavailable, the authors made an effort to address my concerns by performing

Reviewer #1 (Public review):

Summary:

In this study, the authors used a multi-alternative decision task and a multidimensional signal-detection model to gain further insight into the cause of perceptual impairments during the attentional blink. The model-based analyses of behavioural and EEG data show that such perceptual failures can be unpacked into distinct deficits in visual detection and discrimination, with visual detection being linked to the amplitude of late ERP components (N2P and P3) and discrimination being linked to coherence of fronto-parietal brain activity.

Strengths:

The strength of this paper lies in the fact that it presents a novel perspective on the cause of perceptual failures during the attentional blink. The multidimensional signal-detection modelling approach is explained clearly, and the results of the study show that this approach offers a powerful method to unpack behavioural and EEG data into distinct processes of detection and discrimination. The discussion of the paper addresses how the findings of separable neural processes involved in detection and discrimination might be linked to extant findings on object recognition and the question of whether the attentional blink involves an all-or-none or gradual impairment in perception.

Weakness:

A minor, unnecessary weakness of the paper is that the authors introduce their study with the aim of determining whether the attentional blink might be due to a criterion shift or to reduced sensitivity in the perceptual process. The criterion shift account remains to be no more than a strawman as the argumentation for this account is weak and easily refuted based on many previous findings. Specifically, the authors suggest that criterion shift might explain the lag-dependent AB effect because participants might be able to infer the lag of a specific trial, thus raising their criterion in case of a short-lag trial, based on factors such as the length of the trial sequence. Importantly, however, attentional blinks have also been observed in many studies in which the sequence length was not indicative of the T1-T2 lag, including - for instance - the many experiments reported in the seminal study by Chun and Potter (1995). The criterion shift account was and remains, therefore, highly implausible and should not have deserved such a prominent role in describing the theoretical motivation for the study.

Reviewer #2 (Public review):

Summary:

Chromosomal inversions have been predicted to play a role in adaptive evolution and speciation because of their ability to "lock" together adaptive alleles in genomic regions of low recombination. In this study, the authors use a combination of cutting-edge genomic methods, including BioNano and PacBio HiFi sequencing, to identify six large chromosomal inversions segregating in over 100 species of Lake Malawi cichlids, a classic example of adaptive radiation and rapid speciation. By examining the frequencies of these inversions present in species from six different linages, the authors show that there is an association between the presence of specific inversions with specific lineages/habitats. Using a combination of phylogenetic analyses and sequencing data, they demonstrate that three of the inversions have been introduced to one lineage via hybridization. Finally, genotyping of laboratory crosses suggests that two inversions are associated with XY sex determination systems in a subset of species. The data add to a growing number of systems in which inversions have been associated with adaptation to divergent environments. However, like most of the other recent studies in the field, this study does not go beyond describing the presence of the inversions to demonstrate that the inversions are under sexual or natural selection or that they contribute to adaptation or speciation in this system.

Strengths:

All analyses are very well done, and the conclusions about the presence of the six inversions in Lake Malawi cichlids, the frequencies of the inversions in different species, and the presence of three inversions in the benthic lineages due to hybridization are well-supported. Genotyping of 48 individuals resulting from laboratory crosses provides strong support that the chromosome 10 inversion is associated with a sex-determination locus.

Weaknesses:

The evidence supporting a role for the chromosome 11 inversion is based on relatively few individuals and therefore remains suggestive. The authors are mostly cautious in their interpretations of the data, although there are places where the language is imprecise and therefore a little misleading.

Reviewer #1 (Public review):

Summary:

The current work explored the link between the pulvinar intrinsic organisation and its functional and structural connectivity patterns of the cortex using different dimensional reduction techniques. Overall they find relationships between pulvinar-cortical organization and cortico-cortical organization, and little evidence for clustered organization. Moreover they investigate PET maps to understand how neurotransmitter/receptor distributions vary within the pulvinar and along its structural and functional connectivity axes.

Strengths:

(1) There is a replication dataset and different modalities are compared against each other to understand the structural and functional organisation of the pulvinar complex

In their revision, the authors further detailed the motivation of their study and performed various robustness checks, answering my concerns. Nevertheless, further work is needed to fully understand the role of the pulvinar nuclei and the rest of the thalamic nuclei as well as the rest of the brain, including more diverse datasets and techniques.

Reviewer #1 (Public review):

In the revision of their paper, N'Guessan et al have improved the report of their study of expression QTL (eQTL) mapping in yeast using single cells. The authors make use of advances in single cell RNAseq (scRNAseq) in yeast to increase the efficiency with which this type of analysis can be undertaken. Building on prior research led by the senior author that entailed genotyping and fitness profiling of almost 100,000 cells derived from a cross between two yeast strains (BY and RM) they performed scRNAseq on a subset of ~5% (n = 4,489) individual cells. To address the sparsity of genotype data in the expression profiling they used a Hidden Markov Model (HMM) to infer genotypes and then identify the most likely known lineage genotype from the original dataset. To address the relationship between variance in fitness and gene expression the authors partition the variance to investigate the sources of variation. They then perform eQTL mapping and study the relationship between eQTL and fitness QTL identified in the earlier study.

This paper seeks to address the question of how quantitative trait variation and expression variation are related. scRNAseq represents an appealing approach to eQTL mapping as it is possible to simultaneously genotype individual cells and measure expression in the same cell. As eQTL mapping requires large sample sizes to identify statistical relationships, the use of scRNAseq is likely to dramatically increase the statistical power of such studies. However, there are several technical challenges associated with scRNAseq and the authors' study is focused on addressing those challenges. My main suggestion from my review of the revised version of the manuscript has been addressed in the revised figure 3. I agree with the authors that they have successfully demonstrated their stated goal of developing, and illustrating the benefit of, a one-pot scRNA-seq experiment and analysis for eQTL mapping.

Reviewer #1 (Public review):

This work provides a new Python toolkit for combining generative modeling of neural dynamics and inversion methods to infer likely model parameters that explain empirical neuroimaging data. The authors provided tests to show the toolkit's broad applicability and accuracy; hence, it will be very useful for people interested in using computational approaches to better understand the brain.

Strengths:

The work's primary strength is the tool's integrative nature, which seamlessly combines forward modelling with backward inference. This is important as available tools in the literature can only do one and not the other, which limits their accessibility to neuroscientists with limited computational expertise. Another strength of the paper is the demonstration of how the tool can be applied to a broad range of computational models popularly used in the field to interrogate diverse neuroimaging data, ensuring that the methodology is not optimal to only one model. Moreover, through extensive in-silico testing, the work provided evidence that the tool can accurately infer ground-truth parameters, which is important to ensure results from future hypothesis testing are meaningful.

Weaknesses:

Although the tool itself is the main strength of the work, the paper lacked a thorough analysis of issues concerning robustness and benchmarking relative to existing tools.

The first issue is the robustness to the choice of features to be included in the objective function. This choice significantly affects the training and changes the results, as the authors even acknowledged themselves multiple times (e.g., Page 17 last sentence of first paragraph or Page 19 first sentence of second paragraph). This brings the question of whether the accurate results found in the various demonstrations are due to the biased selection of features (possibly from priors on what worked in previous works). The robustness of the neural estimator and the inference method to noise was also not demonstrated. This is important as most neuroimaging measurements are inherently noisy to various degrees.

The second issue is on benchmarking. Because the tool developed is, in principle, only a combination of existing tools specific to modeling or Bayesian inference, the work failed to provide a more compelling demonstration of its added value. This could have been demonstrated through appropriate benchmarking relative to existing methodologies, specifically in terms of accuracy and computational efficiency.

Reviewer #1 (Public review):

Summary:

In this study, Donofrio et al. investigated cerebellar Purkinje cell (PC) degeneration during normal aging using both mouse and human samples. They found that PC loss followed a stripe pattern rather than occurring randomly. Although this pattern resembled the pattern of zebrin II expression in the anterior cerebellum, the overall pattern was different from zebrin II expression. Surviving PCs exhibited severe degeneration, including thickened axons, axonal torpedoes, and shrunken dendrites. These structural changes were accompanied by functional deficits in motor coordination and tremor. Understanding why certain PC subpopulations are more vulnerable than others may provide insight into regional susceptibility (or resilience) to aging and inform potential therapeutic strategies for age-related neurological disorders. Overall, the findings are novel and significant, supported by compelling evidence from structural and functional analyses. However, I have several concerns about the results and hope that my comments will help improve the clarity and impact of this paper.

Strengths:

The cerebellum is often overlooked in aging research, despite its increasingly recognized role in motor and non-motor functions. This study, which examines the pattern of PC loss during normal aging, offers a new perspective on the aging process.

The finding that PC loss follows a stripe pattern is a major conceptual advance, challenging the previous assumption that PC loss occurs uniformly in the cerebellum.

The analyses using wholemount immunohistochemistry, PC-specific reporter mice, and light-sheet imaging of cleared brain tissue are meticulous. By visualizing PCs in three dimensions, this study provides strong evidence for the patterned loss of PCs across different cerebellar subdivisions during aging.

The inclusion of human samples along with the animal model strengthens the impact and translational relevance of these findings.

The data are clearly presented, and the manuscript is very well written.

Weaknesses:

While the authors have largely ruled out zebrin II as the key protein underlying PC vulnerability or resistance to age-related loss, the molecular basis of this phenomenon remains unidentified. This reviewer acknowledges the complexity of this investigation and considers it a minor issue, as the manuscript thoughtfully discusses the gap and highlights it as a future direction.

In cases where no PC loss is observed in aged mice (Figure 1F), it is unclear whether these PCs undergo morphological degeneration, such as thickened axons and shrunken dendrites. Further characterization of these resilient PCs would help understand why the aged mice without PC loss still exhibit motor deficits (Figure 7).

The histologic analysis is based on mice with different genetic backgrounds. For example, the PC-specific reporter mice include two strains: Pcp2-Cre; Ai32 and Pcp2-Cre; Ai40D. These genetic variations may contribute to the heterogeneity of PC loss (Figure 1). To improve clarity, please add the genetic background details to Table 1.

Please indicate from which lobule in the anterior or posterior human cerebellum the images in Figure 8 were taken.

Reviewer #1 (Public review):

Summary:

The authors note that there is a large corpus of research establishing the importance of LC-NE projections to the medial prefrontal cortex (mPFC) of rats and mice in attentional set or 'rule' shifting behaviours. However, this is complex behavior, and the authors were attempting to gain an understanding of how locus coeruleus modulation of the mPFC contributes to set shifting.

The authors replicated the ED-shift impairment following NE denervation of mPFC by chemogenetic inhibition of the LC. They further showed that LC inhibition changed the way neurons in mPFC responded to the cues, with a greater proportion of individual neurons responsive to 'switching', but the individual neurons also had broader tuning, responding to other aspects of the task (i.e., response choice and response history). The population dynamics were also changed by LC inhibition, with reduced separation of population vectors between early-post-switch trials, when responding was at chance, and later trials when responding was correct. This was what they set out to demonstrate, and so one can conclude they achieved their aims.

The authors concluded that LC inhibition disrupted mPFC "encoding capacity for switching" and suggest that this "underlie the behavioral deficits."

Strengths:

The principal strength is the combination of inactivation of LC with calcium imaging in the mPFC. This enabled detailed consideration of the change in behavior (i.e., defining epochs of learning, with an 'early phase' when responding is at chance being compared to a 'later phase' when the behavioral switch has occurred) and how these are reflected in neuronal activity in the mPFC, with and without LC-NE input.

Weaknesses:

Methodologically, some improvement could be made in terms of the statistical descriptions. Supplementary Figure 2: For the peripheral CNO, the 'control group' (saline) was n=4 and the test group (CNO), n=5. For the central CNO, the test group was n = 8 and the control was n = 7. The authors explain that the group sizes were not statistically determined and mice were assigned to groups 'arbitrarily', but why did they not at least make the group sizes equal?

In Figure 1 (e), given the small sample size, it would be helpful if all the data points were included on the bar charts. As a t-test was performed on only the ED stage of the test, seeing all the data points would reassure that there would not have been a statistically significant 'improvement' in the ID stage in the group given mPFC CNO. It would also be helpful to give effect sizes for all statistical tests.

Reviewer #1 (Public review):

Summary:

This study presents compelling evidence for a novel treatment approach in a challenging patient population with MSS/pMMR mCRC, where traditional immunotherapy has often fallen short. The combination of SBRT and tislelizumab not only yielded a high disease control rate but also indicated significant improvements in the tumor's immune landscape. The safety profile appears favorable, which is crucial for patients who have already undergone multiple lines of therapy.

Strengths:

The results underscore the potential of leveraging radiation therapy to enhance the effectiveness of immunotherapy, especially in tumor environments previously deemed hostile to immune interventions. Future research should focus on larger cohorts to validate these findings and explore the underlying mechanisms of immune modulation post-treatment.

Comments on revisions:

The author provided satisfactory responses to my queries, offering clarifications and additional explanations to address potential points of confusion. The supplementary experimental data further corroborate the author's conclusions. Although a more in-depth and detailed analysis did not yield significant results, this does not undermine the overall integrity of the article's structure or the reliability of its conclusions. Based on the content and the supporting evidence presented, I believe this article meets the necessary criteria for publication.

Reviewer #1 (Public review):

Summary:

The Authors investigated the anatomical features of the excitatory synaptic boutons in layer 1 of the human temporal neocortex. They examined the size of the synapse, the macular or the perforated appearance and the size of the synaptic active zone, the number and volume of the mitochondria, the number of the synaptic and the dense core vesicles, also differentiating between the readily releasable, the recycling and the resting pool of synaptic vesicles. The coverage of the synapse by astrocytic processes was also assessed, and all the above parameters were compared to other layers of the human temporal neocortex. The Authors conclude that the subcellular morphology of the layer 1 synapses is suitable for the functions of the neocortical layer, i.e. the synaptic integration within the cortical column. The low glial coverage of the synapses might allow the glutamate spillover from the synapses enhancing synpatic crosstalk within this cortical layer.

Strengths:

The strengths of this paper are the abundant and very precious data about the fine structure of the human neocortical layer 1. Quantitative electron microscopy data (especially that derived from the human brain) are very valuable, since this is a highly time- and energy consuming work. The techniques used to obtain the data, as well as the analyses and the statistics performed by the Authors are all solid, strengthen this manuscript, and support the conclusions drawn in the discussion.

Comments on latest version:

The third version of this paper has been substantially improved. The English is significantly better, there are only few paragraphs and sentences which are hard to understand (see my comments and suggestions below). Almost all of my suggestions were incorporated.

Remaining minor concerns:<br /> About epileptic and non-epileptic (non-affected) tissue. I am aware that temporal lobe neocortical tissue derived from epileptic patients is regarded as non-affected by many groups, and they are quite similar to the cortex of non-epileptic (tumour) patients in their electrophysiological properties and synaptic physiology. But please, note, that one paper you cited did not use samples from epileptic patients, but only tissue from non-epileptic tumor patients (Molnár et al. PLOS 2008).<br /> When you look deeper, and make thorough comparison of tissues derived from epileptic and non-epileptic patients, there are differences in the fine structure, as well as in several electrophysiological features. See for example Tóth et al., J Physiol, 2018, where higher density of excitatory synapses were found in L2 of neocortical samples derived from epileptic patients compared to non-epileptic (tumor) patients. Furthermore, the appearance of population bursts is similar, but their occurrence is more frequent and their amplitude is higher in tissue from epileptic compared to non-epileptic patients. So, I still cannot agree, that temporal neocortex of epileptic patients with the seizure focus in the hippocampus would be non-affected. Therefore I suggested to use the term biopsy tissue.

It is still not emphasized in the first paragraph of the Discussion, that only excitatory axon terminals were investigated.

The text in the Results and the Discussion are somewhat inconsistent.<br /> The last two paragraphs of the Results section ends with several sentences which should be part of the discussion, such as line 328: This finding strongly supports multivesicular release... or line 344: --- pointing towards a layer-specific regulation of the putative RRP. Moreover, the results suggest that... and line 370: ... it is most likely... Please, correct this.<br /> The first paragraph of the Discussion summarizes the work of the quantitative EM work and gives one conclusion about the astrocytic coverage. This last sentence is inconsistent with the other parts of the paragraph. I would either write that "astrocytic coverage was also investigated" (or something similar), or move this sentence to the paragraph which discusses the astrocytic coverage.<br /> Results line 180-183. "Special connections" between astrocytic processes and synaptic boutons are mentioned, but not shown. Either show these (but then prove with staining!), or leave out this paragraph.

Reviewer #1 (Public review):

Summary:

Fecal virome transfer (FVT) has the potential to take advantage of microbiome-associated phages to treat diseases such as NEC. However, FVT is also associated with toxicity due to the presence of eukaryotic viruses in the mixture, which are difficult to filter out. The authors use a chemostat propagation system to reduce the presence of eukaryotic viruses (these become lost over time during culture). They show in pig models of NEC that chemostat propagation reduces the incidence of diarrhea induced by FVTs.

Strengths:

The authors report an innovative yet simple approach that has the potential to be useful for future applications. Most of the experiments are easy to follow and are performed well.

Weaknesses:

The biggest weakness is that the authors show that their technique addresses safety, but they are unable to demonstrate that they retain efficacy in their NEC model. This could be due to technical issues or perhaps the efficacy of FVT reported in the literature is not robust. If they cannot demonstrate the efficacy of the chemostat-propagated virome mixture, the value of the study is compromised.

The above issue is especially concerning because the chemostat propagation selected for bacteria that may not necessarily be the ones that harbor the beneficial phages. Without an understanding of exactly how FVT works, is it possible to make any conclusion about the usefulness of the chemostat approach?

Finally, can the authors rule out that their observations in THP-1 cells are driven by LPS or some other bacterial product in the media?

Reviewer #1 (Public review):

Summary:

Mackie and colleagues compare chemosensory preferences between C. elegans and P. pacificus, and the cellular and molecular mechanisms underlying them. The nematodes have overlapping and distinct preferences for different salts. Although P. pacificus lacks the lsy-6 miRNA important for establishing asymmetry of the left/right ASE salt sensing neurons in C. elegans, the authors find that P. pacificus ASE homologs achieve molecular (receptor expression) and functional (calcium response) asymmetry by alternative means. This work contributes an important comparison of how these two nematodes sense salts and highlights that evolution can find different ways to establish asymmetry in small nervous systems to optimize the processing of chemosensory cues in the environment.

Strengths:

The authors use clear and established methods to record the response of neurons to chemosensory cues. They were able to show clearly that ASEL/R are functionally asymmetric in P. pacificus, and combined with genetic perturbation establish a role for che-1-dependent gcy-22.3 in the asymmetric response to NH4Cl.

Weaknesses:

The mechanism of lsy-6-independent establishment of ASEL/R asymmetry in P. pacificus remains uncharacterized.

Comments on revisions: Looks good - all the best

Reviewer #1 (Public review):

Summary:

In this study, the authors sequenced emm89 serotype genomes of clinical isolates from patients in Japan, where the number of invasive Group A Streptococcus (GAS), especially those of the emm89 serotype, has drastically increased over the past 10-15 years. The sequences from this cohort were compared against a large collection of publicly available global isolates, yielding a total of almost 1000 genomes in the analysis. Because the researchers focused on the emm89 serotype, they could construct a common core genome, with subsequent ability to analyze genomic differences in accessory genes and intergenic regions that contributed to the invasive phenotype using multiple types of GWAS analysis (SNP, k-mer). Their analysis demonstrates some mutations responsible for invasiveness are specific to the Japanese strains, and that multiple independent virulence factors can contribute to invasiveness. None of the invasive phenotypes were correlated with new gene acquisition. Together, the data support that synergy between bacterial survival and upregulation of virulence factors contribute to the development of severe infection.

Strengths:

• The authors verify their analysis by confirming that covS is one of the more frequently mutated genes in invasive strains of GAS, as has been shown in other publications.

• A mutation in one of the SNPs attributed to invasiveness (SNP fhuB) was introduced into an invasive strain. The authors demonstrate that this mutant strain survives less well in human blood. Therefore, the authors have experimental data to support their claims that their analysis uncovered a new mutation/SNP that contributed to invasiveness.

Weaknesses:

• It would be helpful for the authors to highlight why their technique (large scale analysis of one emm type) can yield more information than a typical GWAS analysis of invasive vs. non-invasive strains. Are SNPs easier to identify using a large-scale core genome? Is it more likely evolutionarily to find mutations in non-coding regions as opposed to the core genome and accessory genes, and this is what this technique allows? Did the analysis yield unexpected genes or new genes that had not been previously identified in other GWAS analyses? These points may need to be made more apparent in the results and deserves some thought in the discussion section.

• The Alpha-fold data does not demonstrate why the mutations the authors identified could contribute to the invasive phenotype. It would be helpful to show an overlay of the predicted structures containing the different SNPs to demonstrate the potential structural differences that can occur due to the SNP. This would make the data more convincing that the SNP has a potential impact on the function of the protein. Similarly, the authors discuss modification of the hydrophobicity of the side chain in the ferrichrome transporter (lines 317-318) due to a SNP, but this is not immediately obvious in the figure (Fig. 5).

Comments on revisions:

The authors have addressed the concerns from reviewers. The implemented revisions have improved the manuscript's clarity.

Reviewer #1 (Public review):

The authors introduces DIPx, a deep learning framework for predicting synergistic drug combinations for cancer treatment using the AstraZeneca-Sanger (AZS) DREAM Challenge dataset. While the approach is innovative, I have following concerns and comments, and hopefully will improve the study's rigor and applicability, making it a more powerful tool in real clinical world.

(1) The model struggles with predicting synergies for drug combinations not included in its training data (showing only Spearman correlation 0.26 in Test Set 2). This limits its potential for discovering new therapeutic strategies. Utilizing techniques such as transfer learning or expanding the training dataset to encompass a wider range of drug pairs could help to address this issue.

(2) The use of pan-cancer datasets, while offering broad applicability, may not be optimal for specific cancer subtypes with distinct biological mechanisms. Developing subtype-specific models or adjusting the current model to account for these differences could improve prediction accuracy for individual cancer types.

(3) Line 127, "Since DIPx uses only molecular data, to make a fair comparison, we trained TAJI using only molecular features and referred to it as TAJI-M.". TAJI was designed to use both monotherapy drug-response and molecular data, and likely won't be able to reach maximum potential if removing monotherapy drug-response from the training model. It would be critical to use the same training datasets and then compare the performances. From Figure 6 of TAJI's paper (Li et al., 2018, PMID: 30054332) , i.e., the mean Pearson correlation for breast cancer and lung cancer are around 0.5 - 0.6.

The following 2 concerns have been included in the Discussion section which are great:

(1) Training and validating the model using cell lines may not fully capture the heterogeneity and complexity of in vivo tumors. To increase clinical relevance, it would be beneficial to validate the model using primary tumor samples or patient-derived xenografts.

(2) The Pathway Activation Score (PAS) is derived exclusively from primary target genes, potentially overlooking critical interactions involving non-primary targets. Including these secondary effects could enhance the model's predictive accuracy and comprehensiveness.

Reviewer #1 (Public review):

Summary:

The authors performed bidirectional two-sample Mendelian randomization using publicly available GWAS summary data to assess the directional causal association between atherosclerosis and intracranial aneurysms. They have used a similar strategy to identify the role of matrix metalloproteinases (MMP), especially MMP12, in mediating the above causal association. They finally substantiated these results by measuring and comparing the MMP12 levels in the plasma samples collected from carotid atherosclerosis and intracranial aneurysm patients with those of healthy controls. Local tissue levels of MMP12 were also measured in experimental mouse models.

Strengths:

The authors have chosen to address an important problem that could be of interest to many researchers and clinicians in the subfield.

Weaknesses:

Mendelian Randomization (MR) is a powerful approach to explore the directional causal relationship between comorbid conditions using genetic variants as instrumental variables. The validity of causal inference derived from MR strongly depends on genetic instruments satisfying the three core assumptions- relevance, independence, and exclusion restriction. The violation of these assumptions is hard to verify in many real-world situations and may result in spurious results. Rigorous sensitivity analysis is essential to ensure the robustness of the results. The sensitivity analysis presented in the current manuscript is incomplete. The key points are as follows:

(1) The GWAS summary datasets used by the authors for assessing the causal relationship between atherosclerosis and intracranial aneurysms were all from the FinnGen study and thus may have overlapping samples which is known to introduce bias into the causal estimates and inflate type 1 error rates.

(2) Both atherosclerosis and aneurysms share common risk factors (mentioned by the authors as well) such as hypertension, cholesterol, diabetes, smoking, etc., which could lead to correlated pleiotropy while performing Mendelian randomization. MR-PRESSO may not effectively account for the same.

(3) The authors explored the role of matrix metalloproteinases as intermediate biomarkers mediating the risk of atherosclerosis in the intracranial aneurysms. Separating the exposure to biomarker MR from biomarker to outcome MR limits the interpretation of the results. The effect size of the indirect effect cannot be assessed.

(4) The scatter plots presented in Supplementary Figures 1-3 are neither cited nor discussed in the manuscript. Some of the plots show variability in the direction and magnitude of the causal estimates from MR-Egger and MR-IVW methods, indicating either masking of the causal estimates or directional pleiotropy. Discussing these results is crucial to inform the readers of the limitations of the derived causal estimates.

(5) When there is substantial evidence available for the frequent coexistence of atherosclerosis and aneurysms, the additional value of the cross-sectional data showing the increased prevalence of atherosclerosis in patients with intracranial aneurysms without adjusting for confounding risk factors is not clear.

(6) It is also not clear from the manuscript whether the authors are projecting the MMP12 as a shared biomarker or as a mediator between atherosclerosis and intracranial aneurysms. As also noted by the authors, assessment of plasma MMP12 levels in a cross-sectional sample is not sufficient to substantiate the role of MMP12 as an intermediate biomarker connecting atherosclerosis to the increased risk of intracranial aneurysms.

Impact:

The findings from this study can form the basis for a more systematic analysis towards identifying molecular intermediates mediating the risk of atherosclerosis in patients with intracranial aneurysms or vice versa, which in turn helps develop novel strategies to manage these comorbid conditions.

Reviewer #1 (Public review):

Summary:

The authors, Dalal, et. al., determined cryo-EM structures of open, closed, and desensitized states of the pentameric ligand-gated ion channel ELIC reconstituted in liposomes, and compared them to structures determined in varying nanodisc diameters. They argue that the liposomal reconstitution method is more representative of functional ELIC channels, as they were able to test and recapitulate channel kinetics through stopped-flow thallium flux liposomal assay. The authors and others have described channel interactions with membrane scaffold proteins (MSP), initially thought to be in a size-dependent manner. However, the authors reported that their cryo-EM ELIC structure interacts with the large nanodisc spNW25, contrary to their original hypotheses. This suggests that the channel's interactions with MSPs might alter its structure, possibly not accurately representing/reflecting functional states of the channel.

Strengths:

Cryo-EM structural determination from proteoliposomes is a promising methodology within the ion channel field due to their large surface area and lack of MSP or other membrane mimetics that could alter channel structure. Comparing liposomal ELIC to structures in various-sized nanodiscs gives rise to important discussions for other membrane protein structural studies when deciding the best method for individual circumstances.

Weaknesses:

The overarching goal of the study was to determine structural differences of ELIC in detergent nanodiscs and liposomes. Including comparisons of the results to the native bacterial lipid environment would provide a more encompassing discussion of how the determined liposome structures might or might not relate to the native receptor in its native environment. The authors stated they determined open, closed, and desensitized states of ELIC reconstituted in liposomes and suggest the desensitization gate is at the 9' region of the pore. However, no functional studies were performed to validate this statement.

Reviewer #1 (Public review):

Summary:

This study presents compelling evidence for a novel treatment approach in a challenging patient population with MSS/pMMR mCRC, where traditional immunotherapy has often fallen short. The combination of SBRT and tislelizumab not only yielded a high disease control rate but also indicated significant improvements in the tumor's immune landscape. The safety profile appears favorable, which is crucial for patients who have already undergone multiple lines of therapy.

Strengths:

The results underscore the potential of leveraging radiation therapy to enhance the effectiveness of immunotherapy, especially in tumor environments previously deemed hostile to immune interventions. Future research should focus on larger cohorts to validate these findings and explore the underlying mechanisms of immune modulation post-treatment.

Weaknesses:

I believe the author's work is commendable and should be considered with some minor modifications:

(1) While the author categorized patients based on the type of RAS mutation and the location of colorectal cancer metastasis, the article does not adequately address how these classifications influence treatment outcomes. Such as whether KRAS or NRAS mutations, as well as the type of metastatic lesions, affect the sensitivity to gamma-ray treatment and lead to varying responses.

(2) In Figure 2, clarification is needed on how the author differentiated between on-target and off-target lesions. I observed that some images depicted both lesion types at the same level, which could lead to confusion.

(3) The author performed only a basic difference analysis. A more comprehensive analysis, including calculations of markers related to treatment efficacy, could offer additional insights for clinical practice.

(4) The transcriptome sequencing analysis provides insights into how stereotactic radiotherapy sensitizes immunotherapy; however, it currently relies on a simple pre- and post-treatment group comparison. It would be beneficial to include additional subgroups to explore more nuanced findings.

(5) The author briefly discusses the effects of changes in tumor fibrosis and angiogenesis on treatment outcomes. Further experiments may be necessary to validate these findings and investigate the underlying mechanisms of immune regulation following treatment.

Reviewer #1 (Public review):

Summary:

In this manuscript, Ning et al. reported that Bcas2 played an indispensable role in zebrafish primitive hematopoiesis via sequestering β-catenin in the nucleus. The authors showed that loss of Bcas2 caused primitive hematopoietic defects in zebrafish. They unraveled that Bcas2 deficiency promoted β-catenin nuclear export via a CRM1-dependent manner in vivo and in vitro. They further validated that BCAS2 directly interacted with β-catenin in the nucleus and enhanced β-catenin accumulation through its CC domains. They unveil a novel insight into Bcas2, which is critical for zebrafish primitive hematopoiesis via regulating nuclear β-catenin stabilization rather than its canonical pre-mRNA splicing functions. Overall, the study is impressive and well-performed, although there are also some issues to address.

Strengths:

The study unveils a novel function of Bcas2, which is critical for zebrafish primitive hematopoiesis by sequestering β-catenin. The authors validated the results in vivo and in vitro. Most of the figures are clear and convincing. This study nicely complements the function of Bcas2 in primitive hematopoiesis.

Comments on revisions:

The authors have nicely answered all my questions, I have no problem.

Reviewer #1 (Public review):

Du et al. address the cell cycle-dependent clearance of misfolded protein aggregates mediated by the endoplasmic reticulum (ER) associated Hsp70 chaperone family and ER reorganisation. The observations are interesting and impactful to the field.

Strength:

The manuscript addresses the connection between the clearance of misfolded protein aggregates and the cell cycle using a proteostasis reporter targeted to ER in multiple cell lines. Through imaging and some biochemical assays, they establish the role of BiP, an Hsp70 family chaperone, and Cdk1 inactivation in aggregate clearance upon mitotic exit. Furthermore, the authors present an initial analysis of the role of ER reorganisation in this clearance. These are important correlations and could have implications for ageing-associated pathologies. Overall, the results are convincing and impactful to the field.

Weakness:

The manuscript still lacks a mechanistic understanding of aggregate clearance. Even though the authors have provided the role of different cellular components, such as BiP, Cdk1 and ATL2/3 through specific inhibitors, at least an outline establishing the sequence of events leading to clearance is missing. Moreover, the authors show that the levels of ER-FlucDM-eGFP do not change significantly throughout the cell cycle, indicating that protein degradation is not in play. Therefore, addressing/elaborating on the mechanism of disassembly can add value to the work. Also, the physiological relevance of aggregate clearance upon mitotic exit has not been tested, nor have the cellular targets of this mode of clearance been identified or discussed.

Reviewer #1 (Public review):

Summary:

The authors quantified information in gesture and speech, and investigated the neural processing of speech and gestures in pMTG and LIFG, depending on their informational content, in 8 different time-windows, and using three different methods (EEG, HD-tDCS and TMS). They found that there is a time-sensitive and staged progression of neural engagement that is correlated with the informational content of the signal (speech/gesture).

Strengths:

A strength of the paper is that the authors attempted to combine three different methods to investigate speech-gesture processing.

Comments on revisions:

I thank the authors for their careful responses to my comments. However, I remain not convinced by their argumentation regarding the specificity of their spatial targeting and the time-windows that they used.

The authors write that since they included a sham TMS condition, that the TMS selectively disrupted the IFG-pMTG interaction during specific time windows of the task related to gesture-speech semantic congruency. This to me does not show anything about the specificity of the time-windows itself, nor the selectivity of targeting in the TMS condition.

It could still equally well be the case that other regions or networks relevant for gesture-speech integration are targeted, and it can still be the case that these timewindows are not specific, and effects bleed into other time periods. There seems to be no experimental evidence here that this is not the case.

To be more specific, the authors write that double-pulse TMS has been widely used in previous studies (as found in their table). However, the studies cited in the table do not necessarily demonstrate the level of spatial and temporal specificity required to disentangle the contributions of tightly-coupled brain regions like the IFG and pMTG during the speech-gesture integration process. pMTG and IFG are located in very close proximity, and are known to be functionally and structurally interconnected, something that is not necessarily the case for the relatively large and/or anatomically distinct areas that the authors mention in their table.

But also more in general: The mere fact that these methods have been used in other contexts does not necessarily mean they are appropriate or sufficient for investigating the current research question. Likewise, the cognitive processes involved in these studies are quite different from the complex, multimodal integration of gesture and speech. The authors have not provided a strong theoretical justification for why the temporal dynamics observed in these previous studies should generalize to the specific mechanisms of gesture-speech integration.

Moreover, the studies cited in the table provided by the authors have used a wide range of interpulse intervals, from 20 ms to 100 ms, suggesting that the temporal precision required to capture the dynamics of gesture-speech integration (which is believed to occur within 200-300 ms; Obermeier & Gunter, 2015) may not even be achievable with their 40 ms time windows.

I do appreciate the extra analyses that the authors mention. However, my 5th comment is still unanswered: why not use entropy scores as a continous measure?

In light of these concerns, I do not believe the authors have adequately demonstrated the spatial and temporal specificity required to disentangle the contributions of the IFG and pMTG during the gesture-speech integration process. While the authors have made a sincere effort to address the concerns raised by the reviewers, and have done so with a lot of new analyses, I remain doubtful that the current methodological approach is sufficient to draw conclusions about the causal roles of the IFG and pMTG in gesture-speech integration.

Reference:<br /> Obermeier, C., & Gunter, T. C. (2015). Multisensory Integration: The Case of a Time Window of Gesture-Speech Integration. Journal of Cognitive Neuroscience, 27(2), 292-307. https://doi.org/10.1162/jocn_a_00688

Reviewer #1 (Public review):

Summary:

This is a significant study because it adapts current methods to develop an approach for identifying promising targets for therapeutics in viral genomic RNA. The authors provide a wide array of data from different methods to help support their findings.

Strengths:

There are a number of strengths to highlight in this manuscript.

(1) The study uses a sophisticated technique (SHAPE-MaP) to analyze the PEDV RNA genome in situ, providing valuable insights into its structural features.

(2) The authors provide a strong rationale for targeting specific RNA structures for antiviral development.

(3) The study includes a range of experiments, including structural analysis, compound screening, siRNA design, and viral proliferation assays, to support their conclusions.

(4) Finally, the findings have potential implications for the development of new antiviral therapies against PEDV and other RNA viruses.

Overall, this interesting study highlights the importance of considering RNA structure when designing antiviral therapies and provides a compelling strategy for identifying promising RNA targets in viral genomes.

Reviewer #1 (Public review):

This is a very interesting paper addressing the hierarchical nature of the mammalian auditory system. The authors use an unconventional technique to assess brain responses -- functional ultrasound imaging (fUSI). This measures blood volume in the cortex at a relatively high spatial resolution. They present dynamic and stationary sounds in isolation and together, and show that the effect of the stationary sounds (relative to the dynamic sounds) on blood volume measurements decreases as one ascends the auditory hierarchy. Since the dynamic/stationary nature of sounds is related to their perception as foreground/background sounds (see below for more details), this suggests that neurons in higher levels of the cortex may be increasingly invariant to background sounds.

The study is interesting, well conducted, and well written. I am broadly convinced by the results. However, I do have some concerns about the validity of the results, given the unconventional technique. fUSI is convenient because it is much less invasive than electrophysiology, and can image a large region of the cortex in one go. However, the relationship between blood volume and neuronal activity is unclear, and blood volume measurements are heavily temporally averaged relative to the underlying neuronal responses. I am particularly concerned about the implications of this for a study on dynamic/stationary stimuli in auditory cortical hierarchy, because the time scale of the dynamic sounds is such that much of the dynamic structure may be affected by this temporal averaging. Also, there is a well-known decrease in temporal following rate that is exhibited by neurons at higher levels of the auditory system. This means that results in different areas will be differently affected by the temporal averaging. I would like to see additional control models to investigate the impact of this.

I also think that the authors should address several caveats: the fact that their measurements heavily spatially average neuronal responses, and therefore may not accurately reflect the underlying neuronal coding; that the perceptual background/foreground distinction is not identical to the dynamic/stationary distinction used here; and that ferret background/foreground perception may be very different from that in humans.

Major points

(1) Changes in blood volume due to brain activity are indirectly related to neuronal responses. The exact relationship is not clear, however, we do know two things for certain: (a) each measurable unit of blood volume change depends on the response of hundreds or thousands of neurons, and (b) the time course of the volume changes are are slow compared to the potential time course of the underlying neuronal responses. Both of these mean that important variability in neuronal responses will be averaged out when measuring blood changes. For example, if two neighbouring neurons have opposite responses to a given stimulus, this will produce opposite changes in blood volume, which will cancel each other out in the blood volume measurement due to (a). This is important in the present study because blood volume changes are implicitly being used as a measure of coding in the underlying neuronal population. The authors need to acknowledge that this is a coarse measure of neuronal responses and that important aspects of neuronal responses may be missing from the blood volume measure.

(2) More importantly for the present study, however, the effect of (b) is that any rapid changes in the response of a single neuron will be cancelled out by temporal averaging. Imagine a neuron whose response is transient, consisting of rapid excitation followed by rapid inhibition. Temporal averaging of these two responses will tend to cancel out both of them. As a result, blood volume measurements will tend to smooth out any fast, dynamic responses in the underlying neuronal population. In the present study, this temporal averaging is likely to be particularly important because the authors are comparing responses to dynamic (nonstationary) stimuli with responses to more constant stimuli. To a first approximation, neuronal responses to dynamic stimuli are themselves dynamic, and responses to constant stimuli are themselves constant. Therefore, the averaging will mean that the responses to dynamic stimuli are suppressed relative to the real responses in the underlying neurons, whereas the responses to constant stimuli are more veridical. On top of this, temporal following rates tend to decrease as one ascends the auditory hierarchy, meaning that the comparison between dynamic and stationary responses will be differently affected in different brain areas. As a result, the dynamic/stationary balance is expected to change as you ascend the hierarchy, and I would expect this to directly affect the results observed in this study.

It is not trivial to extrapolate from what we know about temporal following in the cortex to know exactly what the expected effect would be on the authors' results. As a first-pass control, I would strongly suggest incorporating into the authors' filterbank model a range of realistic temporal following rates (decreasing at higher levels), and spatially and temporally average these responses to get modelled cerebral blood flow measurements. I would want to know whether this model showed similar effects as in Figure 2. From my guess about what this model would show, I think it would not predict the effects shown by the authors in Figure 2. Nevertheless, this is an important issue to address and to provide control for.

(3) I do not agree with the equivalence that the authors draw between the statistical stationarity of sounds and their classification as foreground or background sounds. It is true that, in a common foreground/background situation - speech against a background of white noise - the foreground is non-stationary and the background is stationary. However, it is easy to come up with examples where this relationship is reversed. For example, a continuous pure tone is perfectly stationary, but will be perceived as a foreground sound if played loudly. Background music may be very non-stationary but still easily ignored as a background sound when listening to overlaid speech. Ultimately, the foreground/background distinction is a perceptual one that is not exclusively determined by physical characteristics of the sounds, and certainly not by a simple measure of stationarity. I understand that the use of foreground/background in the present study increases the likely reach of the paper, but I don't think it is appropriate to use this subjective/imprecise terminology in the results section of the paper.

(4) Related to the above, I think further caveats need to be acknowledged in the study. We do not know what sounds are perceived as foreground or background sounds by ferrets, or indeed whether they make this distinction reliably to the degree that humans do. Furthermore, the individual sounds used here have not been tested for their foreground/background-ness. Thus, the analysis relies on two logical jumps - first, that the stationarity of these sounds predicts their foreground/background perception in humans, and second, that this perceptual distinction is similar in ferrets and humans. I don't think it is known to what degree these jumps are justified. These issues do not directly affect the results, but I think it is essential to address these issues in the Discussion, because they are potentially major caveats to our understanding of the work.

Reviewer #1 (Public review):

The ventral nerve cord (VNC) of organisms like Drosophila is an invaluable model for studying neural development and organisation in more complex organisms. Its well-defined structure allows researchers to investigate how neurons develop, differentiate, and organise into functional circuits. As a critical central nervous system component, the VNC plays a key role in controlling motor functions, reflexes, and sensory integration.

Particularly relevant to this work, the VNC provides a unique opportunity to explore neuronal hemilineages-groups of neurons that share molecular, genetic, and functional identities. Understanding these hemilineages is crucial for elucidating how neurons cooperate to form specialized circuits, essential for comprehending normal brain function and dysfunction.

A significant challenge in the field has been the lack of developmentally stable, hemilineage-specific driver lines that enable precise tracking and measurement of individual VNC hemilineages. The authors address this need by generating and validating a comprehensive, lineage-specific split-GAL4 driver library.

Strengths and weaknesses:

The authors select new marker genes for hemilineages from previously published single-cell data of the VNC. They generate and validate specific and temporally stable lines for almost all the hemilineages in the VNC. They successfully achieved their aims, and their results support their conclusions. This will be a valuable resource for investigating neural circuit formation and function.

Comments on revisions:

The manuscript has been amended, and the points raised by the reviewers have been addressed.

DOI: 10.1038/s41586-025-08993-1

Resource: (DSMZ Cat# ACC-305, RRID:CVCL_0045)

Curator: @dhovakimyan1

SciCrunch record: RRID:CVCL_0045

What is this?

Reviewer #1 (Public review):

Summary:

Oor et al. report the potentially independent effects of the spatial and feature-based selection history on visuomotor choices. They outline compelling evidence, tracking the dynamic history effects based on their clever experimental design (urgent version of the search task). Their finding broadens the framework to identify variables contributing to choice behavior and their neural correlates in future studies.

Strengths:

In their urgent search task, the variable processing time of the visual cue leads to a dichotomy in choice performance-uninformed guesses vs. informed choices. Oor et al. did rigorous analyses to find a stronger influence of the location-based selection history on the uninformed guesses and a stronger influence of the feature-based selection history on the informed choices. It is a fundamental finding that contributes to understanding the drivers of behavioral variance. The results are clear, and the authors convincingly addressed all previously raised concerns, strengthening their conclusions.

Reviewer #1 (Public review):

Summary:

This is a very well-written paper presenting interesting findings related to the recovery following the end-Permian event in continental settings, from N China. The finding is timely as the topic is actively discussed in the scientific community. The data provides additional insights into the faunal, and partly, floral global recovery following the EPE, adding to the global picture.

Strengths: The conclusions are supported by an impressive amount of sedimentological and paleontological data (mainly trace fossils) and illustrations.

Weaknesses: [eliminated in revision]

Reviewer #1 (Public review):

Summary:

The paper by Papagiannakis et al is an elegant, mostly observational work detailing observations that polysome accumulation appears to drive nucleoid splitting and segregation. Overall I think this is an insightful work with solid observations.

Strengths:

The strengths of this paper are the careful and rigorous observational work that leads to their hypothesis. They find the accumulation of polysomes correlates with nucleoid splitting, and that the nucleoid segregation occurring right after splitting correlates with polysome segregation. These correlations are also backed up by other observations:

(1) Faster polysome accumulation and DNA segregation at faster growth rates.<br /> (2) Polysome distribution negatively correlating with DNA positioning near asymmetric nucleoids.<br /> (3) Polysomes form in regions inaccessible to similarly sized particles.

These above points are observational, I have no comments on these observations leading to their hypothesis.

Comments on revisions:

The authors have satisfied all of my concerns.

for - Medium article - cogress - Part 1 - progress trap - James Gien Wong - definition - cogress - to - Medium article cogress - Part 2 - progress trap - James Gien Wong - https://hyp.is/t8FhpDGAEfC4J7f0NEFujg/medium.com/@gien_SRG/human-cogress-part-2-d6fd075a55c7 - to - Stop Reset Go hypothesis annotations - progress trap - Ronald Wright - https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=ronald+wright - General - https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=progress+trap

for - definition - cogress - Medium article - Cogress - Part 2 - Stop Reset Go - Deep Humanity - James Gien Wong - from - Medium article - Cogress - Part 1 - Stop Reset Go - Deep Humanity - James Gien Wong - https://hyp.is/_Nyg2DF_EfCBeu_iuDroYg/medium.com/@gien_SRG/human-cogress-part-1-5159a575e1c4 - to - Stop Reset Go hypothesis annotations - progress trap - Ronald Wright - https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=ronald+wright - General - https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=progress+trap

Reviewer #1 (Public review):

Summary:

This manuscript is a focused investigation of the phosphor-regulation of a C. elegans kinesin-2 motor protein, OSM-3. In C-elegans sensory ciliary, kinesin-2 motor proteins Kinesin-II complex and OSM-3 homodimer transport IFT trains anterogradely to the ciliary tip. Kinesin-II carries OSM-3 as an inactive passenger from the ciliary base to the middle segment, where kinesin-II dissociates from IFT trains and OSM-3 gets activated and transports IFT trains to the distal segment. Therefore, activation/inactivation of OSM-3 plays an essential role in its ciliary function.

Strengths:

In this study, using mass spectrometry, the authors have shown that the NEKL-3 kinase phosphorylates a serine/threonine patch at the hinge region between coiled coils 1 and 2 of an OSM-3 dimer, referred to as the elbow region in ubiquitous kinesin-1. Phosphomimic mutants of these sites inhibit OSM-3 motility both in vitro and in vivo, suggesting that this phosphorylation is critical for the autoinhibition of the motor. Conversely, phospho-dead mutants of these sites hyperactivate OSM-3 motility in vitro and affect the localization of OSM3 in C. elegans. The authors also showed that Alanine to Tyrosine mutation of one of the phosphorylation rescues OS-3 function in live worms.

Weaknesses:

Collectively, this study presents evidence for the physiological role of OSM-3 elbow phosphorylation in its autoregulation, which affects ciliary localization and function of this motor. Overall, the work is well performed, and the results mostly support the conclusions of this manuscript. During revision, the authors further supported conclusions and ruled out alternative explanations by filling some logical gaps with new experimental evidence and in-text clarifications.

Comments on revisions: I have no additional comments or concerns.

Reviewer #1 (Public review):

Summary:

Ma & Yang et al. report a new investigation aimed at elucidating one of the key nutrients S. Typhimurium (STM) utilizes with the nutrient-poor intracellular niche within macrophage, focusing on the amino acid beta-alanine. From these data, the authors report that beta-alanine plays important roles in mediating STM infection and virulence. The authors employ a multidisciplinary approach that includes some mouse studies, and ultimately propose a mechanism by which panD, involved in B-Ala synthesis, mediates regulation of zinc homeostasis in Salmonella.

Strengths and weaknesses:

The results and model are adequately supported by the authors' data. Further work will need to be performed to learn whether the Zn2+ functions as proposed in their mechanism. By performing a small set of confirmatory experiments in S. Typhi, the authors provide some evidence of relevance to human infections.

Impact:

This work adds to the body of literature on the metabolic flexibility of Salmonella during infection that enable pathogenesis.

Reviewer #2 (Public review):

Summary:

In contrast to the recent findings reported by Schuster S et al., this brief paper presents evidence suggesting that the stumpy form of T. brucei is likely the most pre-adapted form to progress through the life cycle of this parasite in the tsetse vector.

Strengths:

One significant experimental point is that all fly infection experiments are conducted in the absence of "boosting" metabolites like GlcNAc or S-glutathione. As a result, flies infected with slender trypanosomes present very low or nonexistent infection rates. This provides important experimental evidence that the findings of Schuster S and colleagues may need to be revisited.

In the revised submission the authors also compared trypanosome midgut infection levels in tsetse flies when either young (teneral) or mature adult flies received infected bloodmeals, with or without 60 mM GlcNAc. The data clearly show that, unlike in teneral flies, the addition of GlcNAc to the trypanosome-infected bloodmeal does not enhance midgut infection in mature adult flies. This is now convincingly demonstrated in Figure 2 and provides strong experimental support for the suggestion that the effect reported by Schuster S. et al. may have been influenced by both fly age and the inclusion of metabolic "boosters" in the bloodmeal.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors performed an integration of 48 scRNA-seq public datasets and created a single-cell transcriptomic atlas for AML (222 samples comprising 748,679 cells). This is important since most AML scRNA-seq studies suffer from small sample size coupled with high heterogeneity. They used this atlas to further dissect AML with t(8;21) (AML-ETO/RUNX1-RUNX1T1), which is one of the most frequent AML subtypes in young people. In particular, they were able to predict Gene Regulatory Networks in this AML subtype using pySCENIC, which identified the paediatric regulon defined by a distinct group of hematopoietic transcription factors (TFs) and the adult regulon for t(8;21). They further validated this in bulk RNA-seq with AUCell algorithm and inferred prenatal signature to 5 key TFs (KDM5A, REST, BCLAF1, YY1, and RAD21), and the postnatal signature to 9 TFs (ENO1, TFDP1, MYBL2, KLF1, TAGLN2, KLF2, IRF7, SPI1, and YXB1). They also used SCENIC+ to identify enhancer-driven regulons (eRegulons), forming an eGRN, and found that prenatal origin shows a specific HSC eRegulon profile, while a postnatal origin shows a GMP profile. They also did an in silico perturbation and found AP-1 complex (JUN, ATF4, FOSL2), P300, and BCLAF1 as important TFs to induce differentiation. Overall, I found this study very important in creating a comprehensive resource for AML research.

Strengths:

(1) The generation of an AML atlas integrating multiple datasets with almost 750K cells will further support the community working on AML.

(2) Characterisation of t(8;21) AML proposes new interesting leads.

Weaknesses:

Were these t(8;21) TFs/regulons identified from any of the single datasets? For example, if the authors apply pySCENIC to any dataset, would they find the same TFs, or is it the increase in the number of cells that allows identification of these?