Reviewer #1 (Public review):

[Editors' note: The revised manuscript addressed the concerns of both reviewers, who have concluded that the manuscript is convincing and important. The manuscript can move towards the Version of Record.]

Summary:

This study is built on the emerging knowledge of trained immunity, where innate immune cells exhibit enhanced inflammatory responses upon challenged by a prior insult. Trained immunity is now a very fast-evolving field and has been explored in diverse disease conditions and immune cell types. Earhart and the team approached the topic from a novel angle and was the first to explore a potential link to the complement system.

The study focused on the central complement protein C3 and investigated how its signalling may modulate immune training in alveolar macrophages. The authors first performed in vivo experiments in C57BL mouse models to observe the presence of enhanced inflammation and C3a in BAL fluid following immune training. These changes were then compared with those from C3-deficient mice, which confirmed the involvement of C3a. This trained immunity was further validated in ex vivo experiments using primary alveolar macrophage, which was blunted in C3-deficiency, and, intriguingly, rescued by adding exogenous C3 protein, but not C3a. The genetic-based findings were supported by pharmacological experiments using the C3aR antagonist SB290157. Mechanistically, transcriptomic analyses suggested the involvement of metabolism-linked, particularly glycolytic, genes, which was in agreement with an upregulation of glycolytic flux in WT but not C3-deficient macrophages.

Collectively, these data suggest that C3, possible through engaging with C3aR, contributes to trained immunity in alveolar macrophages.

Strengths:

The conclusions reached were well supported by in vivo and ex vivo experiments, encompassing both genetic-knockout animal models and pharmacological tools.

The transcriptomic and cell metabolism studies provided valuable mechanistic insights.

Weaknesses:

For the in vivo experiments, the histopathological and other inflammatory markers (Fig 1.) were not directly linked to alveolar macrophages by experimental evidence. Other innate immune cells (e.g. dendritic cells, neutrophils) and endothelial cells could also be involved in immune training and contribute to the pathological outcomes. These cells were not examined or mentioned in the study.

For the ex vivo experiments assessing immune training in alveolar macrophages, only the release of selected inflammatory factors were measured. Macrophage activities constitute multiple aspects (e.g. phagocytosis, ROS production, microbe killing), which should also be considered to better depict the effect of trained immunity.

The proposed mechanism of C3 getting cleaved intracellularly then binding to lysosomal C3aR need to be further supported by experimental evidence.

There was an absence of any validation in human-based models.

Comments on the revised version.

The revised manuscript now encompasses a much wider scope and stronger evidence.

The authors have included the re-analysis of a recently published dataset of human volunteers who received aerosolized BCG exposure compared to saline. Although not proven causality, this data helped strengthen the human relevance of the findings presented in this research and directly rationalized the decision to focus on Ams. The persistence of elevated C3/C3aR1 expression to day 7 further supports the idea that complement‑associated reprogramming is not merely an acute inflammatory phenomenon. Whilst it may be outside of the scope of this current study, it would be helpful to clarify in future studies whether other complement components (C5, factor B, factor D) were also modulated in the dataset, to contextualize whether the response is uniquely centered on C3/C3aR1 or part of a broader complement activation program.

The authors have also expanded the functional characterization of trained alveolar macrophages by including phagocytosis and ROS generation measurements. It is intriguing that HKPA training did not markedly alter the phagocytosis and ROS production by alveolar macrophages relative to the control group, however, C3 deficiency significantly dampened these responses in both trained and untrained groups. This reduction is in congruence with the cytokine release data, but there could be other factors involved.

I appreciate the careful revision and much more expansive mechanistic interpretation regarding intracellular C3aR, and that further studies are underway to better understand the cell type-specific, subcellular localization of C3a-C3aR in alveolar macrophages.

Overall, the revised data interpretation and discussion significantly improved in balance and contextualization of the findings.

Reviewer #2 (Public review):

Earhart et al. investigated the role of the complement system in trained innate immunity (TII) in alveolar macrophages (AM). They used a WT and C3 knockout murine model primed with locally administered heat-killed P. aeruginosa (HKPA). Additionally, they employed ex vivo AM training models using C3 knockout mice, where reconstitution of C3 and blockade of C3R were performed. The study concluded that the C3-C3R axis is essential for inducing TII in macrophages in the ex vivo model. The manuscript is well-written and easy to follow.

Comments on revised version.

My concerns have been addressed, and the provided data is convincing supporting the manuscript's claims.

Reviewer #1 (Public review):

The investigators elegantly utilized single-cell co-assay of RNA and ATAC seq to unveil the heterogeneous gene regulatory networks in Ewing sarcoma. The authors should be commended on their ability to identify multiple unique modules of gene regulation of Ewing sarcoma utilizing complex computational methods between numerous Ewing sarcoma cell lines. Additionally, they complimented their single cell findings with xenografts as well as primary Ewing sarcoma patient tumors - validating the intratumoral heterogeneous gene regulatory networks of Ewing sarcoma. More importantly, they have revealed that exogenous TGF-B may modify these distinct epigenetic and transcriptional signatures within Ewing sarcoma tumors. Overall, the manuscript highlights an important discovery of the heterogenous gene regulatory programming of Ewing sarcoma and further highlights the role that TGFB plays within the tumor microenvironment of Ewing sarcoma. There are some areas of ambiguity that require clarification to increase the impact of the manuscript.

Comments on the latest revision:

The responses to my review were appropriate and my comments were all addressed.

Reviewer #2 (Public review):

Summary:

This work by Waltner, et. al. provides a comprehensive single cell multiomics analysis of plasticity in gene regulatory networks present in Ewing sarcoma using single cell RNA-sequencing (scRNA-seq) and single cell assay for transposase accessible chromatin with sequencing (scATAC-seq). They find that Ewing sarcoma cell lines models have distinct patterns of chromatin accessibility compared to non-Ewing sarcoma models, and that there is significant variability across Ewing sarcoma cell lines, and sometimes within a single cell line. These differences across models are linked to 3 distinct gene regulatory modules, 2 of which are present across the range of model systems studied here. The first modules present across models is activated when the fusion is expressed and includes genes enriched for the known EWSR1::FLI1 response element, GGAA microsatellites along with other neural crest transcription factors. The other module primarily consists of genes repressed by EWSR1::FLI1, which are activated in EWSR1::FLI1-low states. Interestingly, EWSR1::FLI1-low cells have already been tied to more migratory and metastatic phenotypes and the data here suggest these cells are more responsive to external signals from TGF-β and this may be mediated through FOSL2-mediated gene regulation. This is a technically rigorous study, with a variety of different analytical techniques used to address similar questions and this approach elevates confidence in the answers provided. This is further strengthened by the diverse set of model systems used, including patient-derived cell lines, cell line xenograft models, patient-derived xenografts, mining available single cell data from patient samples, and validation of the gene modules identified in a larger set of patient microarray samples. In whole, this study provides a valuable resource for understanding heterogeneity, plasticity, and gene expression networks in Ewing sarcoma. This may be a useful resource for future studies of metastatic disease and provide a framework for similar questions in other fusion-driven sarcomas.

Comments on revised version.

The authors have addressed comments from my prior review. Thank you!

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review: Definitions and terminology have been made more precise. Additional analysis confirms the conclusions previously stated and clarifies concerns about the computational tractability of the method.]

Summary:

The manuscript puts forward a statistical method to more accurately report the significance of correlations within data. The motivation for this study is two-fold. First, the publication of biological studies demands the report of p-values, and it is widely accepted that p-values below the arbitrary threshold of 0.05 give the authors of such studies justification to draw conclusions about their data. Second, many biological studies are limited by the number of replicate samples that are feasible, with replicates of less than 5 typical. The authors report a statistical tool that uses a permute-match approach to calculate p-values. Notably, the proposed method reduces p-values from around 0.2 to 0.04 as compared to a standard permutation test with a small sample size. The approach is clearly explained, including detailed mathematical explanations and derivations. The advantage of the approach is also demonstrated through analysis of computer-generated synthetic data with specified correlation and analysis of previously published data related to fish schooling. The authors make a clear case that this method is an improvement over the more standard approach currently used and also demonstrate the impact of this methodology on the ability to obtain p-values that are the standard for biological research. Overall, this paper is very strong. While the subject matter seems somewhat specialized, I would make the case that this will be an important study that has broad general interest to readers. The findings are very general and applicable to many research contexts. Experimentalists also want to report accurate p-values in their work and better understand how these values are calculated. Although I believe the previous statement is true, I am not sure that many research groups doing biological work are reading specialized statistics journals regularly. Therefore, a useful and broadly applicable statistical tool is well placed in this journal.

Strengths:

The proposed method is broadly applicable to many realistic datasets in many experimental contexts.

The power of this method was demonstrated with both real experimental data and "synthetic" data. The advantages of the tool are clearly reported. The zebrafish data is a great example dataset.

The method solves a real-life problem that is frequently encountered by many experimental groups in the biological sciences.

The writing of the paper is surprisingly clear, given the technical nature of the subject matter. I would not at all consider myself a statistician or mathematician, but I found the text easy to follow. The authors did an impressive job guiding the reader through material that would often be difficult to grasp. The introduction was also well-written and clearly motivated the goals of the study.

Reviewer #2 (Public review):

Summary:

This paper presented a hypothesis testing procedure for the independence of two time-series that was potentially suitable for nonlinear dependence and for small-sample cases. This should bring potential benefits for biology data.

Strengths:

The test offers good flexibility for different kinds of dependence (through adjusting \rho) and seems to have good finite sample performance compared to the literature. The justification regarding the validity of the test procedure is clear.

Reviewer #1 (Public review):

In this study, Otgonbaatar and colleagues investigate the stability of Armadillo (Arm) during Drosophila development using a creative tandem fluorescent protein timer approach via endogenous tagging of Arm. The tagging strategy allows for newly synthesised and longer-term stabilised Arm pools to be distinguished from one another. Specifically, the authors address the functional relevance of and mechanism behind the stabilisation of junctional Arm during dorsal closure.

The authors show that Arm is stabilised at the leading edge during dorsal closure. Using a sophisticated optogenetics approach, which allows for acute perturbations, they show that stabilised Arm is functionally required for dorsal closure. Increasing Wg (by overexpression) did not affect dorsal closure or Arm stability, in contrast to Axin overexpression, which reduces Wg/Arm signalling. In line with canonical signalling control of Arm levels being critical, stabilisation of Arm by N-terminal mutations disrupted dorsal closure. However, the same deletion is also expected to affect interaction with alpha-catenin. Co-localisation with E-cadherin and actin suggests a junctional role of leading-edge localised Arm. Optogenetic targeting of alpha-catenin points towards a key role of adherence junctions in dorsal closure. Allele replacement with mutant variants of Arm to affect adherence junction complex assembly further indicates an important contribution of coupling between Arm and alpha-catenin. Using overexpression approaches, the authors suggest that Dsh and Jnk contribute to dorsal closure.

This microscopy- and optogenetics-based study is generally well-conducted and provides strong evidence for stabilised Arm during dorsal closure, as well as its functional importance. This is an important discovery relevant to morphogenesis and potentially mechanotransduction. From a technical perspective, the validated beta-catenin timer provides a valuable tool for the field. The timer has revealed that Arm stabilisation does not coincide with Wg stripes, suggesting a Wg-independent stabilisation mechanism that may instead depend on adherence junction assembly, especially the interaction of Arm with alpha-catenin. However, as N-terminal deletion within Arm and Axin overexpression also disrupted dorsal closure, substantial ambiguity remains. Can suppression of the beta-catenin degradation machinery be ruled out as a regulatory mechanism? An expansion of ArmTimer mutant variants could contribute to testing the authors' conclusion further. Structural insights into junctional interactions involving Arm (e.g., 10.1074/jbc.M114.554709) could, for example, be used for further functional exploration by mutagenesis. The direct mechanistic impact of JNK and its potential link to Dsh in dorsal closure remains less compelling.

In summary, this is a highly relevant and important study, potentially pointing to a novel stabilisation mechanism of beta-catenin in development. Further corroboration of the mechanism, to test whether it is indeed distinct from canonical signalling, would be needed to support the conclusions.

Reviewer #2 (Public review):

Summary:

Otgonbaatar et al. sought to investigate β-catenin/Arm protein lifetime and stabilization dynamics in vivo during embryonic development. To address this question, the authors developed an endogenous tandem fluorescent protein timer (tFP) system that enables the visualization of newly synthesized versus long-lived Arm protein in vivo. Using this approach, the authors sought to determine where stabilized Arm accumulates during development and how it contributes to dorsal closure.

Strengths:

A major strength of the study is the development and application of the endogenous Arm timer system, which provides a powerful approach for monitoring protein stabilization dynamics in living tissues. Using this system, the authors unexpectedly found that the strongest Arm stabilization occurs not in Wnt signaling regions, but at the leading edge cells during dorsal closure. The study combines quantitative live imaging, optogenetic perturbation, genetic analysis, and structure-function approaches to demonstrate that stabilized junctional Arm interacts with α-catenin and contributes to tissue mechanics required at the leading edge for dorsal closure. Particularly compelling is the combination of multiple perturbations, including optogenetic disruption of Arm or α-catenin, Axin overexpression, and Arm mutants, which produce consistent dorsal closure defects.

Some conclusions are generally supported by the presented data. The work provides strong evidence that Arm plays an important role in dorsal closure. The identification of a requirement for the Dishevelled DEP domain and JNK signaling supports a non-canonical regulatory mechanism controlling dorsal closure.

Weaknesses:

(1) Conclusions are made regarding force transmission;(however, no experimental evidence is provided to support these conclusions.

(2) The conclusion was made that Wingless does not affect dorsal closure. However, this was based solely on Wingless overexpression in the amnioserosa, and the level of Wingless expression was not quantified. One possibility is that this level was not sufficient to see an effect. Alternatively, Wingless may have a role in migrating epithelium rather than the amnioserosa. Indeed, it is known that wingless mutants display a defect in dorsal closure.

(3) The effect of JNK knockdown on Arm localization maybe is indirect, and due to a secondary consequence on disruption of epithelial morphology rather than a direct effect of JNK on Arm.

(4) Some conclusions rely on overexpression-based perturbations (e.g., Axin or Arm mutants), which may not fully recapitulate endogenous physiological regulation.

(5) The Arm timer was not able to detect Wingless-dependent Arm stabilization in stripes. This finding demonstrates that the timer is not sensitive enough to thoroughly analyze Arm dynamics.

Overall, this work provides important conceptual advances in understanding junctional β-catenin/Arm function during dorsal closure. The endogenous fluorescent timer approach will likely be broadly useful to the community for studying protein stability dynamics in vivo, and the findings expand current views of β-catenin by highlighting its mechanical and junctional functions during tissue morphogenesis.

Reviewer #1 (Public review):

Summary:

In the paper, the authors propose a new RNA velocity method, TSvelo, which predicts the transcription rate linearly based on the expression of RNA levels of transcription factors. This framework is an extension of its recent work TFvelo by including unspliced reads and designing a coherent neuralODE framework. Improved performance was demonstrated in six diverse datasets.

Strengths:

Overall, this method introduces innovative solutions to link cell differentiation and gene regulation, with a balance between model complexity (neuralODE) and interpretability (raw gene space).

Comments on revised version:

I thank the authors for further revision, and I do not have any other concerns. I believe it is an important contribution to this field of trajectory inference and gene regulation.

Reviewer #3 (Public review):

Despite the abundance of RNA velocity tools, there are still major limitations, and there is strong skepticism about the results these methods lead to. In this paper, the authors try to address some limitations of current RNA velocity approaches by proposing a unified framework to jointly infer transcriptional and splicing dynamics. The method is then benchmarked on 6 real datasets against the most popular RNA velocity tools.

Comments on revised version:

The Authors addressed my 2 follow-up comments suitably.

Thanks for the time you took addressing them. I have no further comments.

Reviewer #1 (Public review):

Summary:

In this manuscript, Seegren and colleagues demonstrate that in a mouse model of neonatal E. coli meningitis, loss of toll-like receptor 4 (TLR4) in VE-cadherin+ endothelial cells and a subset of meningeal fibroblasts leads to a marked decrease in transcriptional dysregulation across multiple leptomeningeal cell types, a decrease in vascular permeability, and a decrease in macrophage abundance. In contrast, loss of macrophage TLR4 had less pronounced effects. Using cultured wildtype and TLR4-knockout endothelial cells, the authors further demonstrate that TLR4 signaling leads to reversible internalization of the tight junction protein claudin-5, establishing a potential mechanism of increased vascular permeability. Authors also show that claudin-5 internalization is independent of NF-κB. Finally, the authors use RNA-sequencing of wildtype and TLR4-knockout endothelial cells to define the TLR4-dependent cell-autonomous transcriptional response to E. coli.

Comments on revised version.

The authors have considerably improved and strengthened the work through the addition of new experimental data, new data analyses, and modifications to their interpretation. Notably, the authors used additional Cre-reporter mice to clarify that Cdh5-CreER is active in endothelial cells and some meningeal fibroblasts, and thus revised nomenclature and interpretation to acknowledge that the Tlr4fl/-;Cdh5-CreER cKO (Tlr4-VEKO) is not exclusively endothelial. The authors also demonstrated that Tlr4-VEKO does not affect peripheral E.coli burden, but acknowledge that changes to periphery-derived signals (e.g., cytokines) may contribute to observed leptomeningeal phenotypes.

The authors added PCA plots to show similarity in gene expression shifts across biological replicates (mice). This provides support for the claim that Tlr4-VEKO attenuates infection-associated transcriptional changes. With respect to differential expression analysis, I agree with authors that characteristics of individual cells (e.g. heterogeneity) are of interest. I remain concerned, however, that the formal differential analysis strategy appears to consider cells as independent experimental units, which they are not because a single cell cannot be randomly assigned to an experimental group (control or cKO, uninfected or infected). The mouse is the correct experimental unit for a comparison across these groups because it can be randomized. I appreciate that many of the gene expression changes appear consistent across mice (e.g. Figure 1 - Figure supplement 7) and that there are clear infection- and genotype-associated phenotypes in other assays. I would simply caution that the authors' analysis strategy likely leads to a larger number of type I errors (false positives) than is generally accepted; a mixed (hierarchical) model or pseudo-bulk approach would be more appropriate for future studies.

Reviewer #2 (Public review):

Summary:

The authors use a postnatal mouse model of E. coli bacterial meningitis and a mouse brain endothelioma cell line combined with cell type specific gene deletion to study the function of endothelial TLR4, a cell surface receptor that recognizes gram positive bacterial wall components, in the local leptomeningeal (LPM) response with a focus on endothelial barrier breakdown mediated by TLR4. Single cell transcriptional profiling and imaging studies using wholemount preps of the LPM support that LPM endothelial, CD206+ local macrophage and LPM fibroblast and arachnoid barrier cell inflammatory response and is abrogated in endothelial specific KO of TLR4, pointing to a role for endothelial TLR4 in local LPM response. Culture studies using Bend3.1 cells (a mouse brain endothelioma cell line) support a direct role for TLR4 in the bacteria-mediated inflammatory response and in internalization of Cldn5 via the endosomal-lysosomal pathway, resulting in loss of barrier integrity

Strengths:

The local LPM cell response in meningitis and the role of specific LPM cells in inflammation and CNS barrier breakdown has not been extensively studied, despite ample evidence for primary immune response in the meninges in human patients and in animal models. The authors employ a robust, multi-model approach using both in vivo and in vitro models with cell-type specific knockout to study the function of TLR4 in brain endothelial cell response. The authors nicely combine functional barrier assays with IF for junctional localization in their experimental design and they delve into potential mechanisms of Cldn5 internalization using markers of endosomal-lysomal pathway localization. The authors also describe a new type of barrier assay using a streptavidin-coated plates upon which barrier forming cell cultures can be plated, this could be a very useful alternative or complement to other size-selective barrier assays and presumably could work for other barrier forming cell types, like epithelial cells.

Comments on revised version.

In their revision, the authors addressed prior noted weaknesses with new data and analysis. They now show that TLR4-VE-cad cKO mice have a largely similar disease progression as control mice, including increased bacterial burden in the LPM and brain. This underscores that that the reduced vascular leakage and blunted inflammatory response is due to loss of TLR4 response to bacteria on VE-cad recombined cells and not because the mice are protected from meningitis. The authors also performed additional experiments to show that Cldn5 internalization via the endosomal-lysosomal pathway is independent of NFKB signaling. The authors also added in important discussion points about how their results fit into the broader literature on TLR4 in BBB endothelial cell junctional protein localization and prior work on meningitis in global TLR4.

Reviewer #3 (Public review):

Summary:

This study investigates the molecular underpinnings of immune responses in the leptomeninges in neonatal bacterial meningitis. Bacterial meningitis is a major disease burden, particularly for neonates, and it has previously been noted that the meningeal immune environment in infants is permissive to opportunistic infection (Kim et al., Sci Immunol, 2023). There is less known about the contribution of the stromal compartment to meningeal immune responses. Seegren et al. interrogate the role of leptomeningeal endothelium in host defense in E. coli infected neonatal mice using mouse genetic tools to delete the LPS receptor Tlr4 from either endothelial cells/stromal cells (using Cdh5-CreER) or myeloid cells (using LysM-Cre). The authors use snRNAseq, cleared cortical mounts, and in vitro work to define the impact of E. coli infection on leptomeningeal endothelial cells. This study uses a range of innovative techniques to probe the role of the stromal compartment in meningitis. With additional experiments to confirm the specificity of their Cre models, this strengthens the interpretation of the study significantly. The only major weakness is the inability to confirm TLR4 knockout in myeloid cells.

Strengths:

This study makes excellent use of cleared cortical mounts to examine the biology of the leptomeninges, in particular, changes to the endothelium, with unprecedented detail. In combination with high-quality sequencing data provide new insights into the impact of meningitis on the leptomeninges. The data presented by the authors is of very high quality.

The authors have also done substantial work to address my two major comments regarding 1) the specificity of their Cre systems and 2) peripheral impacts of the interventions.

(1) The authors identified and acknowledged some impacts in the leptomeningeal stroma (the relatively high level of recombination in ECs vs FBs presumably reflects a single low dose being given, where other groups have done more aggressive tamoxifen regimens that drive recombination in FBs as well). Given the incomplete recombination in the leptomeningeal FBs, I agree with their conclusion that it is probably endothelial driven. Acknowledging the contributions of other myeloid cells with the L. The Cre-NLS experiments with nuclear markers provided excellent data and had beautiful staining.

(2) The authors did not observe differences in bacterial burden in peripheral organs in either CKO model, suggesting that CNS impacts are not downstream of peripheral bacterial control.

Weaknesses:

(1) The inducible Cre lines used by the authors target peripheral tissues as well as CNS tissues. Although this is mollified by the lack of impact on peripheral disease burden.

(2) The authors were not able to confirm TLR4 knockout in myeloid cells, and this caveat is acknowledged. The lack of response in TLR4 VEKO mice strongly suggests successful conditional knockout.

(3) The cell line model (bEnd.3) is a relatively low fidelity model of BBB endothelial cells. The authors acknowledge this, and it is likely that endothelial cell responses to LPS are highly conserved.

(4) It is perhaps not surprising that Tlr4 is required for meningitis responses with E. coli. However, it is unclear if these findings can be generalised to other, more common, meningitis infections (streptococcal/pneumococcal).

Reviewer #1 (Public review):

Summary:

The authors sequence the transcriptome of three sensory neurons from D. melanogaster to study the cell-cell and animal-animal variability in these cells, with a focus on cell adhesion molecules. The work reports useful cell-specific transcriptomics datasets that will be of great interest to those studying cell types, transcriptomes, neuronal development, and cell surface proteomes. The authors also report large numbers of knockdown data (gene-by-gene or in combinations) and report neuronal wiring and behavioral phenotypes. The manuscript is highly descriptive of the system studied - in a good way, but often over-speculates in rationale or conclusions.

Strengths:

The manuscript is data-rich. The single-cell transcriptomics datasets, not trivial to collect, are a major strength of the work and will prove useful to the field. Also, the biased expression of Dscam is interesting, even though the authors cannot pursue the mechanism or a function for this.

Weaknesses:

The study lacks depth (i.e., mechanism) in explaining observations.

Reviewer #2 (Public review):

Summary:

In this manuscript, dos Santos et al seek to identify cell-specific programs that drive neuronal wiring patterns. They focus on two chemosensory and mechanosensory neurons in the Drosophila nervous system, as they both display stereotyped connectivity in the ventral nerve cord. Single-neuron RNA sequencing identified cell surface molecules that distinguish the sensory neurons and may instruct their respective wiring patterns. They functionally test several of these candidates and observe miswiring phenotypes upon knockdown experiments. Additionally, they attempt to miswire the chemosensory neurons. Overall, this manuscript addresses an important question about how neurons identify appropriate synaptic partners through precise cell surface molecular codes. However, there are significant deficiencies in the experimental logic and rigor, and the manuscript can be very difficult to digest.

Strengths:

The use of two sensory neurons with stereotyped connectivity is a significant strength, as this enables the authors to identify genes that are required for wiring. Additionally, analyzing the transcriptomes of single neurons repeatedly could potentially be a robust approach to identifying cell-specific cell-surface molecules that drive wiring.

Weaknesses:

(1) The authors perform RNAseq for single identifiable neurons, as opposed to neuronal subclasses, which has been reported before. It would be beneficial to elaborate on the significance of using single neurons for answering the scientific question. This is briefly mentioned toward the end of one of the results subsections: "Repeated RNA sequencing of an identifiable neuron seeks to address the fundamental nature of variability in connectomics, axonal branching, and cellular identity." But this should be in the Introduction.

(2) The authors chose the P14 pupal stage for one of the analyses. It is not clear why this specific stage is chosen. Does pSc and aPa connectivity occur at this stage?

(3) This reviewer is confused as to why looking at differentially expressed CSMs between pupal and adult stages of two different neurons is useful. This does not seem like an appropriate comparison. This data might be better in the supplemental material, especially given the lack of precise age synchronization across pupal samples (as reported).

(4) It is very difficult to follow the logic because the manuscript seems to jump around between different results and lacks a compelling through line.

(5) "Single cell sequencing of the same neuron reveals transcriptome precision": What are the controls here? An aPa neuron is shown in Figure 3 as an example of a different neuronal subtype, but were other factors (e.g., lack of Repo expression) checked to ensure that samples were not contaminated?

(6) "However, whether any of these exon 6 or 9 splicing specificities are biologically significant can only be determined using exon 6 and 9 isoform-specific RNAi." The authors could alternatively use CRISPR techniques to target specific isoforms that they hypothesize might be important for neural wiring, enabling them to assess isoform-specific wiring defects.

(7) In the section "The set of cell surface receptors required to wire up the pSc mechanosensory neuron": Several previous subsections of the Results use RNAseq to identify molecules expressed in pSc neurons across different stages. It's unclear why the authors did not start with the identified list of candidate cell surface receptors identified in their RNAseq experiments.

a. Were any of the genes screened the same as those identified by the authors as differentially expressed in pSc mechanosensory neurons, either across developmental stage (pupa vs. adult) or across neuronal subtype (pSc vs. Gr59d)? If so, it would be helpful to state this here. (They do mention later on that five CSMs identified were more highly expressed in pSc than aPa. However, changes in expression across developmental stages within the pSc neuron would still be helpful to comment on, especially since the authors identified greater transcriptomic differences across developmental stages than they did between different neuronal subtypes.)

b. The 39 genes not expressed in pSc neurons served as their negative control, but the average axonal targeting grade was 2.3 (between moderate and severe). This calls into question the use of this method as an appropriate measure of whether a gene expressed by pSc neurons is truly required for proper axon targeting; there seems to be a strong probability of significant off-target effects. Performing a global knockdown and cell-specific rescue could potentially complement these experiments and serve as a stronger indicator of candidate receptors' roles in pSc-specific axon targeting.

(8) It seems as though the purpose of the experiments described in the last results subsection ("Re-wiring the Gr59 chemosensory neuron") is to redirect the Gr59d neuron toward the pSc neuron's axonal targeting phenotype. However, the authors do not state whether they were able to do so effectively (i.e., whether or not there were significant differences between the rewired Gr59d neuron and the pSc neuron). This leaves the story unfinished.

(9) At the end of the discussion, the authors state that "...if a Gr59d chemosensory neuron is functionally rewired to a pSc mechanosensory circuit, activation of the Gr59d neuron using a bitter tastant molecule should elicit a grooming (mechanosensory) response...". The authors should attempt this experiment, especially given that they have developed the PXGS technique.

Reviewer #1 (Public review):

Summary:

The authors present evidence that during acetaminophen (APAP)-induced liver injury, mid-zone hepatocytes activate an integrated stress response (ISR) program via Atf4 and Chop, leading to induction of Btg2. This program suppresses proliferation in the early phase of injury, prioritizing hepatocyte survival before regeneration begins. The study uses spatial transcriptomics, immunohistochemistry, CUT&RUN, and AAV overexpression to support this model.

Strengths:

(1) Innovative use of spatial transcriptomics to capture zonal differences in hepatocyte stress responses.

(2) Identification of a mid-zone specific ISR signature and candidate downstream regulator Btg2

(3) Functional experiments with Atf4-Chop-Btg2 modulation provide causal evidence linking ISR activation to proliferation inhibition.

(4) Conceptually significant model that hepatocytes actively balance survival and regeneration dynamically in a zone-specific manner.

(5) Multiple models validation of the finding

(6) The functional link of such zone2 phenotype is added.

Reviewer #2 (Public review):

The manuscript reports protection of midlobular hepatocytes from APAP toxicity by activation of Atf4-CHOP (Ddit3)-mediated cell cycle arrest and stress response. The authors acknowledge that their finding is unexpected because CHOP typically induces cell death. Therefore, they functionally validate several aspects of the proposed Atf4-CHOP mechanism. Along these lines, the mitigation of APAP toxicity by AAV expression of Atf4 or Btg2, the latter identified as CHOP effector, is impressive. Whether Atf4 indeed acts through CHOP and whether midlobular hepatocytes are protected because of cell cycle arrest is less clear. These and other criticisms are described in the following.

Major points:

(1) Starting with the basics, one wonders why midlobular hepatocytes manage to mount a defensive response to APAP, but PC hepatocytes don't. Is this because midlobular hepatocytes express the relevant Cyps (2e1 but also 1a2 and 3a11) at lower levels, which mitigates toxicity and buys them time? This would be supported by F2A but not by F3B, at least not for the most important Cyp2e1. A moderate difference is shown for Cyp1a2 expression in F3D but is that enough to explain the different fates? Or are additional post-transcriptional effects on these Cyps at work? The difference in baseline Cyp2e1 expression between F2A and F3B remains unexplained after revision.

(2) The evidence presented in support of cell cycle arrest of midlobular hepatocytes is not fully convincing: there is no overt difference in S and G2/M gene scores in F2F; the marker genes used for S phase and G1 to S progression in F2G are unusual. Along these lines, one wonders if spatial transcriptomics confirmed the Ki67 immunostaining results in F1 also for specific zones, not only overall as shown in F2E? In contrast to the revised discussion, the abstract does not reflect that limited evidence for a cell cycle arrest in pericentral hepatocytes was found.

(3) The authors conclude in line 364 that halting of proliferation by Btg2 favors survival, which raises the question of whether Btg2 knockout causes death in midlobular hepatocytes in F6K. Data addressing this question, that is, localization and extent of tissue necrosis and ALT levels after APAP, are missing. The efficiency of knockout of Btg2 is also not given. Additional Btg2 knockout data support its proposed role in the revised manuscript.

(4) Related to the previous question, the BTG2 immunostaining in F6F is not convincing when compared to F6D. One also wonders if it is necessary to apply APAP to find induction of BTG2 by AAV-Ddit3? The BTG2 immunostaining remains weak, not only in in F6F but now also in F6D of the revised manuscript, which together with lack of high-resolution immunostaining of AAV-Ddit3-induced BTG2 in the absence of APAP results in limited support for the conclusion that APAP promotes nuclear localization of BTG2.

(5) Related to the previous question, the proposed Atf4-Ddit3 axis is challenged by the lack of midlobular induction of Atf4 in the APAP scRNA-seq data published by another group presented in S4F and G. Further analysis of AAV-Atf4 samples generated for F5 could address if it is really Atf4 that acts on Ddit3 in APAP toxicity. The extended list of transcription factors (from 30 to 50) includes Atf4 but direct evidence for an interaction with Ddit3 is missing from the revised manuscript.

(6) Related to the previous question, the ATF4 immunostaining in F5A doesn't look convincing, with many brown pigments appearing to be outside of the nucleus. The ATF4 immunostaining after APAP challenge remains weak.

(7) It is not ruled out that AAV expression of Atf4 or Btg2 reduces hepatocyte sensitivity to APAP by affecting expression of the Cyps needed for activation. In other words, does AAV-Atf4 or AAV-Btg2 change the expression of any of the Cyps relevant to APAP in the 3 weeks before APAP application (F5B)? S5A of the revised manuscript rules out loss of Cyp2e1 expression as a confounding factor.

(8) It is laudable that the authors tried to extend their findings to human by using snRNA-seq data from a published study (line 391) but it is unclear why they didn't analyze all 10 patients in that study but instead focused on 2 and stated that this small sample number prevented drawing definitive conclusions and could therefore only be mentioned in the discussion. The revised manuscript continues to focus on rare spatial transcriptomics analyses of patients with APAP toxicity although more snRNA-seq analyses of such patients are available which should also allow for analysis of hepatocyte zonation.

Comments on revised version.

After revision, the proposed role of Btg2 is substantiated but it remains unclear why midlobular hepatocytes don't proliferate after APAP challenge and whether the observed protective effects are indeed mediated by Atf4 acting directly through CHOP.

Reviewer #1 (Public review):

In this study, Hossain et al. investigated the role of Interleukin-2-inducible T cell kinase (ITK) in autoimmune lung injury, demonstrating that ITK-deficient (Itk-/-) mice are protected against pristane-induced pulmonary hemorrhage (PH). The authors suggest that this protection correlates with a significant remodeling of the T cell compartment in Itk-/- mice, including increased frequency of memory-like CD4+ and CD8+ T cells (CD44⁺CD62L⁺) as well as higher frequency of Treg populations. Furthermore, adoptive transfer of ITK-deficient Treg isolated from injured ITK-deficient mice confers protection against pulmonary hemorrhage in WT recipients.

Strengths:

The adoptive transfer of wild-type and Itk-/- Treg populations demonstrates that ITK-deficient Treg can actively rescue pre-existing lung injury and reverse systemic secondary metrics like proteinuria in wild-type recipients, providing proof-of-concept validation for the therapeutic utility of the ITK-Treg axis.

Weaknesses:

A primary limitation of this manuscript is its omission of foundational literature from the Schwartzberg and Littman laboratories, which originally established the indispensable role of IL-2-inducible T-cell kinase (ITK) in proximal T-cell receptor (TCR) signaling dynamics and thymic lineage commitment. Because classic studies demonstrate that ITK is a critical regulator of thymic T cell development and cellular proliferation (PMID: 8777721, 10213685), the authors' claim that "these findings indicate that ITK deficiency skews the T cell compartment toward a memory-like state, establishing a distinct immune baseline that may favor protective and regulatory responses over pathogenic inflammation" is not substantiated by evidence and requires more robust validation.

The exclusive reliance on splenic immunophenotyping is a major limitation, as it fails to capture the local cellular dynamics within the primary organs of injury (the lung and kidney). Evaluating canonical and non-canonical Treg expansion solely in the spleen overlooks the distinct functional programming of tissue-resident subsets. The authors should extend their characterization of regulatory T cell compartments directly to the lungs and draining lymphoid structures.

More importantly, the authors overlook key historical publications that explicitly established ITK as a negative "rheostat" or gatekeeper for regulatory T cell (Treg) differentiation. Specifically, Huang et al. (PMID: 25063868) previously demonstrated that Treg abundance is inversely correlated with ITK expression, and that ITK activity serves as a vital negative tuner of IL-2-driven Foxp3⁺ Treg expansion. Since it is already well-established that suppressing or deleting ITK promotes Treg accumulation and function, and that these cells are intrinsically vital to suppressing systemic autoimmunity, it is unclear how these findings expand upon our existing mechanistic understanding of ITK regulatory biology.

Reviewer #2 (Public review):

Summary:

In this manuscript, Hossaim and colleagues investigate the role of the ITK kinase in modulating inflammation in a pristane-induced lung hemorrhage model. Using a germline ITK KO mouse, they report that loss of ITK skews the T cell compartment toward a memory-like state, expanding Tregs, and conferring protection against alveolar hemorrhage, inflammatory monocyte recruitment, proteinuria, and systemic cytokine elevation. They further show that transfer of ITK-deficient Tregs into wild-type hosts with established disease attenuates injury and shifts the cytokine balance toward resolution, and that ITK-deficient Tregs carry a transcriptional signature enriched for OXPHOS, mTORC1, MYC, and cell-cycle programs. While these observations are interesting for the development of potential immunotherapies, there are several issues with the methodological approach that support the authors' claims, tempering my enthusiasm for this manuscript.

Strengths:

(1) The clinical motivation and potential targeted therapies are relevant.

(2) The murine phenotype seems robust.

Weaknesses:

(1) All loss-of-function experiments are from a global ITK knockout. This is a major limitation and weakness of this study. The protection observed in the intact knockout, therefore, cannot be attributed to Tregs specifically. The Treg-intrinsic claim rests almost entirely on a single adoptive-transfer experiment. In order to show that this effect is Treg-specific, the authors would need to generate a Treg-specific ITK-deficient mouse

(2) In their sufficiency experiment (adoptive Treg cell transfer), donor and/or host cells are not congenically marked, so persistence, lung trafficking, and in vivo expansion of transferred Tregs are not demonstrated.

(3) The authors claim that ITK-deficient Tregs possess enhanced metabolic fitness. This conclusion is based on transcriptional profiling of isolated splenic Tregs from unchallenged mice, yet it concerns lung protection during active disease. A disease-state and ideally lung-relevant transcriptome would more directly support the mechanistic narrative. Additional functional validation would be needed (Seahorse assay, mitochondrial mass/potential, etc). Some of these GSEA programs enriched in ITK-deficient Tregs could reflect a more general proliferative signature.

Reviewer #3 (Public review):

Summary:

Hossain et al. investigate the role of ITK as a central regulator of autoimmune lung injury. They used ITK-deficient mice and the pristane-induced pulmonary hemorrhage (PH) model to show that ITK deficiency confers protection against PH. The adoptive cell transfer experiment suggests a possible role for altered Treg cells in ITK-deficient mice in regulating the inflammatory response in the lungs of pristane-injected mice. This study shows that targeting the ITK axis may be beneficial by reducing systemic inflammatory injury that contributes to poor outcomes in PH.

Strengths:

This study highlights the importance of ITK in regulating pulmonary hemorrhage. The enrichment of Treg cells is known to confer protection in autoimmunity-mediated alveolar damage. However, ITK's involvement in regulating Treg cell function is interesting and could be explored as a novel therapeutic approach for chronic inflammation.

Weaknesses:

The novelty of this study lies in the association between ITK-deficient Tregs and pulmonary hemorrhage in autoimmunity. The weakness of the manuscript is the lack of sufficient experiments to support the claim that ITK-deficient mice show protection specifically mediated by Treg cells, and to demonstrate that ITK-deficient Treg cells are more efficient than WT Treg cells in regulating other immune cells that drive pulmonary damage. The authors performed all the experiments in ITK global knockout mice, in which not only T cells but all other cell types are deficient in ITK. Furthermore, they have not performed any functional analysis to demonstrate the functional differences between WT Treg and ITK-deficient Treg cells, undermining the novelty of this study.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have made minor revisions to address the comments raised in the previous round of review.]

Summary:

This manuscript by Alonso-Caraballo et al, is a novel piece of work that examines the impact of oxycodone self-administration on neural plasticity within paraventricular thalamic (PVT) to nucleus accumbens shell (Shell) pathway - two regions shown to play a key role in cue-induced drug seeking on their own, and whether this plasticity varies based on abstinence period and biological sex.

Strengths:

The authors show using a clinically relevant long-access model of opioid self-administration promotes dependence and acute withdrawal in both male and female rats. During subsequent cue-induced relapse tests at 1 or 14-days following the conclusion of self-administration, data show that while both male and females demonstrate drug-seeking behavior at both time points, females show a further elevation in responding on day 14 versus day 1 that is not observed in the males. When accounting for past work showing elevations in drug seeking in males after 30 days, these data indicate that craving-induced relapse for opioids may develop faster and may be more pronounced in females compared to males.

These behavioral findings were paralleled by use of ex vivo acute slice electrophysiology and circuit-specific ex vivo optogenetics to examine the impact of oxycodone self-administration on synaptic strength within the paraventricular thalamus (PVT) to nucleus accumbens shell (NAcSh) pathway(s). Data support a time-dependent but sex independent strengthening of glutamatergic signaling at PVT-to-NAcSh medium spiny neurons (MSNs) that is only present following a relapse test at 14 days post abstinence in males versus females, providing the first evidence that opioid self-administration and/or cue-induced drug-seeking augments this pathway. Using an extensive set of physiological measures, the authors show that this increased synaptic strength reflects a upregulation of presynaptic release probability. Further, this upregulation of excitatory signaling aligned temporally with an increase in MSN excitability, as assessed by increases in action potential firing frequency. Finally, the authors provide the first evidence that similar to other inputs to the NAcSh, PVT projections innervate both MSN as well as local interneurons, promoting a GABA-A specific feedforward inhibitory circuit. Interestingly, unlike direct excitatory inputs to MSNs, no changes were observed ostensibly within this feedforward circuit, highlighting a selective enhancement of excitatory drive and output of MSNs with protracted abstinence.

Overall, these data highlight a potential role for heightened synaptic strength within the PVT-NAcSh pathway in cue-induced relapse behavior during protracted abstinence and identify a potential therapeutic target during abstinence to reduce relapse risk in abstaining individuals.

Weaknesses:

Overall, the experimental approach and data provided appear rigorous and support their overall conclusions and achieve their goal of understanding how opioid self-administration impacts synaptic strength within the PVT-NAcSh pathway. Although not undermining these data, there are a few potential weaknesses that reduce the impact of the work. For example, the inability to directly assess whether cue-induced drug-seeking is in fact augmented compared to daily intake during self-administration in the maintenance face only permits the authors to denote that reexposure to cues and the context is sufficient to promote active lever pressing without demonstrating whether seeking behavior is in fact elevated further during a cue test. This is notably understandable as drug available sessions were 6-hours versus a 1hour relapse test. Importantly, it is clearly demonstrated that drug seeking is higher on average in female mice after 14 days versus 1 day.

With regard to interpretation of electrophysiology findings, the lack of inclusion of an abstinence only group does not permit interpretations to parse out whether observed increases in synaptic strength (or the lack of) reflect abstinence or an interaction between abstinence period and re-exposure to the operant chamber, as slices were taken 30-45 min post relapse test. While much literature has shown that drug induced adaptations in the NAc requires a post drug period for plasticity to measurably emerge, studies have also shown that re-exposure to heroin-associated cues following abstinence seemingly "reverses" increases in cell excitability in prelimbic-NAc pyramidal neurons (Kokane et al., 2023) and that depotentiation of morphine-induced increases in synaptic strength in the NAc shell can be depotentiated by drug re-exopsure -- an effect also observed with cocaine re-exposure (Madayag et al., 2019). Notably, the lack of effect at 14 but not 1 day supports the likelihood that the relapse test does not in fact influence the plasticity within the PVT-NAcSh circuit.

While the lack of effect on AMPAR:NMDAR ratio and rectification indices do support the notion that enhanced EPSC amplitudes in input-output curves do not reflect a change in AMPAR subunit expression (i.e., increased GluA2-lacking receptors that exhibit inward rectification at depolarized potential) nor a change in postsynaptic sensitivity to glutamate, without direct assessment of AMPAR-specific and NMDAR-specific input-output curves, it doesn't definitively exclude the possibility that both AMPA and NMDA receptor currents are being upregulated, thus negating an observable change in postsynaptic strength.

Overall, these findings provide novel insight into how the PVT-NAcSh pathway is altered by opioid self-administration and whether this is unique based on abstinence period and sex. Importantly, these were the primary objectives stated by the author. Data highlight a potential role for the observed adaptations in relapse behavior and identify a potential therapeutic target during abstinence to reduce relapse risk in abstaining individuals. However, it should be noted that no causal link is demonstrated without experiments to reduce/prevent relapse.

Comments on previous revisions:

The authors addressed previous concerns brought up, specifically by clarifying data interpretation as well as text modifications related to potential caveats of these interpretations.

Reviewer #2 (Public review):

Summary:

This is an interesting paper from Alonso-Caraballo and colleagues that examines the influence of opioid use, acute and prolonged abstinence, and sex on cue-induced relapse and paraventricular thalamus (PVT) to nucleus accumbens shell (NAcSh) medium spiny neurons circuit physiology. The study presents a valuable finding that following prolonged, but not acute abstinence from oxycodone self-administration, female rodents exhibit higher relapse rates to drug paired cues. Additionally, the study presents the useful finding that prolonged abstinence increased PVT-NAcSh MSN synaptic strength in both sexes, an effect that is likely due to presynaptic adaptations. While the evidence to support these two findings is solid, further experiments are required to determine the functional role of the PVT-NAcSh MSN circuit in relapse following prolonged oxycodone abstinence, and the mechanism underlying the heightened relapse vulnerability in females in this model of opioid use disorder.

Strengths:

The paper is interesting, well written and presented, and the experiments are well designed and conducted. The revised analysis of spike count data that models the hierarchical structure of the data is appropriate to overcome low animal numbers and the potential for oversampling. The authors are transparent in reporting the results related to this analysis in figure 5 and acknowledge the study is underpowered to confirm the trend of increased intrinsic excitability in male MSNs following prolonged oxycodone analysis.

Impact:

The topic is of interest to the field of substance use disorders and gives solid evidence for the need to consider targeted therapeutics aimed at relapse prevention in opioid use disorder.

Reviewer #3 (Public review):

Summary:

Alonso-Caraballo et al. use behavioral testing and ex vivo patch-clamp electrophysiology combined with circuit-specific optogenetic stimulation of PVT terminals to examine how oxycodone self-administration and abstinence duration shape cue-induced relapse and PVT-NAcSh synaptic transmission in male and female rats. In the revision, the authors reanalyzed intrinsic excitability using nested hierarchical GLMMs, acknowledged the low power in the male prolonged-abstinence group, and expanded the discussion of relevant PVT-NAc literature. These changes improve the manuscript. That said, most of the revisions are textual and the main experimental gap remains. Both sexes show increased oxycodone seeking compared to saline at 14 days, but only females show a time-dependent incubation from 1 to 14 days, and the PVT-NAcSh synaptic strengthening is the same in both sexes. Nothing in the revision brings those two observations closer together. The excitability data also come from NAcSh MSNs with no confirmation of PVT connectivity, which limits what circuit-specific conclusions can be drawn. The study is a solid characterization of abstinence-related synaptic changes in this pathway, but some of the conclusions still go further than the data allow.

Strengths:

The behavioral characterization is thorough and well-executed, covering self-administration, somatic withdrawal, and cue-induced relapse across two abstinence durations in both sexes. The sex-specific escalation in oxycodone seeking from 1 to 14 days in females but not males is a clear and compelling finding. The use of circuit-specific ex vivo optogenetics to isolate PVT terminal inputs onto NAcSh neurons is a genuine methodological strength, and the demonstration of feedforward inhibitory recruitment through local GABAergic interneurons adds meaningful novelty to the circuit characterization. The reanalysis of intrinsic excitability using nested hierarchical GLMMs appropriately accounts for the non-independence of cells recorded within the same animal and is a real improvement over the original approach. The expanded discussion of prior PVT-NAc work, particularly the more accurate treatment of Keyes et al. (2020) and Paniccia et al. (2024), better situates the findings within the existing literature.

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.

Comments on revised version:

I thank the authors for their thorough revisions and detailed responses. All of my previous concerns have been satisfactorily addressed, and I have no further comments.

Reviewer #2 (Public review):

Tittelmeier et al. investigated the role of sphingolipid (SL) metabolism in the maintenance of endolysosomal vesicle integrity. They find that both impaired SL biosynthesis and degradation in C. elegans decreases the fluidity of endolysosomal membranes and promotes their rupture, while it has little effect on plasma membrane fluidity. Endolysosomal membrane fluidity is also negatively affected in human cells upon knockdown (KD) of a gene (SPHK2) involved in the SL degradation pathway. Aggregated forms of tau in both models (C. elegans and human cells) can also cause rigidification of the endolysosomal membrane, with SL homeostasis disruption having an additive effect, exacerbating endolysosomal rupture. Notably, KD of SPHK2 also increased the formation of tau foci, suggesting that compromised endolysosomal integrity may promote tau aggregation. These data provide a clearer understanding of how genetic manipulation of SL metabolism affects endolysosomal membranes and their rigidification in the context of tau aggregation. Supplementation of polyunsaturated fatty acids (PUFAs), which has a beneficial effect on Alzheimer's patients, improved membrane fluidity and reduced tau propagation in human cells and tau-associated neurotoxicity in C. elegans, suggesting a possible mechanism of action.

Comments on revised version:

The authors have:<br /> Corrected editorial errors (Points 1 and 2).

Clarified the experimental rationale, added new data to rule out alternative explanation, and improved the presentation of the C. elegans model (Point 3).

Provided experimental evidence and appropriate discussion regarding the specificity and broader physiological context of SL gene knockdown effects (Point 4).

Overall, the authors' responses are thorough, supported by new data where appropriate, and demonstrate a clear understanding of the concerns raised. All points raised have been satisfactorily resolved.

Reviewer #3 (Public review):

Summary:

The authors set off with an analysis of the lysosomal integrity upon knockdown of genes of the sphingolipid metabolic pathway that they identified in a previous work of an RNA screen using a new C.elegans Tau model. They then used cell culture and C.elegans experiments to study the link between lysosomal rupture and Tau propagation.

Strengths:

The authors use two complementary model systems and used probes to assess membrane rigidity that allow a quick assessment of the membrane dynamics and offer the opportunity to treat the cells with lipids, RNAi. Tau seeds etc.

Comments on revised version:

The authors have addressed the majority of my critical comments and thus I support the manuscript.

They have still not analysed the knockdown efficiencies of their RNAi experiments. But this is their choice.

The other publication establishing their Tau model is meanwhile published and there is no disconnect anymore between the model their analysis builds on.

Reviewer #2 (Public review):

Summary:

The JAK-STAT pathway (JSP) exhibits cell-type-specific functional heterogeneity in breast cancer. This study investigates the JSP in breast cancer and its response to anti-PD‑1 immunotherapy. JSP displays distinct cell‑type heterogeneity: it promotes malignant phenotypes and immunosuppression in tumor cells, while enhancing cytotoxicity and reducing exhaustion in T cells. Elevated JSP expression correlates with improved immunotherapy responses, especially in triple‑negative breast cancer. These findings highlight the paradoxical roles of JSP, indicating that broad inhibition may compromise anti‑tumor immunity.

Strengths:

The major strengths of this study include the comprehensive characterization JSP heterogeneity across epithelial, tumor, and T cells in breast cancer. The identification of JSP and STAT4 as predictive biomarkers for immunotherapy response, particularly in triple‑negative breast cancer, provides clinically relevant insights for patient stratification.

Comments on revised version.

The corresponding content has been revised.

Reviewer #3 (Public review):

Summary:

This multi-omics study by Zhou et al elucidates the context-dependent roles of the Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway (JSP) across different cellular compartments in the breast cancer tumor microenvironment. While bulk JSP activity is associated with a favorable prognosis, single-cell analysis reveals a paradoxical landscape: high JSP in T cells drives anti-tumor cytotoxicity and reduces exhaustion, whereas high activity in tumor epithelial cells promotes malignancy and immunosuppression via the MIF-CD74 signaling axis. The JSP score (immune-related) serves as a robust predictive biomarker for response to anti-PD-1 immunotherapy, particularly in triple-negative breast cancer (TNBC). Furthermore, the study identifies the STAT4/SLC47A1 axis as a critical mechanism through which tumor cells resist ferroptosis, facilitating disease progression. These findings suggest that broad JAK-STAT inhibition may be counterproductive in cancer therapeutics; instead, therapeutic success depends on precise modulation and carefully timed interventions to preserve its T-cell-associated functions. This study may inspire future studies to explore specific factors that selectively modulate JAK-STAT activity in immune cells to achieve favorable therapeutic outcomes.

Strengths:

Significant therapeutics implications

Weaknesses:

Limited molecular mechanisms

Comments on revised version:

The authors have addressed my comments

Reviewer #1 (Public review):

Summary

In this study, the authors have performed tissue-specific ribosome pulldown to identify gene expression (translatome) differences in the anterior vs posterior cells of the C. elegans intestine. They have performed this analysis in fed and fasted states of the animal. The data generated will be very useful to the C. elegans community, and the role of pyruvate shown in this study will result in interesting follow-up investigations.

However, several strong claims made in the study are solely based on in silico predictions and are not supported by experimental evidence.

Comments on revised version.

The authors have been responsive to the comments, but have not added new experiments in this manuscript that would have clarified and improved some of the mentioned shortcomings of the study.

There are 3 comments that the authors should address:

(1) In their response to reviewers, the authors agree that "the Pges-1deltaB promoter is not absolutely restricted to INT1 and that weak GFP expression can also be detected in INT2." They also mention that "because Pges-1deltaB is an engineered promoter derived from the intestine-specific Pges-1 promoter, this low-level INT2 expression is not unexpected." However, in line 93 of the revised manuscript, the authors claim that "Pges-1deltaB is strictly expressed in INT1 cells". This discrepancy should be fixed. They should instead describe this in line 93 as "Pges-1deltaB expression is very strongly enriched in INT1 cells, but low-level expression in INT2 was also detected".

(2) In response to reviewers, the authors explained that "Our model is that fasting induces INS-7 secretion by lowering intracellular pyruvate in INT1 cells. Under this framework, blocking mitochondrial pyruvate breakdown would be expected to reduce pyruvate utilization and thus maintain intracellular pyruvate, preventing the drop in pyruvate that normally occurs during fasting. This would explain why these manipulations suppress fasting-induced INS-7 secretion." However, the effect of blocking import of pyruvate from cytosol into mitochondria (via knockdown of mitochondrial pyruvate carrier genes mpc-1 and mpc-2) does not agree with their proposed model. Blocking mitochondrial import of pyruvate should maintain cytosolic pyruvate levels and thus prevent the drop in pyruvate that normally occurs during fasting. In such a scenario, we would expect to see no increase in INS-7 secretion during fasting, which is opposite to the result in Fig.7D. If the pyruvate sensor is in the cytosol, we would expect that the mpc-1/2 RNAi treated animals would be unable to increase INS-7 secretion upon starvation. If the pyruvate sensor is in the mitochondrial matrix, we would expect that the mpc-1/2 RNAi treated animals would have higher INS-7 secretion than vector RNAi control animals in fed conditions. How do the authors explain this discrepancy between their observed results and their proposed model? Why does blocking mitochondrial import of pyruvate affect only refeeding-induced reduction in INS-7 secretion but not fasting-induced increase in INS-7 secretion? Is it possible that instead of responding to absolute intracellular concentrations of pyruvate, the pyruvate sensor increases INS-7 secretion upon detecting a relative drop in the mitochondrial levels of pyruvate (or its downstream metabolite)? This should be described in the text to better interpret the mpc-1/2 RNAi results.

(3) Line 493: The authors refer to 'Table S4', which is not included in the manuscript.

Reviewer #3 (Public review):

In this study, Liu and colleagues utilize TRAP-seq to profile the repertoire of actively translated mRNAs in different intestinal cell types (anterior INT1 vs. posterior INT2-9 cells) in C. elegans. A key goal of this study was to identify transcripts differentially expressed/translated between these intestinal cell subtypes in the context of animals being well fed or subjected to acute (30 minutes) or chronic (3 hours) starvation, followed by refeeding.

The authors identify a number of differentially expressed genes across all of the conditions tested. They then provide an initial survey of the landscape of translatome changes through Weighted Gene Network Correlation Analysis (WGNA), and some high-level functional surveys via Gene Ontology (GO) term analysis and protein domain analysis. The authors validate the enriched expression patterns of some of their identified candidate genes using fluorescent promoter fusion reporters, confirming INT1-specific expression. The authors further implicate the role of several other candidate genes in pathogen avoidance and in response to nutritional cues by knocking them down specifically in INT1 cells by RNAi. Finally, the authors identify pyruvate as a major nutrient signal coming from the bacterial diet that suppresses the release of a key insulin peptide (INS-7) and identify some of the genes expressed in INT1 that are required for this response.

Strengths:

(1) Good use of and justification for TRAP-seq, because scRNA-seq would be difficult under the varied conditions used (starvation, refeeding)

(2) The manuscript is generally clear to read, and the data are generally well-presented with good supporting data that includes replicates, sample sizes, error measurements, and associated statistics.

(3) The dataset will be an interesting resource to mine for future studies focusing on mechanisms of how particular intestinal cell types respond to different environmental signals.

Weaknesses:

(1) A limitation of TRAP-seq, although powerful, is that only relative comparisons can be made between genotypes/conditions to identify differentially-expressed genes, rather than assessing whether a given gene is expressed at a certain level in a cell type under a certain condition. This limitation is due to the non-specific association of sticky RNA species to the beads during the immunoprecipitation step. This is a minor point however, and the authors do a nice job of focusing their analysis on differentially expressed transcripts in the current study.

(2) Another limitation of the current study is that the experiments testing the role of candidate genes identified by their profiling experiments do not dive a bit deeper into providing a mechanistic understanding of the phenotypes being studied. At present, the results are thus viewed more as a genomics-based screen with some limited follow-up on interesting hits. However, this reviewer appreciates that when placed in context of the work presented, a presentation of the profiling data along with some validation is an excellent starting point for future mechanistic studies elaborating on these interesting candidates.

Appraisal of whether the authors achieved their aims, and whether the results support their conclusions.

The main goal of the study was to survey the dynamic responses at the level of actively translated mRNAs of the INT1 vs INT2-9 cells in response to metabolic challenge.

Overall, the authors use established methods to perform their genome-wide analysis, and the set of differentially regulated genes are enriched for expected molecular functions and form coherent networks in anticipated pathways.

The validation experiments (promoter::GFP fusion reporters, INT1-specific knockdowns of highly regulated genes) further corroborate the quality of the TRAP-seq datasets generated.

I have a few points for the authors that would further strengthen this work:

(1) The authors rightfully focus on the top differentially-regulated candidates, but it's unclear at present how far down their fold change list would lead to expression pattern validations. It would be useful to test a few more promoter::GFP fusion reporters at different enrichment/fold-change/statistical cutoffs.

(2) Although the INT1-specific RNAi provides a convenient strategy for rapidly perturbing and testing genes of interest for phenotypes, independently validating the knockdowns with genetic mutants, or alternatively (if genes are essential), degron alleles.

Likely impact of the work on the field, and the utility of the methods and data to the community.

The TRAP-seq data and list of differentially-expressed candidate genes will form an interesting set of high-priority candidates to study for their role in the reception and transduction of nutritional cues in response to food status and pathogens. This data will thus benefit the C. elegans community of researchers studying the mechanisms governing these phenomena.

Comments on revised version:

I think the authors have done a good job of addressing the suggestions from the previous round of review in this new version.

Reviewer #2 (Public review):

Summary:

This manuscript investigates how neural cell development is affected in Lowe syndrome. Using neural cultures differentiated from human iPSCs carrying either a LS mutation or a genetically engineered mutation in OCRL, the authors show a depletion of mitochondrial DNA and decrease in mitochondrial activities that correlate with an increased formation of astrocytes at the expense of neurons. Similar effects on mitochondria and on astrocyte development were observed in a LS mouse model. Moreover, these mutant brain cells are less likely to be ciliated and show a reduction in Sonic hedgehog signalling.

Strengths/Weaknesses:

The study derives strength from the analyses of two different models of Lowe syndrome, both reaching similar conclusions. However, the observed changes in mitochondrial defects, neuronal/astrocytic development and primary cilia are only correlated, with no attempt to investigate a causal relationship. Moreover, the mouse model is only analysed at the adult stage providing no insights into the development of the defects. Different brain regions are analysed with immunostainings and qRT-PCR making it challenging to draw clear correlations between these findings. The quality of the corresponding figures is often poor and the selection of markers is frequently inappropriate. Taken together, these limitations complicate the interpretations of the data and significantly limit the conclusions that can be drawn from the study.

Although the study remains incomplete as main claims are only partially supported it can be used as a starting point for future functional studies into the link between mitochondrial defects and primary cilia in neural development.

Comments on revised version:

I am afraid the revised manuscript does little to address the concerns I raised in my initial review. The authors have primarily revised the text, removed over-interpretations and discussed critical points as limitations of the study. This gives the impression that key concerns have merely been rationalised, particularly as only a few new experiments are presented. My main concerns therefore remain:

(1) The authors present three different phenotypes (altered neural differentiation, mitochondria dysfunction, alterations in primary cilia and ciliary Shh signalling) but a link between these phenotypes is not investigated. No mechanistic experiments are presented. Instead, the authors try to address the lack of a mechanism through refined wording but still use formulations that imply a direct link between these phenotypes. For example, their rebuttal letter finishes with the statement that the manuscript "provides a multi-model, cross-species framework linking mitochondrial dysfunction, ciliary signaling, and altered neural differentiation in Lowe syndrome". Similar formulations are used in the text.

(2) The authors still claim that ciliary Shh signalling is reduced but ignore the fact that Shh mRNA in iN cells and Shh protein in the IOB mouse are significantly decreased. This reduction represents the most likely explanation for the reduced levels of Gli1 and Ptc1 mRNAs (Shh target genes), rather than dysfunction of cilia. In order to test for cilia dysfunction, the authors need to use experiments in which they quantify the response of control and OCRL mutant cells to exogenously added Shh protein or Shh agonists. Moreover, the increased Gli1 protein expression in the IOB mouse contradicts the reduced levels of Gli1 mRNA.

(3) The analyses of the IOB mice are only done in 2 months old adult animals, nevertheless claims are made that changes in cell proportions are consequences of altered cell fate decisions. Alterations in proliferation and cell death are not addressed by experiments.

Reviewer #1 (Public review):

The authors of this study developed a method to quantify calvarial bone marrow from MRI head scans, enabling study of its composition in large datasets of adults, usually collected to study the brain. Bone marrow intensity can be semi-quantitatively measured in T1-weighted MRI scans due to the greater signal intensity of fat than watery red marrow. This is an ingenious use of the MRI-produced information for other important phenotypes, such as bone structure and marrow content. Different head types were tested for complying to the model, which is notable.

The model was also successfully validated using several publicly available MRI resources - real data - in (1) dataset consisting of 30 individuals that were scanned 10 times each at 3-day intervals, and (2) the monozygotic (MZ) twin data from the Human Connectome Project cohort. Then the authors applied this validated method to head-MRI scans from the UK Biobank (n=33,042) to extract information on spatial distribution of bone marrow adiposity (BMA) in the calvaria, allowing a GWAS to identify associated genes.

The authors revealed high heritability and identified 41 genetic loci significantly associated with the BMA trait, including six sex-specific loci. Of note, statistics estimate that 99% of BMA trait-influencing variants are shared with BMD (497 of 500 variants), which may mean these results demonstrate the biological relevance to bone health. Some of the BMA genes were found related to the Wnt pathway, including WNT16, WNT4, NXN; this is a "positive control", since the Wnt/β-catenin signaling pathway was suggested as an important determinant of BMA. Also, associations in genes (BMP4, DLX5, LGR4, LRP4, SFRP4) that are known to specifically influence adiposity, are encouraging. Integrating mapped genes with bone marrow single-cell RNA-seq data revealed patterns of adipogenic lineage differentiation and lipid loading.

The study also investigated genetic overlap between BMA and twelve (or 13) "brain and body" traits, and identified significant genetic correlations with BMI, cognitive ability and Parkinson's disease.

In sum, since MRI head scans present a hitherto unexplored opportunity to address unresolved aspects of bone marrow biology, this study is both timely and innovative.

Comments on revised version:

The authors responded most of this reviewer's comments. Their explanations are convincing. Yet, upon re-reading the revised version of this paper, I still have concerns about the clarity of mostly analysis presentation, e.g.:

Line 130-133: the sentence is still unclear: "To obtain the BM signal intensity for an individual datapoint of the calvarium, we ... averaged these BM intensities to get the (average?) BM intensity for that datapoint. Then, we averaged (again?) these datapoint intensities across the calvarium to produce the global BMA measure for the scan."

Also, I still cannot understand whether the "overlap between the true and predicted bone marrow ...below 0.7" is concerning or not, - whether this threshold of 0.7 is arbitrary.

Genetic correlation: pls. make sure it's clear that the Rg was calculated using SNP "effect sizes".

Reviewer #2 (Public review):

Summary:

The authors set out to enable large-scale measurement of fat in skull bone marrow using routine structural brain MRI scans. They present a neural-network pipeline trained largely on realistic simulated examples and show that the resulting skull marrow measure is highly repeatable in test-retest data and consistent in monozygotic twins. Applying it to ~33,000 UK Biobank participants, they report expected population patterns (including sex- and menopause-related differences) and identify genetic and health-related associations, creating an important resource that can be built upon by researchers interested in BMA, imaging, bone, metabolism, neuroscience, ageing, haematology, and other fields.

Major strengths:

A notable methodological strength is the training strategy: by using a large, simulated dataset that captures plausible variation in skull-layer thickness and MRI intensity, the authors reduce reliance on scarce expert-labelled images. The modelling choice (using 1D intensity profiles through the skull rather than analysing the full 3D volume) appears well matched to the anatomy and offers an efficient approach for thin, layered structures. Multiple validation steps (including test-retest reliability and twin concordance) support the robustness of the measurement pipeline.

On the biological and genetic side, the study demonstrates that the skull BMA estimate relates to known correlates of marrow fat (e.g., age/sex/menopause patterns/bone density) and integrates population imaging with large-scale genetic analysis to highlight loci and candidate genes with plausible relevance to skeletal and marrow biology. The inclusion of cross-ancestry analyses and integration with cell-type-resolved gene-expression resources further improves interpretability and usability for the community.

Major limitations:

The main limitation is conceptual rather than technical: the phenotype is derived from T1-weighted MRI intensity, which does not directly separate fat and water signals and can vary with scanner and sequence settings. The manuscript provides convincing evidence that the measure is reproducible and biologically meaningful, but it should still be interpreted as a semi-quantitative proxy for marrow fat rather than a direct fat-fraction measurement. Accordingly, the genetic and phenotypic associations are likely informative, but the most direct claims about "adiposity" would be stronger if anchored to established quantitative fat-measurement imaging or spectroscopy in the skull.

The genetic "replication" analysis in a smaller, ancestrally heterogeneous non-European-ancestry sample is useful as a test of transferability, but it is not equivalent to replication in an independent cohort of similar ancestry and is expected to show reduced SNP-level reproducibility because of differences in sample size and genetic background. This should be clearly framed so readers understand what level of generalisation is supported by the current evidence.

Likely impact and utility:

Overall, the work provides a practical method for extracting new biological information from widely available brain MRI scans and should be particularly useful to researchers working with large imaging biobanks and those studying connections between bone, blood, metabolism, and brain ageing. The combination of a scalable measurement approach and openly reported genetic results is likely to accelerate follow-up studies, including cross-cohort comparisons and mechanistic work on candidate pathways.

Reviewer #3 (Public review):

Summary:

This paper addresses a fundamental gap in bone biology: our near-complete ignorance of the in vivo dynamics of calvarial bone marrow adiposity (BMA) at population scale. The authors developed an elegant artificial neural network trained on simulated data to automatically localize and quantify the bone marrow layer within standard T1-weighted MRI head scans; scans originally acquired to study the brain but harboring rich, unexploited information about adjacent bone. Applying this method to over 33,000 individuals from the UK Biobank, they accomplished three things that had never been done before: (1) they precisely quantified the sex-dimorphic age trajectory of calvarial BMA, including the dramatic post-menopausal rise and the protective role of hormone replacement therapy; (2) they performed the first well-powered GWAS of this trait, identifying 41 genome-wide significant loci including six sex-specific ones, with SNP heritability of 31.5%; and (3) they revealed significant genetic correlations and overlap between BMA and traits including bone mineral density, Parkinson's disease, and general cognitive ability, a finding made all the more intriguing by the recently described direct vascular channels connecting calvarial bone marrow to the meninges. Integration of GWAS genes with single-cell RNA-sequencing data from mesenchymal lineage cells further illuminated which genes govern lineage commitment to the adipogenic pathway versus lipid loading in mature adipocytes.

Comments on revised version.

The reviews raised substantive points across three domains, and the authors engaged with every one of them seriously and thoroughly.

On the validation of T1-weighted MRI as a measure of BMA: Reviewer 2 raised the strongest concern, arguing that T1-weighted signal intensity had never been formally validated as a quantitative fat-fraction measure in the calvarium. The authors responded with both a principled scientific argument and new data. They assembled existing literature demonstrating that T1-weighted signal is an established semi-quantitative proxy for marrow fat in multiple skeletal sites (Loevner et al. 2002, Shen et al. 2013, Zhang et al. 2020), and provided additional comparative analyses against quantitative T1 relaxation maps, multiple intensity normalization strategies (KDE, WhiteStripe, GMM, FCM, Z-score), DEXA-derived bone mineral density, and osteoporosis status. The biological coherence of their findings, recapitulating known sex and age profiles, identifying genes already established in cell and animal models of BMA biology, and estimating heritabilities consistent with twin data constitutes powerful, convergent evidence for construct validity. Their point that a semi-quantitative measure of a highly variable, well-demarcated biological signal can outperform a perfectly precise measure of a poorly defined entity is methodologically sound and well-argued.

On sex differences and the role of Hyperostosis frontalis interna: Reviewer 1 raised the clinically astute concern that Hyperostosis frontalis interna (HFI), a condition of inner table thickening prevalent in up to 49% of postmenopausal women, could confound calvarial BMA measurements and drive apparent sex differences. The authors performed a dedicated new analysis, stratifying BMA-BMD associations by sex and age group. They demonstrated that (1) the BMA-BMD association is robust in both males and females, (2) it remains stable across age groups, and (3) the neural network trained on simulations incorporating wide anatomical variation including inner table thickness is inherently resistant to moderate inner table thickening. Given that HFI is restricted to the frontal bone, which represents only a fraction of the calvarial surface, and that severe cases are rare (ICD-10 prevalence ~0.02% in the UK Biobank), the authors make a convincing case that this does not materially bias their results. Their suggestion that the method could itself be used in future work to study the genetic architecture of HFI is a nice forward-looking addition.

On genetic correlation interpretation and cross-trait pleiotropy: Reviewer 1 asked for clarification of the vertical versus horizontal pleiotropy distinction and for formal Mendelian randomization to support the possible causal effect of BMA on cognition. The authors appropriately clarified the conceptual framework in the revised text and, rather than overstating a causal claim without the supporting analysis, responsibly softened the language to "may be consistent with the hypothesis that BMA could have a causal effect on cognition." This is scientifically honest and appropriate.

On mouse scRNAseq and its relevance to humans: The authors acknowledged that the results section had not explicitly stated the mouse origin of the scRNAseq data, corrected this, and provided a well-justified rationale for the relevance of mouse mesenchymal lineage data to human BMA biology, which is a well-established and widely accepted model system in this field.

On GWAS replication: The claim that the study lacked replication was addressed by clarifying the a priori separation of discovery (white British, n=33,042) and replication (non-white British, n=4,958) samples, with 62% of significant discovery SNPs and 95% of lead SNPs replicating in the correct direction.

Overall Assessment:

This is a technically innovative, scientifically rigorous, and biologically meaningful paper. The method is genuinely novel, the sample size is among the largest ever applied to this phenotype, the genetic findings are well-powered and well-replicated, and the integration across imaging, genetics, and single-cell transcriptomics is exemplary. The authors have engaged with every substantive reviewer criticism in good faith, producing new analyses where appropriate and defending, and convincingly, with findings that were challenged without adequate basis. The revised manuscript is strengthened throughout.

This paper opens a new window quite literally, through the skull - into bone marrow biology at a scale and resolution that has never been achieved before.

Reviewer #1 (Public review):

Summary:

The authors demonstrate the stereoselective role of D-serine in 1C metabolism showing that D-serine competes with L-serine and inhibits mitochondrial L-serine transport. They observe expression of 1C metabolites in their metabolomics approach in primary cortical neurons treated with L-serine, D-serine and mixture of both. Their conclusions are based on the reduction in levels of glycine, polyamines and their intermediates and formate. Single cell RNA sequencing of N2a cells showed that cells treated with D-serine enhanced expression of genes associated with mitochondrial functions such as respiratory chain complex assembly and mitochondrial functions with downregulation of genes related to amino acid transport, cellular growth and neuron projection extension. Their work demonstrates that D-serine inhibits tumor cell proliferation and induces apoptosis in neural progenitor cells highlighting the importance of D-serine in neurodevelopment.

Strengths:

D-amino acids do not merely function as ligands at receptors but have underlying roles in signaling and metabolism. These roles are just beginning to be uncovered. The authors elucidate the metabolic role of D-serine in the context of neuronal maturation by its suppression of mitochondrial L-serine availability for SHMT2 and 1C flux. This is the strength of the manuscript. The implications for the metabolic role of D-serine in neurons is a highlight and underlines its roles in neuronal metabolism.

Weaknesses:

These are some minor issues that come up on critical assessment of the manuscript and is only intended to strengthen the manuscript. The comments below are based on the revisions made by the authors including the justification of their approach and rebuttal.

(1) Kinetic assessment of D-serine versus L-serine: The authors have made reference to prior work by Miyamoto et al. and justify their rationale. This is acceptable.

(2) Molecular Dynamics simulations while a good first step in modeling interactions at the active site, relies on force fields. The authors state that any elaborate study into longer simulations is beyond the scope and their simulations data are supported by other experimental work. This is justified.

(3) The use of N2a cell line is also justified to reflect the proliferative nature of immature neurons.

(4) With regards to caspase 3 comment, the whole blot is convincing and shows cleaved caspase-3 band at approx. 15 kDa.

(5) Scale Bars are clearly visible and Fig S6 which was earlier S5 is legible. If possible, the authors can include an magnified inset in the merged image to show the clear activation of caspase-3.

(6) Issue of phosphatidyl serine standard in LC-MS is justified by the use of L-serine standard due to lack of availability.

(7) The authors mention about enantiomeric shift of serine metabolism during neural development which appears to be a discussion of prior published data from Hubbard et al 2013, Burk et al 2020, and Bella et al 2021 in Supplementary Figure panels 8 A-E.<br /> The authors justify by citing references to the work which may be acceptable and also the current norms of publication. This reviewer felt contrary to the fact, however it is left to the editors to make a decision on this.

(8) The discussion section has been substantially revised and now reads well.

(9) The relevant references have been cited. In doing so, the work integrates and elucidates a mechanistic and functional role of D-serine in neurons.

(10) Figure S7A in the revised manuscript shows the specificity of D-serine in the cleaved caspase-3 assay which is informative.

Comments on revised version.

This reviewer is satisfied by the effort made by the authors based on the prior comments raised.

Reviewer #2 (Public review):

Summary:

This study by Suzuki et al. reports an interesting stereo-selective role of D-serine in regulating one-carbon metabolism during neurodevelopment to adapt the functional transition, probably through the competition with mitochondrial transport of L-serine. The authors provide a multi-layered set of evidence, including metabolomics, enzyme assays, mitochondrial transport competition and functional assays in immature/neural progenitor cells, to build up a conceptual integration of D-serine as both a neurotransmitter and a metabolic regulator in central neural system, which raises a broad potential interest to the neuroscience and metabolism communities.

Strengths:

This work provides a conceptual advance that D-serine is not only serves as a traditional neurotransmitter in central neural system but also critically contributes to metabolic regulation of neural cells. The authors performed solid metabolomic assays to validate the suppressive effect of D-serine on one-carbon metabolic pathway, providing some evidence that D-serine competitively inhibits mitochondrial serine transport, but not directly impairs SHMT2 enzymatic activity. All these data indicate a critical role of D-serine synthesis during neural maturation and suggest a potential translational strategy for targeting serine metabolism in neural tumors.

Comments on revised version.

My previous concerns have been appropriately addressed or discussed in this revised version of manuscript. I have to say that, at this stage, I have no further questions.

Reviewer #3 (Public review):

Summary:

This manuscript presents a comprehensive and well-executed investigation into the metabolic role of D-serine in the central nervous system. The authors provide solid evidence that D-serine competitively inhibits mitochondrial L-serine transport, thereby impairing one-carbon metabolism. This stereoselective mechanism reduces glycine and formate production, suppresses cellular proliferation, and induces apoptosis in immature neural cells and glioblastoma stem cells. Developmental analyses further reveal a physiological enantiomeric shift in serine metabolism during neurogenesis, aligning with the transition from proliferation to maturation. Overall, the study bridges developmental neurobiology, cancer metabolism, and amino acid transport, uncovering a previously unrecognized metabolic function of D-serine beyond its role in neurotransmission.

Strengths:

(1) The discovery that D-serine inhibits one-carbon metabolism by competing for mitochondrial L-serine transport-rather than through enzymatic inhibition or receptor-mediated signaling-represents a significant and previously underappreciated mechanism. This finding has broad implications for understanding metabolic regulation during neurodevelopment and offers potential relevance for targeting metabolic vulnerabilities in cancer.

(2) The authors integrate metabolomics, mitochondrial transport assays, molecular dynamics simulations, genetic and pharmacologic perturbations, transcriptomics, and both in vitro and ex vivo models. The breadth of experimental approaches, combined with the coherence of the findings across systems, provides strong support for the central conclusions and enhances the overall impact of the study.

(3) The temporal shift in D-/L-serine levels during neurodevelopment is elegantly linked to the transition from proliferative to mature neuronal states. The selective vulnerability of neural progenitors and tumor cells-contrasted with the resistance of mature neurons-highlights a biologically meaningful and potentially targetable metabolic distinction.

Weaknesses:

(1) While the authors attribute D-serine's metabolic effects to competition with mitochondrial L-serine transport, the specific identity of the transporter(s) mediating this process remains undefined. This represents a meaningful mechanistic gap, as the central conclusion depends on D-serine limiting mitochondrial L-serine availability to inhibit one-carbon metabolism.

(2) The effective concentrations of D-serine used in vitro (IC₅₀ ≈ 1-2 mM) exceed typical brain levels (~0.3 mM). While the authors acknowledge this, a more focused discussion on whether higher local D-serine concentrations could arise in specific microenvironments-such as synaptic compartments, tumor niches, or pathological states-would help contextualize the in vitro findings and strengthen their physiological relevance. For example, disruptions in D-serine clearance or altered expression of serine racemase and transporters in disease contexts could lead to localized accumulation. Moreover, differences between extracellular and intracellular D-serine pools-and the mechanisms governing their regulation-may further influence its metabolic impact in vivo.

(3) While the manuscript focuses on neural stem/progenitor cells and neural tumors, it remains unclear whether the anti-proliferative effects of D-serine are specific to neural lineages or extend to other highly proliferative non-neural cell types. A brief discussion addressing this point would help clarify the scope of D-serine's metabolic impact and whether its mechanism of action reflects a unique vulnerability in neural cells or a more general feature of proliferative metabolism. This distinction is particularly relevant for assessing the broader therapeutic potential of targeting mitochondrial L-serine transport.

Reviewer #1 (Public review):

Summary:

The authors aim to understand how changes in the balance between excitatory and inhibitory interactions influence the stability and reorganization of network connections. To address this question, they extend a coupled-phase-oscillator model by adding plasticity rules. The central finding is that stronger inhibitory interactions lead to relatively stable and desynchronized network dynamics, whereas weaker inhibitory interactions produce a bistable regime in which intermediate-strength connections fluctuate while stronger connections are preserved.

Strengths:

This study offers a simple theoretical framework for linking network state, coupling stability, and reorganization. The model produces clear qualitative results, showing that different dynamical regimes are associated with different balances of excitatory and inhibitory interactions. This could be useful as a conceptual starting point for considering how network states may regulate the stability and flexibility of connections. The manuscript also explores several model parameters.

Weaknesses:

The evidence is incomplete in supporting the biological interpretations. The model is a highly simplified coupled-phase-oscillator system and does not directly represent spiking activity, membrane potentials, synaptic currents, conduction delays, cellular excitability, or detailed biological plasticity mechanisms. Although the authors clarify that the model units are not actual neurons or synapses, the discussion often interprets the results in terms of neuronal inhibition, synaptic stability, sleep-related reorganization, and preservation of strong biological connections. This creates a gap between the abstract model and the biological conclusions. In particular, the manuscript does not sufficiently discuss what biological oscillatory activity the modeled phases are intended to represent, such as population-level activity reflected in electroencephalography or local field potentials. In several places, the manuscript appears to assume that neurons can generally be treated as oscillators, but this is not always a valid assumption. The authors should more clearly distinguish between rhythmic or phase-like activity at the population level and the dynamics of individual neurons, and should frame the model more cautiously as a phenomenological description of collective synchronization rather than a mechanistic model of spiking neuronal circuits.

There are also important methodological limitations. Although the manuscript presents the model equations, parameter values, time step, simulation duration, and coupling update rules, several other essential details are not clearly specified, including the number of simulation runs, the procedure for setting initial conditions, and the numerical method used to solve the ordinary differential equations. Critically, technical details such as the integration scheme, solver settings, initialization procedure, and random seed handling are essential for reproducibility. Because the main findings depend on the interaction between phase dynamics and adaptive coupling, even small implementation differences could affect the reported dynamical regimes and coupling fluctuations.

A further concern is the presentation of the mathematical formulation. Several equations appear to contain notation errors and inconsistencies, making it difficult to follow the exact model definition. The authors should carefully revise the mathematical notation throughout the manuscript to ensure that the model can be understood and reproduced unambiguously.

Overall, the study provides a useful but limited theoretical account of how network dynamics may regulate coupling stability and reorganization. The results support the internal behavior of the proposed model, but the broader biological claims are not yet fully convincing. The likely impact of the work is therefore mainly conceptual: it may stimulate further modeling studies, but additional methodological detail, stronger justification of the modeling assumptions, and comparison with more biologically grounded models would be needed before the conclusions can be applied confidently to neuronal circuit dynamics or sleep-related synaptic reorganization.

Reviewer #2 (Public review):

Summary:

This manuscript investigates the impact of plasticity mechanisms in an excitation-inhibition (EI) network model on the emergence of synchronization patterns that the authors associate with different sleep phases. The model consists of an EI Kuramoto network in which recurrent excitatory couplings evolve according to Hebbian and homeostatic adaptation rules. Through numerical simulations, the authors analyze how these plasticity mechanisms modify both the collective dynamics and the structure of the coupling matrix.

Strengths:

The topic addressed in the manuscript is timely and potentially relevant, as understanding the interplay between synaptic adaptation and collective neural dynamics remains an important challenge in theoretical neuroscience.

Weaknesses:

In its current form, the work suffers from substantial conceptual, methodological, and technical limitations that significantly weaken the conclusions.

From a biological perspective, the model is highly abstract and qualitative. The connection between the model variables and the physiological processes that the authors aim to describe remains unclear. Consequently, the manuscript does not provide sufficient evidence to support biologically meaningful conclusions regarding sleep dynamics. In my opinion, the work is more naturally positioned within the framework of theoretical or computational dynamical systems than within the scope of a biology-oriented journal.

From a mathematical and dynamical-systems perspective, the analysis is incomplete, and several important technical aspects are either missing or inadequately addressed. In particular, the characterization of the dynamical regimes is often imprecise, the numerical evidence is not sufficiently robust, and little effort is made to interpret the results within the broader context of synchronization theory, adaptive networks, or collective dynamics.

More specifically:

(1) The biological interpretation of the model variables is ambiguous throughout the manuscript. At several points, the authors suggest that individual oscillators should not be interpreted as neurons but rather as abstract biological units (lines 78-82, 86-89, 418-420). However, other parts of the manuscript refer to the coupling matrix entries, particularly $J_{ee}$, as synaptic weights (e.g., line 118). These two interpretations are not obviously compatible. If the oscillators represent coarse-grained or abstract units, the biological meaning of the adaptive couplings should be carefully justified. More generally, the manuscript lacks a clear discussion of what aspects of neural circuits are captured by the model and which aspects are intentionally neglected.

(2) More fundamentally, the manuscript inherits the well-known limitations associated with interpreting Kuramoto oscillators as neural elements. Kuramoto phase oscillators provide a minimal description of synchronization phenomena, but they do not explicitly represent membrane dynamics, firing rates, spiking activity, synaptic currents, or realistic neuronal timescales.

Under certain assumptions, Kuramoto-like models can be rigorously derived from more detailed neuronal models through phase-reduction techniques (see, for instance, Chapter 10 of Izhikevich's \textit{Dynamical Systems in Neuroscience}). However, the authors do not employ such a reduction procedure, nor do they establish a formal connection between their model variables and the dynamics of neuronal populations. As a consequence, the biological interpretation of the model remains unclear.

The authors should therefore explicitly discuss these limitations and carefully justify why the synchronization patterns observed in such a highly reduced model can be related to neural sleep states. At present, the biological interpretation appears considerably stronger than what the model itself can support, for instance, the claims in lines 321-322 or 330-337. In particular, it remains unclear whether the reported dynamical regimes should be interpreted as genuine mechanisms underlying sleep rhythms or merely as generic synchronization phenomena arising in adaptive oscillator networks.

(3) The numerical methodology raises serious concerns regarding the robustness of the reported results. According to the Methods section, simulations are performed using only $N=100$ oscillators and integration times of approximately 50 time units. Such choices may be sufficient for illustrative purposes but are generally inadequate for drawing conclusions about asymptotic collective behavior in adaptive dynamical systems. Finite-size fluctuations can strongly affect synchronization measures, and adaptive networks are well known to exhibit extremely long transients, metastability, and slow convergence processes. No systematic finite-size analysis is provided, nor is there any demonstration that the reported states persist for larger system sizes or longer integration times.

(4) The use of the term "bistable regime" to describe the dynamics shown in Figure 1C is incorrect. A bistable regime refers to a parameter region in which multiple attractors coexist and the asymptotic state depends on the initial condition. The figure instead presents a single trajectory displaying oscillatory dynamics. No evidence is provided for the coexistence of attractors, nor are multiple initial conditions explored. Furthermore, the displayed time series are too short to determine whether the observed dynamics correspond to a stable limit cycle, quasiperiodic motion, intermittent behavior, or a long transient approaching another attractor. The authors should perform a proper dynamical characterization of this regime. Similar collective oscillatory states have been extensively studied in synchronization and adaptive-network models and should be discussed in relation to the existing literature.

In particular, several time series shown in the manuscript (e.g., Figures 1C and 2F) exhibit trends that suggest the possibility of unresolved transient dynamics. The authors should demonstrate convergence of the reported regimes by substantially extending simulation times and by performing finite-size analyses. Simulations with at least one order of magnitude more units ($N\gtrsim 1000$) and integration times sufficient to establish asymptotic behavior would be expected in a study whose main claims rely on collective dynamical phenomena.

(5) The manuscript lacks several standard tools routinely employed in the analysis of nonlinear dynamical systems. The conclusions are largely based on visual inspection of time series and order parameters. However, no bifurcation analysis, stability analysis, phase-space characterization, attractor reconstruction, or systematic exploration of parameter dependence is provided. As a consequence, many of the identified "phases" or "regimes" remain only qualitatively described. A more rigorous dynamical-systems treatment would substantially strengthen the work and would help distinguish genuine asymptotic states from finite-size or transient phenomena.

(6) A substantial fraction of the results appears to extend the authors' previous work by incorporating plastic adaptation mechanisms. While incremental advances are acceptable, the manuscript would benefit from a broader theoretical context. The discussion is heavily centered on previous studies by the same authors, whereas there exists an extensive literature on synchronization, adaptive networks, neural mass models, balanced EI systems, and sleep-related oscillations that is largely absent from the discussion. The novelty and significance of the present contribution would be easier to assess if the results were more carefully compared with alternative theoretical approaches.

Reviewer #1 (Public review):

Summary:

The authors present a nanobody-based pulse-labeling system to track yeast NPCs. Transient expression of a nanobody targeting Nup84 (fused to NeonGreen or an affinity tag) permits selective visualization and biochemical capture of NPCs. Short induction effectively labels NPCs, and the resulting purifications match those from conventional Nup84 tagging. Crucially, when induction is repressed, dilution of the labeled pool through successive cell cycles allows the visualization of "old" NPCs (and potentially individual NPCs) providing a powerful view of NPC lifespan and turnover without permanently modifying a core scaffold protein.

Strengths:

(1) A brief expression pulse labels NPCs, and subsequent repression allows dilution-based tracking of older (and possibly single) NPCs over multiple cell cycles.

(2) The affinity-purified complexes closely match known Nup84-associated proteins, indicating specificity and supporting utility for proteomics.

Weakness:

Reliance on GAL induction introduces metabolic shifts (raffinose → galactose → glucose) that could subtly alter cell physiology or the kinetics of NPC assembly. As acknowledged by the authors, alternative induction systems (e.g., β-estradiol-responsive GAL4-ER-VP16) could be implemented as a way to avoid carbon-source changes.

Comments on revised version.

The authors have thoughtfully addressed all of my concerns. In particular, they have updated the proteomic analysis in Figure 1I, showing that they recover most NPC components (including basket Nups), including non-NPC proteins as controls, and providing all data as a supplementary table. These changes strengthen the authors conclusion and improve transparency. I have no further recommendations and congratulate the authors for their exciting work.

Reviewer #2 (Public review):

Summary:

This preprint describes a practical and useful approach for labeling and tracking NPCs in situ, using a fluorescently conjugated nanobody that binds directly to the core scaffold nucleoporin Nup84 with nanomolar affinity. Useful applications including timelapse imaging, affinity purification, and proximity labeling are envisioned.

Strengths:

Clever use of a fluorescently conjugated nanobody that binds directly to the core scaffold nucleoporin Nup84 with nanomolar affinity.

Reviewer #3 (Public review):

Summary:

Submitted to the Tools and Resources series, this study reports on the use of a single-domain antibody targeting the nucleoporin Nup84 to probe and track NPCs in budding yeast. The authors demonstrate their ability to rapidly label or pull down NPCs by inducing the expression of a tagged version of the nanobody (Fig. 1).

Strengths:

This tool's main strength is its versatility as an inexpensive, easy-to-set-up alternative to metabolic labelling or optical switching. This same rationale could, in principle, be applied to the study of other multiprotein complexes using similar strategies, provided that single-chain antibodies are available.

Weaknesses:

This approach has no inherent weaknesses, but it would be useful to verify in the future that this pulse labelling strategy can also be used to detect assembly intermediates, structural variants, or damaged NPCs, e.g. NPC clusters formed in some nucleoporin mutants.

Overall, the data clearly shows that Nup84 nanobodies are a valuable tool for imaging NPC dynamics and investigating their interactomes through affinity purification.

Comments on revised version.

None at this stage.

Reviewer #1 (Public review):

This manuscript by Rudich ZD et al. systematically profiled the transcriptomic changes in nine long-lived C. elegans mutants and presented a careful and informative comparative analysis of these aging-related changes. In addition to these valuable datasets and bioinformatics analyses, the authors performed a large-scale RNAi screen to assess the role of the differentially expressed genes (DEGs) in these mutants and identify several potential targets to promote healthy aging. Moreover, the authors have provided a user-friendly website to examine genes of interest in those longevity mutants from their datasets.

Strengths:

Compared to previous transcriptomic analyses of these mutants in different reports, this study minimized the technical variations and benefitted from the advances in RNA-Seq technology and bioinformatics tools. Therefore, it should provide a more consistent and comprehensive view of the molecular mechanisms underlying the longevity of these mutants. The datasets in this manuscript are valuable to other researchers in the biology of aging.

Weaknesses:

Meanwhile, since these mutants have been extensively studied, the advance of this study in unknown ageing mechanisms remains limited.

Comments on revised version.

In the revised manuscript, the authors have addressed most of my concerns. In the text of this manuscript, the authors should still include more discussion on why osm-5 and daf-2 are categorized into two different groups.

Reviewer #2 (Public review):

Summary:

In the manuscript titled "Multiple Molecular Pathways to Longevity: Opposing Gene Expression Programs Define Distinct Aging Strategies", the authors investigated diverse genetic pathways that contribute to lifespan extension in Caenorhabditis elegans and aimed to identify shared and distinct molecular mechanisms among various longevity mutants. Through comprehensive RNA sequencing of different longevity mutants representing seven distinct pathways, the authors showed that these mutants cluster into three primary groups based on their gene expression profiles. This transcriptomic analysis revealed that while some longevity genes are commonly regulated across multiple pathways, others exhibit opposing expression patterns, suggesting that distinct molecular strategies can lead to increased lifespan. Specifically, they identified a set of 196 genes that are consistently upregulated in most longevity mutants, many of which are involved in innate immunity and stress defense. By performing RNAi-based screening, the authors further validated the functional roles of several candidates, including C08F11.7, ugt-62, and K05C4.9, supporting their contributions to longevity and stress resistance. The authors conclude that longevity is mediated through multiple molecular pathways and provide a public online tool to study these complex transcriptomic landscapes.

Significance:

This study provides a systematic, side-by-side transcriptomic comparison of nine genetically distinct long-lived C. elegans mutants, revealing that lifespan extension arises from both shared and opposing gene expression programs. By identifying three distinct longevity groups and demonstrating that key pathways can be modulated in opposite directions to achieve long life, the work challenges the notion of a single universal transcriptional signature of aging. Importantly, functional validation shows that select commonly regulated genes can directly modulate lifespan and stress resistance, highlighting actionable molecular targets for promoting healthy aging.

Comments on revised version:

The authors addressed my concerns successfully.

Reviewer #1 (Public review):

Summary:

This study aims to clarify MATR3's function and molecular mechanism in oocyte growth and maturation, explore its association with OMA and its potential as a diagnostic and therapeutic target using specific knockout mouse models, human OMA samples and multi-omics technologies. And it has fully achieved preset objectives with results strongly supporting conclusions. Specifically, it addresses the gap in the synergistic mechanism of epigenetic and secretory signals regulated by RNA-binding proteins (RBPs) in oocyte growth and enriches the molecular etiological spectrum of oocyte maturation disorders. It is the first time to reveal the conservative function of MATR3 in multiple species, providing a paradigm for cross-species research on RBPs in the field of reproductive biology. And it provides a new candidate target for OMA, a clinically refractory infertility disease, and is expected to promote the optimization of assisted reproductive technology and the development of precision medicine.

Strengths:

The strengths of this study are significant and prominent. First, the research system is comprehensive, integrating knockout mouse models, in vitro knockdown models, multi-species (mouse, porcine and human) verification, combined with scRNA-seq, LACE-seq, CO-IP and other multi-omics and molecular biology technologies, forming a complete and progressive evidence chain. Second, the mechanism analysis is in-depth, clarifying the dual molecular mechanisms of MATR3 regulating the transcriptional synthesis and secretion of GDF9 through "recruiting KDM3B to regulate H3K9me2 demethylation" and "directly binding to Rdx mRNA", with a clear logical closed loop. Third, the clinical correlation is close. It is the first time to find abnormal nuclear localization of MATR3 in oocytes of OMA patients, providing new clues for clinical disease mechanism research, and verifying the downstream function of GDF9 through rescue experiments, effectively enhancing the translational value of the results.

Weaknesses:

This study included only one OMA patient's oocyte sample. Without clinical screening for MATR3 mutations or abnormal expression, establishing a causal relationship between MATR3 and OMA remains difficult.

Reviewer #2 (Public review):

Summary:

This study investigates the role of MATR3 in oocyte development and folliculogenesis using conditional knockout mouse models together with in vitro follicle culture and molecular analyses. The authors aim to determine whether MATR3 regulates oocyte maturation and follicle development and to explore potential mechanisms linking MATR3 function to transcriptional and epigenetic regulation in growing oocytes.

Strengths:

A major strength of the work is the use of a conditional knockout mouse model combined with complementary in vitro follicle culture approaches, which together provide a useful framework for examining gene function during oocyte development. The study also attempts to integrate cellular phenotypes with molecular analyses of transcriptional activity and epigenetic markers.

Weaknesses:

Several weaknesses limit the strength of the conclusions. These include insufficient validation of key experimental manipulations (such as the efficiency of MATR3 knockdown in siRNA experiments), limited quantification or statistical analysis for some datasets, inconsistencies between the text and presented data in certain figures, and incomplete methodological descriptions that make it difficult to fully evaluate reproducibility.

Comments on revised version.

Thank you for submitting the revised manuscript. I believe the revisions have substantially improved the quality and clarity of the study, and the authors have addressed the major concerns raised during the initial review.

Reviewer #3 (Public review):

Summary:

The study aims to elucidate the dual molecular mechanisms of the RNA-binding protein MATR3 in oocyte growth and maturation. The authors propose that MATR3, highly expressed in growing oocytes (GOs), regulates oocyte quality through two pathways: epigenetically, by recruiting KDM3B to remove the repressive H3K9me2 mark at the Gdf9 locus to activate transcription; and post-transcriptionally, by binding Rdx mRNA to maintain microvillus structure for GDF9 secretion. This mechanism ensures oocyte-granulosa cell communication and female fertility. The study also explores the link between MATR3 and human oocyte maturation arrest (OMA).

Strengths:

The study proposes an innovative dual-mechanism model encompassing "epigenetic transcriptional activation and cytoskeletal regulation," which not only expands the functional understanding of RNA-binding proteins in chromatin regulation but also reveals the coordination between nuclear transcription and organelle structure. By integrating scRNA-seq and LACE-seq, the authors constructed a comprehensive regulatory network for MATR3, identifying both key targets and numerous potential molecules, thereby providing rich resources for future mechanistic studies. Furthermore, the inclusion of oocyte samples from human OMA patients directly links the basic findings to clinical reproductive disorders. Despite the limited sample size, this approach demonstrates strong translational potential.

Weaknesses:

The partial phenotypic improvement achieved by exogenous GDF9 supplementation suggests that the downstream effector pathways may involve a more complex network regulation, implying that the current interpretation of GDF9 central role could be further explored. Regarding the developmental abnormalities of granulosa cells in the conditional knockout model, their pathological origins require in-depth analysis to determine whether they represent primary alterations or secondary adaptive responses resulting from the loss of oocyte signaling.

Reviewer #1 (Public review):

Summary:

This study identifies three redundant pathways-glycine cleavage system (GCS), serine hydroxymethyltransferase (GlyA), and formate-tetrahydrofolate ligase/FolD-that feed the one-carbon tetrahydrofolate (1C-THF) pool essential for Listeria monocytogenes growth and virulence. Reactivation of the normally inactive fhs gene rescues 1C-THF deficiency, revealing metabolic plasticity and vulnerability for potential antimicrobial targeting.

Strengths:

(1) Novel evolutionary insight-Reversible reactivation of a pseudogene (fhs) shows adaptive metabolic plasticity, relevant for pathogen evolution.

(2) They systematically combine targeted gene deletions with suppressor screening to dissect the folate/one-carbon network (GCS, GlyA, Fhs/FolD).

Reviewer #3 (Public review):

Summary:

In this study, Freier et al., demonstrate that 3 distinct metabolic pathways are critical for the synthesis of 1C-THF, a metabolite that is crucial for the growth and virulence of Listeria monocytogenes. Using an elegant suppressor screen, they also demonstrate the hierarchical importance of these metabolic pathways with respect to the biosynthesis of 1C-THF.

Strengths:

This study uses elegant bacterial genetics to confirm that 3 distinct metabolic pathways are critical for 1C-THF synthesis in L. monocytogenes and lack of either one of these pathways compromises bacterial growth and virulence. The study uses a combination of in vitro growth assays, macrophage-CFU assays and murine infection models to demonstrate this.

Comments on revisions:

The revised manuscript is improved, and the additional genetic experiments provide further support for the proposed metabolic model. However, the central conclusion is not fully established without direct measurement of 1C-THF levels. While I appreciate the authors' explanation regarding the technical limitations, quantitative metabolite measurements (e.g., by mass spectrometry) would have provided much stronger evidence linking the genetic perturbations to altered 1C-THF pools.

Reviewer #1 (Public review):

[Editors' note: This revised version of your article has been assessed by the Reviewing Editor without further input from the original reviewers. The comments raised by the original reviewers in the earlier round of review have been addressed. The study findings are quite insightful and important, and the evidence is strong, convincing, and a substantial addition to the evidence base.]

A well-designed and preregistered simulation study investigating whether replication-success metrics can be applied to assess animal-to-human translation. The study is comprehensive, uses realistic parameter settings, and provides valuable insights into how different metrics behave under varied conditions.

Strengths:

(1) Methodologically rigorous and transparently preregistered.

(2) Comprehensive simulation design covering a wide range of plausible scenarios.

(3) Clear description of metrics and decision rules.

(4) Valuable contribution to understanding the limitations of applying replication metrics to translation questions.

Reviewer #2 (Public review):

Summary:

The authors attempt to address the issue of high rates of translation failure from animal studies to humans in the literature, where promising results in animal studies fail when conducting human clinical trials. Using parameters from a previous meta-analysis on prenatal amino acid supplementation and the effects it has on maternal blood pressure, the authors assessed the performance of the metrics used and whether they can quantify translation success. Performing a simulation study, the authors compared nine translation success metrics and found that no one method was uniformly optimal. The authors list several limitations of the study, such as comparability of effect sizes between animal and human studies, different goals of animal studies versus human studies, and the focus of the study on one aspect (statistics of translation) is part of a broader, more complex decision-making process before proceeding to human trials. The authors recommend using multiple metrics in combination while taking into consideration their strengths and weaknesses to assess the translation of animal studies to human outcomes. The paper achieves the aim of providing a model with several metrics to evaluate translation success from animal studies to humans.

Strengths:

(1) Utilizing 9 different translation success metrics in combination provides strong flexibility in evaluating whether results in animal studies can translate to humans. This would allow researchers to evaluate translation success using multiple different metrics according to the context of the study.

(2) The authors accommodated for the limited sample size in animal studies, which are typically underpowered, and also caution that special attention should be given to heterogeneity when interpreting translation results.

(3) Overall, this approach has the potential to be applied to other biomedical studies, provided the limitations for each of the metrics are considered. It would provide a useful tool in assessing translation from animals to humans, in addition to other factors such as safety, pharmacokinetics, etc.

Weaknesses:

While the study has several strengths, there are some limitations.

(1) Preclinical animal study sizes tend to be much smaller than human studies, which results in underpowered results. The authors adjusted for this by pooling animal study data. However, high heterogeneity in the animal studies can affect translation results.

(2) The study focuses only on evaluating the statistical component of translation, which is only one aspect of the decision-making process to move on to human trials. The study does not take into account safety and toxicological profiles, pharmacokinetics, or genetics, which are important considerations that influence the overall effect in humans.

Reviewer #3 (Public review):

Summary:

This paper focused on how to navigate the complex decision-making process of whether to go into human trials. This is a critical topic considering the well-documented challenges in replicating and translating findings. While these are two distinct topics (i.e., replication and translation), they are related, and the authors simulated many conditions to assess the utility of replication assessment metrics.

Strengths:

A major strength of the study is the detailed approach to identifying relevant conditions and metrics, and to providing rich results that outline the strengths and weaknesses of each metric. Any simulation study is challenged by trying to identify the most relevant variables of interest, and this study provided sound justification for its chosen variables of interest. While this study does not make a strong recommendation (which I see as a strength), it does provide a comprehensive overview of the various metrics and conditions that were investigated.

Conclusion:

This paper provides a much-needed investigation and discussion of how decisions are made when assessing whether to go into human trials. This is an important topic that productively challenges the status quo, considering documented challenges in replication and translation in biomedical research.

Reviewer #1 (Public review):

In this manuscript, Clausner and colleagues use simultaneous EEG and fMRI recordings to clarify how visual brain rhythms emerge across layers of early visual cortex. They report that gamma activity correlates positively with feature-specific fMRI signals in superficial and deep layers. By contrast, alpha activity generally correlated negatively with fMRI signals, with two a higher frequency within the alpha reflecting feature-specific fMRI signals. This feature-specific alpha code indicates an active role of alpha oscillations in visual feature coding, providing compelling evidence that the functions of alpha oscillations go beyond cortical idling or feature-unspecific suppression.

The study is very interesting and timely. Methodologically, it is state of the art. The findings on a more active role of alpha activity that goes beyond the classical idling or suppression accounts is in line with recent findings and theories. In sum, this paper makes a very nice contribution to the literature. In particular, it provides a novel characterization of how oscillatory signals orchestrate the coding of visual contents in the visual cortex and provides a starting point for further research examining how this oscillatory coding changes across visual contents and tasks.

Reviewer #2 (Public review):

The authors address a long-standing controversy regarding the functional role of neural oscillations in cortical computations and layer-specific signalling. Several studies have implicated gamma oscillations in bottom-up processing, while lower-frequency oscillations have been associated with top-down signalling. Therefore, the question the authors investigate is both timely and theoretically relevant, contributing to our understanding of feedforward and feedback communication in the brain. This paper presents a novel and complicated data acquisition technique, the application of simultaneous EEG and fMRI, to benefit from both temporal and spatial resolution. A sophisticated data analysis method was executed in order to understand the underlying neural activity during a visual oddball task. The authors defined both feature-specific and feature-unspecific contrasts, further subdivided by EEG power regressors, to examine how orientation information is signalled across cortical layers. Feature specific contrast was established via comparing trials where stimulus orientation (respectively) was left with those where the stimulus orientation was right. Further specifying it depending on EEG power regressors as congruent where stimulus orientation of EEG regressor matches voxel preference or incongruent (stimulus orientation of EEG regressor does not match voxel preference).

Figures are well-designed and appropriately represent the results, which seem to support the overall conclusions. However, some of the claims (particularly those regarding the contribution of gamma oscillations) feel somewhat overstated, as the results offer indeed some significant evidence. On the other hand, the lower-frequency findings are compelling, the functional specificity observed within the alpha frequency band is a particularly interesting result and further highlights the importance of distinguishing feature specificity in order to reveal more nuanced characteristics of neuroimaging data.

Overall, main findings are very interesting, and mainly in line with our current understanding of feedback and feedforward signalling. The paper is well-written, addresses a relevant and timely research question, introduces a novel and elegant analysis approach, and presents interesting findings.

The evidence for gamma involvement in the observed effects is selective: no significant gamma-related clusters were found for the feature-unspecific BOLD signal (Figure 5C,F), with significant effects emerging only in positively responding voxels and only for the contrast between congruent and incongruent conditions in the feature-specific BOLD response. The authors address this in the Discussion, noting that the stimulus may have elicited a weaker gamma response overall, and the contrast of EEG congruent vs. incongruent is necessary in order to achieve the largest contrast-to-noise ratio.

Authors reported negative relationship between the alpha frequency band and the feature specific BOLD signal increases (for congruent condition, Figure 5A,D). Furthermore, testing for the functional specificity between lower vs. upper alpha (Figure 5B,E), the authors included statistical test on the mixed effects model coefficients, and found significant interaction between alpha frequencies in the congruent condition. This interaction was mainly driven by the upper alpha band (which was later confirmed with simple effects analysis) and revealed stronger negative relationship of upper alpha and the BOLD signal for the subtraction of congruent over incongruent conditions. These are exciting results, which further advocate for a more active role of upper alpha band involvement (relative to lower alpha band) in processing visual features.

Expanding on this, the authors have also conducted an exploratory analysis of the relationship between the behavioural findings and underlying neural activity for non-oddball trials (Figure S12 in Supplementary Figures). This confirmed a positive relationship between task performance and alpha frequency, suggesting that high behavioural accuracy is reflected by a stronger modulation of high-frequency alpha power.

This study provides a valuable and exciting contribution to the literature on oscillatory dynamics and laminar fMRI.

Comments on revised version.

Thank you for the thorough revision and for addressing the comments so carefully. The new figures are super beautiful and make the results considerably easier to interpret, they are a real improvement to the paper.

Reviewer #1 (Public review):

Summary:

The article is testing the relative advantages of plant lineages with differing ploidy and admixture across environmental gradients. The results show that intraspecific variation in ploidy and admixture between lineages impacts plant traits that may enable persistence and range expansion.

Strengths:

Suitable marker panel size and convincing results that include attempts to analyse mixed ploidy level data, which is a challenge.

Weaknesses:

(1) Inadequate explanation of allele dosage for ploidy levels, some of which do not match the allele counts expected for genome copy number.

(2) The setup and sample sizes of the common garden experiments are very unclear. The numbers implied are extremely low to draw robust conclusions.

(3) Unclear how allele dosage is determined. Given it's so central to many analyses, it would be useful to see how this is done rather than use a citation.

Reviewer #2 (Public review):

Summary:

This manuscript describes a combination of species distribution mapping experimental data from common garden and physiological experiments to project the future distribution of genetic subgroups with the widespread grass Phragmites australis. Overall, the sample sizes seem appropriate for the questions being asked, and the key results regarding projected change in distribution of the focal lineages are well supported. However, at this point, it is difficult to evaluate the broader impact of the work on the field or the utility of the data for the broader community outside of those studying the focal species, P. austrina.

Strengths:

A key strength of the paper is the use of common garden and physiological experiments in conjunction with species distribution modeling. The experiments provide a mechanistic basis for the correlations between interspecific lineage and climatic data, suggesting that the distributional patterns are more likely to result from genetic differences rather than limited dispersal among regions. I would, in fact, emphasize the experimental validation of modeling efforts even more in the introduction.

Weaknesses:

I see two weaknesses with the framing of the ms and the presentation of the results. First, no data support the claims that polyploidy has any causal effect. The ploidy levels are, in fact, completely confounded with other genetic differences, so it is not possible to eliminate genetic variation, independent of ploidy, as the causative factor. As the authors note, ploidy was not manipulated in the reported experiments. Thus, the focus on polyploidy in the introduction and elsewhere distracts from the novel and informative experiments that were conducted. Second, the manuscript indicates that intraspecific variation is critical for the evolutionary potential of a species to respond to environmental change, but intraspecific variation is seldom considered in species distribution models. To me, an assessment of evolutionary potential requires estimates of heritable genetic variation and responses to selection. The sample sizes presented here are modest to estimate heritabilities, but the manuscript could be framed with this perspective in mind. However, instead, the manuscript performs species distribution modeling on a small number of sub-specific lineages, essentially treating them as homogeneous "species" - thus the analysis commits the same oversimplification that the manuscript highlights, but does so at a finer evolutionary scale than species. Not acknowledging this simplification (or better, examining phenotypic variation within the genetically defined lineages) hinders what would otherwise be a strength of the manuscript.

The title suggests that asymmetric introgression and thermal tolerance are the most important findings of the work. However, the introduction contains no explanation of the potential importance of gene flow (other than to say that asymmetric gene flow was suggested by some preliminary analyses), and the discussion offers only a limited explanation of either the potential mechanisms underlying the asymmetric gene flow or its importance for the long-term evolution of the species. Similarly, the novelty of combining experiments and species distribution modeling is scarcely mentioned, and there is no exploration of the connection between tolerance alleles and gene flow. Could introgression of heat tolerance alleles alter the spread of the hybridizing lineages, for example? A greater emphasis on these general population genetic parameters could potentially highlight the broader impact of this work.

Reviewer #1 (Public review):

Summary:

This manuscript describes an investigation of peptide analogue agonists selective for the human Y4 receptor for pancreatic polypeptide over Y1, Y2 and Y5 receptors. After studies of mutated Y4R in transiently transfected COS-7 cells, binding models were calculated. Then, screening of a virtual library identified three non-peptidergic (albeit somewhat peptide-like) compounds with potential agonist activity that were subsequently confirmed and furthermore were found to have receptor interactions similar to the peptide analogues. This study provides fundamental new information that improves understanding of the Y4R structure and mechanism of activation by the native agonist and the selective peptide analogues. The non-peptide agonists have potential for future pharmacotherapy.

Strengths:

All of the experiments seem to be well performed, using state-of-the-art methods. The manuscript is quite comprehensive and has used a broad range of methods. The conclusions are convincingly supported by the experimental results.

Weaknesses:

The mutagenesis was almost exclusively based on the replacement of potentially interesting amino acid residues with alanine. Replacement with other residues, based on modelling and docking, could have refined the model further. Neither molecular dynamics nor cryo-EM was used to study the agonists' interactions with the Y4 receptor and these are therefore likely next steps in the characterization of the Y4R mechanism of activation.

Reviewer #2 (Public review):

Summary:

Pelczyk et al. investigated the binding site of the neuropeptide Y Y4 receptor with the aim of identifying novel small-molecule agonists. The authors first assessed small cyclic peptides as tool compounds and then identified interactions between peptides and receptor residues, which were confirmed by single-point mutagenesis combined with functional assays for intracellular signalling. It is interesting that a peptide receptor can be activated by the relatively small cyclic peptides used in the study. The authors identified both common and peptide-specific interactions. The identified interactions guided ultra-large library screening, which yielded 53 compounds, 3 of which were confirmed as Y4R-specific agonists in an IP-one accumulation assay.

Strengths:

The combination of techniques (docking, mutagenesis and functional assays) strongly supports the identification and evaluation of small molecules as agonists at the neuropeptide Y Y4 receptor. Functional assays highlight residues that are important for the binding of all tested peptides, as well as residues with peptide-specific importance.

The structure-activity relationship component of the study nicely highlights which components of the peptide are important for binding to the different members of the neuropeptide Y receptor family.

Weaknesses:

It would have been great to see concentration-response curves for the three identified small-molecule agonists, as this would have stengthened the case for these agonists.

Reviewer #1 (Public review):

Summary:

In this manuscript, Flamholz and colleagues use metagenomic sequencing to profile the microbiome of individuals with sickle cell disease (SCD), the most common genetic blood disorder in the world. To build on previous studies that found dysbiosis in SCD, this manuscript aims to examine whether changes in either bacterial species or bacteriophages correlate with inflammatory hallmarks of the disease. The authors claim that sickle cell dysbiosis does not correlate with inflammatory hallmarks of the disease, but instead, aged neutrophil numbers and bacteriophages do. Appropriate control subjects and additional analyses are needed to support that conclusion.

Strengths:

The primary strength of this paper is the investigation into disease-associated changes in bacteriophages. This is an entirely novel idea in the sickle cell field, and based on the current results, may be an important, under-recognized disease hallmark. It is unclear, however, if phages are "the chicken or the egg" in terms of sickle cell inflammatory profiles; do these increases in phage number simply result from other disease processes, or are they in any way contributing to disease pathophysiology?

Weaknesses:

A primary weakness of the manuscript is the fact that the majority of individuals included in the control group maintain sickle cell trait (HbAS genotype). Although typically asymptomatic, it is unclear if this genotype is associated with microbial changes that would not be observed in a true control group (HbAA genotype). This is a significant limitation that may limit the ability to draw conclusions from the current data set.

Another key weakness is the lack of beta diversity assessment. Although decreased alpha diversity is observed in individuals with SCD, and specific bacterial taxa are differentially abundant following multivariate analyses, there is no overall comparison of bacterial community composition between individuals with SCD and controls. Prior to drawing conclusions about the relationship (or lack thereof) between the SCD microbiome and inflammatory markers, it is important to know if this study did indeed find disease-associated changes in microbiome composition.

It is unclear which individuals were used for aged neutrophil (AN) and molecular data assessments. For example, were children who were still receiving penicillin prophylaxis included in these specific assessments? Given the authors' previous work demonstrating that antibiotic treatment decreases AN pathology, it seems critical to limit all AN/molecular analyses to older subjects who are not on daily penicillin treatment (if possible).

A minor weakness is the continued use of "disease" vs. "healthy" indicators as primary microbiome metrics that are used for molecular correlations. The lack of metric specificity - and lack of discussion regarding which diseases were used to generate these indicators (how similar/different are they to sickle cell?) - could be said to make these metrics essentially meaningless.

Reviewer #2 (Public review):

Summary:

The study analyzes stool metagenomes from 98 SCD patients and 46 controls, with SCD and control groups matched on age, race, sex, and ethnicity. The authors report lower Shannon diversity, lower Firmicutes/Bacteroidetes ratio, loss of health-associated taxa, increased disease-associated indicators, altered butyrate/fatty-acid metabolism pathways, and enrichment of provirus/prophage fractions in SCD. They further correlate aged-like neutrophils and prophage fractions with inflammatory cytokines. The main strength is that this is not just another 16S comparison. The use of whole-community metagenomics, immune profiling, neutrophil assays, and clinical metadata makes the study more biologically interesting than prior small SCD microbiome papers. The main weakness is that the causal and mechanistic interpretation is too strong. The data support an association between SCD status and microbiome/virome features, but they do not yet establish a clear "axis of pathophysiology." The provirus findings are intriguing, but require stronger statistical control, better validation, and more cautious interpretation.

Strengths:

The major strengths of the study include the clinically relevant disease setting, the use of whole-community sequencing, the integration of microbial, immune-cell, cytokine, and clinical measurements, and the novel attention to bacterial virus-related features. A particularly interesting aspect of the work is the analysis of virus-like elements integrated into bacterial genomes. The authors report that these elements are enriched in the gut microbial communities of patients with sickle cell disease and are associated with several inflammatory signals in blood. This observation is potentially important because it suggests that the microbial contribution to inflammation in sickle cell disease may involve not only bacteria but also bacterial virus-related genetic elements.

Weaknesses:

The evidence for this proposed immune-related mechanism is incomplete. The study is cross-sectional and largely based on associations, so it cannot determine whether these virus-like elements drive immune activation, reflect immune activation, or are linked indirectly through disease severity, treatment history, or other clinical factors. The main limitations are the single-center design, modest sample size for some immune measurements, limited ability to control for treatment and disease heterogeneity, and the need for clearer multiple-testing correction in the correlation analyses. In particular, stronger adjustment for available clinical factors such as hydroxyurea use, transfusion history, pain admissions, genotype, and other markers of disease burden would help readers judge how specific the microbial and viral findings are to sickle cell disease itself.

Overall, the authors largely achieve their descriptive aim of identifying gut microbial differences associated with sickle cell disease. The evidence is solid for the presence of broad microbial community differences, but incomplete for the stronger conclusion that virus-like elements form a pathophysiological immune axis. The work will likely be useful to researchers studying the microbiome, inflammation, and sickle cell disease, especially as a hypothesis-generating dataset. Its impact would be strengthened by more cautious interpretation, stronger control of clinical confounders, clearer statistical correction, and future longitudinal or experimental studies to test causality.

Reviewer #3 (Public review):

Summary:

In this manuscript, Flamholz et al. sought to determine whether consistent and significant interactions exist between the gut microbiome and disease pathology in sickle cell disease (SCD). By sequencing and analysing metagenomes from faecal samples collected from 98 SCD patients and 46 control subjects, they identified community-level shifts in both the bacterial and proviral gut microbiome of SCD patients. They further reported correlations between the proviral microbiome and multiple blood cytokines, whereas similar associations were not observed for the bacterial microbiome. Based on these findings, the authors propose the existence of a viral-immune axis in SCD pathophysiology and targetable functional alterations in the gut microbiome.

Strengths:

This work includes the largest SCD cohort analysed to date, enabling analysis with relatively strong statistical power. In addition to profiling the bacterial microbiome, the study also examines the gut proviral microbiome, thereby providing a more comprehensive investigation of the topic. The newly generated metagenomic dataset will also be valuable for further meta-analysis by the wider community. Overall, the authors have largely achieved their aims.

Weaknesses:

However, this study represents a single-centre cross-sectional investigation, and most findings remain correlative in nature. In particular, the claim that the study identifies targetable functional alterations in the gut microbiome for disease treatment may be somewhat overstated. Although the reported functional module changes in SCD patients are intriguing, additional mechanistic and/or longitudinal evidence would be required before these features can realistically be considered targetable.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have satisfactorily addressed the comments raised in the previous round of review with textual revisions.]

Summary:

The manuscript by Singh et al. presents an application of MOA-seq to better define transcriptional control underlying the hypoxia response in human endothelial cells. This group's previously described MOA-seq technique allows for precise, identity-agnostic mapping of occupied sites of DNA-binding proteins across the epigenome and over time. Here, they applied MOA-seq to HUVECs under normal oxygen conditions or variable lengths of hypoxia treatment, comparing changes in occupancy over time and associating these changes with corresponding transcriptome alterations. This approach revealed thousands of dynamically occupied sites comprising 10 major kinetic clusters that appear to define distinct subsets and phases of the hypoxia response. Analysis of DNA motifs in these dynamically occupied regions captured the known major roles of HIF1A in the hypoxia response and also implicated new HIF1A-associated regulators. Importantly, they also identified many potential HIF1A-independent candidate TFs that act at HREs, which has been an outstanding question in the field. Additionally, this study identified ~7K additional sites not previously defined as regulatory elements by ENCODE.

Strengths:

Overall, this study is well executed and described, providing new biological insights as well as a rich data resource for the field. As MOA-seq was previously developed for use in plants, this work demonstrates the application of this method in mammalian cells and highlights its utility in identifying new potential regulatory sites not captured by DNase-seq or ATAC-seq. The conclusions made by the authors are well supported by the results, with the caveat that extensive use of DNA motif identification and ontology analyses invariably leads to some uncertainty regarding factor identity and gene network properties.

Reviewer #2 (Public review):

Summary:

Singh et al. apply MOA-seq to map transcription factor occupancy genome-wide in HUVECs across a hypoxia time course. The study provides a well-validated, high-resolution view of cistrome dynamics and identifies both HIF1A-associated and independent regulatory programs.

Major comments from the first round of review:

Methodological validation is strong. MOA-seq's ability to map protein-bound DNA at near-nucleotide resolution without factor-specific antibodies is a genuine advance, and the cross-validation against independent ChIP-seq and ENCODE datasets is convincing. As noted, future work with additional biological replicates could further strengthen confidence in the smaller kinetic clusters.

Imaging-based validation would strengthen the key biological claims. The kinetic clustering and pathway enrichments are computationally inferred. Orthogonal approaches, for example, live-cell fluorescence imaging of HIF1A nuclear translocation to confirm the proposed temporal binding waves, would provide independent experimental support.

Reviewer #2 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers.]

Summary:

This paper is an exciting follow-up to two recent publications in eLife: one from the same lab, reporting that slender forms can successfully infect tsetse flies (Schuster, S et al., 2021), and another independent study claiming the opposite (Ngoune, TMJ et al., 2025). Here, the authors address four criticisms raised against their original work: the influence of N-acetyl-glucosamine (NAG), the use of teneral and male flies, and whether slender forms bypass the stumpy stage before becoming procyclic forms.

Strengths:

We applaud the authors' efforts in undertaking these experiments and contributing to a better understanding of the T. brucei life cycle. The paper is well-written and the figures are clear.

Comments on revisions:

We thank the authors for the revised manuscript and for considering our comments.

Reviewer #1 (Public review):

Summary:

This manuscript reports the discovery and characterization of the first bifunctional degrader of tankyrase. Notably, the tankyrase degrader exhibits stronger β-catenin inhibition and tumor growth suppression compared to conventional tankyrase inhibitors. Mechanistically, while tankyrase inhibitors stabilize tankyrase and promote Axin puncta formation-thereby impairing β-catenin degradation-the degrader avoids this effect, resulting in deeper suppression of β-catenin signaling. These findings suggest that targeted degradation of tankyrase offers a novel therapeutic strategy for β-catenin-driven cancers. Overall, this is a compelling study with significant translational potential.

Strengths:

(1) The manuscript presents a rigorous and well-executed study on a timely and impactful topic.

(2) The biochemical and cellular characterization of the tankyrase degrader is thorough, and the comparative analysis with tankyrase inhibitors is insightful.

(3) The finding that tankyrase stabilization by inhibitors may interfere with Axin function is novel and significant. It aligns with earlier observations (e.g., Huang 2009) that transient tankyrase overexpression can stabilize β-catenin independently of PAR domain activity.

(4) The use of TNKS1/2 knockout cells expressing catalytically inactive tankyrase to demonstrate β-catenin inhibitory activity of the tankyrase degrader is elegant.

(5) The finding that the tankyrase degrader has superior anti-proliferative effects in colorectal cancer models has important therapeutic implications.

Comments on revised version:

I had a favorable opinion of the manuscript in the first round of review. I don't have additional comments on the revised manuscript. The manuscript looks fine to me.

Reviewer #2 (Public review):

Summary:

The ADP-ribosyltransferase tankyrase controls many biological processes, many of which are relevant to human disease. This includes Wnt/beta-catenin signalling, which is dysregulated in many cancers, most notably colorectal cancer. Tankyrase is a positive regulator of Wnt/beta-catenin signalling in that it counters the activity of the beta-catenin destruction complex (DC). Catalytic inhibition of tankyrase not only blocks PAR-dependent ubiquitylation and degradation of AXIN1/2, the central scaffolding protein in the DC, but also tankyrase itself. As a result, blocking tankyrase gives rise to tankyrase accumulation, which may accentuate its non-catalytic functions, which have been proposed to drive Wnt/beta-catenin signalling. Most tankyrase catalytic inhibitors have shown limited efficacy and substantial toxicity in vivo. By developing tankyrase-directed PROTACs, the authors aim to block both catalytic and non-catalytic functions of tankyrase, aspiring to achieve a more complete inhibition of Wnt/beta-catenin signalling. The successfully developed PROTAC, based on the existing catalytic inhibitor IWR1, IWR1-POMA, induces the degradation of both TNKS and TNKS2, blocks beta-catenin-dependent transcription without stabilising the DC in puncta/degradasomes, and inhibits cancer cell growth in vitro. Mechanistically, this points to a scaffolding role of tankyrase in the DC, at least under conditions of tankyrase catalytic inhibition, in line with previous proposals.

Strengths:

The study clearly illustrates the incentive for developing a tankyrase degrader, namely, to abolish both catalytic and non-catalytic functions of tankyrase. By and large, the study achieves these ambitions, and the findings support the main conclusions, although the statement that a more complete inhibition of the pathway is achieved requires corroboration. The proteomics studies are powerful. IWR1-POMA constitutes a very useful tool to re-evaluate targeting of tankyrase in oncogenic Wnt/beta-catenin signalling. The paired compounds will benefit investigations of tankyrase scaffolding functions across many different biological systems controlled by tankyrase. The findings are exciting.

Comments on revised version:

I thank the authors for responding to the queries raised in the original review, most of which have now been addressed. This further strengthens this well-conducted study and well-presented manuscript. I congratulate the authors for this interesting and insightful work.

A few minor points remain:

I appreciate the authors acknowledge that testing the physical properties of the degradasome puncta is necessary to explore whether they indeed represent condensates. The term "condensates" implies liquid-liquid phase separation (rightly or wrongly). However, this question has not yet been resolved in the case of degradasomes. I therefore suggest the term "condensates" to be avoided. A simple morphological description as "puncta" may suffice.

I thank the authors for including the additional data comparing tankyrase binding by IWR and IWR-POMA. I agree that using the BRET signal of IWR-POMA is informative. Adding the IC50 values directly to the figure panels (S3E, S3G) would help the reader to quickly assess binding. The comparison between these two panels is insightful.

Regarding the use of the terms TNKS, TNKS1 and TNKS2, if the authors would like to use the name "TNKS" to refer to both paralogues collectively, can this please be specified early in the manuscript to limit confusion with the official gene name "TNKS", which of course only refers to one paralogue?

Reviewer #3 (Public review):

In this manuscript, Wang et al employ a chemical biology approach to investigate the differences between the enzymatic and scaffolding roles of tankyrase during Wnt β-catenin signalling. It was previously established that, in addition to its enzymatic activity, tankyrase 1/2 also plays a scaffolding function within the destruction complex, a property conferred by SAM-domain-dependent polymerization (PMID: 27494558). It is also known that TNKS1/2 is an autoregulated protein and that its enzymatic inhibition leads to accumulation of total TNKS proteins and stabilization of Axin punctae (through the scaffolding function of TNKS1/2), leading to rigidification of the DC and decreased β-catenin turnover. The authors surmised that this could, in part, explain the limited efficacy of TNKS1/2 catalytic inhibition for the treatment of colorectal cancers. To test this hypothesis, they evaluated a series of PROTAC molecules promoting the degradation of TNKS1/2 to block both the catalytic and scaffolding activities. They show that IWR1-POMA (their most active molecule) promotes more efficient suppression of beta-catenin-mediated transcription and is more active in inhibiting colorectal cancer cell and CRC patient-derived organoids growth. Mechanistically, the authors used FRAP to demonstrate that catalytic inhibitors of TNKS led to a reduced dynamic assembly of the DC (rigidification), whereas IWR1-POMA did not affect the dynamics.

Overall, this is an interesting study describing the design and development of a PROTAC for TNKS1/2 that could have increased efficacy where catalytic inhibitors have displayed limited activity. Knowing the importance of the scaffolding role of TNKS1/2 within the destruction complex, targeting both the catalytic and scaffolding roles certainly makes sense. The manuscript contains convincing evidence of the different mechanisms of the PROTAC vs catalytic inhibitors. Some additional efforts to quantify several of the experiments and to indicate the reproducibility and statistical analysis would strengthen the manuscript. Ultimately, it would have been great to evaluate the in vivo efficacy of IWR1-POMA in an in vivo CRC assay (APCmin mice or using PDX models); however, I realize that this is likely beyond the scope of this manuscript.

Reviewer #4 (Public review):

From the Reviewing Editor:

This important study reports the development of the first PROTACs targeting the ADP-ribosyltransferases tankyrase 1 and 2, with the goal of inhibiting Wnt/β-catenin signaling more completely than is possible with catalytic tankyrase inhibitors. The work addresses a significant limitation of existing tankyrase inhibitors: although catalytic inhibition stabilizes AXIN1/2 and suppresses Wnt signaling, it also stabilizes tankyrase itself, potentially enhancing non-catalytic scaffolding functions and promoting accumulation of degradasome-like puncta.

The evidence is convincing. The authors use appropriate and well-validated approaches, including chemical biology, cellular assays, and proteomic profiling, to show that PROTAC-mediated degradation of tankyrase avoids tankyrase accumulation while still stabilizing AXIN and inhibiting Wnt/β-catenin signaling. The data support the conclusion that degradation of tankyrase can separate pathway inhibition from the confounding effects of stabilized tankyrase protein and may therefore offer advantages over conventional catalytic inhibitors.

A strength of the study is the clear mechanistic comparison between tankyrase degradation and catalytic inhibition. The manuscript provides convincing evidence that the PROTAC and catalytic inhibitors act through distinct mechanisms, with the PROTAC targeting both catalytic and scaffolding roles of tankyrase. The study is well conducted and clearly presented, and the authors have addressed most concerns raised during review.

A remaining limitation is that the therapeutic potential of the compound is not tested in vivo, for example in APC-mutant colorectal cancer models, APCmin mice, or patient-derived xenografts. Such experiments would strengthen claims about practical efficacy, although they are not essential for the main mechanistic conclusions of the manuscript.

Overall, this is an important and insightful contribution. It advances the tankyrase and Wnt signaling fields by providing a new chemical strategy to suppress tankyrase function more completely than catalytic inhibition alone, and it offers a useful framework for future therapeutic exploration of tankyrase degradation.

Reviewer #1 (Public review):

Summary:

This "Tools and Resources" submission describes a platform for the modeling of stimulus-response relationships in the retina. It includes a repository for experimental data sets with standardized programmatic access, and a suite of software for constructing stimulus-response models and evaluating them.

Strengths:

(1) The paper is well written.

(2) The platform could serve an integrative function by connecting different research programs and offering a common baseline for evaluating stimulus-response models.

(3) The finding that there is "substantial explainable variance remains uncaptured by current models" is a useful insight to motivate further work and measure progress.

Weaknesses:

(1) The modeling supported by the package focuses on predictive accuracy at the cost of less interpretability.

(2) The article needs to make a stronger argument that this style of modeling is fruitful, especially when applied to the retina.

Main comments:

(1) Abstract machine learning vs mechanistic models. The "Core + Readout" architecture advocated here seems to be divorced from all the neurobiological detail that is already known in the retina. It mostly aims at prediction, not interpretation. Such a black-box modeling framework is useful in brain regions where we know very little about connectivity, or mechanisms, or even about the primary function being performed there, like in the mammalian cortex. In those cases, any model that can deliver a prediction is a step forward, even if it does not connect to biological mechanisms. But that's decidedly not the situation in the retina, where so many mechanistic details are known: from consensus cell types, to synaptic detail, to single-neuron biophysics, to circuit motifs. How can one connect this ML modeling approach with the extensive mechanistic knowledge available in retinal neuroscience? And can the combination somehow lead to a better understanding? The authors seem to recognize this tension (e.g. line 215ff and 370ff) but don't give it much weight. A stronger case needs to be made here for how this kind of modeling will advance the field.

(2) The "gradient field" approach. Figure 4c illustrates a case of this dissonance. The gradient field of the response increases with contrast in multiple directions. This is obvious a priori (see line 274) from the more mechanistic model we already have of this On-Off cell. These are the W3 cells described in www.pnas.org/cgi/doi/10.1073/pnas.1211547109. The circuit-based model from that paper, with rectifying on and off subunits from bipolar cells, gives a much more compact explanation for what the neuron does. Because each of the subunits has a spatio-temporal receptive field, this model can predict the entire dynamics to arbitrary stimuli, rather than just 2 dimensions of static stimuli as in the present analysis. So what is the value added here? Again, a stronger case needs to be made that these "Core + Readout" modeling activities enhance understanding.

(3) The "most exciting input" approach (Line 193ff):

- Presumably, some power constraint must be put on the stimulus? Otherwise, increasing the contrast will make it more exciting. What are these constraints?

- Presumably, this optimal stimulus is computed from the model based on non-optimal stimuli? What are the assumptions going into that?

- The most exciting stimulus is not necessarily the most useful characterization. Near its maximal firing rate, the neuron doesn't discriminate stimuli much, because the slope there is zero (line 237). Instead (or in addition), one would like to know along which stimulus axis the neuron is most sensitive. See e.g. discussion in Dayan & Abbott 2000, Figure 3.11.

Reviewer #2 (Public review):

Summary

openretina is a Python package for training and applying convolutional neural network-based models of retinal ganglion cell responses. The package integrates dataloading, model training, and evaluation in a unified framework built on PyTorch Lightning and Hydra, and ships with pre-trained model checkpoints and publicly available datasets (whitenoise, natural scenes) spanning multiple species (marmoset, mouse, axolotl, salamander) and recording modalities (multielectrode array recordings or 2-p calcium imaging). Beyond predictive modelling, openretina includes a suite of in silico analysis tools for probing learned representations, including maximally exciting input synthesis, discriminatory stimulus optimisation, and model weight visualisation. The broader openretina initiative aims to establish a community-driven platform for computational retina research, lowering barriers to entry and facilitating cross-dataset model benchmarking. This is a valuable contribution given the longstanding fragmentation of datasets, codebases, and analysis practices across retina laboratories.

Strengths:

The tool has several strengths. By providing a framework built on deep learning infrastructure, the package substantially lowers the barrier to entry for researchers without extensive machine learning backgrounds. The inclusion of pre-trained model checkpoints across multiple species and recording modalities will allow users to apply state-of-the-art models. The in silico toolkit - and in particular the MEI synthesis pipeline - has already demonstrated its scientific potential, with prior work using optimised stimuli to discover a previously uncharacterised RGC type confirmed experimentally, illustrating what becomes possible when these tools are made broadly accessible. The current modular Core + Readout architecture is a well-suited architecture for modeling retina responses. The HDF5-based data standard provides a sensible common format for contributing new datasets. Overall, the initiative is well-motivated, the engineering is competent, and the vision of a collaborative, community-driven platform for retina modelling is one that the retina community would benefit from.

Weaknesses:

(1) The in silico tools provided are valuable, but users should interpret their outputs in light of the performance of the underlying models. The predictive performances of current models and datasets in the package are far from performance ceilings.

(2) The authors appropriately note that optimised stimuli reveal what a neuron responds to but not how the computation is implemented. I would encourage readers to keep this distinction in mind when using the weight visualization tools as well - convolutional filters in a shared, unconstrained core do not map onto retinal circuit elements, and should be treated as model descriptors rather than circuit proxies. For example, RGCs of the same type may appear to sample inputs from two different filters, which should have been a single filter. Or a single RGC may be sampling from two filters, which under more constrained conditions could be approximated with a single filter. These are degeneracies in the CNN modeling framework that should be kept in mind when drawing circuit-level interpretations.

(3) The datasets currently distributed with the package vary in recording quality, and users should be aware that model performance may not only reflect architectural limitations but may also be limited by noise and data artifacts, including spike sorting errors.

(4) As the platform grows and community-contributed datasets are added, explicit data quality standards will be essential. I encourage the authors to develop dataset standards to ensure that their resource provides access to highly curated datasets, which I believe is an important step in having high-fidelity models whose functional interpretations can be trusted.

Reviewer #3 (Public review):

Summary:

This manuscript presents openretina, a Python-based platform designed to facilitate collaborative retinal modeling across datasets, laboratories, species, and recording modalities. The package provides standardized model architectures, evaluation metrics, and analysis tools, while also integrating several publicly available retinal datasets. The authors further demonstrate the platform through examples of in silico analyses and model benchmarking.

Strengths:

(1) Emphasis on standardization and reproducibility. Retinal modeling has become increasingly dependent on deep learning approaches, yet datasets and evaluation procedures remain fragmented across laboratories. By providing a unified framework, the authors lower barriers to entry and create opportunities for more systematic comparisons of models and datasets.

(2) The manuscript is clearly written, and the examples effectively illustrate the range of analyses supported by the platform.

(3) The benchmarking results are useful, particularly because they reveal substantial remaining gaps between current model performance and explainable variance ceilings.

Weaknesses:

Not a weakness per se, but rather a limitation, is that the manuscript focuses on software infrastructure rather than new biological or computational insights. While this is appropriate for a resource paper, some of the scientific examples, such as the gradient-field analysis of ON-OFF cells, function more as demonstrations than as rigorous validations of novel hypotheses. It might be useful to add a few sentences discussing potential scientific projects that can be immediately facilitated by the openretina (the current text in the Discussion focuses more on advancements in the technical/social aspects of science that will be supported by openretina).

Overall, this is a valuable and timely resource that is likely to benefit the retinal and computational neuroscience communities.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors apply the AsLOV2 domain to control the localisation and the exposure of two peptides (PMI and PMI-M3) that compete with Mdm2/MdmX for binding to p53, thus freeing p53 from these negative regulators and allowing its levels to rise. The authors follow an established strategy in optogenetics, which is to combine two layers of regulation for tighter control: (1) caging the peptide into the Ja helix of AsLOV2; 2) sequestration of the peptide away from its site of action using the LOVTRAP system.

Strengths:

The authors show that a reporter is activated when cells are exposed to light. A strength is in the lower background that was achieved after adding the second layer of regulation.

Weaknesses:

This study claims to be focused on the control of endogenous p53; however, endogenous p53 levels are not quantified. Moreover, endogenous p53 target genes are also not analysed. Only a synthetic reporter is quantified, which has been placed in the genome of HCT116 cells after the creation of a stable cell line. Microscopy images show only one or a maximum of two cells. Finally, the authors claim their strategy is a general one that can be applied to control other peptides, but they do not show this generality in this paper.

Reviewer #2 (Public review):

The authors developed Opto-MDMi, an optogenetic system for light-controlled activation of endogenous p53. The main idea is to target the p53-MDM2/MDMX regulatory interaction using PMI inhibitory peptides. This is a nice strategy because it avoids overexpression of p53, which can have adverse effects that might confound the study of p53 activity. The authors first tested a LOVTRAP-based localization strategy, which showed some efficacy but also showed basal activation. They then developed a LOV2-PMI peptide-caging module to control the activity of the PMI peptide itself, testing for interactions first in vitro and then in vivo. Finally, they combined the two systems into a dual-lock design, where LOVTRAP controls localization and LOV2-PMI controls peptide activity. This combination led to somewhat more potent stimulation of p53 activity.

Another useful aspect of the paper is the detailed description of the development and testing of the LOV2-PMI peptide-caging module, which may aid in the design of other LOV2-based peptide-caging designs.

Strengths

Overall, the paper is novel and rigorous, and the claims are supported by the data. The optoMDMi tool seems ready for implementation, for example, to manipulate and study the role of p53 signaling dynamics. A few points of clarification would strengthen the work.

Weaknesses

The authors develop many tool variants, but there is some lack of clarity over how all of these tools compare to each other, and which ones interested users should use. The work would also be strengthened by showing modulation of endogenous p53 in more than one cell line.

Reviewer #1 (Public review):

Summary:

This is an important and interesting manuscript that uncovers the cross-talk between mitochondrial quality control and phagosome maturation arrest imposed by Mtb.

A broader host pathogen (intracellular) question pertains to evading phagosomal maturation/arrest. While cellular events that culminate in this arrest have been largely elucidated, involvement of other organelles, such as mitochondria, has not been highlighted mechanistically. This manuscript paints a larger picture than the well-known conventional endolysosomal pathway and portrays a larger landscape involving elements of the mitochondrial quality control, such as mitophagy and mitochondrial-derived vesicles' involvement in the host-pathogen tussle.

Strengths:

The systematic characterisation to unravel the interplay between mitochondrial-related pathways and the endolysosomal system allows the authors to unearth some important findings.

Weaknesses:

The conclusions drawn require more robust experimentation and analysis.

Reviewer #2 (Public review):

This manuscript examines the role of autophagy receptor proteins, particularly p62/SQSTM1, in regulating intracellular Mtb survival in human macrophages. Counterintuitively, depleting p62 reduces bacterial survival rather than enhancing it, pointing to a previously unrecognised mechanism. The authors demonstrate that in the absence of p62, mitochondrial quality is maintained through enhanced TOM20⁺ mitochondria-derived vesicle (MDV) biogenesis, dependent on MIRO1/MIRO2. During Mtb infection, these MDVs are redirected to bacterial phagosomes, promoting RAB7 recruitment, overcoming phagosome maturation arrest and facilitating lysosomal targeting of Mtb. In parallel, bacteria experience increased oxidative stress, further contributing to bacterial killing.

Strengths:

The mechanistic chain is built using multiple complementary approaches, including genetic perturbation, redox biosensors, metabolic assays and microscopy. The use of primary human macrophages from multiple donors alongside established cell lines increases confidence that the phenotype is not cell-line specific. The replication clock experiment is particularly elegant and clearly demonstrates that the reduction in bacterial burden reflects enhanced killing rather than impaired bacterial replication. Overall, the study identifies an unexpected connection between mitochondrial quality control and phagosome maturation and provides a potentially important advance in our understanding of host-pathogen interactions.

Weaknesses:

The study remains entirely in vitro, and the phenotype is absent in mouse macrophages, limiting the immediate physiological and translational relevance of the findings. In addition, many of the central mechanistic conclusions rely heavily on colocalisation analyses, making it difficult to distinguish direct mechanistic relationships from associated trafficking events.

Overall, this is an interesting and technically strong study that uncovers a novel link between mitochondrial quality control and anti-mycobacterial defence. The mechanistic model is plausible and supported by substantial experimental work. However, several aspects of the proposed pathway require stronger experimental support before some of the broader conclusions can be fully justified.

Major points

(1) The central conclusion that TOM20⁺ MDVs are recruited to Mtb-containing phagosomes is based largely on microscopy and colocalisation analyses. Additional orthogonal approaches would strengthen this key aspect of the study and help establish the nature of the vesicles recruited to bacterial phagosomes.

(2) The proposed mechanism whereby TOM20⁺ MDVs facilitate RAB7 recruitment and reverse phagosome maturation arrest remains incompletely demonstrated. While the MIRO1/2 and RAB7 knockdown experiments support the model, they do not directly establish a causal link between MDV recruitment and phagosomal RAB7 acquisition. Additional experiments addressing this step would considerably strengthen the manuscript.

(3) The absence of a phenotype in mouse macrophages raises important questions regarding the conservation and physiological relevance of the proposed mechanism. The authors should discuss possible explanations for this species-specific effect and, if feasible, provide additional experimental insight into the basis of this difference.

(4) The conclusion that mitochondrial quality is maintained despite impaired p62-dependent mitochondrial turnover is based primarily on mitochondrial content, membrane potential, ROS measurements and Seahorse analysis. These are informative but relatively indirect measurements. Additional assessment of mitochondrial turnover by mitophagy would strengthen this aspect of the study.

(5) The proteins studied throughout the manuscript (p62/SQSTM1, NDP52, OPTN, TAX1BP1 and NBR1) are generally classified as selective autophagy receptors rather than adaptors. The terminology should be corrected throughout the manuscript.

Minor points:

(1) Several conclusions throughout the manuscript are based primarily on colocalisation analyses. The limitations of these approaches should be acknowledged explicitly.

(2) The discussion would benefit from a clearer consideration of how the proposed mechanism relates to established pathways regulating phagosome maturation arrest during Mtb infection.

(3) The authors may wish to comment on whether enhanced MDV biogenesis could represent a broader host defence mechanism against intracellular pathogens beyond Mtb.

Reviewer #1 (Public review):

Summary:

Fang et al. characterize the cellular basis of early ovarian development through a comparative analysis of single-cell transcriptomic data. The authors integrate a novel bovine scRNA-seq dataset, spanning six gestational stages (E38-E112), with stage-matched human (PCW6-16) and mouse (E11.5-E18.5) counterparts. Beyond identifying shared gonadal cell types across these three species, the study uncovers a previously uncharacterized bovine-specific cell population with steroidogenic features. Their analysis highlights conserved, dynamically expressed regulators, including TFAP2C and ZCWPW1 in germ cells and FOS and JUNB in granulosa cells. Furthermore, by employing a machine learning Support Vector Machine (SVM) model, the authors quantify cell-type conservation, demonstrating that while immune and germ cells are highly conserved across species, granulosa cells exhibit substantial evolutionary divergence. This study makes a significant contribution to developmental biology by establishing a comprehensive, cross-species single-cell roadmap of fetal ovarian development. By integrating livestock data with human and rodent models, the authors identify novel cellular states and provide a framework for assessing transcriptional conservation across species.

Strengths:

(1) While human and mouse fetal ovaries have been mapped, the inclusion of a high-resolution bovine dataset (107,930 cells total across the study) provides a critical "large mammal" perspective that is often missing from comparative studies.

(2) The identification of a bovine-specific cell population is an important finding. It suggests that ruminants may have a different developmental timeline for steroidogenic precursors (potentially theca cell ancestors) compared to rodents or humans.

(3) Training a Support Vector Machine (SVM) to quantitatively assess cell-type similarity is a major strength. It moves beyond qualitative UMAP "eye-balling" to provide a statistical probability of conservation.

(4) The study links gene expression to higher-order biological processes like epigenetic reprogramming and cell-cell communication (CellChat), providing a holistic view of the gonadal niche.

Weaknesses:

(1) The authors integrated publicly available scRNA-seq datasets generated across different laboratories and technical platforms. However, the specific methods used to control for and evaluate batch effects are not clearly described. It is critical to clarify whether the observed species-specific differences are purely biological or partly influenced by technical variation between datasets.

(2) A challenge inherent to all single-cell studies is the reliance on manual marker-gene-based annotation. While this is standard practice, it remains unclear how robust these assignments are, particularly for the novel "bovine-specific" population. Further evidence or cross-validation (e.g., through varied clustering resolutions or automated annotation tools) is required to ensure these clusters represent true biological states rather than computational artifacts.

(3) The authors utilized a linear SVM to assess cross-species similarity. However, it is not clear how this model performs compared to established single-cell mapping and comparative tools (e.g., MetaNeighbor or Seurat v5). Providing a justification for this specific SVM-based approach, or a brief comparison with existing benchmarks, would strengthen the methodological rigor of the study.

(4) While the computational evidence is compelling, the study would be significantly enhanced by independent validation of the "unclassified bovine-specific" cell population. To confirm the biological reality and reproducibility of this novel cell state, the authors should provide additional evidence. This could include in situ validation (e.g., immunofluorescence or in situ hybridization) to determine its physical location and morphology within the gonad, or demonstrating the presence of this specific cell population within an independent, non-overlapping bovine dataset.

Reviewer #2 (Public review):

Summary:

The authors generate a comparative single-cell transcriptomic atlas of fetal ovarian development in cattle, human, and mouse, with the goal of identifying conserved and species-specific cellular and molecular features of early ovarian differentiation. The study provides a valuable resource for the field and reveals potentially interesting species-specific characteristics, including a putative bovine steroidogenic cell population. While the dataset is substantial and the computational analyses are generally appropriate, several major conclusions rely primarily on computational inference without independent experimental validation, limiting the strength of evidence supporting some of the central claims.

Strengths:

This study provides a valuable cross-species single-cell atlas of fetal ovarian development by integrating newly generated bovine data with human and mouse datasets. The work fills an important gap in reproductive biology and offers a useful resource for investigating conserved and species-specific features of ovarian development.

The analyses are comprehensive and combine developmental trajectory reconstruction, regulatory network inference, cell-cell communication analysis, and cross-species classification. The identification of a putative bovine-specific steroidogenic cell population is particularly intriguing and may provide a basis for future studies of species-specific ovarian development.

Weaknesses:

The main limitation is that several key conclusions rely primarily on computational analyses without independent experimental validation. In particular, the proposed bovine-specific steroidogenic cell population, which represents the major novel finding of the study, is supported only by transcriptomic evidence.

In addition, many mechanistic interpretations derived from trajectory, regulatory network, and cell-cell communication analyses remain speculative. While the study succeeds as a comparative resource, the evidence supporting several of the central biological claims remains incomplete, and the biological significance of some cross-species differences is not fully explored.

Reviewer #1 (Public review):

Summary:

This manuscript is a narrative review addressing age-related alterations in SR-mitochondria interactions in skeletal muscle and their contribution to sarcopenia. It synthesizes existing literature on calcium signaling, mitochondrial dynamics, redox balance, and structural remodeling, and discusses potential interventions including exercise and pharmacological strategies. While the topic is timely and relevant, the manuscript largely reiterates established concepts without providing sufficient conceptual novelty, critical synthesis, or mechanistic insight beyond the current literature.

Strengths:

(1) Timely topic: The focus on SR-mitochondria communication in aging muscle is relevant and of growing interest.

(2) Broad coverage: The review compiles a wide range of literature spanning calcium handling, mitochondrial biology, ROS signaling, and exercise physiology.

(3) Clear organization: The manuscript is structured logically with thematic sections (SR, mitochondria, MAMs, aging, interventions).

(4) Didactic value: Could serve as a general overview for non-specialists entering the field.

Weaknesses:

(1) Lack of novelty and conceptual advance: The manuscript does not offer new hypotheses, frameworks, or critical reinterpretation of the field. Most statements summarize already well-established knowledge, and no unifying model or novel perspective is developed to justify publication in a high-impact journal like eLife.

(2) Limited critical analysis: The review is predominantly descriptive rather than analytical. Conflicting findings (e.g., MFN2 roles, MAM density changes, Ca²⁺ overload vs deficiency) are mentioned but not critically evaluated or reconciled. There is little discussion of limitations in the cited studies or gaps in the field.

(3) Overgeneralization and speculative claims: Several assertions are presented with insufficient nuance (e.g., causal links between MAM disruption and sarcopenia, or therapeutic efficacy of interventions). The distinction between correlation and causation is often unclear, reducing scientific rigor.

(4) Insufficient depth for a specialist audience: Despite its length, the manuscript lacks mechanistic depth in key areas (e.g., precise molecular regulation of MAMs in vivo, tissue-specific differences, quantitative aspects of Ca²⁺ flux). It reads more like a textbook summary than a high-level scholarly review.

(5) Redundancy and verbosity: Many sections repeat similar concepts (Ca²⁺ dysregulation, ROS effects, mitochondrial dysfunction) without adding new insight, leading to an unnecessarily long manuscript with limited added value.

(6) Weak integration of recent literature into a coherent narrative: Although many references are cited, they are not effectively synthesized into a cohesive argument. The manuscript lacks a strong central thesis or clearly defined take-home messages.

(7) Limited translational or experimental perspective: The section on therapeutic targeting is largely speculative and does not critically assess feasibility, limitations, or current clinical evidence.

Reviewer #2 (Public review):

This review addresses a highly relevant and timely topic, namely the role of sarcoplasmic reticulum-mitochondria communication and mitochondria-associated membranes (MAMs) in skeletal muscle aging. The manuscript successfully brings together literature from several interconnected fields, including calcium signaling, mitochondrial biology, excitation-contraction coupling, muscle metabolism, and sarcopenia. Given the growing interest in organelle crosstalk as a determinant of muscle health and disease, the topic is undoubtedly of considerable interest to the readership and has the potential to make a valuable contribution to the field.

However, in its current form, the manuscript devotes a substantial proportion of its content to the description of well-established concepts that are already extensively covered in the literature. Large sections are dedicated to general skeletal muscle physiology, excitation-contraction coupling, calcium handling, mitochondrial biology, and MAM structure and composition. While this background information is useful, the level of detail is often excessive for a review that aims to focus on aging-induced alterations in SR-mitochondria interactions. As a consequence, the central theme of the manuscript becomes diluted, and the review reads more like a broad overview of skeletal muscle physiology than a focused analysis of aging-related MAM remodeling.

In contrast, the sections specifically dedicated to aging and MAM dysfunction, which represent the most novel and potentially impactful aspects of the review, are comparatively brief and largely descriptive. The discussion of how aging alters MAM architecture, calcium microdomains, mitochondrial calcium signaling, and organelle communication would benefit from substantially greater depth. For example, although the manuscript highlights alterations in proteins such as MFN2, IP3R, VDAC, and MCU, the mechanistic implications of these changes for sarcopenia and age-associated muscle dysfunction are not critically developed. Similarly, the review would be strengthened by a more comprehensive discussion of the evidence linking MAM disruption to impaired muscle performance, metabolic inflexibility, denervation, and mitochondrial dysfunction during aging.

Another limitation is that much of the manuscript summarizes published findings without sufficiently evaluating the strength of the evidence or discussing existing controversies. Several statements imply causal relationships between MAM disruption and sarcopenia, whereas in many cases, the available data remain largely correlative. The authors should more clearly distinguish between established mechanisms, experimental observations, and emerging hypotheses. A more critical assessment of conflicting findings, particularly regarding the role of MFN2 and the dual consequences of altered mitochondrial calcium uptake, would considerably improve the scientific rigor of the review.

A major omission concerns the role of mitochondrial Ca²⁺ uptake in skeletal muscle physiology and aging. Throughout the manuscript, mitochondrial Ca²⁺ uptake is presented as a central determinant of muscle function and as a key mechanism linking MAM disruption to sarcopenia. However, the authors do not adequately discuss evidence that challenges this view. In particular, genetic mouse models lacking MCU exhibit surprisingly mild skeletal muscle phenotypes under basal conditions despite a near-complete abolition of rapid mitochondrial Ca²⁺ uptake. These findings have generated considerable debate regarding the physiological importance of mitochondrial Ca²⁺ uptake for muscle function and metabolic regulation. While MCU deletion clearly affects exercise adaptation and certain stress responses, the relatively modest baseline phenotype suggests the existence of compensatory pathways and raises important questions regarding the extent to which impaired mitochondrial Ca²⁺ uptake alone can explain age-associated muscle dysfunction. A balanced review should acknowledge these observations and discuss the ongoing debate regarding the relative contributions of mitochondrial Ca²⁺ deficiency versus mitochondrial Ca²⁺ overload in aging skeletal muscle.

Similarly, the discussion of MFN2 would benefit from greater nuance. The manuscript largely presents MFN2 as a structural tether linking the sarcoplasmic reticulum and mitochondria. However, MFN2 is a multifunctional protein with well-established roles in mitochondrial fusion, mitochondrial network organization, mitophagy regulation, and metabolic signaling. Consequently, many of the phenotypes associated with altered MFN2 expression cannot be unequivocally attributed to changes in MAM formation. The review does not sufficiently distinguish between the effects of MFN2 on organelle tethering and its effects on mitochondrial dynamics. This distinction is particularly important because several studies have questioned whether MFN2 acts primarily as a positive tether, a negative regulator of contacts, or whether its influence on organelle communication is secondary to its role in controlling mitochondrial morphology. As a result, attributing age-related alterations in SR-mitochondria communication solely to changes in MFN2-mediated tethering may oversimplify a considerably more complex biological scenario.

The manuscript's organization could also be improved. The sections discussing aging-related alterations, mitochondrial dysfunction, calcium dysregulation, oxidative stress, and therapeutic interventions contain significant overlap and repetition. Streamlining some background sections and reallocating space to a more detailed discussion of aging-specific mechanisms would help maintain focus and improve readability. In particular, the manuscript would benefit from expanding the sections on aging-induced MAM remodeling, age-dependent changes in MAM composition and ultrastructure, and the potential of MAM-targeted interventions as therapeutic strategies for sarcopenia.

Finally, the review would gain from a stronger future perspectives section. Several important questions remain unresolved, including whether MAM disruption is a primary driver of muscle aging or a secondary consequence of mitochondrial dysfunction, how MAM architecture differs among muscle fiber types during aging, and whether MAM-associated proteins could serve as reliable biomarkers or therapeutic targets in human sarcopenia. Highlighting these knowledge gaps would further enhance the review's impact.

Overall, the manuscript covers an important and emerging area of research and contains a valuable compilation of the relevant literature. Nevertheless, substantial revision is required to reduce the emphasis on well-established background information, deepen and critically analyze the aging-specific sections, and provide a more focused discussion of the role of MAMs in skeletal muscle aging and sarcopenia.

Reviewer #1 (Public review):

Summary:

The question posed on cell-type-dependent relationships to theta-nested gamma rhythms is an important one. The authors use a variety of ontogenetic, imaging, electrophysiology, and computational techniques to show that reciprocal interactions between excitatory neurons and interneurons in the medial entorhinal cortex generate gamma oscillations. They measure LFP gamma, gamma power of postsynaptic currents in different neurons, spike phases with reference to LFP gamma, and spatial correlations of membrane potentials across a large population of neurons. Arguing (correctly) that gamma rhythm in this setting is generated through a pyramidal-interneuron network gamma (PING) mechanism, they demonstrate cell-type-specific differences in gamma phase-locking. While they show spatial dependencies of sub-threshold voltages and even argue for topographic clustering, these could simply be reflections of the synchronous stimulation paradigm that they use.

Overall, I appreciate the methodology and rigor, but would have expected more from the study in terms of relevance to physiological stimulation conditions as well as in terms of mechanisms underlying the differences that they report here..

Strengths:

The authors are rigorous in how they conduct the experiments, report the data, and perform the analyses. The modeling respects the heterogeneities and is truthful to the experimental design. The conclusions on PING mechanisms are fine, but are not unexpected given the circuitry of the mEC.

Weaknesses:

The interpretation of the conclusions, while for the most part is fine, could have been better, especially given the conceptual limitations of the experimental design. The modeling part could have gone beyond simple descriptive matching and addressed mechanistic questions.

Reviewer #2 (Public review):

In this manuscript, the authors studied the cellular mechanism of theta-nested gamma oscillations in the medial entorhinal cortex (MEC) in vitro. The theta-nested gamma activity was induced by theta-modulated optogenetic stimulation of CaMKII+ neurons. In Figures 1 through 4, they describe the firing phase, synaptic input, and LFP-IPSC coupling of stellate cells, pyramidal cells, and interneurons. They then conducted voltage imaging, capturing the simultaneous activity of 41 cells, and found that subthreshold membrane potentials cluster in a weakly distance-dependent manner (Figure 5). The experiments and analysis are done rigorously for the most part.

However, the results described in Figures 1 to 4 are largely descriptive and highly similar to those in their recent publication, which utilized almost identical experiments. While the voltage imaging data during theta-nested gamma oscillations are novel, the authors report data from only a single experiment, leaving it unclear whether the results are reproducible. Furthermore, without a comparison to in vivo data, it remains unclear what novel insights this manuscript provides to advance our understanding of the cellular mechanisms underlying theta-nested gamma oscillations.

(1) The authors recently published another paper on the topic of theta-nested gamma oscillations in the MEC (Williams et al., eNeuro, 2026). In that study, they utilized a Thy1 promoter instead of the CaMKII promoter used here. The motivation for testing the CaMKII promoter in the current manuscript, as well as the novel insights expected from this experimental setup, remains unclear. Given that existing literature suggests inhibitory MEC cells play a critical role in theta activity (e.g., Gonzalez-Sulser et al., 2014)-implying that theta modulation should drive inhibitory rather than excitatory cells-the previous use of the Thy1 promoter appears closer to in vivo conditions than the CaMKII promoter used here.

The overall conclusion of the current manuscript is that excitatory-inhibitory (E-I) interactions dominate the generation of theta-nested gamma oscillations. However, in their previous eNeuro paper, the authors demonstrated that the interneuron network gamma (ING) mechanism can sustain gamma oscillations without excitatory synaptic transmission. It seems expected that excitatory cells would be involved when the optogenetic stimulation selectively drives excitatory cells. If CaMKII stimulation is less physiological and artificially forces the theta-nested gamma activity to rely on excitatory connections, this conclusion could be misleading. It may potentially describe a mechanism that is irrelevant to physiological processes in vivo. Please see my comment 3, which is related to this point.

In addition, Figures 1 and 2 heavily overlap with the authors' previous eNeuro publication. The differences in experimental settings and the motivation for performing almost identical experiments must be clearly articulated prior to these figures to avoid confusion. The authors must also justify why it is necessary to present such similar data, and explicitly point out the novel findings in the current paper compared to their previous work.

(2) Using voltage imaging to investigate theta-nested gamma oscillations is novel. However, the impact of the findings from this experiment appears minimal in the manuscript's current state. The most novel and interesting observation is likely presented in Figure 6, where the authors identified clustered voltage correlations. However, this appears to be an n=1 experiment, and these findings should be replicated at least in a few experiments. Furthermore, the manuscript lacks a discussion or interpretation of this observation, making it unclear whether the result is biologically meaningful. Please find specific suggestions regarding this point below.

(3) The authors' primary motivation for investigating the mechanisms underlying theta-modulated gamma oscillations is their potential role in grid cell firing. Therefore, it is critical that the mechanisms studied here in vitro accurately reflect in vivo processes. For this reason, greater effort should be made to better link this in vitro study with existing in vivo data. Numerous public in vivo datasets are available that detail the firing activity of putative principal cells and interneurons during exploratory behavior in mice. Intracellular recordings in awake animals have also been published, some of which the authors already cite. The data presented in Figures 1 and 4, for example, could be straightforwardly compared with those existing in vivo metrics. Furthermore, available in vivo silicon probe recordings could provide a reliable estimate of the spatial distribution of gamma-related spike activity. Such data should be compared with the voltage imaging results presented in this study.

This limitation connects back to the first point. In this manuscript, the authors tested a different method for inducing theta-nested gamma oscillations (via the CaMKII promoter) than in their recent eNeuro paper (via the Thy1 promoter). The outcomes of these two induction methods must be systematically compared against in vivo data to determine which approach aligns more closely with physiological conditions. Without such a comparison, the scientific justification for testing a different promoter in this study remains unclear.

Reviewer #3 (Public review):

Summary:

In this manuscript, Williams et al. combine optogenetics, whole-cell electrophysiology, local field potential recordings, large-scale voltage imaging, and computational modeling to investigate the cellular and circuit mechanisms underlying theta-nested gamma oscillations in superficial medial entorhinal cortex (mEC). The authors propose that fast-spiking interneurons receive strong gamma-frequency excitatory drive and provide rhythmic inhibition onto principal neurons, supporting a pyramidal-interneuron network gamma (PING) mechanism. They further report cell-type-specific differences in gamma phase locking, spatial clustering of subthreshold voltage signals, and a network model reproducing several observed features, including interneuron bursting and gamma-cycle skipping in excitatory neurons.

Strengths:

The study is technically sophisticated and addresses an important question in entorhinal circuit function. The combination of intracellular recordings, voltage imaging, and computational modeling is a clear strength.

Weaknesses:

Several key conclusions developed from experimental results require additional raw data, statistical support, clearer methodological description, and more cautious interpretation. The computational modeling focuses primarily on stellate cells, whereas the experimental results suggest an important role for pyramidal neurons in PING dynamics. This creates inconsistency between theory and experiments.

Reviewer #1 (Public review):

Summary:

This study investigates how Ca2+ levels inside the RGCs' mitochondria relate to whether these cells survive or die after injury to the optic nerve. The authors used advanced in vivo fundus live imaging techniques in mice to watch these changes unfold in real time, combined with genetic and drug-based tools to alter calcium flow into these compartments. Their central finding is a striking paradox: cells that naturally survive injury tend to have higher baseline calcium levels in these compartments, yet experimentally reducing calcium entry protects the broader population of cells from death.

Strengths:

The authors are applying sophisticated biosensors to track cellular chemistry in living animals over days and weeks. The tools and methods are creative and direct to detect the longitudinal RGC degeneration with mito-Ca2+ imaging. The topic and research aspect are novel and attractive. The results are significant, showing a clear relationship between the mito-Ca2+ regulatory machinery and cell survival.

Weaknesses:

The details of the mitochondrial-located signal of the Ca2+ sensor need to be further proved in the mito-matrix or between the mito-membranes. The study primarily describes a correlation and a surprising experimental outcome without fully explaining the underlying biological reasons for the paradox. While the evidence supporting the phenomenon is good, the mechanistic insight into why high calcium is linked to survival, or why lowering it helps after injury, remains limited.

Reviewer #2 (Public review):

Summary:

The manuscript by McCraken and colleagues provides a continuation of their 2023 study (Cell Reports 42:113165) characterizing calcium regulation in retinal ganglion cells (RGCs) after acute optic nerve damage (a 10s crush using an intraorbital approach). This work is principally focused on how mitochondrial calcium stores change in both RGCs that are resilient and susceptible to injury. They report that resilient RGCs typically exhibited high calcium levels, but paradoxically, manipulating mitoCa2+ levels was more protective when the stores were reduced. Overall, regardless of susceptibility, mitoCa2+ levels decreased after injury, which is opposite to other reports that mitoCa2+ increases in degenerating neurons. The manipulation of mitoCa2+ was conducted both pharmacologically (Ru265) and by overexpression or knockdown of a primary calcium uniporter MCU. The evaluation of mitoCa2+ was conducted by using a reporter (Twitch2b) that was targeted to the mitochondria.

Strengths:

Many of the experiments are elegant and well-performed.

Weaknesses:

(1) Some experiments require further controls to validate that reagents are doing what they are intended to do.

(2) Some findings can have alternate interpretations that are not considered.

(3) There is a broad generalization to the biology of all RGCs that may not be biologically relevant to different RGC subtypes.

Reviewer #3 (Public review):

Summary:

Following previous work that demonstrated a relationship between higher homeostatic cytosolic calcium and lower retinal ganglion cell (RGC) apoptosis following injury to their axons, McCracken et al. investigated whether homeostatic calcium levels of the endoplasmic reticulum (ER) or mitochondria provide additional insights into the mechanisms by which calcium influences RGC survival. Their study reveals that homeostatic mitochondrial calcium shows a similar positive correlation with RGC survival. Despite that correlation, pharmacologic or genetic methods to lower mitochondrial calcium improved, rather than reduced, the survival of injured RGCs, while a genetic approach intended to increase mitochondrial calcium resulted in more RGC loss. These findings highlight the complexities of calcium regulation in modulating neuronal survival and raise important questions of how homeostatic levels of mitochondrial calcium affect stress responses that themselves can be either neuroprotective or neurodegenerative.

Strengths:

This study tackles an intriguing hypothesis that differences in calcium ion homeostasis in specific organelles may contribute to differences in survival of various RGC subtypes after optic nerve injury. This is a technically demanding question, and a primary strength of this work is its attention to, and meticulous reporting of, appropriate controls and, where applicable, seemingly contradictory results. Among these are careful evaluation of the effects of drug (or vehicle) delivery and genetic manipulations with and without injury and over extended time courses. The combination of thoughtful pharmacologic and genetic approaches makes for a thorough analysis of a challenging set of questions. The result is a study that provides a helpful perspective on the complicated roles that calcium, and especially mitochondrial calcium, can play across neuronal insults, neuronal types, and neuronal subtypes.

Weaknesses:

Given the paradoxical results, it would be helpful to have a clearer picture of how strongly the overexpression and knockdown of MCU altered the mitochondrial calcium levels. There may be potential for extraordinarily strong effects that would need to be tuned by using different shRNAs or promoters to more closely align with the observed differences between surviving RGCs and those that die. The investigation includes a relatively small number of resilient RGC subtypes, using the markers SPP1 and TBR2, raising questions of how generalizable the trend is between mitochondrial calcium levels and RGC resilience. The analysis and implications of Figure 3D might benefit from including not only the provided 50:50 split between "high" and "low" but also views of the data after splitting into thirds, fourths, and perhaps even fifths. The authors' inference that higher homeostatic calcium in more resilient RGCs may result in chronic mitochondrial stress is intriguing and worthy of more experimental investigation than is currently provided.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

Chen et al. describe metabolic phenotypes in Dp16 Down Syndrome mice, specifically the Dp(16)1Yey/+ mice - segmental duplication model carrying a majority of the triplicated Hsa21 gene orthologs. The group has performed metabolic phenotyping data in chow and high-fat diets, as well as undertaking a transcriptomic and metabolomic approach in tissues such as white and brown adipose tissues, liver, skeletal muscle, and hypothalamus to reveal both shared and sex-specific differences. The group describes sexual dimorphism in body weight, body temperature, food intake, and physical activity. Core shared features are insulin resistance, glucose intolerance, impaired lipid clearance, and dyslipidaemia in the Dp16 mice. They report tissue signatures of immune activation and a pro-inflammatory state, ER and oxidative stress, fibrosis, impaired glucose and fatty acid catabolism, altered lipid and bile acid profiles, and reduced mitochondrial respiration in Dp16 mice.

Strengths:

Overall, this is a good study with detailed, comprehensive data from an excellent group who have previously published on metabolic phenotyping of 2 other Down Syndrome mouse models. Although somewhat descriptive, it does certainly add to the current field and understanding of strengths and weaknesses of Down Syndrome mouse models, as well as identifying new features whilst strengthening previously suggested mechanisms.

Reviewer #2 (Public review):

Summary:

Human DS is associated with metabolic dysfunction in humans, but the precise details of this have not been studied in detail. Here, the authors use a mouse model of DS to study systemic metabolic and transcriptional responses in key metabolic tissues to provide a deep understanding of the metabolic changes associated with DS. As part of his work, the authors also aimed to help inform the selection of a mouse model that best reflects the metabolic profile of DS, through comparison with other DS model metabolic data.

The data presented in this model will be of interest to those in the field of metabolism. The immediate impact is unclear, but the breadth of data presented makes this a very useful resource.

Strengths:

(1) This work builds on other comprehensive analyses that the authors have performed in other DS mouse models.

(2) The authors note common metabolic disturbances between male and female mice (e.g., insulin resistance) alongside clearly sexually dimorphic phenotypes (e.g., body weight). Studying both sexes in this context is important.

(3) The authors have written the paper in a way that integrates a large number of observations well. There is complex data, and a high degree of sexual dimorphism. The study has generated a valuable and wide-ranging dataset comprising molecular, biochemical, and physiological data that will be useful for further, more mechanistic studies of metabolism in DS.

(4) For specific observations, like the findings of altered body temperature in male and female mice, the authors undertake follow-up hypothesis-driven analyses of BAT mitochondria and specific hormones. Although these analyses do not explain the change in temperature, they ensure the study is not purely descriptive in nature.

Reviewer #3 (Public review):

Summary:

The article by Chen et al. describes the comprehensive metabolic profiling of DP16 mice, a Down syndrome model that carries a duplicated segment of the mouse chromosome syntenic to human chromosome 21. The authors note that this model is superior to previously used models, based on genetics, as ~65% of the chromosome 21 orthologues. The metabolic phenotypes also appear to be more consistent with those observed in humans with Down Syndrome. The study lays the groundwork for a more detailed genetic dissection of dosage-sensitive genes that contribute to the metabolic deficits observed in Down Syndrome.

Strengths:

There is an enormous amount of data in this manuscript, and the methods are described with adequate attention to detail. A strength of the manuscript is that both male and female mice were analyzed, so that concordant and discordant phenotypes were identified. Both males and females had evidence of insulin resistance. Transcriptomic and metabolomic data revealed impaired pathways for lipid metabolism, a pro-inflammatory state, reduced mitochondrial health and oxidative stress. Although the effects of a high-fat diet on weight gain were divergent, this diet caused worsened insulin resistance in both males and females.

The discussion is excellent. Limitations of the study are well described. This reviewer does not identify any critical missing data.

Joint public review:

Summary:

In this study, Stirtz et al., performed a targeted screen of 80 Drosophila strains carrying heterozygous MiMIC insertions in genes that are homologous to human genes that have been linked to autism spectrum disorders (ASD). This is an important and timely topic, as human genetic studies have identified a large number of ASD risk genes, yet the functional characterization of many of these candidates remains limited. The authors identify 48 putative mutants with altered sleep, activity, or social behavior. They then focus on one hit, domino (the orthologue of human SRCAP), for which the heterozygous MiMIC mutants show altered behavior in males but not in females. They show that domino is a candidate regulator of sleep, activity, social behavior, transcriptional programs, and RNA splicing. The authors molecularly validate that the heterozygous MiMIC insertion in domino causes a 50% reduction in gene expression, and use RNA-seq to show that the heterozygous MiMIC males and females have altered gene expression profiles and splicing patterns. Finally, they use immunostaining against the commonly used synaptic marker, Bruchpilot, to show that both males and female heterozygous domino flies express a higher immunosignal compared to the wild-type control.

Strengths:

This work provides potential genetic links between human ASD genes and fly behavioral phenotypes. Overall, it represents an ambitious and technically valuable effort that generates a substantial behavioral dataset across a large number of ASD-associated orthologues and develops quantitative analytical approaches to extract information from complex phenotypes. One strength of this study is its focus on heterozygous mutants, which is more representative of human scenarios. The study also provides a potentially useful resource for the field, particularly through the identification of candidate genes and behavioral signatures that may warrant future mechanistic investigations. The screening experiments and analysis are well conceived, the manuscript is very clearly written and is easily understandable, and the concise, accurate interpretations for each result, aided by clear graphic representation of multiple dimensions in the behaviors tested, allow the reader to understand the paper with ease.

Weaknesses:

The work presents a few important weaknesses, especially with regard to the genetic and molecular validation of the mutants identified.

(1) The authors validate that the MiMIC insertion affects the gene of interest only for the domino gene. The original MiMIC study (PMID: 25824290, eLife) reported that ~8% (5/63) MiMIC lines do not function as strong loss-of-function alleles. Thus, of the 48 hits identified here, one would estimate that ~4 of them may not cause the loss of function of the gene defined by the MiMIC insertion. To strengthen their claim, the authors would need to confirm that all of the MiMIC lines that they consider as hits do indeed significantly reduce the expression of the target genes.

(2) Although the authors document that they validated the phenotype seen in the domino MiMIC line using a second mutant allele (Trojan), these two mutants share the same genetic background because the Trojan line was made from the MiMIC line via recombinase-mediated cassette exchange. Thus, the phenotype seen in the MiMIC and Trojan lines would need to be confirmed using a completely independent mutant in order to demonstrate that the reported behavioral, molecular, and synaptic defects reported can be fully attributed to the partial loss of domino function. Also, while the authors performed an RNA-seq experiment in both the MiMIC and Trojan lines, they do not show whether the Bruchpilot phenotype is also seen in the Trojan allele. Thus, this phenotype would also need to be examined in the Trojan allele or, preferably, in a mutant allele that is independent of the MiMIC line.

(3) The RNA-seq results would benefit from a discussion of potential compensatory or secondary transcriptional effects resulting from the constitutive domino reduction, particularly since the expected global bias toward transcriptional downregulation was not observed. In addition, some neurobiological interpretations appear stronger than currently justified by the literature or the data presented, particularly regarding the Bruchpilot immunoreactivity analyses and their relationship to sleep-regulatory circuits. Additional validation using better-established sleep-related neuronal populations, together with a clearer discussion of sex-specific effects and alternative interpretations of the observed phenotypes, would substantially strengthen the manuscript.

(4) An explanation of the extensive PCA analyses performed would help the naïve reader.

Reviewer #1 (Public review):

Summary:

In the manuscript "A stable cryogenic fluorescence microscope for correlative super-resolution light and electron microscopy," the authors demonstrate a new cryogenic light microscopy design and characterize its temperature and spatial stability. The manuscript does a good job of reviewing the state of the field and highlights the need for improved cryogenic microscope stages. The system avoids challenges associated with vacuum-based designs, particularly vacuum transfer systems that can be difficult to engineer, while also showing minimal ice contamination and drift, which are the primary challenges associated with open cryostat systems.

Strengths:

The key strengths of the manuscript are the simple design and the significant level of detail provided in the description of the cryogenic stage. This represents a valuable step forward for the field by providing a home-built, non-vacuum stage design that others can emulate.

Weaknesses:

There are only minor weaknesses or issues to address, which, if resolved, would strengthen the manuscript overall.

(1) A key element of the design gets little attention, which is the plastic cap for the objective. It is not entirely clear to the reader how this is being used except as something of a thermal break between the cryogen environment and the objective, but there are some questions. Is the objective housing touching the plastic cap? Where is the front of the cap relative to the front objective lens? Is the front objective lens exposed to the cryogenic environment? Could the authors provide some 3D views of that in an SI figure? This would help clarify.

(2) The refilling system is not shown in the diagrams provided in Figure 1 and S1 in sufficient detail. How is the system mechanically coupled to the dewar on the microscope stage? Are there any concerns about coupling vibrations onto the table?

(3) There is a description on page 6 that a rectangular aperture is used to align the excitation with the position and orientation of the sample. I know the authors are using this for excitation of the lamella, but without saying so in this text, it is confusing. I would consider stating that this is for future work involving excitation of lamella and then citing their preprint.

(4) In Figure 2d, the z-drift is shown with the focus lock correction applied. This is highly relevant, but I also think it would be good to plot the z position plus the stage position in an SI figure. This will give a better idea of the mechanical stability of the system. Also, in this figure, I wonder if the authors could comment on the source of the jumps in lateral position. For example, just before 30 minutes. Lastly, I would make the lower plot have a tighter y-axis range. It is hard to see anything, hence the inset.

(5) The ice contamination looks minimal in Figure 3. I think it would benefit the manuscript to have lower magnification images as well, to show the level of ice contamination across a representative square. This would be good, but only if the authors have it in hand.

(6) In Figure 4b, the y-axis is unclear. It looks like it has been normalized. Consider revising.

(7) A fluorescence intensity trace for the data shown in Figures 4c and f would be helpful to show the single-molecule behavior.

Reviewer #2 (Public review):

Summary:

This manuscript reports the development of a cryo super-resolution fluorescence microscopy system. The authors demonstrate that they can achieve a mechanical and thermal stability that is sufficient to perform cryo-SMLM over the course of several hours. Focus instability is compensated for by tracking a fluorescent bead for its movement in the axial direction and adjusting the sample stage accordingly during data acquisition. Lateral instabilities are corrected after data acquisition. An enclosure around the microscope allows to significantly reduce ice contamination during cryo-SMLM imaging and sample transfer. The authors show an example of correlative cryo-SMLM and cryo-ET imaging achieved with their microscope system, which depicts the distribution of FtsZ-rsEGFP2 in E. coli.

Strengths:

The authors have designed a microscopy system for SR-cryo-CLEM, which achieves high stability while reducing complexity and costs substantially when compared to vacuum-insulated systems (e.g., Hoffman et al., 2020). They also provide software for controlling the microscope and data acquisition. This lowers the barrier for other labs to implement SR-cryo-CLEM into existing cryo-ET workflows. Reduction of ice contamination helps to increase throughput, which is currently one of the biggest bottlenecks for SR-cryo-CLEM.

Weaknesses:

To correct for focus drift, the authors track a fluorescent bead in the far-red channel. This is possible for bacterial samples as used in this work, as beads can easily be introduced to surround the cells.

Recommendations:

(1) It is not discussed how this can be achieved in other samples than bacterial samples, such as lamellae in mammalian cells. Here, it would be much more difficult to introduce bright point-like markers with far-red fluorescence that would be distributed in the entire cell to capture at least one in the final lamella. Furthermore, it might be important to know for readers whether the far-red channel has to be sacrificed entirely for the focus correction.

(2) The authors show an application of SR-cryo-CLEM imaging of FtsZ-rsEGFP2 in E. coli. In the chosen correlative example (Figure 4d.f), no clear structure can be seen in the fluorescent images. The overview image (Figure 4d) shows no distinct signal in the cell, as it is shown for the non-correlative example in Figure 4a. The cryo-SMLM image (Figure 4f) does not show any ring-like features or accumulations of signals at the constriction site, as would be expected for a projecting along the optical axis. A clearer application example, which would show how increased resolution in cryo fluorescence microscopy enables resolving certain structural details or adds information not accessible in cryo electron tomography, would have strengthened the work. Particularly if taking into consideration that bacteria have a strong auto-fluorescence in the green range (Dahlberg et al., 2020), which could lead to high background or false positive localizations when using green fluorophores as labels.

(3) Access to CAD drawings (particularly for custom-made parts, such as cryostat or humidity enclosure) and a parts list is highly important for other researchers who would like to set up this SR-cryo-CLEM system in their own lab or institution. This is currently missing and, therefore, creating a hurdle for a wider adaptation of the technique.

Reviewer #1 (Public review):

Summary:

The authors investigate how site-specific acetylation within the histone H3 folded domain affects RNA polymerase II transcription through nucleosomes. They focus on H3K56ac, H3K64ac, and H3K122ac, prepare chemically defined nucleosomes carrying each modification, and compare their effects using an in vitro transcription assay, cryo-electron microscopy structures, and micrococcal nuclease sensitivity assays.

The main finding is that H3K56ac and H3K122ac increase production of full-length run-off transcripts and reduce pausing near the nucleosomal dyad region, whereas H3K64ac has little detectable effect under the same reconstituted conditions. The structural analyses suggest that H3K56ac weakens or destabilizes DNA near the entry/exit region, while H3K122ac alters histone-DNA contacts near the dyad. These observations support a model in which different acetylation sites within the H3 folded domain influence nucleosomal transcription barriers through distinct local effects on histone-DNA interactions.

This is a useful study because it examines histone core-domain acetylation using chemically defined nucleosomes and directly compares several modifications in the same experimental system. However, the broader cellular context of these modifications is not sufficiently developed, and some mechanistic conclusions rely on correlations between static nucleosome structures and endpoint transcription assays rather than direct observation of polymerase passage through modified nucleosomes.

Strengths:

(1) The study uses site-specifically acetylated H3 proteins and reconstituted nucleosomes, allowing direct comparison of H3K56ac, H3K64ac, and H3K122ac under controlled conditions.

(2) The combination of transcription assays, cryo-electron microscopy, and nuclease sensitivity assays provides multiple lines of evidence, particularly for increased DNA end flexibility in H3K56ac nucleosomes.

(3) The authors analyze unmodified, H3K56ac, H3K64ac, and H3K122ac nucleosomes in parallel, with reported structural resolutions of approximately 3 Angstroms and accompanying validation materials.

(4) The negative result for H3K64ac is informative, because it distinguishes the direct effect of this modification in a minimal reconstituted system from prior cellular associations with active chromatin and histone eviction.<br /> The comparison with H3 N-terminal acetylation highlights that acetylation within the folded domain may affect transcription at different positions or by different mechanisms than tail acetylation.

Weaknesses:

The rationale for focusing on H3K56ac, H3K64ac, and H3K122ac has not been developed sufficiently. The manuscript would benefit from a clearer summary of what is known about the abundance of these modifications in cells, the enzymes or histone metabolic pathways that may introduce or remove them, and whether they are thought to occur before histone deposition, on assembled nucleosomes, or during nucleosome remodeling.

The central mechanistic model is based mainly on correlations between structures of free nucleosomes and endpoint transcription assays. The study does not directly observe RNA polymerase II paused at or passing through the relevant nucleosomal positions, so the proposed link between local structural changes and reduced pausing should be stated with appropriate caution.

The H3K56ac interpretation is supported by both structural observations and nuclease sensitivity data, but the map comparison underlying the reduced entry/exit DNA density is still mostly qualitative. The manuscript should more clearly state the map comparison conditions, such as contouring and local map quality, so that non-specialist readers can judge how robust the local density differences are.

The H3K122ac mechanism is plausible, but the evidence for dyad destabilization is more indirect. The main support comes from the orientation of the K122 side chain and its distance from DNA, while an independent biochemical test of dyad-region destabilization is not provided.

The transcription assay appears to include statistical testing, but the figure legend and methods should more clearly state which tests were used, what comparisons were made, how n was defined, and whether multiple-comparison correction was applied.

The relationship between the 198 bp transcription template, the linker DNA, the 9-base mismatched region, and the DNA regions modeled in the cryo-electron microscopy structures is somewhat difficult to follow. This does not necessarily require new experiments, but a clearer explanation would help readers connect the transcription assay design with the structural models.

The use of H3.2 C110A for chemical ligation and the use of the PL2-6 single-chain antibody fragment for cryo-electron microscopy sample stabilization are reasonable technical choices, but their purposes and possible effects on interpretation should be explained more clearly for readers outside structural biology.

Because the work uses a minimal in vitro system with human nucleosomes and Komagataella phaffii RNA polymerase II/TFIIS, the conclusions should be limited to direct physical effects on nucleosome transcription barriers unless cellular cofactors, remodelers, histone chaperones, additional modifications, and nucleosome positioning are addressed or discussed.

Reviewer #2 (Public review):

Summary:

Chromatin regulates a wide range of biological processes. The nucleosome, composed of 147 bp of DNA wrapped around a histone octamer containing histones H2A, H2B, H3, and H4, is the fundamental unit of chromatin. Post-translational modifications of histone proteins regulate the dynamic properties of nucleosomes and thereby influence chromatin accessibility and gene expression. Among these modifications, lysine acetylation on histone H3 is closely associated with transcriptional activation. While the epigenetic functions of acetylation on the histone H3 N-terminal tail have been extensively studied, the molecular mechanisms by which acetylation within the histone H3 core domain, particularly at Lys56, Lys64, and Lys122, modulates nucleosome architecture to facilitate RNA polymerase II (RNAPII) transcription remain unclear.

In this study, Oishi et al. investigated the effects of histone H3 acetylation at K56, K64, and K122 on RNAPII transcription using in vitro transcription assays. Furthermore, the authors determined the three-dimensional structures of nucleosomes containing these acetylation marks by cryo-electron microscopy single-particle analysis, revealing distinct structural dynamics depending on the acetylation site. Overall, this study advances our understanding of the molecular mechanisms linking histone H3 core acetylation to transcriptional regulation.

Strengths:

(1) Site-specifically acetylated histone H3 proteins were chemically synthesized using a unique and rational peptide ligation strategy, representing a major technical strength of this study.

(2) The in vitro transcription assays demonstrated that H3K56ac and H3K122ac increase the production of run-off transcripts, whereas H3K64ac has little effect on transcription efficiency. These findings highlight the distinct functional roles of individual acetylation sites within the histone H3 core domain.

(3) The cryo-EM structures of nucleosomes containing either H3K56ac or H3K122ac revealed that H3 acetylation weakens histone-DNA interactions, providing a structural basis for the observed effects on transcription.

Weaknesses:

(1) Although the biochemical and structural data are convincing and sufficiently support the authors' conclusions, complementary cellular experiments would further strengthen the physiological relevance of the in vitro findings. While such experiments are not essential for supporting the main claims of the study, they would enhance the overall impact and biological significance of the work.

(2) Although the authors demonstrate the structural consequences of individual H3 core acetylation events, the study does not investigate potential synergistic effects among multiple acetylated lysine residues within the H3 core domain. Consequently, the relationship between combinatorial acetylation patterns and their collective impact on RNA polymerase II-mediated transcription remains unclear.

Reviewer #3 (Public review):

This is a short and punchy manuscript that nicely summarises the 4 structures that are determined and provides a basis for the differences seen for acetylation sites shown for RNAPII activity.

The authors build on previous biochemical work that determined the functional outcomes of H3 core acetylation, adapting an assay they have previously used extensively to investigate RNAPII transcription on nucleosomes and, indeed, even H3 N-terminal tail acetylation. This assay is as such well set up and has a wealth of confirmatory previous studies from this lab and the authors are careful not to overanalyse their results, leading to robust and well-considered results. The structures are determined to a high resolution, allowing the interpretation put forward about side chain orientations, with clear densities shown for the regions of interest.

Further discussion or experiments would strengthen the conclusions further:

(1) The conclusion on the role of H3K56Acetylation could be strengthened, especially as the results are somewhat counterintuitive. It is conceptually surprising that acetylation near the entry/exit DNA that destabilises this region also leads to a reduced stall propensity at the dyad but has a limited effect at SHL5? While it can be explained by the clash at the dyad pause being reduced, the more direct effect of DNA breathing amplification would be expected to have a larger effect at SHL 5. Indeed, the density for DNA at SHL5 appears to be weaker in Figure 2A, suggesting the entry/exit DNA flexibility is amplified past this region.

Perhaps another assay that looks more directly at the flexibility of the entry/exit DNA would be useful, either through restriction enzyme-mediated cleavage or FRET (DNA ends and H2AK119 labels), providing stronger evidence of this effect. MNase is rather indirect and similar to the RNAPII assay itself.

Similarly, were the authors surprised by the modest effect (less than 2-fold) in transcriptional pause at SHL 0 for the K122Ac? Presumably, based on the model in Figure 4, this would be expected to be the area with the largest effect? The results of K56Ac and K122Ac almost seem swapped to what would be expected in Figure 1H. Further discussion of this observation would be useful.

(2) Could the local weakening of DNA, especially at the dyad, be observed in the cryo-EM structures? Perhaps comparison of local resolution estimation differences in this region compared to unmodified would be useful.

(3) Caution should be taken, and discussion should include that the structural data presented is after extensive processing. Many nucleosome averaging classes were discarded in the 3D classification steps (nicely summarised in Table 1 as "particles for 3d classification" and "particles in final map"). Indeed, it is likely that higher DNA flexibility particles would be thrown away during this processing step. This can be observed for K56Ac DNA ordering, for example, in Supplementary Figure S4, yellow and cyan classes from the round of 3D classification look to be high resolution and have a higher order of DNA, so there has been some selection here. How was this done? While this is not fully quantifiable, it gives an idea of the extent of wrapping. We would suggest discussing the methodological limitations and showing the models after the first auto refinement to see if the features discussed on end flexibility and dan ordering are retained.

(4) Di Cerbo et al. (reference 13) showed acetylation at K64 alters salt stability and affects transcription. Why do the authors think there is a discrepancy, albeit with different assays? Direct reference and discussion of this in the text should be included.

(5) Why was H3.2 used, while this is relatively abundant in mouse cells, human protein was used, and this appears to be less common than H3.1 and H3.3. We are sure that the effect is not likely to be substantive on structure (as shown by the Kurumizaka lab previously), but should be addressed in the text

Reviewer #1 (Public review):

Summary:

This manuscript uses simulations and MSMs paired with experimental binding assays to examine the binding mechanisms of different antibodies to their targets. The authors argue that contacts in encounter complexes play an important role in determining the association rates and binding affinities that distinguish more mature antibodies from less efficacious antibodies from earlier in the maturation process.

Strengths:

The idea is interesting, and the combination of computational models and experiments is a good direction.

Weaknesses:

The manuscript focuses heavily on kinetics, but it is not clear whether the simulations recapitulate the relative rates of binding of the two antibodies. The relationship between the simulated binding behavior and the experimentally observed kinetic differences is therefore not fully established.

The comparison of committor probabilities or fluxes between the two antibodies may not be appropriate. These properties are related to the barrier height the system has to cross to move forward vs back to the starting state, under the simplifying assumption that the properties of other states aren't critical. Even in this simplified case, the same flux or committor probability could occur with very different barrier heights, e.g., rates or transition probabilities.

Some claims are presented in a very qualitative way that people who aren't experts in MSMs may have difficulty tying to the results in Figure 1.

Reviewer #2 (Public review):

Summary:

The manuscript addresses an important and underexplored question: how affinity maturation alters antibody encounter-state landscapes rather than simply improving bound-state affinity. The authors combine adaptive MD, Markov State Models (MSMs), transition path theory, mutagenesis, SPR kinetics, and double-mutant cycle analysis into a coherent story.

Strengths:

This manuscript presents a compelling computational and experimental analysis of antibody affinity maturation in the HIV-1 DH270 lineage. The main finding is that somatic mutations reshape encounter-state pathways through glycan-mediated steering rather than simply stabilizing the final bound state. This is novel and potentially important for vaccine design. The combination of adaptive MD, MSMs, SPR kinetics, and double-mutant cycle analysis is a major strength.

Weaknesses:

The proposed sequence that somatic mutations cause glycan capture, which causes reorientation, which causes enhanced association, is based on correlation rather than direct causality.

The four MSM states are not convincingly explained, and the robustness of these states is unclear.

The productive collision surface area analysis needs more quantitative data.

The coupling energy values are near the uncertainty range. Some conclusions about long-range communication networks appear stronger than the data justify. The data support coupling, but they do not necessarily support detailed mechanistic networks.

The study investigates one lineage, one epitope class, and one viral system. Hence, the generalization is limited.

Reviewer #3 (Public review):

Summary:

In this work, the authors set out to characterise how encounter states between antibodies and antigens evolve during affinity maturation through molecular dynamics simulations and Markov state modeling. They demonstrate how early glycan-mediated interactions increased association rates rather than modifying the final bound state.

Strengths:

The computational approach is backed up by experimental results and allows for visualising otherwise too short-lived association states, thus allowing to discriminate between different lineages.

Weaknesses:

The figures and captions are not always clear about what they are trying to show. The choice of CVs is not sufficiently discussed.

Reviewer #2 (Public review):

Summary:

In antibiotic research, accurately measuring decreases in bacterial populations is essential. The authors conducted a comprehensive evaluation of the luminescence assay, a commonly used but previously under-quantified method, benchmarking it against the gold-standard CFU counting approach. They found that luminescence measurements generally aligned with CFU results but sometimes reported slower decline rates for certain antimicrobials. These discrepancies were linked to differences in how the two methods capture biomass and colony formation, which vary with the antimicrobial's mechanism of action. The study demonstrates that luminescence assays can serve as a high-throughput alternative to labor-intensive CFU counting, provided their limitations are understood and corrected.

Strengths:

The authors developed a mathematical model to partially correct luminescence-based measurements, making the approach broadly applicable to several commonly used antibiotics. They also analyzed antibiotic-treated single-cell morphologies and linked filamentation to bulk luminescence signals. This analysis helped define the range of drug conditions under which luminescence assays provide reliable estimates of bacterial dynamics.

They extensively evaluated the method using 20 antibiotics and one antimicrobial peptide, encompassing many of the most commonly used agents and experimental factors (e.g. treatment time) typically considered in antibiotic research.

Comments on revised version:

No further comments. The authors have adequately addressed my concerns.

Reviewer #3 (Public review):

Summary:

This preprint proposes luxCDABE-based luminescence as a high-throughput alternative (or complement) to CFU time-kill assays for estimating antimicrobial rates of population change at super-MIC concentrations, by comparing luminescence- and CFU-derived rates across 20 antimicrobials (22 assays) and attributing divergences primarily to filamentation (luminescence closer to biomass/volume than cell number) and changes in culturability / carryover (CFU undercounting viable cells).

Strengths:

The authors do not merely report discrepancies; they experimentally validate the biological causes. Specifically, they successfully attribute the slower decline of luminescence in certain drugs to bacterial filamentation (maintaining biomass despite halted division) and the rapid decline of CFU in others to loss of culturability or carryover effects.

The inclusion of 20 antimicrobials spanning 11 classes provides a robust dataset that allows for broad categorization of drug-specific assay behaviors.

The study critically exposes flaws in the "gold standard" CFU method, specifically regarding antimicrobial carryover (demonstrated with pexiganan) and the potential for CFU to overestimate cell death in the presence of VBNC (viable but non-culturable) states induced by drugs like ciprofloxacin.

The use of chromosomal integration for the lux operon to minimize plasmid copy-number effects and the validation of linearity between light intensity and cell density establish a solid technical foundation.

In summary:<br /> Muetter et al. provide a compelling argument that luminescence is a reliable, high-throughput alternative to CFU for super-MIC investigations, particularly when the quantity of interest is biomass. The paper effectively warns researchers that discrepancies between CFU and luminescence are often biological (filamentation, VBNC) rather than methodological failures.

Comments on revised version:

The revised version addressed my comments well.

Reviewer #1 (Public review):

Summary:

The authors describe a clever genetic system based on rapamycin-inducible expression of a beta-galactose reporter. The authors compare this spectrophotometer-based readout to the parasite reduction rate version 2 (PRRv2) recently described by some of the same authors and based on incorporation of [3H]-hypoxanthine. The results are generally comparable, with some differences for slower-acting compounds. The authors report that this format is better suited for higher-throughput studies and requires less time to quantify the time-dependent onset of parasiticidal action compared with the PRRv2.

Strengths:

This is a very well-executed and well-described body of work with a comprehensive set of analyses.

Weaknesses:

The authors should revise their text to also describe other methods used to quantify parasite growth. This method saves time compared to the PRRv2 but is too complex for simple screening of antiplasmodial activity of agents tested alone. Its value lies in assessing the speed of action of compounds tested in combination.

There are a number of areas for improvement:

(1) Many antimalarials have quite specific times of action. Are these MULTI-i2 assays, and the comparator PRRv2 assays, conducted with asynchronous cultures? This should be described in the methods and referred to in the text (apologies if I missed some references).

(2) The authors correctly state that flow cytometry-based readouts, such as with MitoTracker alone, can limit throughput and that MitoTracker alone can produce spurious results. The authors should cite work from other labs that combine MitoTracker with a nuclear dye, such as SYBR Green I. I think others have also been used, such as YoYo-1, which overcomes the limitations of using MitoTracker alone. Also, many labs use a nuclear dye such as SYBR Green I in a spectrophotometer-based format that enables rapid processing of plates at scale (96, 384, or even 1536 wells per plate). Luciferase-based screens have also been used in large-scale screening campaigns. The introduction should cite these various approaches, especially as the MULTI-i2 method is quite a complex screen with an initial period of drug exposure (up to 3 days) followed by a five-day phase initiated by rapamycin addition to induce expression of the beta-gal sensor.

(3) It would be helpful for authors to provide some indication of the cost comparison between the PPRv2 and MULTI-i2.

(4) Also, the authors should indicate whether these reagents will be deposited in a repository such as BEI Resources. They should also indicate conditions for other groups to request these materials, such as whether an MTA is required.

(5) The pharmacological models are interesting, but likely well out of the range of expertise of many labs. Has code been deposited into public repositories that make it possible for other labs to implement these analyses?

Reviewer #2 (Public review):

Summary

Antimalarial combination therapy is the standard of care for malaria, a disease that impacts hundreds of millions of people annually. Combination therapy is crucial for effectively treating the disease and delaying the emergence of drug resistance. Despite the importance of choosing appropriate partner antimalarials for combination therapy, drug interactions are typically evaluated late in the course of drug development. Standard in vitro assays that determine synergistic, antagonistic, or additive interactions between drug combinations rely on measuring inhibition of parasite proliferation, which is inadequate for translation to pharmacodynamic models for parasite clearance in the patient. Direct measurement of parasite viability under drug treatment has previously relied on methods that are labor and resource-intensive, limiting applications to single compounds and single concentrations. Here, Hellingman et al make use of an inducible chemiluminescence reporter to measure cell viability and apply this novel approach to quantify drug interactions. The methodology is a significant improvement upon prior methods, requiring significantly fewer resources, half the time, and substantially less handling than the standard PRRv2 assay, whilst maintaining high resolution and sensitivity.

They assess the limit of detection for the improved method and cross-reference their results for single drugs at a single concentration with the currently standard PRRv2 assay. The authors next established analytical methods to characterize the impact of drug combinations on parasite viability using the GDPI pharmacodynamic model and compared their MULT-i2 assay to the prior cPRR approach. Their refined workflow allowed them to comprehensively evaluate the known synergistic combination between atovaquone and proguanil with greater resolution than the comparable cPRR assay and identified additional interaction parameters between the fast-acting antimalarials piperaquine and pyrimethamine. Overall, the authors demonstrate that their inducible lacZ system provides significant advantages compared with prior approaches to determine parasite viability. They convincingly demonstrate the strengths of their approach by characterizing two antimalarial combinations at much greater resolution than previously possible with prior methods. The system and methods established here will be particularly useful for evaluating novel antimalarial combinations with chemical series in preclinical evaluation and to optimize future antimalarial therapies.

Strengths:

The streamlined approach relies on induction of the lacZ enzyme only after drug washout. As opposed to when stably expressed, this allows the authors to estimate parasite viability without undergoing serial dilutions to estimate viable parasite titers. This innovation vastly reduced resource and time intensity, enabling greater throughput for parasite viability estimation. The established methodology and analysis pipeline enabled the testing of 49 drug combinations for parasite viability in the MULT-i2 assay compared to only 9 in the conventional cPRR assay. This provided improved resolution in the ability to estimate drug combination parameters in a pharmacodynamic model. The ability to comprehensively characterize combination pharmacodynamic properties in vitro will have important implications for downstream modelling of in vivo combinations, and for optimizing future antimalarial combination therapies.

The authors made good use of modelling and AICc for parametric estimation and model evaluation to demonstrate the advantages of the richer dataset afforded by the MULT-i2 assay.

Weaknesses:

The authors correctly identified a range of confounding effects that lead to artefacts in their assay results when compared to the cPRR assay. For instance, the authors observed reduced signal at high parasite density during recovery due to overgrowth and likely enzyme degradation, and suggested residual signal may remain from non-proliferating sexual stage parasites surviving drug treatment that would not be detected in the cPRR assay.

Measurement of parasite viability in the MULT-i2 assay was achieved by extrapolating the chemoluminescence signal to that of a serial dilution of parasites made at the initiation of drug treatment. How did the authors account for differing levels of enzyme expression at early (e.g., ring) vs late stage parasites (trophozoite or schizonts)? Were cultures synchronized prior to initiation of assays? Could differences in life-cycle progression following drug treatment be an additional confounding factor that may account for differences with the PRRv2 assay?

The addition of an inducible element is an improvement of their earlier lacZ/β-galSENSOR (PMID: 41575867); however, the authors fail to explain why this is an improvement and how this adds additional merit over the initial system. While the authors compare their new assay to the PRRv2, they fail to compare it to their own non-inducible lacZ/β-galSENSOR system. Their non-inducible system already showed superiority to the cPRR assays, and it would be good to show how they compare and what the advantages of the new system are over the old. e.g., how is the signal-to-noise improved? How does the sensitivity compare? How quickly does the can the signal be detected after induction? They show signal after 48h, but it would be very useful to the community to look at earlier timepoints as well and compare them to the uninduced line and a line that has been induced 48h earlier to match the expression patterns throughout the lifecycle (something like 2h,4h,6h, 12h, and 24h).

Is the chemiluminescence signal for the i-lacZ induced parasites comparable to the stably expressed lacZ parasites previously characterized by the group? If so, do the authors consider this inducible iteration a complete replacement for PRR assays?

Reviewer #3 (Public review):

In this manuscript, the authors strived to develop a highly efficient drug survival assay for in vitro cultured human malaria parasites P. falciparum. This was done by generating a transgenic P. falciparum line using a creLox strategy that allows detection of (presumably) viable parasites by a β-lactamase assay. To estimate the Limit of quantification of the recombined P. falciparum NF54i-lacZ, the authors ultimately designed a protocol in which viable parasites are detected by the luminescence of β-D-galactoside generated by β-lactamase within the transgenic parasites. For this, the parasite must be incubated with rapamycin for 120 hours to induce CreLox recombinase, which places β-lactamase under an active promoter. Using this assay, termed MULTI-i2, the author shows interactions between two antimalarial drug pairs that were previously demonstrated by another assay. In the case of pyronaridine and piperaquine pair, the NULT-i2 assay generated some additional insights compared to the previous assay, presumably by virtue of including more concentration datapoints. In conclusion, the authors argue that the MULTI-i2 assay is much less resource-intensive and time-consuming and can be applied on a large scale at a much lower cost and with the highest efficiency.

Overall, the data generated in this manuscript are clear and well represented, and I am convinced that MULTI-i2 provides yet another of many drug assays for malaria parasites and could be put to good use. However, I struggle to fully appreciate the merit of his study, as the manuscript reads more like a technical document than a scientific study.

I particularly lack an understanding of the strengths and weaknesses/limitations of the MULTI-i2 methodology and, thus, its applicability. I also do not fully appreciate the need for such an elaborate luminescence-based experimental setup. It would be good if some of these issues were addressed.

Specifically:

(1) The whole assay is based on detecting parasites by luminescence after 120 hr (5 days) after drug exposure. During that time, presumably the parasites that survived the drug pressure regrow to a detectable level and, at the same time, perform efficacious CreLox-based recombination to produce β-D-galactoside for detection. Is this necessary? How superior is this detection method to other methods, such as Fluorescence-assisted Cell Sorting (FACS), etc? Moreover, the 5-day growth-CreLox-β-D-galactoside production could introduce a series of confounding effects. In my view, more studies (beyond comparisons with a single existing method) would be useful for understanding this entire process.

(2) Related to that above, how would MULTI-i2 perform in case of drugs that do not necessarily kill all parasites, such as artemisinin? In the case of artemisinin, it is becoming evident that at least a small fraction of the parasite revives after treatment via a temporary dormancy state. This has, in fact, also been shown for other drugs such as mefloquine, pyrimethamine, etc. Would such a situation produce a range of false readings? In general, in its current state, it is hard to see what the limitations of this method are, which makes it hard to decide whether to use it for a particular application.

(3) Given the stated cost and labor efficiency of MULTI-i2, it is disappointing to see only two applications for two drug pairs: atovaquone/proguanil and piperquine/pyronaridine, for both of which their interactions were already known. The manuscript would benefit greatly if the authors demonstrated more drug interactions and identified (and ultimately validated) new ones. This would certainly make MULT-i2 method more attractive. In particular, it would be nice to see if one could use MULTI-i2 for studies of triple combinations as enthusiastically suggested.

(4) Throughout the manuscript, the authors claim that MULTI-i2 is considerably less expensive and can be done much faster than previous methods. In my view, this is not exactly a scientific argument. The cost of an assay depends heavily on the cost of reagents and labor, which are subject to market price fluctuations. The efficiency and time consumption can very much depend on laboratory organization, etc. Unless the author could specifically demonstrate where and how these assays are cheaper and faster, I suggest not discussing this.

Reviewer #2 (Public review):

Summary:

The manuscript by Wang and colleagues aims to determine whether hepatic glucose metabolism is differentially regulated by the left and right sides of the LPGi and to reveal decussation of hepatic sympathetic nerves.

The authors used tissue clearing to identify sympathetic fibers in the liver lobes, then injected PRV into the hepatic lobes. Five days post-injection, PRV-labeled neurons in the LPGi, which were identified. The results indicated contralateral dominance of premotor neurons and partial innervation of more than one lobe. Then the authors activated each side of the LPGi, resulting in a greater increase in blood glucose levels after right-sided activation than after left-sided activation, and in changes in protein expression in the liver lobes. These data suggested lobe-specific modulation of HGP. Chemical denervation of a particular lobe did not affect glucose levels due to compensation by the other lobes. In addition, nerve bundles decussate in the hepatic portal region.

Strengths:

The manuscript is timely and relevant. It is important to understand the sympathetic regulation of the liver and the contribution of each lobe to hepatic glucose production. The authors use state-of-the-art methodology.

Weaknesses:

(1) Image clarity was improved in some cases, but not in others. For example, Figure 3I, showing c-Fos expression, is not convincing due to the image quality and lack of orientation.

(2) The methods section states that 8-weeks-old male mice were used in the experiments without specifying the experiments (e.g., brain injection with AAVs or PRV organ inoculation). The authors should include these details.

(3) The authors should use the exact location of pre- and postganglionic neurons as they often refer to neurons in the sympathetic chain. Their findings should be compared with the existing literature on the location of preganglionic cells.

(4) Figure legends should be revised and matched with the text.

Reviewer #4 (Public review):

Summary of General Strengths & Weaknesses:

The studies here are highly informative for anatomical tracing and sympathetic nerve function in the liver in relation to glucose levels, but because they are conducted in a single species, it is challenging to translate them to humans or determine whether these neural circuits are evolutionarily conserved. Dual-labeling anatomical studies are elegant, and the addition of chemogenetic and optogenetic studies provides mechanistically informative. Denervation studies lack proper controls, and sensory innervation in the liver is overlooked.

Specific Weaknesses - Major:

(1) The species name should be included in the title.

(2) Tyrosine hydroxylase was used to mark sympathetic fibers in the liver, but this marker also labels a portion of sensory fibers that need to be ruled out in whole-mount imaging data.

(3) Chemogenetic and optogenetic data demonstrating hyperglycemia should be described in the context of prior work demonstrating liver nerve involvement in these processes. There is only a brief mention in the Discussion currently, but comparing methods and observations would be helpful.

(4) Sympathetic denervation with 6-OHDA can drive compensatory increases in tissue sensory innervation, and this should be measured in the liver denervation studies to implicate potential crosstalk, especially given the increase in LPGi cFOS that may be due to afferent nerve activity. Compensatory sympathetic drive may not be the only culprit, though that is clearly assumed. The sensory or parasympathetic/vagal innervation of the liver is altogether ignored in this paper and could be better described in general.

Comments on the revised version.

Across all reviewer comments, the revised resubmission has adequately addressed all concerns.

Reviewer #1 (Public review):

In this paper, Solyga, Zelechowski & Keller study human visuomotor mismatch responses as an alternative instantiation of prediction errors to classic oddball paradigms. Using VR, they created a condition in which participants were moving around thereby creating a visuomotor coupling between physical movement and visual flow. To attempt to isolate the contribution of specifically movement-related predictions in this condition, they contrasted it to a condition in which participants were seated and rewatching their movement trajectory during the 'active' condition. Visuomotor mismatches were created by temporarily decoupling movement and visual experience by halting the VR display as participants continued to move.

The core finding of the paper is that participants exhibit a positively-valenced response to the visuomotor decoupling in the active but not in the passive condition. Since walking speed only insignificantly slows down following decoupling events in the active conditions, the authors argue that this difference cannot be accounted for by "changes in participants' behavior or to simple visual offset responses" with the latter being equal across both conditions. The following reinstatement of the coupling in turn does not differ between the two conditions. The authors additionally show that this mismatch response differs from visual onset responses elicited by checkerboard inversions and that it's "qualitatively" stronger than more commonly studied auditory oddball mismatch responses.

The design with its focus on ecological validity is impressive, well-rationalized and the results are well illustrated. I additionally appreciate the control analyses with regards to changes in walking speed and playback DOF and, now added, additional participants who experience the passive condition before the active.

My main question in round 1 regarded the isolation of visuomotor mismatch. Although the comparison with a seated control seems like a very sensible way to control for simple visual responses, there seem to be more differences than just a break in visuomotor coupling between the conditions. I therefore wonder whether the reduced offset response in the seated condition may be, in part, explained differently. For example, given that participants always conduct the active condition before rewatching their movement in the seated condition, it seemed likely that there is a component of learning across the session that flow will sometimes be halted. This is confirmed with the analyses. The explanation that there is a visuomotor component here is given further weight by their conduction of an additional group of participants who perform the conditions in the reverse order, so this has strengthened the manuscript considerably. However, it does of course remain an imperfect control because the visual stimulus is now different between the conditions for these participants. It's the best that can be achieved with this type of paradigm though and of course it yields a great deal of ecological validity.

I was also wondering whether the authors may consider the findings in frontal electrodes more closely given that the title of the paper focuses on a specifically occipital effect. Their further analyses have confirmed that there are likely interesting frontal effects. From a theoretical point of view, the spatial dissociation in adaptation effects, which were stronger in frontal and weaker in occipital areas, seems interesting and perhaps worth discussing, especially given the interpretation that "mismatch processing may initially arise in sensory visual areas before engaging higher-order frontal regions." How come the frontal decrease in responses is not accompanied by an analogous decrease in its supposed occipital source? Could these two responses reflect different kinds of prediction error signals (i.e. objective vs subjective)?

I remain concerned that the authors fight too defensively that they have absolutely isolated visuomotor prediction mechanisms with this paradigm. It's a nice, informative study, but it seems odd to argue there are no other possible explanations. One picks a design to optimize some features, but they will always come at some cost to others. Prioritising ecological validity, which is a justifiable aim, necessarily usually weakens some control over confounds.

To outline my reasoning fully: My concerns wrt generic influences of action on perception are reflected in Fig 1. The P1 is smaller when walking than sitting. It seems likely that the mismatch response reflects something about extrapolation or prediction, because it is larger when walking. However, it's not necessarily sensorimotor prediction. Even if you remove action from the equation, the flow can be extrapolated or predicted most of the time in a way it cannot so well when the video is halted. Of course, the sitting condition somewhat controls for it, but when it came second the visual flow disruptions were more predictable here. A reduction in effects over time is indeed confirmed with their analyses. They now have conducted a study with the conditions in the reverse order and they find the same thing. But of course, this necessitates non-identical visual flow because the sitting condition is playing the previous participant's flow. So it is likely that across all of these comparisons, it is the visuomotor mismatch that is especially salient. It's just that each comparison is a bit messy/confounded. It would strengthen the manuscript if there were some consideration given to the other processes likely at play here.

As a more minor point in response to our previous review, whether particular accounts represent an 'orthodox' view at present does not determine whether they raise logical issues in need of consideration. The authors may have missed that the papers in question consider mechanisms underlying the attenuation of particular pieces of information *from perception*. Not perceptual processing. We have one percept at any one moment in time and must understand how different population types synergistically generate that percept.

Similarly, a little strange is the way in which the authors aggressively defend the position that self-generated motion is 'the strongest' type of prediction. Sure, we probably experience the effects of our actions more often than ambulances. But what about objects obeying laws of gravity or others' faces being structured and moving in systematic ways? It is hard to quantify, such that presumably many scientists would be skeptical of such a claim, and it is not needed logically to justify the importance of examining mechanisms enabling action to shape perceptual processing. I'd assume it better to fight the battles you need to (and can) fight, such that the robust claims carry more weight.

Comments on latest version.

Nice to see the added extra analyses. Can't see any more will be achieved via further rounds and happy with the summary to stand as is.

Reviewer #2 (Public review):

Summary:

This study investigates whether visuomotor mismatch responses can be detected in humans. By adapting paradigms from rodent studies, the authors report EEG evidence of mismatch responses during visuomotor conditions and compare them to visual-only stimulation and mismatch responses in other modalities.

Strengths:

- Authors use a creative experimental design to elicit visuomotor mismatch responses in humans.

- The study provides an initial dataset and analytical framework that could support future research on human visuomotor prediction errors.

Weaknesses:

- Methodological issues (e.g., volume conduction) make it difficult to confidently attribute the observed mismatch responses to activity in visual cortical regions. This could be alleviated by increasing the number of channels.

The authors successfully demonstrate that visuomotor mismatch paradigms can, in principle, be applied in human EEG. This approach provides a translational bridge between rodent and human work on predictive processing.

Comments on latest version.

The authors added a brief discussion paragraph which addresses my previous comment.

Reviewer #3 (Public review):

Solyga, Zelechowski, and Keller present a concise report of an innovative study demonstrating clear visuomotor mismatch responses in ambulating humans, using a mobile EEG setup and virtual reality. Human subjects walked around a virtual corridor while EEGs were recorded. Occasionally, motion and visual flow were uncoupled, and this evoked a mismatch response that was strongest in occipitally placed electrodes and had a considerable signal to noise ratio. It was robust across participants and could not be explained by the visual stimulus alone.

This is an important extension of their prior work in mice and represents an elegant translation of those previous findings to humans, where future work can inform theories of e.g. psychiatric diseases that are believed to involve disordered predictive processing. For the most part, the authors are appropriately circumspect in their interpretations and discussions of the implications. The paper in its current form represents an important addition to the literature.

The authors have included analyses of the auditory mismatch using temporal electrodes, referenced to Cz (and therefore should exhibit a mismatch positivity). This added data clearly and convincingly shows that the sensorimotor mismatch is, indeed, stronger than the passive auditory MMN.

Comments on latest version:

The authors added useful points to the discussion and also included time frequency analyses to the paper formally, which strengthens the translational potential, in addition to the bolstering their claims slightly.

Reviewer #1 (Public review):

Li and Wu, in this article, explore the proliferation of wall-less L-forms derived from Bacillus subtilis as mimics for protocells and report an interesting new mechanism for their proliferation. The authors carry out live-cell imaging of the L-forms and find that the clusters of cells forming proto-colonies proliferate better than the isolated single cells of L-forms. They further examine the causes for this indefinite proliferation of proto-colonies of L-forms, as compared to the isolated cells, which lyse and die out sooner. The authors show that when L-forms exist as isolated single cells, the growth in volume exceeds the rates at which surface area increases, leading to lysis. The authors further quantify the circularity and effective radius in growing proto-colonies, qualitatively estimate membrane tension and suggest that the confined space allows for mechanical shear in these cells. They propose that the mechanical stress on the membranes from adjacent cells in confined spaces deforms membranes and supports cell division to keep the population growing. These findings are also supported by modelling the proto-colonies in quasi-2D planes.

The study is quite interesting and significant as it has implications for both evolutionary aspects as well as clinical importance, given the proliferation of certain pathogens as L-forms. The aspect of carrying out long-term imaging of colonies of L-forms as spatially constrained entities and the findings are fascinating. While the conclusions presented are backed by experiments, I only have a few questions concerning the proposed mechanism of division and proliferation of these proto-colonies.

(1) The authors propose that the growth of neighbours leads to shearing forces in membranes and show that membrane tension increases at the periphery of the proto-colonies. They suggest that the increased membrane tension leads to a greater chance of deformation, enabling cell division. However, it is not quite clear how greater membrane tension could lead to cell division. Studies have suggested that membrane fluidisation is important for the cytokinesis event, which includes FtsZ-based division (Ramirez-Diaz, 2025).

(2) Thus, it becomes quite important to rule out any role for the cytoskeletal proteins in the observed division with an increase in membrane tension. The authors note in line 188 that the division in protocells is independent of FtsZ, but this independence is for protocells that divide by extrusions and resolution, where the membrane is highly fluidised (Mercier et al., 2012).

(3) The authors may use the L-form derivative where the FtsZ protein can be depleted and assess the proliferation of the proto-colonies. Likewise, authors should rule out the role of MreB as well.

(4) Although the growth rates have been shown to be similar for proto-cells and the proto-colonies, and only the membrane tension has been shown to be higher at the periphery, it is also important that the authors rule out any increased lipid synthesis in the fraction of dividing cells in these proto-colonies. Without this, one could also envisage a model where membranes are fluidised due to an increase in lipid biosynthesis in a fraction of cells in these confined spaces, leading to increased vesiculations which experience membrane shear and deform. The authors can also consider examining proto-colonies of L-forms of branched-chain fatty acid-deficient strains.

(5) Lastly, why does CellROX stain the proto-colonies? Are these tightly packed cells experiencing higher oxidative stress, and could that also contribute to membrane tension? This should at least be discussed.

Reviewer #2 (Public review):

Summary:

The manuscript "Mechanical interaction enables a collective mode of protocell proliferation" addresses an interesting and potentially high-impact question about protocell proliferation in prebiotic environments. The central observation that wall-deficient B. Subtilis proliferate in dense colonies but die by membrane rupture in isolation is striking and a fundamental contribution to the field. However, the data and the mechanistic explanation offered for this observation are incomplete. The measurement and analyses used to build the mechanistic case raise methodological questions that may be difficult to fully resolve with the existing data and approach, and the authors should therefore consider whether additional independent experiments are needed to support the mechanical shearing hypothesis.

Strengths:

The central observation that wall-deficient B. Subtilis proliferate in dense colonies but die by membrane rupture in isolation is convincing and a significant contribution to the field interested in the growth of protocells. This adds an important aspect of collective growth that is different from individual dynamics.

Weaknesses:

(1) The surface-volume balance ratio η is an elegant concept and provides an intuitively reasonable framework for understanding why isolated cells lyse. However, its application here rests on treating cells as flat discs of uniform thickness, and Figure S4 makes clear that the cells are highly irregular and lobulated in ways that make this approximation questionable. The authors should clarify whether they have validated this assumption, for instance, through direct thickness measurements or sensitivity analysis. However, even with such validation, the modest quantitative differences between aggregated and isolated η trajectories, combined with the inherent difficulty of accurate perimeter measurement in these morphologically complex cells, mean that η measurements are unlikely to provide robust quantitative support for the mechanism. The authors should therefore consider whether η is better presented as a motivating conceptual framework rather than primary quantitative evidence and seek more direct experimental support for the surface-volume balance argument through independent means. For instance, osmotic pressure manipulation to test whether reducing volume expansion pressure preferentially rescues isolated cells.

(2) The comparison of circularity between colony and isolated cells is complicated by the fact that the segmentation approach is fundamentally different in the two conditions; isolated cell boundaries are detected against a clear background, while colony boundaries are detected from inter-cell fluorescence gradients. The authors should address whether this introduces systematic bias. However, this may be difficult to fully resolve given the inherent complexity of the system, and that the deformation-division correlation in Figure 3C, while suggestive, would be substantially strengthened by a more direct perturbative approach. Specifically, can cell deformation be mechanically induced in isolated cells, for instance, using micromanipulation, external flow, or confinement in fabricated microstructures, to test whether artificially deformed isolated cells gain the ability to divide? Such an experiment would provide direct evidence for the deformation-division link that the correlational analysis cannot.

(3) The interpretation of FliptR lifetime as a direct membrane tension readout is complicated in this system because cell-cell interfaces contain two apposed bilayers in proximity, potentially altering FliptR photophysics through changes in local membrane density and dielectric environment independently of tension. The authors should address whether they have considered this possibility and what controls were performed. Disambiguating tension-dependent from environment-dependent lifetime changes is technically challenging and suggests that the membrane tension argument would be more convincingly supported by an independent measurement approach. For instance, tether-pulling experiments using optical tweezers on isolated versus colony cell membranes, or testing whether membrane tension-modulating interventions such as osmotic shifts produce the predicted changes in cell fate, would provide more direct evidence. The current FLIM data should be regarded as suggestive rather than conclusive.

(4) The Cellular Potts Model reproduces the experimental observations, but since its key parameters, particularly the substrate-pinning energy, were calibrated against those same observations, this demonstrates internal consistency rather than independent validation. The η-based lysis criterion is implemented as a model input, meaning the model cannot independently confirm the η hypothesis. The authors should clarify the extent to which model parameters were fitted to data versus independently motivated and be explicit that the model is best understood as a mechanistic illustration rather than independent evidence.

Reviewer #3 (Public review):

Summary

This manuscript reports that protocells derived from wall-deficient B. subtilis proliferate well when densely packed but fail to divide and eventually lyse when isolated. The authors attribute this density-dependent proliferation to mechanical shearing between growing neighbors, which deforms cells and increases the likelihood of membrane stalk formation and subsequent scission, enabling division without any dedicated molecular machinery. Through a combination of quantitative imaging, membrane tension measurements, and Cellular Potts Model simulations, the authors make a compelling case that self-generated mechanical stresses are critical for sustaining population growth in protocolonies. The findings have implications for understanding the lifestyles of primitive life forms, L-form bacterial pathogenesis, and the design of synthetic cells.

Strengths

The central finding is both surprising and counterintuitive: crowding is not just tolerated by protocells but is required for sustained population growth. The mechanism the authors propose is interesting: mechanical shearing between growing neighbors deforms cells, increasing the likelihood of membrane stalk formation and thus division, all without dedicated molecular machinery. Conceptually, this is a type of biophysical "scaffold" (Jacobeen et al. 2018, Nat. Phys.; Day et al. 2022, Biophys. Rev.) in which key elements of a Darwinian loop, namely a life cycle involving growth and reproduction, are provided "for free" by physics, enabling open-ended Darwinian evolution that can eventually bring these life cycle components under developmental control. Such scaffolds, both biophysical and ecological (Black et al. 2020, Nat. Ecol. Evol.; Libby & Rainey 2013, Phys. Biol.), are likely key mechanisms in the origin of life and in evolutionary transitions in individuality, and this paper provides a nice example of how they can work in a protocell context.

The combination of experiments and modeling works well. The membrane tension measurements are the strongest piece of evidence for the proposed mechanism, showing directly that tension is elevated in protocolonies and concentrated at cell-cell interfaces. The Cellular Potts Model captures the key experimental features. The discussion is nicely balanced, particularly the note about Gram-negative L-forms, whose rigid outer membrane may preclude this mechanism, which is a testable prediction for future work. I would suggest the authors also discuss the connection to biophysical scaffolding, as I think this is conceptually important and would help situate their work within a broader framework for understanding how primitive life cycles can arise from physical processes (see also Zamani-Dahaj et al. 2023, Genes; Hammerschmidt et al. 2014, Nature).

Weaknesses

The surface-volume balance analysis is central to the argument, and it depends on the assumption that cells have a fixed thickness of 0.8 µm, taken from the width of walled cells. But these are wall-deficient cells, which are mechanically quite different, and their thickness could plausibly vary during growth or under compression. I think the paper would benefit from either a direct measurement of cell thickness or a sensitivity analysis showing how η responds to plausible variation in this parameter. If the results are robust, that would put the analysis on much firmer ground.

The positive correlation between cell shape deformation and division rate (Figure 3C) is central to the proposed mechanism, but I think the paper needs to be more careful about the jump from correlation to causation. The authors propose that deformation increases the likelihood of membrane stalk formation, leading to scission. That is plausible, but an alternative is that cells with higher local growth rates both deform more and divide more frequently, with the two outcomes driven independently by the same underlying cause. The paper does show that average volume growth rates are indistinguishable between aggregated and isolated cells, which argues against a simple "faster growth explains everything" interpretation, but this does not rule out local variation within protocolonies driving the correlation. I think the most convincing experiment would be to apply external mechanical stress to isolated cells and see if that alone can drive division, decoupling deformation from growth. I realize that this may be technically very difficult, but at a minimum, the paper should acknowledge this as an alternative hypothesis.

The Cellular Potts Model has quite a few free parameters (Table S1), and it is not clear how tightly these are constrained by the data. A sensitivity analysis would go a long way toward showing that the results are robust and not overly dependent on specific parameter choices.

In any case, this is a strong paper with a cool finding and an interesting mechanistic explanation. I think it will be of broad interest, particularly to people thinking about the origins of life and synthetic cell design.

Reviewer #1 (Public review):

Summary:

Flexible natural behavior requires flexible sensory-motor mapping. In the visual domain, a visual stimulus at one location can guide a saccade toward another. How the receptive field (RF) and motor field (MF) properties of oculomotor structures support this flexibility is not known. Dotson and Reynolds address this question in the marmoset, using oblique Neuropixels penetrations across horizontal segments of the frontal eye field+, supplemented by electrical microstimulation. They report that visual RF and saccade MF vector angles each change smoothly with occasional abrupt jumps, that the two maps are organized as mosaics at distinct preferred spatial scales, and that a moiré interference pattern arising from a constrained spatial-scale mismatch between partially correlated mosaics reproduces the empirical distribution of RF-MF angular differences. They conclude that visuomotor flexibility is embedded in the geometry of mismatch and matches between visual and motor maps.

Strengths:

(1) The question is well-motivated. Sensory-motor mapping is known to be flexible, and asking whether the topographic relationship between the two maps itself supports that dissociation is a fresh reframing of a long-standing problem in oculomotor control.

(2) FEF+ lies on the smooth marmoset cortical surface, which permits high-density horizontal sampling that would be difficult in the macaque arcuate sulcus, and oblique penetrations are a sensible way to track tuning across the surface. The dataset is substantial by the standards of the field (39 sites of high-density recordings across two animals, several thousand isolated units).

(3) The data are thorough, and the convergence of three independent lines of evidence is the strongest feature of the paper. Unit recordings, electrical microstimulation, and two architecturally distinct generative models point to the same organization.

(4) The central idea is conceptually novel. The proposal that flexibility can reside in the geometry of the maps, rather than only in time-varying activity, is original, and it generates concrete, testable predictions for tasks that require flexible visuomotor routing.

Weaknesses:

Major concerns

(1) The analysis collapses each oblique penetration onto a single horizontal axis and pools angles across all cortical layers, treating cortical distance as purely tangential. Because the trajectory is angled, horizontal distance and depth are confounded, so some of the apparent RF-MF drift along a penetration could reflect a laminar transition, in addition to tangential mosaic structure.

(2) RFs and MFs are estimated from the same free-viewing sessions in temporally adjacent epochs, leaving each measurement open to contamination by the other. Activity near a saccade can reflect peri-saccadic remapping rather than the stable retinotopic RF, and saccade-aligned activity following a recent flash can carry a residual visual component, given the long-lasting visual responses in FEF+ (>500 ms). Residual cross-contamination of this kind would tend to make RF and MF angles look more similar than they are, inflating the apparent local coupling and biasing the RF-MF difference distribution that the moiré model is fit to.

(3) The paper claims that visual and saccade mosaics occupy distinct spatial scales, but the two preferred spatial frequencies are close, and the separation is summarized by overlapping "failed-test" bands rather than by a statistical test or confidence interval on the preferred frequency itself. The reliability of this separation is not established.

(4) It is not clear whether the moiré model is a better model than the non-mosaic alternative. The moiré models are shown to be consistent with the data through failure to reject a Kolmogorov-Smirnov null, which is a weak form of evidence, and they are not benchmarked against a non-mosaic alternative or null model. The AM/NM convergence demonstrates architecture independence, but not that a mosaic organization is required.

Minor concerns

(1) The link from topography to behavioral flexibility (such as anti-saccades and other context-dependent transformations) is presented as a prediction but is not tested with any task manipulation. The work establishes an organizational principle and a plausible generative mechanism; whether that organization is actually exploited during flexible behavior remains open, and the framing should make this clear so the functional claim is not over-read.

(2) It is unclear how relative depth (depth 0) is defined and how layer boundaries were assigned. The Methods mention common-average re-referencing for CSD and local field analyses, but no CSD or power-depth profile is shown to anchor the layer IV / depth 0 reference across penetrations.

(3) The Discussion is brief relative to the strength of the claims. It would be helpful to address the concerns and alternative explanations above, where these cannot be fully resolved by the data.

Reviewer #2 (Public review):

Summary:

The authors asked how the visuomotor system can keep visual selection and saccade targeting related but not rigidly coupled-the flexibility required for tasks like anti-saccades. They recorded visual receptive fields (RFs) and saccade motor fields (MFs) from individual neurons in marmoset frontal eye fields and adjacent premotor eye fields (FEF+) using obliquely inserted Neuropixels probes that traverse horizontal segments of the smooth marmoset cortex. They reported that visual and motor vector angles each changed smoothly with occasional abrupt jumps (a mosaic, rather than retinotopic, organization), that the two maps drifted with respect to one another, and that they were best described by mosaic-map models tuned to different preferred spatial frequencies. They then proposed that the offset in spatial scale, combined with partial shared structure between the maps, produced a moiré interference pattern, in which the distribution of local visual-motor angle differences matched the data.

Strengths:

(1) Unlike in the macaque brain, where FEF is buried in the arcuate sulcus, the marmoset cerebral cortex is lissencephalic (smooth). The authors used this feature to their great advantage and sampled horizontal mesoscale structure with oblique penetrations of ultra-high-density Neuropixels probes.

(2) The mosaic framing was grounded in previous studies on direction maps in ferret V1 and MT, and the rate-of-change analysis (Supplementary Figure 2) plausibly reproduced the fracture-line phenomenon of those maps.

(3) The authors confirmed the robustness of the finding by reaching the same conclusions using two architecturally distinct generators: the Fourier-based annulus model and the Gaussian-noise model.

(4) They additionally provided an independent confirmation of the mosaic saccade-vector organization using electrical microstimulation. They reconciled the lower microstimulation spatial frequency by matching the spatial-averaging footprint (Supplementary Figure 6).

(5) The Noise Mosaic (NM) model was used thoughtfully to decouple two properties that the Annulus Mosaic (AM) model confounds - spatial-scale offset and inter-map correlation - and to show that both an intermediate correlation (ρ ≈ 0.6) and a scale offset are required. Conceptually, a structural (topographic) substrate for visuomotor flexibility is a fresh alternative to the standard account in which flexibility lives entirely in time-varying activity on a single map.

Weaknesses:

The two claims here are not of the same strength. The first claim that RF and MF angles are organized as mosaics at distinct spatial scales was well supported. The second claim that a moiré interference pattern is the substrate for visuomotor flexibility was an inference rather than a direct observation, and several features of the design contribute to how strongly it can be held.

First, the recordings were one-dimensional. Each oblique penetration yielded a line through the cortex, so the two-dimensional moiré pattern (Figure 4A) existed only in simulations; it was not reconstructed from the data. What the data provided was the marginal distribution of local angular differences, and the model was accepted when its simulated distribution was statistically indistinguishable from the empirical one. Matching a low-dimensional summary statistic is necessary but not strongly sufficient - multiple underlying architectures could produce similar 1-D difference distributions - so the moiré interpretation is best read as a plausible and parsimonious interpretation of the data rather than a confirmed mechanism.

Second, the inferential logic needs to be strengthened. The "preferred" spatial frequencies were those at which a two-sample Kolmogorov-Smirnov test fails to reject equality between model and data. Failure to reject is not confirmation, and the width of the accepted band depends on statistical power, which depends on sample size. The authors did show that most parameter combinations were rejected, so the test did discriminate. That said, a continuous goodness-of-fit landscape with confidence intervals on the preferred SF, and a direct test that the visual and saccade preferred SFs differ, would better support the "distinct spatial scales" claim than visual inspection of two overlapping troughs.

Third, the dataset was from two male marmosets, with 18 of 39 sites contributing to the core analyses, and the angular-difference distributions were pooled across penetrations and animals. This is standard for primate electrophysiology, but it means the spatial statistics were assumed stationary across the region, and individual variability in map layout was averaged over. The oblique-penetration geometry also added some uncertainty: the spatial-frequency estimates (in cycles/mm) are only as accurate as the reconstructed penetration angles (18.2{degree sign} {plus minus} 8.3{degree sign}), and angle error would propagate directly into the inferred scales.

Fourth, while the authors suggested the moiré interference pattern can serve flexible routing for behaviours such as anti-saccades, this was not directly tested. Instead, they used free viewing and natural saccades, so the paper demonstrated a candidate substrate without testing whether behaviour employs it. This does not undercut the main findings, but readers should treat the functional narrative in the introduction and discussion as a set of predictions rather than results.

Reviewer #1 (Public review):

Summary:

The authors wanted to better understand how the various septin-associated kinases contribute to septin organization and function in budding yeast. This question has been recently addressed by similar kinds of studies but there are still some open questions, particularly as regards to what extent the kinases may interact with and/or modify components of the contractile ring that drives cytokinesis.

Strengths:

This study uses sensitive imaging with good temporal and spatial resolution to monitor the localization of various proteins in living cells. Particularly informative is the use of a GFP/GFP-binding-protein "tethering" approach to ask if the requirement for one protein can be bypassed by physically tethering another protein to a third protein. Results from a yeast two-hybrid assay for measuring protein-protein interactions in vivo are buttressed by direct in vitro binding assays using purified proteins, which is important given the likelihood of "bridging" interactions between yeast proteins in the two-hybrid approach. The authors' conclusions are quite well supported by the data.

Weakness:

Ultimately, while the study provides some interesting and novel insights, we still don't understand which phosphorylation events on which proteins are important for the events occurring at the molecular level, so the advance in knowledge is somewhat incremental.

Reviewer #2 (Public review):

Summary and strengths:

In this study, Bhojappa et al. investigate the roles of the septin-associated kinases Elm1, Gin4, Hsl1, and Kcc4 in septin organization and cytokinesis in budding yeast. Through quantitative analyses of kinase localization dynamics, septin organization, actomyosin ring (AMR) constriction, and cell morphology, the authors demonstrate that Elm1 and Gin4 play particularly important roles in maintaining proper septin architecture and cytokinetic progression. The work further identifies an interaction between the Gin4 KA1 domain and the Hof1 F-BAR domain and provides evidence that several cytokinesis-related functions of Gin4 are independent of its kinase activity. Artificial tethering approaches further supports that spatial organization at the bud neck is critical for the execution of septin-dependent cytokinetic processes. The authors combine live-cell imaging, quantitative analyses, biochemical interaction assays, and genetic perturbations to build a comprehensive framework for understanding how these kinases contribute to cytokinesis.

Comments on revised version:

The revised manuscript has been substantially improved. The authors have carefully addressed the concerns raised during review by providing additional experiments, analyses, quantifications, clarifications, and improved presentation of the data. The conclusions are now well supported by the experimental evidence. The study advances our understanding of the mechanisms linking septin organization to cytokinesis and will be of interest to researchers studying septins, cell division, and cytoskeletal regulation.

Overall Assessment:

This work provides valuable mechanistic insight into the coordination of septin organization and cytokinesis by septin-associated kinases. The experiments are carefully executed, the analyses are thorough, and the conclusions are supported by the data presented. The manuscript represents a useful contribution to the fields of cytokinesis and septin biology.

Reviewer #3 (Public review):

Summary:

The study by Bhojappa et al. brings new and interesting elements about the stability of the septin ring and the crosstalk between septin and actomyosin ring assemblies. The study focuses on the four kinases associated with the septin ring, Elm1p, Gin4p, Hsl1p and Kcc4p. Elm1 and Gin4 show the strong knock-out phenotypes, whereas Hsl1p and Kcc4p show the weak knock-out phenotypes. The Elm1p/Kccp1p and Gin4p/Hsl1p pairs show similar timing at the bud neck. While these kinases share redundant functions, Gin4 appears to have a unique interaction with the BAR domain protein Hof1, revealing a novel direct interaction between the septin and actomyosin rings. Interestingly, the kinase activity of Gin4 is not required for its role in septin organisation and AMR constriction. The last part of the manuscript shows an original protein tethering protocol used to show that Hsl1 and its membrane binding ability are required for phenotype rescue of gin4null cells.

Comments on revised version:

I thank the authors for their thorough and thoughtful response to my review. The revised manuscript clearly reflects their efforts to provide rigorous and high-quality science. Addressing the concerns raised in the review required significant effort, but the improvements in the manuscript make it clear that the work was well worth it.

Reviewer #1 (Public review):

Summary:

The extent P. falciparum liver stage parasites export proteins into the host cell is unclear. Most blood stage exported proteins tested in liver stages were not exported. An exception is LISP2 that is exported in P. berghei but not P. falciparum liver stages. While the machinery for export is present in liver stages, efforts to demonstrate export have so far been mostly unsuccessful. Parasite proteins exported during the liver stage could be presented by MHC and thereby become the target of immune control, incentive to study liver stage export and identify proteins exported during this stage. However, particularly for P. falciparum it is very difficult to study liver stages.

This work studies LSA3 in P. falciparum blood and liver stages. The authors show that this protein is exported into the host cell in blood stages but in liver stages no or only very little export was detected. A disruption of LSA3 reduced liver stage load in a humanized mouse model, indicating this protein contributes to efficient development of the parasites in the liver.

The paper also studied the localization of LSA3 in blood stages and used a known inhibitor to show that it is processed by plasmepsin 5, a protease important for protein trafficking. The work also showed that LSA3 is not needed for passage through the mosquito.

Strengths:

The main strength of this work is the use of the humanized mouse model to study liver stages of P. falciparum, which is technically challenging and requires specialized facilities. The biochemical analysis of LSA3 localization and processing by plasmepsin 5 are thorough and mostly overcame adverse issues such as a cross-reactive antibody and negative influence of the GFP-tag on LSA3 trafficking. The mosquito stage analysis is also notable as these kinds of studies are difficult with P. falciparum. However, there was no evidence for a function of LSA3 in mosquito stages.

Weakness:

The cross-reactivity of the antibody together with the co-infection strategy prevents reliable assessment of LSA3 localization in liver stages. Despite of this it seems LSA3 is not exported in liver stages and the paper does not bring us closer to the original goal of finding an exported liver stage protein.

While the localization analysis in blood stages is well done and thorough, the advance is somewhat limited. LSA3 may be in structures like J dots, but this hypothesis was not tested. Although parasites with a disrupted LSA3 were generated, the function of this protein was not explored. However, this was now done in a separate study focussing on blood stage parasites (PMID: 41135800).

Due to the difficulty of working with humanised mice, it was not possible to refine some of the conclusions and questions remain:<br /> The impact on liver stage development is interesting, but which phase of the liver stage is affected, and the phenotype remain largely unknown. The co-infection used (WT together with LSA3 mutant) has the advantage of a direct comparison of the mutant with the control in the same liver but complicates phenotypic analysis if the LSA3 antibody is also cross-reactive in liver stages. This issue adds a question mark to the shown localization and precludes phenotypic comparisons. It was also not possible to determine if the cross-reactive protein is expressed at that stage. While this might have been evident from the mixed WT/mutant infection (if all cells are positive for LSA3 there is cross-reaction; if about half of the cells are negative, there isn't) but assessing this failed.

Significance:

It is important information that LSA3 contributes to efficient liver stage development. However, neither LISP2 nor LSA3 seem to be exported in P. falciparum liver stages and can't confirm the potential of vaccines with proteins exported in this stage. LSA3 is still important and may still be the target of the immune response, but based on this work, probably not due to export in liver stages.

Reviewer #2 (Public review):

Summary:

Immunogenic Plasmodium falciparum proteins that could be targeted to prevent parasite development in the liver are of significant interest for novel anti-malarial vaccine development. In this study, McConville et al evaluate the trafficking and functional importance of LSA3, a protein expressed in the blood and liver stages and previously shown to provide protection in immunized chimpanzees. LSA3 contains a PEXEL motif but the authors have previously shown that this protein does not appear to be exported beyond the PVM in the liver stage (McConville et al PNAS 2024). However, LSA3 trafficking and functional importance have not been comprehensively evaluated across stages. In the present study, the authors find that blood-stage LSA3 undergoes PEXEL processing and a portion of the protein is exported into the erythrocyte where it localizes to punctate structures distinct from Maurer's clefts. Using a knockout mutant, LSA3 is shown to be dispensable for blood and mosquito stages but important to liver-stage development. Collectively, these results validate LSA3 as a liver-stage target and place it among several other PEXEL proteins that display differential trafficking beyond the PVM in the erythrocyte but not the hepatocyte.

Strengths:

(1) The authors present a thorough analysis of LSA3 trafficking in the blood stage. PEXEL processing by Plasmepesin 5 is clearly demonstrated through a combination of mini LSA3-GFP reporters and Plasmepsin 5 inhibitors. Importantly, an LSA3 knockout mutant is used to show that the LSA3-C anti-sera also reacts with additional, unidentified parasite proteins in the blood stage. Nonetheless, comparison between the WT and KO parasites clearly indicates that a portion of LSA3 is exported into the erythrocyte, which is further supported by protease-protection assays with fractionated iRBCs. This contrasts with the liver stage where LSA3 does not appear to traffic beyond the PVM, similar to what has been observed for other PEXEL proteins in the rodent malaria model.

(2) This study provides the first analysis of LSA3 exoerythrocytic function, showing this protein is important for liver stage development in chimeric human liver mice. Several PEXEL proteins in P. berghei have been shown to be exported into the host cell in the blood stage but do not appear to cross the PVM in the liver stage. These observations reinforce that even without detectible export into the hepatocyte, PEXEL proteins play critical roles during liver stage development.

Weaknesses:

The authors previously reported that anti-LSA3-C signal in the liver stage localizes within the parasite and at the parasite periphery but is not exported into the hepatocyte. In the present study, it is shown that anti-LSA3-C reacts with other parasite proteins beyond LSA3 in the blood stage and this may also occur in the liver stage. However, since liver-stage IFAs were only performed on samples co-infected with both WT and ∆LSA3 parasites, non-specific anti-LSA3-C reactivity at this stage could not be determined and the localization of LSA3 in the liver stage remains somewhat unclear.

Comment on revisions:

The authors thoughtfully addressed the reviewer comments.

Reviewer #3 (Public review):

Summary:

This manuscript provides a comprehensive characterization of the Plasmodium falciparum protein LSA3, combining biochemical, genetic, and in vivo approaches. The authors convincingly demonstrate that LSA3 is expressed during liver stage infection and that disruption of the gene leads to a modest but reproducible reduction in liver stage parasite load in humanized mice.

Strengths:

Their biochemical and cell biological analysis of blood stages provides strong evidence that LSA3 is exported to the infected erythrocyte, and the detailed analysis of its PEXEL motif processing is well executed.

Weaknesses:

The study suggests LSA3 as one of only two known P. falciparum PEXEL proteins contributing to this stage, although there is no evidence for the export beyond the vacuolar membrane. Several key conclusions, particularly regarding antibody specificity, localization in liver stage parasites, and the interpretation of the phenotypic data, are not fully supported by the current experiments.

Comments on revised version.

I appreciate the authors' efforts to revise the manuscript and to clarify several aspects of the study.

However, I remain concerned that some conclusions extend beyond the data presented. In particular, the authors acknowledge in their rebuttal letter that antibody specificity in liver stages could not be validated and that cross-reactivity cannot be excluded. Consequently, the localization data shown in Figure 5 cannot currently be considered definitive evidence for liver stage localization of LSA3 itself.

Similarly, the revised manuscript appropriately states that LSA3 was not detected beyond the PVM in liver stages and that export into the hepatocyte remains unresolved. Nevertheless, several statements continue to imply a role for liver stage protein export. At present, the possibility that a domain of LSA3 may face the host-cell side of the PVM remains speculative and is not supported by direct experimental evidence.

The liver stage fitness phenotype is convincing and supports the conclusion that LSA3 contributes to normal liver stage development. However, the current data do not establish the developmental process affected nor connect the phenotype to export beyond the PVM.

I therefore recommend that the manuscript consistently distinguish between (i) demonstrated export of LSA3 during blood stage infection and (ii) the unresolved localization and trafficking of LSA3 during liver stage infection. I would also encourage the authors to consider revising the title to better reflect the findings presented, as the current title may be interpreted as demonstrating liver stage export, which has not been shown.

Reviewer #1 (Public review):

Summary:

The study by Wang et al. investigates cardiac electromechanical modeling and simulation techniques, focusing on the calibration and validation of ventricular models according to ASME V&V40 standards. The researchers aim to calibrate model parameters to align with key biomarkers such as QRS duration and left ventricular ejection fraction and validate the model against independent measurements such as displacement and strain metrics. The authors also examine the impact of parameter variations on deformation, ejection fraction, strains and other biomarkers. The overarching aim of the study is to give credibility to the underlying computational electromechanics framework as a step towards the cardiac Digital Twin vision.

Strengths:

(1) The study presents a solid validation strategy for cardiac models based on independent data.

(2) It integrates electrophysiological, mechanical, and hemodynamic biomarkers for sensitivity analysis and calibration.

Weaknesses and Limitations:

(1) Model Assumptions: The study relies on several simplified modeling assumptions that do not reflect the current state-of-the-art:

a) Isotropic scaling of the ventricular mesh to generate an unloaded reference geometry.

b) Simplified afterload and preload models that do not consistently capture the full range of physiological responses.

c) Simplified epicardial boundary conditions.

These limitations are appropriately acknowledged and discussed by the authors in a dedicated Limitations section.

(2) Numerical Framework:

a) The numerical framework used for the mechanical part of the model may be susceptible to locking effects that could contribute to artificially stiff and less contractile behavior. This is indicated by a ten-fold scaling of the peak active contractile force parameter relative to literature values and notable sensitivity of the model to the tissue compressibility parameter. While - as acknowledged by the authors - part of this can be attributed to simplified modeling choices, other comparable studies have not reported similar issues.

b) The human electrophysiology model is not described in enough detail. Currently, it is not mentioned in the manuscript that an Eikonal model was used to compute activation times on the endocardial surface to be robust against coarse mesh resolutions.

(3) Geometrical model and digital twin: The model presented combines anatomical data, electrical measurements, and physiological reference values from different individuals or population averages, rather than being derived from a single patient. The authors have appropriately moderated their claims in the revision, framing the work as a step towards the cardiac Digital Twin vision rather than asserting that the model itself constitutes a digital twin.

(4) Calibration procedure: The description of the calibration procedure has been substantially improved in the revision. The authors now provide explicit rationale for each calibration step and clarify that the procedure targets multiple physiological biomarkers in sequence. Verification that the calibrated model produces physiological cellular dynamics, including intracellular calcium transients, is now provided. The revised manuscript also shows the simulated electrocardiogram alongside population reference ranges, which partially addresses the question of calibration quality. However, a direct comparison of the simulated electrocardiogram with the individual measured signal used for calibration is not provided, which would give a more stringent and direct assessment of how well that specific calibration target was achieved.

Comments on revised version.

The revision represents a genuine improvement. The calibration procedure is now more transparently described, physiological cellular dynamics are verified, the digital twin framing has been appropriately moderated to reflect a step towards that vision rather than a claim of having achieved it, and an expanded limitations section identifies where the framework falls short.

Several of the concerns raised in the first round have been addressed, but some issues remain:<br /> The model still requires a ten-fold scaling of the peak active contractile force relative to literature values, and the imbalance between left and right ventricular output persists, along with non-physiological right ventricular pressures and ejection fraction. These are partly fundamental limitations of the current modelling approach that may not be fully resolvable within the scope of this paper, and the authors are to be credited for acknowledging them. However, they do constrain the conclusions that can be drawn about the credibility of the framework for reproducing healthy cardiac physiology.

The population-averaged reference dataset and the calibration and validation framework remain contributions of value to the community, and the revised limitations section adds useful transparency about the current state of the art.

Reviewer #2 (Public review):

The authors present an interesting study on calibrating and validating a biventricular cardiac electromechanical model. This is an important contribution, but some questions remain about the quantitative validation and verification aspects of the study.

Major comments:

(1) The title and paper stress the importance of validation on several occasions. However, the actual validation performed is limited to the section in lines 427-439. Furthermore, it is entirely qualitative, making assessing the model's quality difficult. Most of the paper is focused on sensitivity analysis, which is also interesting but unrelated to validation. Can you include a quantitative comparison with deformation biomarkers? E.g., spatially quantify strain differences between simulation and in vivo data, or overlay the current configuration of the geometry with MRI in various views, and calculate a displacement error norm.

(2) You mention the ASME V&V40 standards throughout your paper. Yet, you only address the "second V" validation, ignoring the "first V" verification. How did you ensure that your computational models are implemented correctly?

(3) All parameters discussed in this publication are physical parameters. What is the sensitivity of your model outputs concerning computational parameters?

Comments on revised version.

The authors have addressed my prior comments

Reviewer #1 (Public review):

Wang et al., recorded concurrent EEG-fMRI in 107 participants during nocturnal NREM sleep to investigate brain activity and connectivity related to slow oscillations (SO), sleep spindles, and in particular their co-occurrence. The authors found SO-spindle coupling to be correlated with increased thalamic and hippocampal activity, and with increased functional connectivity from the hippocampus to the thalamus and from the thalamus to the neocortex, especially the medial prefrontal cortex (mPFC). They concluded the brain-wide activation pattern to resemble episodic memory processing, but to be dissociated from task-related processing and suggest that the thalamus plays a crucial role in coordinating the hippocampal-cortical dialogue during sleep.

The paper offers an impressively large and highly valuable dataset that provides the opportunity for gaining important new insights into the network substrate involved in SOs, spindles, and their coupling.

Comments on latest version:

The authors have substantially revised their manuscript and sufficiently addressed all of my previous concerns. I have no further comments.

Reviewer #1 (Public review):

Summary:

The manuscript titled "Petabase-scale papillomavirus discovery" capitalizes on Logan assemblages to identify novel and known PVs.

This is a brilliant use of Logan assemblages, and this paper highlights the use of this, plus also shows that one person's trash is another one's gold. Superb paper and I applaud the authors for starting with the PVs as easier to identify due to their set of genes coupled with the conserved L1 protein and associated typing for PVs (10% pairwise identity threshold for identification of new PV types).

Strengths:

This study highlights the hidden gems in public resources, especially if mined properly. Thanks to Logan assemblages, this is possible, and this manuscript highlights this with their data mining of papillomaviruses, identifying known and novel PVs in pangolins, lizards, fish, and white rhinos.

Weaknesses:

None identified

Reviewer #2 (Public review):

This study applies the Logan assemblage of the Sequence Read Archive to investigate papillomavirus diversity at a large scale. The authors combine sequence similarity searches, phylogenetic analyses, protein annotation, structural comparisons, and metadata integration to identify and characterize novel papillomavirus sequences. Beyond papillomavirus sequence discovery, the study develops a framework for associating viral sequences with host, geographic, and ecological metadata through the integration of both established and recently developed large-scale public sequence repositories. This framework may provide a foundation for similar investigations across other viral taxa.

An important aspect of the work is the systematic processing and integration of metadata across a large number of sequencing libraries. The approaches developed to aggregate, curate, and interpret host and environmental information may be broadly applicable to future large-scale studies of other viral families. At the same time, interpretations based on metadata-derived ecological and host-association patterns should be considered in the context of the inherent limitations of public sequencing repositories, including uneven taxonomic representation, heterogeneous sampling strategies, laboratory-derived samples, and variable sequencing protocols. The comments below primarily address methodological details, interpretation of ecological patterns, and opportunities to further strengthen the robustness of the analyses and conclusions.

Pages 136-137: The manuscript focuses primarily on L1-containing contigs. Could the authors provide a summary of libraries containing other PV hallmark genes (e.g., E1 or E2) but lacking full-length L1 sequences? This would help assess how much additional PV diversity may remain inaccessible under an L1-centered framework. Furthermore, the manuscript does not provide a detailed discussion of technical or biological explanations for libraries with detected PV sequences but lacking L1 sequences. Could such cases represent incomplete assemblies, low-abundance infections, highly divergent PVs, or endogenous papillomavirus-derived elements? Clarifying these possibilities would help readers interpret the biological significance of these detections.

Page 141: The rationale for performing the search in two sequential Logan releases is unclear. Does Logan v1.1 fully supersede v1.0? If so, why was the initial search performed on v1.0 rather than directly on v1.1? Providing a clearer description of the differences between the two database versions and explaining how these differences motivated the two-round search strategy would improve reproducibility.

The data could have been explored at the libraries' read level. The analysis is currently limited to presence/absence and diversity patterns derived from assembled PV contigs. However, the identified PV-positive libraries provide an opportunity to explore abundance-related metrics. Read counts, coverage estimates, or other measures of sequence representation could be used to characterize PV abundance within libraries, providing additional ecological context and helping distinguish low-level incidental detections from strongly represented infections. In addition, the curated PV sequence dataset generated in this study could serve as a reference for targeted read-mapping analyses. Aligning reads from a subset of libraries classified as PV-negative may help determine whether PV sequences are present below assembly detection thresholds. Such an analysis could provide valuable insights into the sensitivity of assembly-based virus discovery approaches and help establish practical coverage or read-count thresholds for detecting low-abundance papillomaviruses. These results could have important implications for future surveillance, clinical, and environmental studies aimed at PV detection.

Pages 155-156: Clustering was performed using sequence identity, while host, geographic, and ecological annotations were assigned from representative centroids. How frequently did clusters contain sequences associated with conflicting metadata (e.g., distinct hosts or geographic regions), and how were such cases handled?

Page 160: The authors state that the 70% query coverage threshold was selected based on an observed bimodal distribution. Could this analysis be shown explicitly (e.g., in a supplementary figure), and could the authors discuss how sensitive the number of novel PV calls could have been to alternative coverage thresholds?

Pages 167-168: The rationale for clustering highly divergent sequences at 60% nucleotide identity should be explained. Is this threshold associated with established genus-level classifications in this viral family, or was it chosen empirically?

Pages 167-168: For the 45 sequences lacking nucleotide-level matches, did the authors investigate amino-acid similarity to known PV L1 proteins? Such analyses would help determine whether these sequences represent deeply divergent PVs or potentially more distant viral lineages.

Pages 181-183: The biological interpretation of host-associated PV diversity may depend on library type. Could the authors summarize the proportion of samples originating from field collections, laboratory animals, cell culture systems, or experimental infections?

Pages 243-248: Could the observed geographic and ecological patterns be influenced by laboratory-derived samples? Distinguishing field-collected samples from laboratory, captive, or experimental material would strengthen the ecological interpretations.

Pages 254-261: The biome analyses focus on PV occurrence. An analysis of host composition across biomes would be highly informative and could help disentangle whether observed patterns reflect PV ecology or underlying host distributions.

Page 294: Statements regarding structural similarity appear to rely primarily on visual comparisons. Could the authors provide quantitative structural alignment metrics (e.g., RMSD, TM-score, DALI score, Foldseek score) to support these conclusions?

Page 321-324: Given the scale and curation of the dataset, the final case-study section is limited. Broader comparative analyses of gene content, ORF architecture, and composition related to host associations, phylogenetic relationships, and/or ecological variables could provide additional evolutionary insights beyond a small number of illustrative examples.

Page 333: Given the emphasis on the feasibility of petabase-scale sequence mining, the manuscript would benefit from a more detailed description of the computational resources required. The reported ~10-hour runtime is difficult to interpret without information regarding hardware specifications, CPU-hours, memory requirements, storage footprint, and cloud infrastructure (if used). Such information is important for evaluating the reproducibility and practical applicability of the approach.

Pages 408-409: Were metadata available regarding viral enrichment procedures, particle purification, or size-selection protocols? Such information could influence the interpretation of PV detection frequencies across library types.

Pages 415-416: The differentiation between viral and endogenous viral sequences is one of the biggest challenges in viral metagenomics and large-scale data mining for viral sequences. This issue is particularly relevant because the distinction between exogenous and endogenous viral sequences may directly affect estimates of novel PV diversity and inferred host associations. The manuscript acknowledges that papillomavirus sequences recovered from DNA-based libraries may derive from integrated viral DNA. However, there is no systematic analysis addressing the potential contribution of endogenous papillomavirus elements (EVEs) to the reported diversity estimates. Given the large number of host genome sequencing projects represented in the SRA, some detected PV-like sequences may correspond to integrated or fossil viral sequences rather than exogenous viruses. The authors could discuss this possibility more explicitly and provide analyses evaluating the prevalence of integration signatures, disrupted ORFs, host-genome flanking regions, or other indicators that would help distinguish endogenous viral elements from actively circulating PVs.

Pages 532-533: The study is described as "petabase-scale"; however, the analyses were performed on a pre-assembled and compressed representation of the SRA rather than directly on petabase-scale raw sequencing data. The authors may wish to clarify this distinction and explicitly acknowledge that the computational burden is substantially reduced by the Logan framework and, from this perspective of computational power applied, this study is not in the same context as Serratus and Logan.

Perspective comment: One of the strengths of this study is the generation of a highly curated papillomavirus protein dataset spanning a broad range of known and newly identified PV diversity. Given the increasing importance of structure-based homology detection in virology, the authors may wish to discuss the potential of this resource for future structure-guided discovery efforts. Recent studies have shown that protein structure prediction and comparison can reveal extremely distant evolutionary relationships that are undetectable at the sequence level. The curated PV dataset generated here could serve as a valuable reference for searching unannotated proteins from metagenomic "dark matter" datasets for structural homologs or convergent folds related to papillomavirus proteins. Such approaches may help identify highly divergent PV lineages or previously unrecognized viral proteins that retain structural similarity despite extensive sequence divergence.

Reviewer #1 (Public review):

The manuscript by Tang et al. characterizes the expression dynamics and functional roles of aldehyde dehydrogenase 1 activity in uterine physiology. Using a combination of in vivo lineage tracing and cell ablation coupled with organoid culture, the authors propose that Aldh1a1 lineage-marked cells contribute to uterine gland development and epithelial regeneration. The descriptive data will be of interest to reproductive biologists and clinicians and builds on established hypotheses in the field. The manuscript is well written and scientifically sound and the important experimental limitations and interpretation caveats are presented throughout.

The majority of my initial comments have been adequately addressed within the text.

Remaining limitations include:

(1) The impact of tamoxifen injection directly on Aldh1a1 expression in the developing uterus.

(2) It would be beneficial to demonstrate the degree of cell death following diphtheria toxin treatment 24-48 hours after injection in Tam-treated mice at PND 10. It is not clear as to why the 4-day timepoint was selected. Cells expressing the DTR should begin undergoing apoptosis within several hours after treatment.

Reviewer #2 (Public review):

Tang et al. investigated the contribution of Aldh1a1+ cells, as putative stem/progenitor cells, to endometrial development, maintenance during the estrous cycle, and postpartum repair in mouse models. They employed in vitro organoid formation and in vivo lineage tracing models coupled with RNA-seq to test the stem-ness of Aldh1a1+ cells. They found that mouse endometrial cells with high ALDH activity (using the ALDEFLUOR assay) formed more and larger organoids and were enriched for stem/progenitor cell gene signatures. Similar results were shown using endometrial cells from a human patient sample. Epithelial ALDH1A1 expression was shown to be hormonally regulated, becoming more restricted to the glands, a putative epithelial stem cell niche, under estrogen stimulation. Using lineage-tracing initiated postnatally/prepubertally, Aldh1a1+ epithelial cells were shown to expand, contributing to both the luminal and glandular epithelium into adulthood, whereas adult initiation of labeling showed expansion of stromal Aldh1a1+ cells but not epithelial. Postnatal ablation of single-labeled Aldh1a1+ epithelial cells resulted in impaired gland development. Lastly, Aldh1a1-lineage traced cells (adult labeled) were present during postpartum endometrial repair as were epithelial/mesenchymal transitional cells.

Comments on revised version.

In the revised manuscript, comments have largely been addressed and the manuscript is improved. The authors have tempered their inference of the contribution of ALDH1A1+ cells to endometrial regeneration, but the conclusions are still somewhat overstated. However, the overall work provides valuable insight and strengthens the growing body of literature characterizing endometrial stem/progenitor cells and their function.

Reviewer #3 (Public review):

Summary:

Tan et al demonstrated the importance of ALDH-high cells in the epithelial development in the mouse endometrium, and these cells displayed properties of stem cells.

Strengths:

The findings are solid, supported and validated through a combination of technical methods. I appreciated this combined use of mouse and human endometrial cells to strengthen the findings. Genomic results from a single-cell sequencing dataset were informative as they depicted the different stages of the estrus cycle during the regeneration process. Verification with immunostainings with various markers made it convincing for readers to visualize the cell's location, progression, and status at different timepoints. Utilizing human endometrial cells further demonstrated that the phenomenon observed in mice can be translated to humans.

This work will greatly advance the understanding of endometrial regeneration for reproductive biologists.

Comments on revised version.

The authors have answered the questions in the revised manuscript, no further comments.

Reviewer #1 (Public review):

This revised paper investigates how heparan sulfate (HS) engagement functions in the cellular entry of SARS-CoV-2. The authors used a series of microscopy techniques, labeled pseudoviruses and authentic SARS-CoV-2 strains, and cells lacking or expressing HS and/or hACE2 to re-examine the specific stage(s) HS and hACE2 function in the entry process. They suggest that HS mediates SARS-CoV-2 cell-surface attachment and endocytosis, and that hACE2 functions downstream of this to facilitate productive infection. Their results also suggest that SARS-CoV-2 binds clusters of HS molecules projecting 60-410 nm, which act as docking sites for viral attachment. The authors conclude their work establishes a revised entry paradigm in which HS clusters mediate SARS-CoV-2 attachment and endocytosis, with ACE2 acting at some stage downstream. They speculate this idea might apply broadly to other viruses known to engage HS and has translational implications for developing antiviral agents that target HS interactions.

The strengths of the study include the use of multiple high-resolution microscopy modalities, the tracking of labelled viruses, the use of both pseudoviruses and authentic SARS-CoV-2, and use of primary airway cells. While some studies were performed in the revision to address the Reviewer concerns, which improved the paper clarity, others were cursorily addressed, which limit the impact of the studies. Particularly. experiments were not performed to account for TMPRSS2 expression and plasma membrane fusion. Moreover, addition of studies in which hACE2 is expressed in cells genetically lacking HS were not designed. Thus, it the picture remains unclear picture exactly where downstream hACE2 functions and how this might differ given new structural models of TMPRSS2 activation (PMID: 42050172), which occur after ACE2 recognition of spike on the cell surface.

Reviewer #2 (Public review):

In the manuscript by Han et al, the authors assess binding of SARS-CoV-2 to heparan sulfate clusters via advanced light microscopy of viral particles. The authors claim that SARS-CoV-2 spike (on the context of pseudovirus and in authentic virus) engages heparan sulfate clusters on the cell surface which then promotes endocytosis and subsequent infection. The finding that HSPGs are important for SARS-CoV-2 entry in some cell types is well described but the authors here attempt to make the claim that HS represents an alternative "receptor" and that HS engagement is far more important than the field appreciates. The data itself appears of appropriate quality and would be of interest to the field, but the overly generalized conclusions lack adequate experimental support. This significantly diminishes enthusiasm for this manuscript as written. Additional controls would be of great benefit.

Further, it is this reviewers opinion that the findings do not represent a novel paradigm as claimed. HS has been well described for SARS-CoV-2 and other viruses to serve as attachment factors to promote initial virus attachment. A more balanced and nuanced view of their interesting data would be of value.

Major:

The authors need to rigorously define a "receptor." This reviewer would argue that a receptor is a host factor that is necessary and sufficient for active promotion of viral entry (genome release into the cytoplasm) while an attachment factor is a host factor that enhances initial viral attachment/endocytosis but is not necessary nor sufficient. The evidence does NOT implicate HS as a receptor under this definition. This is proven in Fig 1 (and elsewhere) in which ACE2 is absolutely required for viral entry.

The authors should genetically perturb HS biosynthesis in their key assays to demonstrate necessity. HS biosynthesis genes have been shown to be important for SARS-CoV-2 entry into some cells but not others (Huh7.5 cells PMID 33306959 but not in Vero cells PMID 33147444, Calu3 cells 35879413, A549 cells 33574281, and others 36597481. This is inconsistent with the claim that HS is broadly important (beyond the BHK cells overexpressing ACE2 that are used here).

Is targeting HS really a compelling anti-viral strategy? The data show a ~5-fold reduction. The strengths and limitations of HS targeting should be presented in a more balanced discussion. Animal data showing anti-viral activity of PIX is warranted. This would enhance this claim and also provide key evidence of a relevant role for HS in a more physiologic model.

The authors provide inadequate discussion into the fact that these studies rely exclusively on cell lines (which also happen to be TMPRSS2 deficient). The role of proteases in the role of HS should be tested in the cell lines and primary cells used as protease expression is a key determinant of the site of fusion.

An alternative method to disrupt HS (other than PIX) is needed in primary airway cells. A genetic approach would be much more convincing. The authors should also demonstrate whether entry in their primary cell assays are TMPRSS2 vs Cathepsin L dependent (using E64d and camostat for instance) as mentioned above.

Each figure legend should clearly state how many independent experiments and replicates per experiment were performed.

All bar plots should show individual dots (i.e. Fig 1G) to better reveal the variance of each dataset.

Reviewer #1 (Public review):

Summary:

The manuscript examines the factors that restrict the induction of IL-17-producing T cells during Mycobacterium tuberculosis (Mtb) infection. The authors show that neither infectious route, nor duration of infection are responsible. But they do show that mice that lack the Th1-defining transcription factor, a finding consistent with prior reports in the field of immunology. They also show that 2 highly attenuated Mtb mutants in ESX-1 and PDIM, two well-known Mtb virulence factors, do induce IL-17 producing T cells. In contrast, Mtb mutants in mmpl4 are also similarly attenuated, but do not induce IL-17-producing T cells, suggesting that this property is not simply a result of attenuation but due to specific properties of ESX-1 and PDIM-deficient mutants.

Strengths:

(1) It is interesting that mice infected with ESX-1 and PDIM mutants have increased induction of Th17 cells.

(2) Data is solid and convincing throughout.

Weaknesses:

There are two main criticisms:

(1) B6 mice, compared to humans are known to be very Th1 skewed and the Th1 transcription factor T-bet is known to be a strong inhibitor of Th17 responses. Thus, these Th17 inhibitory factors may be stronger in B6 mice than humans, as many humans do make Th17 responses to Mtb infection.

(2) The molecular insights about how Th17 induction is somewhat limited. Tbet induction is known to restrict Th17 development and this is a t cell intrinsic mechanism. In contrast, the IL-23 association revealed seems to be extrinsic to T cells and to act on T cells. It is not clear these factors related to each other in restricting Th17 induction.

Additional points:

(1) The manuscript states, "Under the conditions where Th17s are highly induced, mice infected with either ΔESX-1 or PDIM lacking Mtb, the Il17a-/- mice had ~3-5 fold higher CFU than WT mice (Figures 3F-G). These results indicate that the induction of Th17s is not dependent on the attenuation of Mtb in general, but instead Mtb utilizes ESX-1 and PDIM to suppress the induction of a Th17 response that enhances protection against Mtb infection." One consideration, however, is that ESX-1, PDIM, and mmpl4 mutants all have similarly reduced CFUs in the lung, but have different CFUs in the lung-draining LN where T cell priming occurs? The bacterial burden in the LN may be more important for regulating T-bet, IL-23, and Th17 differentiation, since the LN is where T cell priming occurs, than the CFU in the lung. Perhaps ESX-1 and PDIM mutants have reduced CFU in the LN, but mmpl4 does not. This difference in LN burdens may be the primary driver of Th17 priming, as high avidity interactions are thought to be an important driver of T-bet induction. Thus, without examining the LN, some questions remain regarding the conclusion that the altered Th17 response in the attenuated strains is not due to the attenuation itself. However, I agree the CFU in the LN probably reflects that in the lung, and if so, the author's conclusions would be sound.

(2) Do LN cDC1 and high levels of IL-12 p35 manifest in mice infected with the mmpl4 mutant? Likewise do LN cDC2's express low levels of IL-12 p19 (akin to those infected with WT Mtb). If these observations for ESX-1 and PDIM mutants are mechanistically linked to the increased numbers of Th17 cells, then you would expect mice infected with mmpl4 mutants to be more like those infected with WT Mtb than to those infected with ESX-1 and PDIM mutants. These experiments would help provide more convincing evidence that the identified mechanisms are due specifically to outcomes regarding Th17 induction. However, I agree the author's conclusions are the most likely explanation given the current data.

Reviewer #2 (Public review):

In this manuscript, the authors tackle an important question of why IL-17 production and TH17 responses are lower than expected during Mtb infection. The authors identify an axis of cross-regulation between TH1 and TH17 cells and provide data to support roles for Mtb virulence factors ESX1 and PDIM in promoting TH1 responses and/or suppressing TH17 responses.

Strengths:

The strengths include the significance of the work, the combination of host and Mtb genetic models to dissect the mechanistic basis for regulation of IL-17 production from T cells during infection, and the rigor of the experiments. There are a number of exciting findings from the work, including the cross talk between T cell responses and the impact of ESX1 and PDIM on these responses. It is particularly striking that that IL17a deficient mice partially rescue the attenuation of ESX-1 and PDIM mutants.

Comments on revised version.

The revised manuscript has tempered a lot of the language in the original text to more accurately state (and not overstate) interpretations of the data. The claim that the effect is independent of route of infection seems a little too large of a claim when only two routes were tested (aerosol and intranasal). And although the authors revised the results section to acknowledge the contribution of an IFNg-dependent suppression of IL-17 production from T cells, the abstract has not been updated and still claims that all effects are independent of IFNg.

Reviewer #3 (Public review):

Summary:

The manuscript by Zilinskas et al seeks to understand the mechanisms underlying the ability of Mtb to suppress Th17 differentiation. As Th17 responses are needed for protective immunity against TB, this is an important topic of investigation. They use Mtb mutants that lack eccC1 (from ESX-1 locus) and fadD28 (encoding PDIM) and implicate a Tbet-dependent pathway by which Mtb modulates Th17 differentiation. The mechanism by which ESX-1/PDIM function to impact Th17 differentiation is, however, unclear, which limits the novelty of the results.

Strengths:

Understanding how Mtb limits Th17 differentiation has implications for vaccine development. Comparative study of KO mice and Mtb mutants is a strength.

Weaknesses:

(1) Addressing several questions related to the Tbet KO mouse experiments would strengthen the study. Do the Tbet KO mice have elevated IL-4/5/13 (which has been previously reported in non-TB studies) in addition to IL-17? The lack of Th17 cells in the IFNg KO compared to the Tbet KO may reflect a difference in timing, since only 3-week data are shown; earlier and later time points would provide a better interpretation. The authors do not present any data on neutrophil infiltration in WT vs Tbet KO vs IFNg KO mice. Since IL-17 is known to be important for recruiting neutrophils to the lung, neutrophil data are important for clarifying the mechanism underlying the CFU outcomes.

(2) While IL-23 is important for sustaining IL-17 production, IL-6, TGF-b and/or IL-1β are necessary for Th17 polarization. What were the levels of these cytokines in DCs in the lung? (Fig 5). Additionally, Tbet-deficient DCs exhibit impaired activation of antigen-specific Th1 cells and have reduced IL-12 production. Given the data showing higher IL-17 levels in Tbet KO mice, the authors should provide information on the DC phenotype (IL-23, IL-6 etc) in the Tbet KO experiments.

(3) The mechanism by which ESX-1/PDIM function to impact Th17 differentiation is not clear. While data showing a role for ESX-1 and PDIMs in inhibiting Th17 responses is interesting, there is no insight into the potential mechanism of action. Fig 3 showing reduction in IFNg+ CD4 T cells after infection with eccC1 and fadD28 mutants suggests that this outcome is due to a lower bacterial load relative to WT Mtb at the 3-week time point. Since IFNg is known to suppress IL-17, the higher levels of Th17 cells could be due to the reduction in IFNg due to the attenuated growth of the mutants.

Reviewer #1 (Public review):

Summary:

Animal behavior is continuously influenced by the internal state moment by moment, including emotion primitives as the authors pointed out. Although emotion is a more human-related state, evolutional conservation is undeniable, which can be inferred by the behavioral manifestation. To further elaborate the neuronal mechanisms of emotion primitives, the simplest behavioral parameter related to emotional primitives should be well characterized. In this study, the authors described in detail of wall-following behavior (WAFO) and the total walking distance (TOWA) using flies after subjecting them to various conditions or flies being genetically manipulated according to the previous reports that could affect emotion primitives. Overall, the study is well designed and structured. In addition, the discussion on emotion primitives will be of value to the field.

Strengths:

The strength of this study is its use of a simple behavioral parameter, TOWA, and also a simple design of behavior, WAFO. The importance of the behavioral assay is reproducibility and comparability. In fact, the author demonstrated a summary of comparisons where different treatments result in scalable behavioral changes in WAFO and TOWA.

Conceptual concerns:

My suggestion to strengthen the authors' conclusion that "TOWA can be interpreted as a behavioral proxy for exogenously induced arousal" was to show that an increase in TOWA after stress exposure can be observed in a small (1-cm) arena that acts as an exogenous arousing stimulus, but not in a larger arena (>6.6 cm) where such arousing effects are absent. This comparison would demonstrate that basal locomotor activity measured in larger arenas is not altered by stress, whereas the additional component observed in smaller arenas reflects stress-induced internal state. Therefore, the authors would be able to distinguish clearly the effects of stressors or experiences on either simple locomotion or an emotion-like internal state. Then the future works can follow this protocol using smaller and larger arena to assess emotion-like internal state.

I appreciate the significant authors' efforts to monitor TOWA using arenas with different diameters up to 6 cm. However, the conclusion was unfortunately the same as that obtained using the 1-cm arena. As the authors commented, flies do not show persistent and quantifiable wall-following in arenas larger than 5.8 cm, which limits further examination of this question. I personally agree with the authors' interpretation, but I hope that the authors obtain more definitive experimental contrasts to support this claim in the future study.

Reviewer #2 (Public review):

Summary:

In terms of data, the revised manuscript is by and large the same, though the authors added new experiments examining the effects of the Open Field Test (OFT) arena size (Fig. 1 Supplement 1) and sex and mating status (Fig. 6). The authors have also provided textual revisions, partially addressing my previous major criticism about novelty over the work of Mohammad et al., 2016, Curr Biol. They argue that the main advance is the systematic inclusion of Total Walking (TOWA) data (e.g. Introduction, page 6 top in the tracked changes document). While I am still not convinced that the findings represent a huge leap forward over that previous work, the authors' systematic analysis is very nice and may prove of use to those seeking to develop Drosophila as a model for studying emotion primitives.

Strengths:

The main strength of the paper is the rigorous use of several stressful or aversive treatments and their subsequent removal to show that WAFO is a robust proxy for stress-like emotional primitives across multiple stimuli. The pharmacological, molecular, and neuronal activity manipulations, although more limited in scope, lend further credence to the authors' central claim.

Weaknesses:

The authors have addressed some of my previous points with textual revisions and in their rebuttal. As stated above, the conceptual advance over Mohammad et al. remains in my opinion limited, but I appreciate that this point is now clearly discussed in the manuscript.

Reviewer #1 (Public review):

Summary:

This is an interesting study that addresses whether mitochondrial DNA (mitoDNA) variants impact telomere length (TL), which may be relevant to potential maternal inheritance of TL in offspring. The study addresses this question using a cybrid model approach in which mitochondria from donor platelets from 7 individuals that vary in TL and differ in mitoDNA variants are introduced into 143B cells that lack mitochondria. MitoDNA variants that exhibited reduced complex I activity showed telomere shortening in cybrids and increased telomere dysfunction. Interestingly, these phenotypes could be reduced with NAC antioxidant and NAD+ supplementation, suggesting that ROS and oxidative DNA damage at telomeres contributed to the telomere shortening. They further showed that cybrids with lower levels of ROS correlated with longer TL in the lymphocytes of the mitochondrial donors.

Strengths:

This study provides compelling evidence that mtDNA variants influence TL through a mechanism involving mitochondrial-derived ROS, potentially causing telomeric oxidative damage. The data are robust, and the manuscript is well written. However, the study could be strengthened by addressing the following questions and minor weaknesses below.

Weaknesses:

(1) Introduction. Line 81, the relationship between TL and the risk of lymphoid and myeloid leukemia is not straightforward. POT1 variants associated with long TL increase the risk for lymphoid and myeloproliferative neoplasms (see PMID: 41564438 for example).

(2) Figure 1. Since sex also influences TL, it would be good to know the sex of the selected individuals or explain why this is not necessary.

(3) Please include a description of the 143B cells that were used for cybrid formation in the Results section when introducing the cybrids.

(4) Lines 155-156. The authors note that cybrids from donors 1 and 2 show "pronounced" telomere damage. This result indicates an increase in 53BP1-positive telomeres, which could be indicative of telomere dysfunction or damage. Quantification of the increased chromosome end fusions for cybrids 1 and 2 would strengthen the result. Do the increased fusions correlate with an increase in telomere signal-free ends? These should be apparent in the telomere FISH images of metaphase chromosomes.

(5) Lines 168-169. What is the evidence that the "in vitro metabolic shift" causes acute oxidative stress?

(6) Why did the elevated ROS in cybrid #3 (Figure 4C) not translate to shorter telomeres in the cybrid (Figure 2A)? Perhaps there is a difference between factors that determine TL in the cybrid vs the donor's lymphocytes? In Figure 4B, it appears that the statistical comparisons for mitochondrial superoxide are all relative to Cyb3. If so, why are the comparisons not with the parental 143B rho0 cell line? Please clarify.

(7) Given the heterogeneity in TL and mtDNA variants in the human population, the conclusions could be further strengthened by increasing the number of donors and cybrids analyzed. However, there are admittedly practical factors. Overall, these findings are compelling and provide a solid foundation for expanding this analysis in the future. This is more of a comment than a weakness.

Reviewer #2 (Public review):

Summary:

The authors aim to determine whether mitochondrial genotype influences telomere length. By generating cybrids harboring different mitochondrial backgrounds, the authors seek to establish a mechanistic link between mitochondrial status and telomere biology.

Strengths:

A major strength of the study is the use of cybrid technology, which provides a great approach to investigate the role of mitochondrial DNA independently of the nuclear genome. The authors also employ multiple complementary assays to assess telomere-related phenotypes associated with mitochondrial dysfunction. Together, these experiments generate an interesting dataset that will be of value to researchers interested in the intersection between mitochondrial biology, genome stability, aging, and development. These results also build on previous work supporting roles for ROS/mitochondria in driving telomere shortening.

Weaknesses:

The data support the conclusion that mitochondrial background is associated with differences in telomere length and telomere-related phenotypes. However, some of the mechanistic interpretations would benefit from additional evidence. In particular, the manuscript discusses mitochondrial influences on telomere shortening, yet telomere length in some experiments is assessed at a single time point. Consequently, the current data do not directly address the rate of telomere attrition. Differences observed between cybrid lines could potentially arise from events occurring during cybrid formation, clonal selection, or subsequent cell expansion. Longitudinal analyses across multiple passages, ideally beginning immediately after cybrid generation and controlling for population doublings, would help establish whether mitochondrial function directly affects telomere shortening dynamics. Some experimental results would also benefit from additional quantification, clarification, and some biological replicates are missing.

Overall, this study provides interesting evidence linking mitochondrial background to telomere biology. The cybrid models represent a useful resource for the field, and the work raises important questions regarding mitochondria-telomere communication.

Reviewer #3 (Public review):

Strengths:

Mahieu and colleagues address an interesting and underexplored question: whether non-pathogenic variation in the mitochondrial genome contributes to the inter-individual variability of human telomere length (TL). Using a Belgian Flow-FISH reference cohort (n=491) to identify donors at TL extremes, they generate transmitochondrial cybrids from platelets of seven donors of distinct mtDNA subhaplogroups and characterize the resulting cells with a broad and well-executed toolkit (TRF, TeSLA, ddTRAP, EPR-based mitoROS, Seahorse with permeabilized-cell ETC dissection, LC-MS metabolomics, telomeric PAR-FISH). The most compelling finding is that cybrids derived from donors with low complex I (CI) activity undergo rapid telomere shortening during the glycolysis-to-OXPHOS transition of cybrid formation, and that this is largely prevented by co-treatment with NAC and the NAD⁺ precursor nicotinamide riboside, supporting a model in which CI sustains the NAD⁺ pool required for PARP1-mediated repair of oxidative damage at telomeres. The authors further report an inverse correlation between donor lymphocyte TL and mitoROS in the corresponding cybrids, and provide preliminary evidence that the K1a-defining ATP6 A177T variant (m.G9055>A) may be enriched in long-telomere individuals.

Weaknesses:

(1) Statistical support and donor sampling for the central in vivo correlation (Figure 4C).

The inverse correlation between donor lymphocyte TL and cybrid mitoROS (R²=0.794, p=0.007) is the principal in vivo claim of the paper, but it is built on seven donors deliberately selected from the extremes of the Flow-FISH distribution. Sampling at the tails of the outcome variable can substantially inflate apparent correlation strength and significance. I would encourage the authors to (i) explicitly state this sampling structure where the correlation is introduced, (ii) report a leave-one-out sensitivity analysis to confirm the relationship is not driven by one or two donors (Cyb3 and Cyb6 appear to anchor the line), and (iii) where feasible, extend the analysis to additional donors with intermediate TL to test whether the relationship holds across the full distribution. Even a modest expansion (e.g., 4 to 5 additional donors at P25 to P75) would substantially strengthen this central claim.

(2) Reconciling the cybrid CI / TL relationship (Fig 3B) with the absence of a CI / TL relationship in donor lymphocytes (Figure 4A).

Figure 3B shows a strong correlation between CI activity and TL in cybrids (R²=0.87), while Figure 4A shows no correlation between donor CI activity (measured in the same cybrids) and donor lymphocyte TL. The authors acknowledge this, but the manuscript subsequently builds toward a CI-centric model of in vivo TL regulation, which seems to outrun the data. The most internally consistent interpretation is that the cybrid CI phenotype reports a sensitized in vitro response to the acute oxidative stress of the metabolic shift, rather than a steady-state determinant of leukocyte TL. I would suggest reframing the abstract, significance statement, and Discussion to make this distinction clearer. The in vitro CI / NAD⁺ / PARP1 axis is a strong finding on its own, while the in vivo role of CI activity (as opposed to ROS more broadly) is not yet established here. Donor #1's profile (very long lymphocyte TL, low CI activity, severe shortening in cybrids, no telomere inheritance in offspring) is informative in this regard and could be discussed more directly as a case that helps delineate where the cybrid model does and does not recapitulate in vivo biology.

(3) The K1a / ATP6 A177T inheritance claim.

The proposal that K1a (and specifically ATP6 A177T) contributes to maternal inheritance of long telomeres is intriguing but currently rests on three pedigrees (one of which, donor #1, does not support the hypothesis) and a chi-square test that does not reach significance (p=0.153, Figure 4F). The supporting evidence is also limited by the fact that platelet-mediated mitochondrial transfer delivers donor mitochondrial proteins, lipids, and residual mtRNA in addition to mtDNA, making it difficult to attribute the cybrid phenotype of donor #6 specifically to the ATP6 A177T variant. I would recommend either: (a) extending the genotyping screen to additional unrelated donors and, if feasible, confirming the effect of ATP6 A177T through an isogenic approach (e.g., mtDNA base editing in a clean background), or (b) softening the relevant statements to "suggestive trend warranting larger studies," and presenting the K1a observation as hypothesis-generating rather than supportive. The Ashkenazi-centenarian connection raised in the Discussion is an excellent direction for follow-up and could be framed accordingly.

Reviewer #1 (Public review):

Summary:

The predominant view on CHOP's functions during ER stress is that it promotes cell death. This is in contrast to a handful of reports in the literature that claim that CHOP is a positive regulator of protein synthesis during chronic ER stress, and therefore is part of the adaptation program to ER stress. These previous studies were performed in tissue culture cells. Velarde and co-authors have used a mouse model of induction of mild ER stress to study the function of CHOP in hepatocytes.

Major strengths and weaknesses of the methods and results:

The authors use state-of-the-art mice to manipulate (i) CHOP and (ii) ATF6, a protective factor of ER proteostasis, and address the hepatocyte responses to mild ER stress in vivo and in cultures. Validated gene expression programs are well correlated to liver pathology in the mouse models. This is a very well-done study.

The authors clearly show that CHOP transitions hepatocytes under mild ER stress to a chronic ISR state, which is phenocopied by ATF6-depleted hepatocytes. So the conclusion that CHOP exacerbates ER stress in hepatocytes during mild ER stress is correct. It is also clear that CHOP targets negatively the transcription of hepatocyte identity genes, which opens a new direction of studies on the function of CHOP in secretory cells in general.

Conclusion:

This is a significant study that will benefit different research fields, and specifically studies on proteostasis, as was recently highlighted in Nat. Str. Mol. Biol. by experts in the field.

To this reviewer, the importance of the study is that it links the function of a transcription factor (CHOP) to stress intensity (mild versus severe) in a physiological experimental model (hepatocyte function and pathology).

Reviewer #2 (Public review):

The Unfolded protein response (UPR) and related integrated stress response (ISR) are critical signaling systems for cell survival in response to acute stresses. While the UPR directs critical adaptive gene expression, certain chronic stresses switch this pathway towards cell death and disease. An important question concerns the mechanisms by which the UPR switches from being adaptive to maladaptive. Prevailing models focus on the transcription factor CHOP (DDIT3 or GADD153), whose levels are enhanced via the UPR, and extended/amplified amounts of CHOP are suggested to boost death-related gene expression. However, the literature and this manuscript point out a number of observations that do not neatly fit with this model, suggesting that there are still unresolved processes by which CHOP adjusts cell outcomes via the UPR.

This manuscript features a nice hepatocyte-targeted knockout of CHOP to discern the contribution of CHOP in the transition between adaptive and maladaptive outcomes. The key ideas presented in this study are that CHOP-directed gene expression is focused on protein synthesis, metabolism, and hepatocyte identity. In the progression of the UPR, CHOP expression can lead to resumption of protein synthesis, which can assist in the translation of the UPR-directed transcriptome, which includes ATF6/XBP1-directed genes that aid the processing capacity of the endoplasmic reticulum (ER). However, enhanced nascent protein can further stress the ER. CHOP directs gene expression in both the first phase- acute and second phase-chronic in the UPR, and the pivotal decision lies in the transition between the phases.

Overall, the manuscript includes some new ideas as well as refinements of earlier ones for CHOP-determination of UPR-directed cell fate. The CHOP-hepatocyte knockout mouse model helps to delineate the different tissue functions of CHOP, which has been a problem for some earlier studies. The manuscript progression of experiments is solid, and experimental design and documentation are rigorous. The manuscript text is largely clear, but there are portions that would benefit from fuller explanations of ideas.

There are three points of concern. First, the manuscript model (Figure 7) lays out a timeline for the progression of the UPR between two phases. The study is not always clear about the times assayed, and there appears to be a single time point for measurements. Second, there is emphasis on protein synthesis changes in the model. It is true that the literature argues that resumption of protein synthesis concurrent with stress damage (i.e., GADD34-directed gene expression) is a key reason for the potentially debilitating effects of CHOP (e.g., Marciniak et al 2004, Han et al 2013). However, the manuscript does not feature protein synthesis measurements. Inclusion of bulk protein synthesis measurements in the context of this model system would strengthen the study and support for the model. Finally, for this reviewer, some of the most interesting ideas center on CHOP-directed transcription of genes that regulate hepatocyte identity. There is solid evidence for direct CHOP regulation of these genes, but the manuscript does not really develop and test the ramifications of these networks on cell fate during ER stress.

Reviewer Concerns:

(1) The abstract packs in a lot of information. The ideas would not be clear to a general reader. Furthermore, the UPR and ISR are referred to in the second-to-last sentence, but not defined earlier in the abstract.

(2) There are some typos/grammar concerns.

(3) ATF4 diminished with CHOP-depletion (Figure S2A). What is the mechanism here? Does this complicate the analysis of CHOP-directed gene expression? How does this fit with Figure 6J? The timelines for TM treatment are critical. The authors should more fully explain the time courses in the experiments.

(4) Figures 2 and 3: There is a discussion on enhanced protein synthesis with loss of CHOP (reduced GADD34 expression). What is the time point - 8 hours TM? Emphasize, explain, and justify time points of experiments here and in later panels. It would strengthen the model with direct measurements of protein synthesis. The authors could include GADD34 protein measurements in these panels. Figure 3 - panel D - some abbreviations are not standard.

(5) Figure 4: One of the most interesting in the manuscript is the transcription factors downstream of CHOP that are linked with hepatocyte differentiation and metabolism. The manuscript would be bolstered by developing some of these target genes into the Figure 7 transition model.

(6) Figure 6: The comparison of CHOP and ATF6 target genes is a highlight of the manuscript. The literature on this topic is complex, and there are some suggestions that CHOP can be downstream of ATF6. Furthermore, there were some earlier models by Walter and others about extended induction of Perk (death) vs induction of other UPR sensors (survival) (e.g. PMID: 17991856). It would be helpful in the Discussion to delineate between these models and their critical differences.

Reviewer #3 (Public review):

In this manuscript, the authors aim to understand the function of the transcription factor CHOP, which is known to promote cell death during severe stress in the ER. The authors note that CHOP is induced during less severe stress, but its functional output is not well understood in these cases. Here, they study the effects of conditional knockouts of CHOP in hepatocytes of mice challenged with chemical inducers of ER stress.

Tunicamycin (an ER stress inducer) injection leads to the upregulation of CHOP and lipid accumulation in the liver, but no significant cell death in the experiments outlined here. Conditional knockout of CHOP results in a number of differences in the way hepatocytes respond to stress, notably resulting in lower steatosis.

There are two main findings supported by the data presented here. First, the authors show that CHOP suppresses the expression of ONECUT, a master regulator of hepatocyte differentiation and metabolism, during ER stress. They show by ChIP-seq that CHOP binds to the promoter region of this gene, and by RNA-seq that ONECUT expression is suppressed by ER stress in a CHOP-dependent manner. Many predicted targets of ONECUT1 were also suppressed by ER stress in a CHOP-dependent manner, though they were not bound directly by CHOP. The data support a model where CHOP down-regulates hepatocyte metabolism and identity via regulation of ONECUT1. This is a new and interesting finding, perhaps explaining the steatosis phenotype of livers that accompanies ER stress, although this was not tested directly.

The second main finding of this paper is that CHOP deletion leads to an interesting assortment of effects on genes related to the ER stress response and integrated stress response (ISR). As expected, based on prior work, CHOP deletion led to more phosphorylation of eIF2alpha (CHOP is known to upregulate the phosphatase for this translation factor). However, unexpectedly, this did not cause increased expression of ATF4 (a transcription factor whose upregulation during stress is dependent on eIF2alpha phosphorylation) and its downstream targets; in fact, CHOP deletion had the opposite effect on these. In other words, CHOP seems to both turn off the initiating signal for the ISR (namely, eIF2alpha phosphorylation) and also promote the downstream signaling events that rely on this initiating signal. It makes sense that cells would do this, as restoring translation would be important for realizing the effects of the massive changes in gene expression initiated by ER stress, and yet this would exacerbate stress in the short term, so it would be counterproductive to also turn off the entire stress-regulated program. Having a factor (perhaps CHOP) that coordinates these two events makes sense. It will be interesting in future work to understand the mechanisms behind this regulation.

Finally, CHOP deletion led to less activity of other aspects of the ER stress response, notably IRE1 (determined through measurement of XBP1 splicing and RIDD of Bloc1s1). This is explained by the continued phosphorylation of eIF2alpha in these knockouts, as the continued attenuation of translation would lessen the burden of misfolded proteins in the ER. Somewhat confusingly, the same pattern is not seen in downstream targets of XBP1. Less splicing, coupled with perhaps less translation of the spliced mRNA, should result in less active transcription factor and lower expression of its target genes in the CHOP KO. This is not observed in Figure 2, although the more global gene expression analysis suggests that all stress-dependent gene expression changes were weaker in the CHOP KO livers.

The authors characterize the effects of CHOP, promoting restoration of protein synthesis and the accompanying exacerbation of stress while preserving the signaling that should relieve ER stress, as a switch from an acute to chronic phase of ER stress. This is mirrored in their analysis of ATF6 in a similar series of experiments. Although this is an interesting framework for thinking about the stress response, whether CHOP is the key factor or a supporting actor in regulating this transition will require a better understanding of the mechanisms involved.

Reviewer #1 (Public review):

Summary:

This study aims to reveal the contribution of individual gap junction proteins to the signal transmission and connectivity of living C. elegans animals in a completely non-invasive way through all-optical electrophysiology. The authors achieve this by simultaneous expression of bipoles, an excitatory/inhibitory light-activated actuator and Quasar2, a genetically encoded voltage dye. With this study, the authors extend their previous efforts to leverage the strength of optogenetic neurophysiology and set a new standard in this domain. In addition, they adapted their established methods to perform cell-specific optogenetic voltage clamp and revealed changes in gap junction connectivity. They also find that increasing excitability in innexin mutants is indicative of a reduction in gap-junction connectivity and current leaks.

Strengths:

This is an extremely strong manuscript, a technical feat and tour de force to infer junctional coupling through all-optical electrophysiology. The establishment of the voltage clamp method is powerful and allows researchers to obtain not only tight control over voltage signals but also permits the investigation of gap junction function in response to positive and negative voltage steps in a completely non-invasive fashion. This will be a new paradigm for investigating muscle electrophysiology in future.

Weaknesses:

This is a strong pioneering study, and I found very few technical weaknesses. The correlation quantification is relatively weak to establish connective causality, as a shared upstream input may lead to a similar perceived correlation. This is especially concerning for an average lag time of ~0, and the authors may want to investigate if there is unchanged connectivity in an unc-31 or unc-13 mutant. Conceptually, the local connectivity is scaled to account for behaviour: future studies may wish to perform this method on moving animals, and in specific neuronal populations, where a non-invasive optogenetic voltage clamp method will truly shine.

Reviewer #2 (Public review):

Summary:

This technically sophisticated study combines behavioral analysis, voltage imaging, electrophysiology, and a newly developed cell-specific optogenetic voltage clamp (cOVC) approach to investigate gap-junction (GJ)-mediated coupling in C. elegans body-wall muscle cells. The work explores the coordination of muscle cells and systems physiology and introduces a method with potential utility beyond the nematode system studied.

Strengths:

The main strength of the work is the development and application of the cOVC method. This approach enables minimally invasive in vivo assessment of cell-to-cell electrical coupling in intact animals. This technique represents a meaningful advance over traditional electrophysiological techniques that require dissection or cell isolation.

With respect to the GJ biology and function, the authors support their conclusions by integrating additional independent experimental approaches. Findings from behavioural/locomotion assays, voltage imaging, patch-clamp recordings, and cOVC measurements are generally consistent, particularly for unc-9 mutants, which show reduced synchronization of muscle cells, impaired electrical coupling, and severe locomotor defects.

The gain-of-function experiment using murine Cx36 suggests that more or less electrical coupling can disrupt (normal) locomotion.

Weaknesses:

The main issue of this otherwise excellent manuscript relates to interpretation rather than experimental quality. Throughout the manuscript, increased correlation is often interpreted as evidence of increased electrical coupling. Are correlation, synchrony, and conductance equivalent measures? If not, how would this affect these correlations? Furthermore, could broader action potentials and altered excitability also increase correlation values? This concern could be addressed through a discussion of this limitation.

Similarly, the proposed mechanism that reduced GJ coupling increases excitability through reduced leak currents is plausible but not directly demonstrated. Are alternative explanations, e.g., compensatory changes in ion-channel expression or gap-junction composition, possible? These could also be considered to improve the balance of this work.

The conclusions regarding Cx36 overexpression would also benefit from more cautious wording, as developmental or localization effects have not been excluded.

However, the experimental dataset is very strong. In my opinion, no major additional studies are needed. Direct analysis of compensatory changes in innexin expression or localization could strengthen the interpretation of the proposed mechanism. Overall, the study is of high technical quality, contains a notable methodological advance, and provides important insights into muscle synchronization and GJ biology.

Reviewer #1 (Public review):

Summary:

This is a very interesting and well-done study of the effects of selective lesions to the sensorimotor cortex and the red nucleus on control of upper limb movements. The findings that the red nucleus may subserve recovery of upper limb motor function after cortical lesions in macaques and the different motor functions of different cortical sensorimotor areas are significant findings of considerable interest to sensorimotor neuroscientists, neurologists and neurosurgeons. The methods are mostly excellent, but there are some questions about the use of endothelin lesions in cortical areas and the use of trajectory variability as a marker of movement quality and fine motor control. Furthermore, it is questionable that increased trajectory variability in reaching a target reflects reduced movement quality, reduced ability to independently control muscles, and is a proximal analog of reduced dexterity.

Strengths:

The rationale that rubrospinal projections onto spinal neurons may subserve the good recovery of upper limb movements observed after lesions of sensorimotor cortex is compelling. The methods involving complete lesions of the red nucleus followed by recovery prior to lesions affecting various sensorimotor cortical areas are a strength. The excellent interpretations offered in the Discussion section are also a strength.

Weaknesses:

There are weaknesses in the Methods, including:

(1) no information on dimensions of the cup containing the food reward or types of food rewards,

(2) recording 3D hand movements with a single camera,

(3) cortical endothelin lesions were not very precise,

(4) the use of trajectory variability as a measure of movement quality and reduced ability to independently control muscles.

Some interpretations presented in the Discussion are not well supported. The discussion related to movement quality should be modified to focus on trajectory variability. The suggestion that rubrospinal projections onto motor neurons are apparently irreplaceable is not well justified because one monkey receiving a complete red nucleus lesion showed nearly full recovery of maximum movement speed, while the other monkey did not. The nearly full recovery of one monkey was probably due to new corticospinal connections onto motor neurons, whereas it is possible that the other monkey would have recovered better given more time before the 2nd lesion to cortical areas.

Reviewer #2 (Public review):

Summary:

This study made selective lesions in motor cortical subregions and the magnocellular red nucleus in nine macaque monkeys, and evaluated reaching and grasping movements using maximum speed and trajectory variability. The results suggest that damage to the posterior old primary motor cortex (M1) was mainly associated with reduced maximum speed, whereas damage to the new M1 was mainly associated with increased trajectory variability. Damage to the anterior old M1 did not clearly add further impairment. Lesions of the magnocellular red nucleus (RNm) alone mainly reduced reaching speed, but recovery after subsequent cortical lesions was worse than after cortical lesions alone, suggesting that the rubrospinal pathway may be important for compensation after cortical damage in monkeys. Overall, this is a valuable study that examines differences among M1 subregions using selective lesions in macaques.

Strengths:

(1) This study tackles an important question. It attempts to decompose the diverse upper-limb impairments after stroke into the effects of different primary motor cortex subregions.

(2) Another strength is that the lesions and behavioral impairments were evaluated quantitatively. The use of nine macaque monkeys with different lesion patterns, together with quantitative behavioral evaluation, provides a rare and valuable dataset. The authors also followed recovery using quantitative behavioral measures such as maximum speed and trajectory variability.

(3) The inclusion of RNm lesions is also valuable, as it revisits the classic question raised by Lawrence and Kuypers (1968) of how brainstem descending pathways contribute to recovery after cortical motor damage.

Weaknesses:

(1) The main limitation is that the contribution of each cortical lesion is sometimes interpreted from largely qualitative comparisons. Because the lesion extent was not always limited to the intended region, it is difficult to fully separate the independent contribution of each subregion. Some conclusions are also based on comparisons between a small number of animals. The dataset itself is valuable, and the manuscript would be strengthened by presenting these conclusions more cautiously and explicitly acknowledging this limitation.

(2) Because the behavioral evaluation is quantitative, it would be helpful to show the relationship between lesion size and behavioral impairment more quantitatively. For example, rank correlations between the lesion size of each cortical region and behavioral measures could help readers evaluate whether the type and size of lesion are related to behavioral impairment.

(3) The discussion of area 4s could be further developed. The authors suggest that this region may have a different role, but the specific hypothesis is not fully clear. There has also been skepticism in the previous literature about area 4s, for example, Meyers et al. (1954), and this broader background could be discussed. (Meyers R, Knott JR, Skultety FM, Imler R (1954) On the Question as to the Existence of a "4s" Suppressor Mechanism. Journal of Neurosurgery 11:7-23.)

Reviewer #3 (Public review):

Summary:

In this article, the authors performed targeted lesions in cortical areas involved in forelimb control of rhesus macaques. Using a reaching task with kinematic tracking, they compared kinematic variability (as a proxy for dexterity) and reaching speed (as a proxy for strength) before and after cortical (n=7) and magnocellular red nucleus (RNm) (n=2) lesion. Changes in these movement metrics were related to the location and extent of the lesions, reconstructed from histology. The authors report that lesions with a large component in New M1 had a pronounced effect on kinematic variability, whereas lesions with a large component in posterior Old M1 primarily affected reaching speed. Lesions of the RNm were performed in two animals approximately seven to eight weeks before the cortical lesion. By themselves, RNm lesions produced a significant but small reduction in reach speed. They also magnified the effect of the subsequent cortical lesions.

Strengths:

(1) For non-human primate (NHP) research, this is a large cohort.

(2) The behavioural analyses are clear and precise.

(3) The additional red nucleus lesions in two monkeys provide unique complementary information.

Weaknesses:

(1) Description of injuries. As described and reported in the current result section and figures, readers do not have a clear understanding of the lesion extent and location.

(2) Lack of formal correlative analyses between lesion characteristics and behaviour. Currently, it seems that the conclusions are based on impressions between some aspects of the lesions and precise kinematic measures.

(3) The data will be of interest to a large community of researchers working on brain injury and stroke recovery, as well as cortical motor control. There are, however, some major methodological issues in the current version of the manuscript that prevent a clear evaluation of the findings and potential contribution of the work in the field. These issues need to be addressed to support the conclusions.

Reviewer #1 (Public review):

Summary:

Regional differences in the brain's waste-clearance system may interact with neural activity to influence where amyloid-B accumulates. Using intrathecal GBCA administration to produce "Glymphatic MRI" in 96 subjects, the authors mapped cortical glymphatic influx and clearance and found distinct spatial patterns, with transcriptomic analyses linking better glymphatic function to neuronal cell types (through genes). In a subgroup with resting-state fMRI, regions with stronger resting-state activation generally showed higher contrast clearance, indicating a positive coupling between these processes. Notably, cortical regions where neural activity and glymphatic clearance were mismatched showed greater amyloid-β burden in a separate, publicly available PiB-PET dataset, suggesting that activity-clearance decoupling may contribute to regional vulnerability and neurodegeneration.

Strengths:

This is a rare and valuable dataset. Intrathecal contrast injection in ~100 subjects is quite a remarkable accomplishment alone, but the addition of resting-state fMRI, a correlative PiB cohort, and gene-expression pattern data is impressive.

Weaknesses:

This is a cross-sectional study, and we can't determine whether neural activity drives glymphatic clearance, whether glymphatic dysfunction alters neural activity, or whether both are shaped by a third factor. Language describing "flow", "influx", and "clearance" could be made more specific so the reader can more easily follow the methodological approach.

Reviewer #2 (Public review):

Summary:

In this study, Li et al. investigated the relationships among regional cortical tracer dynamics following intrathecal gadolinium administration, neural activity, and amyloid-β deposition in humans. Using serial MRI acquisitions after intrathecal gadodiamide administration in 96 participants, the authors characterized regional signal enhancement and clearance patterns across the human cortex. They integrated these imaging measures with transcriptomic data (Allen Human Brain Atlas), resting-state fMRI outcomes, and an external amyloid PET dataset. The authors report that regions with more efficient tracer clearance are enriched for genes related to synaptic organization and neuronal cell types, that tracer clearance patterns are in parts spatially coupled to spontaneous neural activity, and that regional mismatch between neural activity and tracer clearance is associated with increased amyloid burden according to the PET dataset.

Strengths:

The study addresses an important and very timely question about the interaction among neural activity, cerebrospinal fluid dynamics (waste clearance), and regional vulnerability to neurodegeneration. Integrating serial post-contrast MRI, transcriptomics, resting-state fMRI, and amyloid imaging is ambitious and conceptually very interesting. The spatial characterization of cortical tracer dynamics is potentially valuable for the field, particularly given the increasing interest in human glymphatic imaging approaches and intrathecal contrast MRI, which provides an opportunity to assess CSF tracer dynamics without confounding tracer signal from the blood. The imaging preprocessing pipeline includes normalization of regional cortical signal intensity to a reference region within each session before calculation of longitudinal percentage change, which helps reduce inter-session variability within individuals for conventional T1-weighted imaging. The transcriptomic analyses linking tracer dynamics to neuronal and synaptic gene expression patterns are also interesting. In addition, the manuscript addresses recent literature on neurovascular coupling, glymphatic function, and amyloid vulnerability.

Weaknesses:

Several issues limit the strength of the conclusions. One concern relates to the interpretation of repeated post-intrathecal contrast MRI measurements as direct indicators of glymphatic influx and clearance. The approach presented by the authors measures regional signal changes following intrathecal gadodiamide administration, but does not directly visualize paravascular flow or establish that the observed signal dynamics specifically reflect glymphatic transport mechanisms. Although it is widely accepted that CSF influx occurs primarily along periarterial spaces as part of the glymphatic system, and the terminology "glymphatic MRI" is increasingly used in the literature, the physiological processes contributing to delayed parenchymal enhancement, including CSF-interstitial exchange mediated by convective bulk flow and/or extracellular diffusion, as well as transient and, in the case of linear gadolinium agents, even long-term tracer retention remain incompletely resolved. Importantly, tracer kinetics may not directly reflect interstitial fluid kinetics, as solute transport may also be influenced by compartmental and extracellular barriers, diffusion constraints, and tissue retention effects. As currently written, several sections of the manuscript appear to overstate what can be directly inferred from the imaging data. This issue may be particularly relevant given the intrathecal use of gadodiamide (Omniscan), a linear gadolinium-based contrast agent with known long-lasting tissue retention due to lower kinetic stability compared to macrocyclic agents. Sustained signal at later imaging time points may therefore not only reflect impaired glymphatic clearance dynamics may also be influenced by tissue retention of contrast material, particularly in the context of neurological disease. In addition, the participant cohort is heterogeneous and includes individuals with neuroinflammatory and neurodegenerative diseases, peripheral neuropathy, and motor neuron disease. Although the authors argue that the spatial tracer patterns are relatively preserved across neurodegenerative groups, this heterogeneity complicates interpretation of imaging data and raises the possibility that disease-related factors and altered tracer-tissue interactions contribute to the observed effects. Thus, the rationale for interpreting a greater tracer signal at 39h as evidence of impaired glymphatic clearance should be explained more carefully, particularly given the highly heterogeneous patient population.

In addition, the analyses linking spontaneous neural activity and tracer clearance are based on a very small rs-fMRI subgroup (n = 15), limiting the generalizability. The interpretation of the "mismatch" analysis also requires caution. The mismatch index was computed from z-scored fALFF and tracer clearance and is subsequently associated with amyloid burden derived from the external PET dataset rather than from the studied participants themselves. Therefore, the observed spatial associations should be interpreted with greater caution rather than as evidence for a direct mechanistic relationship. The cross-sectional nature of the analyses also limits conclusions regarding the directionality and temporal sequence of the relationships between neural activity, tracer dynamics, and amyloid burden. Several statements in the Discussion currently imply stronger causal or biological conclusions than are directly supported by the data.

Despite these limitations, the study presents an interesting dataset and proposes a framework for understanding regional vulnerability to protein accumulation in neurodegeneration. This work hopefully motivates further investigation into the important relationships among neural activity, CSF dynamics, and neurodegeneration in humans.

Reviewer #3 (Public review):

This manuscript addresses an interesting and timely question: whether regional glymphatic clearance in the human cortex is spatially coupled to neural activity and whether a mismatch between activity and clearance may help explain regional vulnerability to amyloid-β deposition. The authors use intrathecal gadolinium-based glymphatic MRI in 96 participants, derive cortical influx and clearance maps, integrate these with Allen Human Brain Atlas transcriptomic data, and then relate regional clearance to resting-state fMRI measures in a smaller subgroup. They further compare the resulting activity-clearance mismatch map with an open-source ¹¹C-PiB amyloid PET dataset. The overall concept is attractive because it attempts to connect glymphatic physiology, neuronal activity, and proteopathy at the regional level of the human brain, an important and understudied area.

The main strength of the study is the use of direct intrathecal contrast-enhanced MRI to generate cortical maps of glymphatic tracer dynamics. This is a technically demanding approach and provides a richer spatial readout than indirect MRI proxies of glymphatic function. The authors show that the cortical tracer signal increases from 4.5 h to 15 h and then decreases by 39 h, allowing them to interpret the early signal as reflecting influx and the persistent signal at 39 h as impaired clearance. They further identify regional patterns, with faster influx in medial prefrontal/insular areas and slower clearance in dorsal prefrontal and parietal surface regions. The analysis is visually clear, and the use of cortical gradients is a useful way to reduce complex regional data into interpretable spatial axes.

The multimodal integration is also interesting. The transcriptomic analysis suggests that regions with faster glymphatic clearance are enriched for synaptic organisation and neuronal activity-related pathways, while regions with slower clearance show enrichment for metabolic and mitochondrial pathways. The cell-type enrichment analysis further implicates excitatory and inhibitory neurons, oligodendrocyte lineage cells, microglia and, to a lesser extent, astrocytes. This provides a plausible biological bridge between regional neural activity and clearance function, and the sensitivity analysis using ReHo in addition to fALFF is a useful robustness check.

However, the manuscript should be more careful in its causal interpretation. The study is cross-sectional and largely correlative in space. The finding that regions with higher spontaneous neural activity tend to show better glymphatic clearance is intriguing, but it does not establish that neural activity drives clearance in these participants. Conversely, it remains possible that better tissue integrity, vascular function, CSF access, cortical geometry, vascular density, or disease composition jointly influence both fMRI measures and tracer clearance. The authors do acknowledge some of these limitations, but the abstract and discussion should more consistently frame the findings as associations rather than evidence of an activity-clearance mechanism in humans.

The most important limitation is the small size of the fMRI subgroup. Although the whole glymphatic MRI cohort includes 96 participants, the key activity-clearance analysis is based on only 15 individuals, including 11 with peripheral neuropathy and 4 with motor neuron disease. This is a very small and clinically heterogeneous sample on which to build a central conclusion about regional neural activity and glymphatic clearance. The authors show that the 39 h PC map in the fMRI subgroup resembles the whole-cohort map, which is helpful, but this does not address whether the fALFF-clearance relationship is robust at the individual level. The paper would be strengthened by reporting subject-level stability, leave-one-out analyses, and whether the association persists after excluding the four motor neuron disease cases.

A second major concern is the interpretation of the amyloid analysis. The ¹¹C-PiB map is derived from an external open-source Alzheimer's disease dataset, not from the same participants who underwent glymphatic MRI and fMRI. Therefore, the association between activity-clearance mismatch and amyloid burden is a spatial correspondence across group-average maps, not an individual-level relationship. This is valuable for hypothesis generation, but should not be presented as evidence that a mismatch in the present cohort predicts amyloid deposition. The authors should clearly state that this analysis tests whether mismatch regions overlap with known amyloid-prone cortical regions, rather than directly linking mismatch to amyloidosis in individual participants.

The definition of "mismatch" also needs clarification. The text defines the mismatch index as the negative absolute difference between z-fALFF and z-39h PC, and states that higher scores indicate greater mismatch. Because the index is negative, values closer to zero would normally indicate a smaller absolute difference rather than a greater mismatch. This should be checked carefully and corrected if necessary. More broadly, because a higher 39 h PC indicates worse clearance, the interpretation of match and mismatch categories is not intuitive. The authors should provide a clearer schematic and ensure that the mathematical definition, biological interpretation and figure labelling are fully aligned.

Several technical confounds require more attention. Intrathecal gadolinium MRI is influenced by CSF dynamics, posture, sleep, circadian timing, renal clearance, age, intracranial pathology, and potentially diagnosis-specific differences. The authors acquired scans at fixed time points and noted that patients slept as usual, but individual sleep duration, sleep quality, posture, and daytime activity were not objectively measured. Given that the central claim concerns glymphatic clearance, these are not minor confounders. The authors should consider adjusting for age, sex, diagnosis, vascular risk factors, and relevant clinical variables where possible, and be more explicit about how heterogeneous disease indications may influence cortical tracer kinetics.

The statistics are generally good. However, many correlations are performed across 400 cortical parcels, which are not independent biological samples. The paper would benefit from clearer separation between participant-level inference and region-level spatial inference. For example, the fALFF-clearance and mismatch-amyloid analyses are regional map correlations, not correlations across individuals. This should be clearly stated throughout. The authors should also report effect sizes and confidence intervals more consistently, and explain how multiple comparisons were controlled across transcriptomic, cell-type, fMRI, ReHo and amyloid analyses.

The transcriptomic analysis is useful but should be presented as indirect. AHBA data come from six post-mortem brains; only the left hemisphere was used, and the donors were healthy and younger than the clinical cohort. Therefore, these data capture intrinsic regional gene-expression patterns rather than disease-state expression in the same individuals. The authors should avoid implying that the transcriptomic findings directly explain glymphatic function in their participants. The current discussion partly acknowledges this, but the framing in the abstract and results could be more cautious.

There are also several points of presentation that should be improved. The manuscript should consistently distinguish glymphatic influx, glymphatic clearance, CSF tracer retention, and waste clearance. A 39 h residual gadolinium signal is a useful proxy for delayed clearance, but it is not the same as direct measurement of amyloid or tau clearance. The language around "waste clearance" and "amyloidosis" should therefore be precise. The authors should also clarity whether "higher clearance" corresponds to lower 39 h PC across all analyses, as this inversion is easy for readers to misinterpret.

Reviewer #2 (Public Review):

The authors present the OpenApePose database constituting a collection of over 70000 ape images which will be important for many applications within primatology and the behavioural sciences. The authors have also rigorously tested the utility of this database in comparison to available Pose image databases for monkeys and humans to clearly demonstrate its solid potential. However, the variation in the database with regards to individuals, background, source/setting is not clearly articulated and would be beneficial information for those wishing to make use of this resource in the future. At present, there is also a lack of clarity as to how this image database can be extrapolated to aid video data analyses which would be highly beneficial as well.

I have two major concerns with regard to the manuscript as it currently stands which I think if addressed would aid the clarity and utility of this database for readers.

(1) Human annotators are mentioned as doing the 16 landmarks manually for all images but there is no assessment of inter-observer reliability or the such. I think something to this end is currently missing, along with how many annotators there were. This will be essential for others to know who may want to use this database in the future.

Relevant to this comment, in your description of the database, a table or such could be included, providing the number of images from each source/setting per species and/or number of individuals. Something to give a brief overview of the variation beyond species. (subspecies would also be of benefit for example).

(2) You mention around line 195 that you used a specific function for splitting up the dataset into training, validation, and test but there is no information given as to whether this was simply random or if an attempt to balance across species, individuals, background/source was made. I would actually think that a balanced approach would be more appropriate/useful here so whether or not this was done, and the reasoning behind that must be justified.

This is especially relevant given that in one test you report balancing across species (for the sample size subsampling procedure).

And another perhaps major concern that I think should also be addressed somewhere is the fact that this is an image database tested on images while the abstract and manuscript mention the importance of pose estimation for video datasets, yet the current manuscript does not provide any clear test of video datasets nor engage with the practicalities associated with using this image-based database for applications to video datasets. Somewhere this needs to be added to clarify its practical utility.

Reviewer #1 (Public Review):

This work provides a new dataset of 71,688 images of different ape species across a variety of environmental and behavioral conditions, along with pose annotations per image. The authors demonstrate the value of their dataset by training pose estimation networks (HRNet-W48) on both their own dataset and other primate datasets (OpenMonkeyPose for monkeys, COCO for humans), ultimately showing that the model trained on their dataset had the best performance (performance measured by PCK and AUC). In addition to their ablation studies where they train pose estimation models with either specific species removed or a certain percentage of the images removed, they provide solid evidence that their large, specialized dataset is uniquely positioned to aid in the task of pose estimation for ape species.

The diversity and size of the dataset make it particularly useful, as it covers a wide range of ape species and poses, making it particularly suitable for training off-the-shelf pose estimation networks or for contributing to the training of a large foundational pose estimation model. In conjunction with new tools focused on extracting behavioral dynamics from pose, this dataset can be especially useful in understanding the basis of ape behaviors using pose.

Since the dataset provided is the first large, public dataset of its kind exclusively for ape species, more details should be provided on how the data were annotated, as well as summaries of the dataset statistics. In addition, the authors should provide the full list of hyperparameters for each model that was used for evaluation (e.g., mmpose config files, textual descriptions of augmentation/optimization parameters).

Overall this work is a terrific contribution to the field and is likely to have a significant impact on both computer vision and animal behavior.

Strengths: - Open source dataset with excellent annotations on the format, as well as example code provided for working with it. - Properties of the dataset are mostly well described. - Comparison to pose estimation models trained on humans vs monkeys, finding that models trained on human data generalized better to apes than the ones trained on monkeys, in accordance with phylogenetic similarity. This provides evidence for an important consideration in the field: how well can we expect pose estimation models to generalize to new species when using data from closely or distantly related ones? - Sample efficiency experiments reflect an important property of pose estimation systems, which indicates how much data would be necessary to generate similar datasets in other species, as well as how much data may be required for fine-tuning these types of models (also characterized via ablation experiments where some species are left out). - The sample efficiency experiments also reveal important insights about scaling properties of different model architectures, finding that HRNet saturates in performance improvements as a function of dataset size sooner than other architectures like CPMs (even though HRNets still perform better overall).

Weaknesses: - More details on training hyperparameters used (preferably full config if trained via mmpose). - Should include dataset datasheet, as described in Gebru et al 2021 (arXiv:1803.09010). - Should include crowdsourced annotation datasheet, as described in Diaz et al 2022 (arXiv:2206.08931). Alternatively, the specific instructions that were provided to Hive/annotators would be highly relevant to convey what annotation protocols were employed here. - Should include model cards, as described in Mitchell et al (arXiv:1810.03993). - It would be useful to include more information on the source of the data as they are collected from many different sites and from many different individuals, some of which may introduce structural biases such as lighting conditions due to geography and time of year. - Is there a reason not to use OKS? This incorporates several factors such as landmark visibility, scale, and landmark type-specific annotation variability as in Ronchi & Perona 2017 (arXiv:1707.05388). The latter (variability) could use the human pose values (for landmarks types that are shared), the least variable keypoint class in humans (eyes) as a conservative estimate of accuracy, or leverage a unique aspect of this work (crowdsourced annotations) which affords the ability to estimate these values empirically. - A reporting of the scales present in the dataset would be useful (e.g., histogram of unnormalized bounding boxes) and would align well with existing pose dataset papers such as MS-COCO (arXiv:1405.0312) which reports the distribution of instance sizes and instance density per image.

Reviewer #1 (Public review):

This rigorous and creative study uses an elegant combination of metabolomics, transcriptomics, and budding yeast molecular genetics to discover that (i) activating AMPK to maintain mitochondrial respiration fuelled by cytosolic Acetyl CoA and (ii) increasing fatty acid synthesis independent of respiration drive independent pathways that increase the fitness of replicatively-aged budding yeast cells, albeit without increasing their lifespan. The reviewers have achieved their aims and the results support their conclusions. This work provides important insight into molecular mechanisms that allow aging without loss of fitness and will be of interest to scientists in the field of aging and metabolism.

Reviewer #2 (Public review):

Summary:

In this study, the authors investigate how cytosolic acetyl-CoA metabolism influences replicative aging in budding yeast. They propose that acetyl-CoA regulates aging through three major pathways: (1) mitochondrial transport to support mitochondrial function, (2) fatty acid synthesis, and (3) global protein acetylation. The data show that AMPK activation promotes mitochondrial import of acetyl-CoA and partially mitigates mitochondrial decline in a subset of aging cells. Furthermore, the engineered A2A strain, which enhances mitochondrial acetyl-CoA utilization while relieving inhibition of fatty acid synthesis, increases the proportion of cells exhibiting a "low senescence" phenotype.

Overall, this is a thoughtful and potentially impactful study that advances our understanding of metabolic control of aging. Addressing the points below, particularly by refining interpretations and, where feasible, incorporating additional analyses, will further strengthen the manuscript and its conclusions.

Strengths:

The study has several notable strengths. It addresses an important question by shifting the focus from lifespan to preservation of late-life fitness, which is highly relevant to aging biology. The work integrates metabolic, genetic, and functional analyses to link cytosolic acetyl-CoA flux with distinct aging outcomes, and the engineering of the A2A strain provides a clear and elegant demonstration of how coordinated pathway modulation can improve cellular fitness.

Comments on revised version.

I am fine with the revisions.

Reviewer #1 (Public review):

Summary:

The authors scrutinized difference in C terminal region variant profiles between Rett syndrome patients and healthy individuals and pinpointed that subtle genetic alternation can cause benign or pathogenic output, which harbors important implication in Rett syndrome diagnosis and proposing therapeutic strategy. This work will be beneficial to clinicians and basic scientists who work on Rett syndrome and carries potential to be applied to other Mendelian rare diseases.

Strengths:

Well-designed genetic and molecular experiments, translating genetic differences into functional and clinical changes. This is a unique study resolving subtle changes in sequences give rise to dramatic phenotypic consequences.

Comments on revised version.

Improvements were made during the revision.

Reviewer #2 (Public review):

Summary:

This study by Guy and Bird and colleagues is a natural follow-up to their 2018 Human Molecular Genetics paper, further clarifying the molecular basis of C-terminal deletions (CTDs) in MECP2 and how they contribute to Rett syndrome. The authors combine human genetic data with well-designed experiments in embryonic stem cells, differentiated neurons, and knock-in mice to explain why some CTD mutations are disease-causing while others are harmless. They show that pathogenic mutations create a specific amino acid motif at the C-terminus, where +2 frameshifts produce a PPX ending that greatly reduces MeCP2 protein levels (likely due to translational stalling) whereas +1 frameshifts generating SPRTX endings are well tolerated.

Strengths:

This is a comprehensive and rigorous study that convincingly pinpoints the molecular mechanism behind CTD pathogenicity, with strong agreement between the cell-based and animal data. The authors also provide a proof of principle that modifying the PPX termination codon can restore MeCP2-CTD protein levels and rescue symptoms in mice. In addition, they demonstrate that adenine base editing can correct this defect in cultured cells and increase MeCP2-CTD protein levels. Overall, this is a well-executed study that provides important mechanistic and translational insight into a clinically important class of MECP2 mutations.

Weaknesses:

The adenine base editing to change the termination codon is shown feasible in generated cell lines, but yet to be shown in vivo in animal models.

Comments on revised version.

The authors have addressed all of my questions and comments.

Reviewer #1 (Public review):

Summary:

This manuscript by Noirot-Gros et. al. presents a herculean effort to map the protein-protein interactome of the c-di-GMP signaling network in Pseudomonas fluorescens (Pf). C-di-GMP, the key driver of biofilm formation in bacteria, is controlled by a highly complex network of synthesis, degradation and effector proteins. Pf is no exception as it encodes dozens of such proteins. The authors use a Yeast Two-Hybrid approach genome-wide screen with 10 diguanylate cyclase (DGC) enzymes as bait to assess protein-protein interactions in this network. The results identify over one hundred such interactions with several different hubs, including c-di-GMP signaling, other signaling systems, membrane proteins, etc. The authors then explore the original bait proteins as well as identify interactors on biofilm formation-related phenotypes and swarming using a high-throughput CRISPRi expression knockdown approach. The amount of data generated is quite impressive. Much of the manuscript uses statistical-based network analysis to group different proteins based on their interactions or impact on phenotypes, which is a high-level analysis that can catalyze further study into this system. The authors chose three specific proteins to assess their impact on cell morphology, DNA repair, and protein localization. Overall, in my view, this is perhaps the best analysis of a c-di-GMP protein-protein interactome, and it provides a multitude of hypotheses to be tested. However, therein lies the weakness of the manuscript in that very few of these hypotheses are actually tested. But such is not the goal of this network analysis type of approach. Overall, I think the work will be highly impactful to those in the c-di-GMP field, and it provides a template for others attempting such analyses of protein-protein interactions.

Strengths:

The manuscript is impressive in the sheer scale of the protein-protein interactions identified, network analysis, and phenotypic analysis of specific proteins in the network. It is an impressive amount of work that could be very useful to the field. It is also statistically rigorous in its analysis of significant interactions or network nodes.

Weaknesses:

The weakness of the manuscript is that, with three exceptions, very few of the hypotheses are actually tested. For example, BifA is shown to be a network hub protein that interacts with many other diguanylate cyclases, and this is hypothesized to be through GGDEF heterodimerization. I appreciate that experimentally testing such a hypothesis is probably another entire manuscript, but some early forays into such ideas could be undertaken using AlphaFold structural modeling of protein-protein interactions compared with GGDEFs that don't form heterodimers. Also, an inherent weakness is that such detailed analyses of a c-di-GMP signaling network, in which each diguanylate cyclase and phosphodiesterase may respond to a unique cue, is that the network identified and the conclusions made are highly specific to the experimental conditions in which the work was done. Therefore, it is unclear how broadly these conclusions (i.e. BifA is the central regulator of c-di-GMP signaling) apply to other conditions. But it is impossible to get around such a limitation, and this work can lead to testing the robustness of the identified network in other environments.

Reviewer #2 (Public review):

Summary:

In this manuscript, Noirot-Gros and coworkers investigated the network of c-di-GMP associated protein complexes in Pseudomonas fluorescens. They did so by using a genome-wide yeast two-hybrid screen, and that was further probed by phenotypic screening that focused on biofilm and motility phenotypes. From this network map, they discovered that the phosphodiesterase DipA interacts with the GGDEF domains of many c-di-GMP-binding proteins.

Strengths:

(1) Broadness of screen led to identification of new interactions: The genome-wide yeast two-hybrid screening approach permitted broad investigation of c-di-GMP-associated protein-protein interactions. These interactions included some previously validated interactions as well as newly discovered interactions.

(2) Complementary experimental validation: The proposed network was experimentally validated, including by using a CRISPRi-based approach in which the expression of genes encoding proteins identified in the network was systematically suppressed, and then the impact on the biofilm and motility phenotypes was assessed.

Weaknesses:

The findings would have been strengthened by further biochemical analysis, but this is likely beyond the scope of the paper.

Reviewer #3 (Public review):

Summary:

In this manuscript, Noirot-Gross et al take an open-ended approach to elucidate the c-diGMP-associated protein complexes in Pseudomonas fluorescens. Starting with 10 cyclic d-GMP putative proteins, they use a combination of genome-wide two-hybrid system followed by CRISPRi-mediated exploration of phenotypes to describe the cyclic di-GMP-associated regulation of biofilm formation, and how it relates to other functions. Overall, this work presents an excellent example of how genome annotations can be further confirmed with the use of integrated functional genomic approaches. Some areas of improvement can be applied to this manuscript to enhance readability and provide a clearer distinction between confirmatory results and new findings, which are provided below:

Strengths:

(1) The authors have explored their findings extensively and provide a comprehensive view of the topic.

(2) The combination of genome-wide explorations of protein-protein interactions with the more focused phenotypic exploration of the interactions found provides a solid framework for the work presented.

Weaknesses:

(1) Overall goal of the work:

While articles that describe open-ended approaches can be comprehensive and descriptive in nature, the authors should have a main overall goal, which can guide the reader through the main and most compelling findings at the end. As written, the overall goal is not clear. The network perspective is interesting, and the focus on biofilm formation appears in the title. Why P. fluorescens? How is cyclic di-GMP-mediated regulation of biofilm formation in P. fluorescens different from P. aeruginosa? Why would it be studied?

(Positive or negative regulation of biofilm formation?)

(2) Abstract:

The abstract is very well written and guides the reader to the DipA as a hub protein in the network. From further reading, the article could clarify whether this finding is confirmatory or novel (does DipA play a similar role in P. aeruginosa?) It would be appropriate to mention the role of DipA in other Pseudomonas species from the beginning, and not only in the discussion session.

(3) Introduction:

The introduction is nicely written. An area of improvement could be giving more attention to protein interactions as relevant to c-di-GMP. The authors could consider an independent paragraph starting with line 84-85 "Protein-protein interactions involving DGCs, PDEs, and target effectors are crucial in establishing localized signalling through the generation of local pools of c-di-GMP", expanding on this particular aspect with an example of localized signal, after explaining that localization could help decipher specific function within the network of DGCs and PDEs. Then go into connecting biofilms with c-di-GMP and protein-protein interactions, using the example of GcbC and LapD.

(4) The rationale of choosing 10 PDEs could be clarified. The nice diagrams shown in the supplementary table could be used as part of Figure 1, so the reader understands why these proteins were used, and what is known about them (for example, add them as Figure 1a).

(5) Figures 1b and 2 convey the same information as in Figure 1a. They could be removed without affecting the understanding of the article.

(6) CRISPRi and Figure 3. Figure 3 shows the methodology of CRICPR phenotypic screening. A diagram showing the CRISPRi system in P. fluorescens could help the non-expert reader. While the choice of 23 proteins related to the emerging hub DipA is clear, the choice of the other 33 genes could be better explained. Are these proteins already related to biofilm formation? Where are they part of the network detected? How about the other 14 SBW25 genes? The authors could clarify the rationale of the choices. Figure 4 could be combined with Figure 3 or moved to the supplementary material.

(7) Figures 5, 6 and 7 represent solid network analysis of the findings. Still, they could be improved in clarity on the main findings. The authors conclude at the end of section 3.2.3 that there are networks that exert a "positive role" and a "negative role". The authors could show that in the figures, explaining what those roles are: more biofilm structural coding genes? positive or negative regulation of biofilm formation?)

Reviewer #1 (Public review):

This manuscript by Hall et al. uses a multi-omic approach to investigate how distinct members of the Mycobacterium tuberculosis complex (MTBC: M. bovis, M. tuberculosis, the attenuated M. bovis BCG vaccine strain, and gamma-irradiated M. bovis) affect bovine alveolar macrophage epigenetic and transcriptional responses after 24 hours. The investigators used RNA-Seq, ATAC-Seq, and ChIP-Seq to assess differential gene expression in each complex type and integrated gene transcription with chromatin accessibility and epigenetic modifications, highlighting key immune response genes/pathways upregulated in response to infection and pathogen-specific host adaptation mechanisms. The analysis also revealed that the most pronounced transcriptional and epigenetic responses were in the M. bovis-infected cells compared with the other complex types. Comparing top genes associated with M. bovis infection of macrophages to a GWAS data set revealed 4 key genes associated with increased susceptibility to infection.

Overall, this is a technically sound manuscript that contains highly interesting and useful data on bovine innate immune responses to different types of Mycobacterium tuberculosis, which are important to the immunology and infectious disease community as well as the livestock industry. However, in its current format, the manuscript presents the data/figures in a way that is not particularly informative (despite the rich data set) and is too descriptive. We also have some general concerns and suggestions listed below.

Reviewer #2 (Public review):

Summary:

In this manuscript, Hall et al. present a rigorous and comprehensive multi-omic comparative analysis investigating how host-adapted and non-host-adapted mycobacteria reconfigure the bovine host immune response. By utilizing RNA-seq, ATAC-seq, and ChIP-seq across four histone marks (H3K4me3, H3K4me1, H3K27ac, and H3K27me3) plus CTCF binding, the authors track the regulatory dynamics of primary bovine alveolar macrophages (bAM) challenged with Mycobacterium bovis (MBO), Mycobacterium tuberculosis (MTU), M. bovis BCG, and gamma-irradiated (killed) M. bovis (IRR).

The study highlights a profound, pathogen-driven epigenomic reprogramming that is largely unique to the host-adapted virulent pathogen (M. bovis). Crucially, the authors integrate these regulatory networks with existing Holstein-Friesian GWAS datasets to prioritize novel candidate genes (ERBB4, LRCH1, MRTFA, and RNPC3) associated with M. bovis infection susceptibility. This work represents a significant advancement in our understanding of host-pathogen interactions and animal resilience to bovine tuberculosis (bTB).

Strengths:

(1) The manuscript addresses a major socioeconomic problem in global livestock agriculture and human zoonotic health. By profiling host-adapted vs. non-host-adapted and live vs. dead bacilli, it provides fundamental insights into mycobacterial virulence mechanisms and evolutionary adaptation.

(2) The multi-omic approach is robustly executed, and the sample size (n=6 for RNA-seq, n=3 for ChIP/ATAC-seq subgroups) is highly appropriate for primary livestock cell cultures.

(3) The inclusion of live virulent, live attenuated, non-host-adapted, and killed strains allows the authors to dissect whether host responses are driven by passive PAMP recognition or active, pathogen-directed virulence factors.

(4) The parallel mapping of four distinct histone marks alongside chromatin accessibility mapping (ATAC-seq) yields a highly refined picture of enhancer and promoter dynamics.

Weaknesses:

(1) The profound transcriptional response of the gamma-irradiated (IRR) M. bovis group (3,320 DEGs vs. 2,312 for MTU) is intriguing but lacks a deep biochemical and functional explanation.

(2) While the paper provides a clear atlas of epigenetic alterations, the underlying mycobacterial effectors driving these specific chromatin alterations remain largely correlative.

Reviewer #3 (Public review):

Summary:

Hall et al. use a multi-omics approach to investigate the responses of bovine alveolar macrophages to Mycobacterium tuberculosis infections and the underlying mechanisms that are shared between bacterial family members. The study is of particular importance for multiple reasons, including the impact of bovine infections on food supply (and resulting economic impacts) as well as the use of bovines as a large animal model to investigate the effects of M. tuberculosis infection. The authors isolated bovine alveolar macrophages and exposed them to infection with M. bovis, M. bovis BCG, irradiated M. bovis, or M. tuberculosis. 24 hours post-infection, samples were analyzed by RNAseq, ChIP-seq, and ATAC-seq to look at alterations in the transcriptome and epigenome. Through fluorescence imaging-based analysis, the authors show equivalent infection (bacterial uptake) in all groups, except for the irradiated M. bovis. Principal component analysis of the transcriptomic data demonstrated strong segregation for the M. bovine-infected cells compared to the other groups, which had some intermixing in the PCA. Among the differentially expressed genes, the cytokine IL36G was significantly upregulated across all four groups. This is significant as this cytokine enhanced autophagy in macrophages and subsequent M. tuberculosis killing activity. To further investigate the transcriptional changes, ChIP-seq and ATACseq were utilized to investigate chromatin changes in the form of differential affinity binding sites (DABS) and differential open chromatin regions (DOCR). TPMRSS2, a protease that plays an important role in multiple types of infections (tuberculosis, COVID, etc.), was found to be a significant DOCR in both the M. bovis and M. tuberculosis challenge groups, conferring enhanced TPMRSS2 expression in both of these groups. Using the integrative approach between all the omics data, the authors found that CD274, which encodes the PD-L1 protein, was upregulated in all four groups. PD-L1 is known to play an immunosuppressive role, and PD-L1+ macrophages have been shown to create "cold" microenvironments that would likely favor the mycobacterium. Lastly, SNP analysis found variants in four genes (ERBB4, LRCH1, MRTFA, RNPC3) that could serve as susceptibility genes.

Strengths:

Overall, this study demonstrates that challenge with M. bovis elicits a more extensive remodeling of chromatin and subsequent gene expression changes in macrophages compared to the other closely related strains. The work demonstrates the power of functional genomics and its utility in investigating the underlying changes that can affect responses to infections and subsequent outcomes. While the study lacks functional validation, the cohesive dataset is quite compelling, and from it, the authors draw conservative conclusions and are frank about their study limitations.

Weaknesses:

Lack of functional validation of some of the targets found.

Reviewer #1 (Public review):

Summary:

In this manuscript, Sun et al. investigate the hemispheric lateralization of functional brain networks during verbal versus nonverbal working memory tasks. Utilizing state-of-the-art precision neuroimaging in highly sampled individuals, the authors define a set of distributed association networks and examine their task-evoked responses. The authors report a "generalized laterality effect," wherein multiple association networks appear to functionally split across the hemispheres, with left hemisphere components exhibiting a relative preference for verbal stimuli and right hemisphere components preferring nonverbal stimuli.

Strength:

The use of dense-sampling fMRI is a major strength of this study, allowing for a highly accurate, individual-specific mapping of network topologies that group-averaging typically obscures. Despite the interpretational concerns raised below, this high-quality, within-subject imaging dataset represents a valuable resource for the community. Furthermore, the inclusion of an independent prospective replication dataset provides valuable confidence in the robustness of the core imaging metrics. However, while the data quality is exceptionally high, the conceptual interpretations regarding "network splitting", "preferential recruitment", and the generalizability of the verbal/nonverbal dichotomy require significant refinement. Several methodological and statistical clarifications are needed to fully support the authors' claims.

Weaknesses:

Major:

(1) The manuscript relies heavily on task contrast values (e.g., Face > Word) to conclude that networks functionally "split" their profiles, with specific hemispheres being "preferentially recruited" by either verbal or nonverbal materials. While the data clearly demonstrate relative hemispheric differences, claiming absolute bidirectional specialization and active recruitment appears to overstate the findings in two key ways:

First, statistical evidence for true bidirectional "splitting" is scarce. A significant hemispheric difference confirms a relative shift in processing, but it does not permit claims about absolute preference. When examining the face>word effects against zero in the discovery dataset (Figure 3), the right hemisphere of the LANG, FPN-B, CG-OP, and SAL networks shows no significant preference for faces over words. In the replication dataset (Figure 6), two of the four targeted networks (FPN-A, CG-OP) similarly fail to show a significant right-hemisphere preference. Furthermore, it is unclear whether these tests against zero were corrected for multiple comparisons (e.g., 18 individual tests in Figure 3). Networks reporting significance at the uncorrected p < 0.05 level (such as the left hemisphere of LANG and FPN-B) might not survive standard correction, suggesting that even the left hemisphere's preference for words may be statistically marginal. Second, contrast differences in networks exhibiting negative signals may reflect relative deactivation rather than active recruitment. A mathematically positive contrast value derived from two negative activation states (e.g., Face [-6] > Word [-8]) does not indicate active "recruitment" for face processing. Instead, it merely reflects a relative difference in deactivation. Characterizing this dynamic as "preferential recruitment" misleads the reader regarding the actual physiological state of the network. Furthermore, such asymmetric suppression is frequently driven by generalized differences in task difficulty or cognitive effort, rather than true stimulus-specific processing.

(2) Building on the previous point, it would be highly beneficial to include the behavioral data (such as accuracy and reaction times) for the N-Back conditions, which do not currently appear to be reported in the manuscript. This information is important because if one condition (e.g., the Face N-back) was significantly more challenging or required greater cognitive effort than the other (e.g., the Word N-back), the observed hemispheric dissociations might reflect differences in arousal, effort, or attentional deployment rather than stimulus-specific processing. ion

(3) The manuscript claims a "generalized" hemispheric laterality effect. However, the supplemental figures suggest this effect may be highly sensitive to the specific stimuli used in the main text (unfamiliar Faces vs. rhyming Words), which represent extreme ends of visuospatial and phonological processing. As we talked about earlier, a true functional "split" implies that the hemispheres respond in opposite directions. However, visual inspection of the supplemental graphs reveals that for the vast majority of networks, both hemispheres are actually driven in the exact same direction (Figures S8 and S9).

In the Face > Letter contrast (Figure S8), true bidirectional splits largely disappear. With the exception of FPN-A, the bars for both the left and right hemispheres point in the exact same visual direction for every network (e.g., both hemispheres are visually positive in DN-A and dATN-B, and visually negative in CG-OP and dATN-A). This indicates that the hemispheres actually share the same categorical preference and merely differ in magnitude. Strikingly, the LANG network shows no significant difference between Faces and Letters in either hemisphere, suggesting that the robust leftward shift observed in Figure 3 was possibly driven by the heavy semantic and phonological demands of the rhyming task, rather than a generic preference for "verbal" processing.

Similarly, in the Scene > Word contrast (Figure S9), the hemispheres do not visually diverge in their response direction for most networks. For example, both hemispheres are visually negative (indicating a shared preference for Words) in the LANG, FPN-B, CG-OP, and SAL networks. Conversely, both hemispheres are visually positive (indicating a shared preference for Scenes) in the dATN-B and DN-A network.

Because the hemispheres do not visually diverge in their response direction for most networks across these supplementary contrasts, the claim of a robust, generalized hemispheric "split" is unsupported.

Reviewer #2 (Public review):

Summary:

In this manuscript, Sun and colleagues use precision fMRI to investigate the spatial patterns of verbal versus nonverbal processing in the cortex. They first show that the left hemisphere tends to be more active for word than face processing, whereas the right hemisphere tends to be more active for face than word processing during a working memory task. They then show that this is not confined to a particular network specialized for verbal vs. nonverbal processing but is a pan-network hemispheric difference across 8/9 association networks. This was unexpected, as prior precision imaging work emphasized network specialization and the authors had hypothesized that verbal vs. nonverbal processing would show bilateral network-level effects in a single, right-lateralized network (FPN-B). They then replicated this pan-network effect in an independent dataset.

Strengths:

(1) This paper is neat, clear, and succinct. The authors convincingly show that there exists a hemispheric difference in face vs. word processing during a working memory paradigm across many association networks.

(2) They replicate this result in a fully independent dataset. They do a particularly nice job setting up a prospective replication analysis over 4 distinct association networks.

(3) They do a wonderful job framing the experiment - they provide context on how previous precision imaging findings would have suggested a specialized network for verbal vs. nonverbal processing, they replicate major findings from that work in this data (network laterality and bilateral network activation in multiple task contexts), and then show the surprising pan-network hemispheric laterality in two independent datasets.

(4) This paper adds a unique perspective to precision imaging findings. Most precision imaging has shown that different networks seem to be specialized for different cognitive tasks - individual task activations tend to follow network boundaries and networks tend to be cohesively activated. These types of findings led to the idea that previously reported broad hemispheric effects for verbal vs. nonverbal processing could instead be due to a lateralized network specialized for verbal versus nonverbal processing. However, this paper accounts for individualized network topography and yet finds a hemispheric effect that transcends individual networks. I think this result will have a strong influence on how many readers think about network specialization.

Weaknesses:

(1) The evidence for the main result comes only from a single fMRI task (n-back) with a particular set of stimuli (faces, words) in which processing demands are not matched across verbal and nonverbal conditions (word blocks use rhyming, face blocks use an exact match). While the claim made is fairly broad (hemispheric laterality in verbal vs. nonverbal processing), it isn't clear how well this finding would generalize to other types of stimuli or processing. This was mentioned in the limitations section, but the paper would be strengthened by both additional evidence for a general verbal versus nonverbal processing effect and by a discussion of how these specific stimuli (words and faces) and processing demands (differences between rhyming and exact match) might affect the results. The authors did include supplemental post-hoc analyses of scene and letter conditions that are matched in processing, but did not discuss them in the main text.

(2) While lateralization is seen in 8/9 networks, the effect is much larger in some networks (FP-A, DATN-A) versus others. Similarly, the face > word effect is much stronger in some regions of the cortex than others. For example, all the individuals shown exhibit a patch of RH mid-LPFC cortex with particularly strong face > word preference compared to anywhere else in association cortex and an analogous LH mid-LPFC region that shows a particularly strong word > face preference. While the authors are correct that lateralization is seen across many networks, there does seem to be a topography to it rather than a diffuse hemispheric difference. I wonder to what degree the general hemispheric laterality pattern could be driven by a subset of regions that happen to cross several association networks. Neither the differences between networks nor the finer-scale activation patterns are considered in this paper. The paper would be strengthened by considering them.

(3) The paper is focused on association networks and provides an interesting report on face versus word processing in those networks specifically. In the brain maps, it is possible to see face versus word preference in non-association regions as well. The authors don't discuss these patterns, but the paper would be strengthened by describing the relationship of these patterns with known face and language processing systems in the sensory cortex.

Reviewer #3 (Public review):

Summary:

This work takes a precision neuroscience approach to examining how different task demands elicit lateralized vs. bilateral activity in large-scale brain networks. Using ~35-150+ minutes of resting state data per person, the authors identify individualized networks and map their degree of laterality. They find that all association networks are bilateral, with some networks. such as the language network (left) and fronto-parietal B network (right), showing some marked degree of laterality. A sentence reading task evokes activity bilaterally in the language networks, while working memory load during an n-back task evokes bilateral activity largely in fronto-parietal, dorsal attention, and salience networks. Interestingly, though, the authors find that when digging into the N-back task and contrasting blocks that have rhyming words vs. faces, this elicits a more lateralized pattern of activity; left activation for rhyming and right activation for faces. This lateralization is seen across multiple association networks, not just the language or fronto-parietal networks. These findings are then replicated in another precision data set.

Strengths:

This work has several notable strengths. This study boasts a lot of data for each individual, allowing them to examine individualized functional networks and task activations. Given the marked individual differences in laterality (see Figures S4 and S5), a group-averaged network atlas and group-averaged activation maps would likely muddle some of the interesting effects.

The authors also use an elegant approach for individualized network estimation, multisession hierarchical Bayesian modeling, or MSHBM. MSHBM allows vertex-based functional connectivity to steer individualized networks while also incorporating meaningful priors to identify comparable networks across individuals. This is a nice approach combining elements of a common atlas across individuals with data-driven approaches.

The authors have a rich working memory N-back task with four different stimuli types with which they can examine processing different types of stimuli.

A major strength of this work is the replication. The authors take their surprising findings and replicate the entire experiment in another sample. The replication sample notably has even more data per person than the discovery sample, allowing for robust and precise estimation of individual networks and task activity.

Weaknesses:

I'd like to frame this section as 'unsolved challenges' rather than 'weaknesses'.

One of the strengths of this paper is that the working memory task that incorporates so many different stimuli and conditions also poses a caveat for interpreting the task stimuli effects. The 'word' condition requires multiple cognitive demands - working memory and rhyming/phonological processing. This makes it a little hard to draw complete parallels between the word and face conditions. It does, however, provide a useful backdrop to explain why there are such strong left laterality effects for the word condition. I would expect that explicit phonological processing that is required for a rhyming task would elicit more left lateralized activation than the sentence processing task, as fluent readers are likely not using explicit phonological processing for sentence processing. This could explain why, for the sentence reading task, they find more bilateral activation, but a task that specifically targets phonological processing (i.e., the 2-back word condition) would evoke more left lateralized activation above and beyond the activation supporting working memory, which is held constant across both the 'words' and 'faces' conditions. Ultimately, I believe this supports the broad idea of this work - that large-scale association networks can show lateralization, even beyond language network boundaries. However, the fact that there is a dual-task load that evokes phonological processing for the word condition is important for contextualizing these findings.

When looking at plots of individual differences, it is clear that some people are more bilateral than others in certain networks (and sometimes overall). Because of the amount of data per person in this precision study, it naturally limits the overall sample size (N=29). This makes it difficult to interrogate individual differences in laterality and what might predict this effect across people.

Reviewer #1 (Public review):

Summary:

This paper examines potential sex differences in the conflict between exploitation, pursuing food and rewards in previously-associated locations/paradigms, or exploration of new locations that might result in better outcomes. Dysregulation of this conflict may be an underlying behavioral modality of psychiatric diseases. They used four distinct tasks: a two-armed Bandit 100:0 task, a standard fixed ratio 1 task, a two-armed Bandit 80:20 task, and a closed-loop economy PR1 task that allows for the assessment of motivational breakpoint.

Male mice show significantly higher accuracy under conditions of high probability known rewards, sticking with an action that just resulted in a reward or "win-staying". This was demonstrated in multiple paradigms, and there was a predictive nature of this behavior that could predict animal sex with modest accuracy. Under probabilistic environments, males were no longer more accurate than females but still used a higher win-stay strategy. A closed-loop PR1 task showed that there were no inherent differences in motivational breakpoint between sexes. Finally, the authors use simulations to determine an appropriate number of animals needed to detect these differences.

Strengths:

The manuscript attempts to resolve inconclusive sex differences that have heretofore been neglected or inconclusive due to insufficient power. The most impressive aspect of this paper is its scale, assaying 62 female mice and 74 male mice in identical exploration-exploitation tasks using high-throughput and noninvasive operant feeding via FED3. Very few labs can achieve this scale, which is necessary to detect sex differences with a small effect size.

The authors use some sophisticated modeling approaches and analysis of data from the 136 mice to investigate the significance of these sex differences and interrogate other conditions. They also use simulations to model the likelihood of replicating these differences given a sample size. This is extremely helpful for other researchers as they consider sex as a biological variable.

Weaknesses:

The study is largely descriptive in nature and does not pursue any mechanism of the underlying differences, like hormones, neuromodulators, or circuits. The lack of estrous cycle tracking is acknowledged as a limitation.

Reviewer #2 (Public review):

Summary:

Murrell and colleagues examine sex differences in mouse decision-making tasks, using the FED3 device, which allows for continuous data collection in the home-cage. Mice performed four tasks across two weeks, which provided all of their food. Across tasks, male mice were more likely to repeat a rewarded choice than females, which benefits decision accuracy in deterministic tasks. This work complements existing results for decision-making differences in males and females, affirming that this domain of cognition is particularly sensitive to sex differences. However, there are some specific features of the FED3 device, such as single housing, closed economy feeding, and 24-hour access that can uniquely influence decision-making in a (likely) sex-dependent manner that encourage considering these data as examining sex differences in a particular context, rather than as a generalized finding. At the same time, these data could offer new insights about nuances of behavior like circadian rhythms or bout analysis, uniquely enabled by the extended availability of the FED3 devices. The analyses in this paper also make an important point, encouraging researchers to use methods that allow for much larger N's to provide clearer and more robust results.

The FED3 devices are an innovative new way to approach behavior, and have allowed the authors to test many dozens of mice in a battery of tasks, over which they see similar patterns of increased win-stay behavior in male C57b6 mice (wildtypes from several knockout lines). The authors point out that there are discrepancies in prior literature across tasks and species in terms of how sex differences influence decision making, but there are some particular ways that sex differences could interact with the FED3 devices that it would be interesting and important to consider further. In particular, the fact that the animals live with the device, singly housed, may be an underrecognized contributor to sex differences. Changes in social interaction and dominance arising from long-term single housing are very likely to impact males and females differently, for example.

Continuous data collection is a fascinating way to look at learning and decision-making, but it also raises interesting questions about whether these dynamics are impacted as a function of continuous access to the device. In addition to summary metrics over the whole task, it might be valuable to look at learning across the task each day, and within circadian periods of each day. For example, it seems based on the example sessions for the 100-0 bandit task that animals take at least a few reversals to learn the task structure. How many trials does it take for a male or female mouse to reach some criteria of success? Do the sex differences exist at all time points? Does the light cycle affect the accuracy or trial counts? There are numerous such analyses that could particularly inform future use of the FEDs across laboratories, and identification of similar or distinct patterns of sex differences or behavior in other apparatuses, and would be a benefit to the field.