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):

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):

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.

The authors employed several computational techniques to identify parameters or features of behavior that might explain the sex differences they observed, and this is a strength of the manuscript. However, the win-stay lose-shift agent may not be an ideal match to make conclusions about exploitation, as it is unclear how win-stay and lose-shift strategies map onto explore/exploit tradeoffs. If an animal were exploiting an option, they may win-stay *and* lose-stay, if the task is probabilistic. Indeed, the model fit is weaker for the 80-20 bandit, suggesting this model may not reflect the actual strategies mice are engaging in, potentially in both bandit tasks. This point is particularly worth considering in light of the criteria for shifts in the tasks being based not on the number of trials completed, but on the number of pellets earned. When shifts are tied to reward collection rather than trials, it can amplify differences in behavior driven by reward consumption.

Reviewer #3 (Public review):

Summary:

The manuscript by Murrell et al. describes a high-throughput approach for evaluating food foraging strategies in mice. Building on their prior publication describing the technical aspects of the Feeding Experimentation Device 3 (FED3), this study demonstrates the utility of the FED3 in evaluating decision-making in mice. The authors identify key differences in male and female foraging strategies that could not be accounted for by total food consumption or overall food motivation. Given the rapid adoption of the open source FED3 platform, this work is likely to be of broad interest and utility in the field.

Strengths:

(1) The use of cost-effective, open-source devices like FED3 provides substantial value to the scientific community. Validation of appropriate conditions for using this equipment is an important step toward broad adoption.

(2) The authors implement a simple but elegant experimental design for studying food-motivated decision-making behavior. This approach could be applied to a wide range of preclinical disease models in future studies.

(3) The study is well-powered to evaluate sex as the primary experimental factor (62 females, 74 males), allowing the authors to make convincing claims about differences in strategy. Additionally, the dataset provides a useful benchmark for power analyses in future studies involving more complex experimental designs.

(4) The figures are clear and generally easy to interpret the primary findings.

(5) The conclusions are appropriate and not overstated

Weaknesses:

(1) A major strength of this study is the potential utility for new investigators trying to implement cognitive behavioral tasks in mice. However, the present version provides limited background on the rationale for selecting the bandit task and on prior work applying it in similar contexts. Including additional background and discussion would better contextualize the approach for other groups considering adopting it in their own studies.

(2) Some methodological details surrounding the initiation of the experiment could be clarified. Specifically, it is unclear if mice transitioned directly from standard housing conditions (group housed, standard chow) to the study conditions (single housed, FED3-based probabilistic learning), or intermediate acclimation/training steps were used, such as autoshaping, free access to new food pellets, or FR1 training. A more detailed experimental timeline (for example, see Figure 1 from PMID 39710132) would address this concern.

(3) The authors evaluated multiple probabilistic conditions (100%, 90%, 80%, 70%, 60%), but ultimately focused on the 80% condition for this study. A more detailed explanation for how this conclusion was reached would be useful for future researchers working under different experimental conditions (i.e., age, strain, genotype, disease model) where other probabilistic conditions may be more appropriate.

Reviewer #1 (Public review):

Summary:

The authors claim that bacteria are guided by diffusiophoresis. They perform experiments of bacterial motility in microfluidic channels with salt gradients. The data show that P. pudita bacteria swim towards higher sodium chloride concentrations, but there is no evidence that this is due to a diffusiophoresis.

Weaknesses:

It is well known that bacteria perform chemotaxis in salt gradients (see e.g., PNAS 86, pp. 8358-8362, 1989). The underlying mechanism based on chemoreceptors is widely accepted, but the authors do not mention this possibility. I recommend a control experiment where the chemotaxis genes are knocked out. Even if this mechanism can be ruled out, the current data show no evidence for a mechanism based on diffusiophoresis.

Reviewer #2 (Public review):

Summary:

The authors investigate how salt gradients influence the transport of Pseudomonas putida in confined microfluidic environments. They report that salt gradients enhance directional migration, increase run persistence, and promote transport toward contaminant-rich regions. To explain these observations, the authors propose a physical steering mechanism in which differential diffusiophoretic mobilities of the cell body and flagellar bundle generate an aligning torque that reorients cells along the salt gradient.

Strengths:

The study addresses an interesting question at the interface of microbiology, complex fluids, and active matter. Their experiments suggest that salt gradients influence bacterial transport behavior and lead to more persistent, directional motion. Once confirmed, the proposed mechanism would broaden our understanding of how environmental gradients can shape microbial migration through physical interactions in addition to more traditional sensing-based pathways.

Weaknesses:

The main limitation of the current study is that the proposed steering mechanism is not directly demonstrated. The evidence for the diffusiophoretic torque is largely inferred from trajectory statistics and theoretical modeling. While the observed transport behavior is convincing, the causal link between the observed migration patterns and the proposed reorientation mechanism remains less well established. In particular, the manuscript focuses primarily on cell trajectories and transport properties, whereas the proposed mechanism fundamentally involves changes in cell orientation. Additional evidence connecting orientation dynamics to the proposed torque mechanism would strengthen the conclusions.

A related concern is whether alternative physical mechanisms associated with the imposed salt gradients have been fully excluded. For example, weak flow-mediated effects or other hydrodynamic influences could potentially contribute to the observed transport behavior. The manuscript would benefit from a more thorough discussion of such possibilities and a clearer justification for why the proposed diffusiophoretic mechanism should be regarded as the dominant explanation.

The manuscript would also benefit from a clearer positioning within the broader literature on physically induced microbial transport and swimmer reorientation. Previous studies have demonstrated directed migration arising from rheotaxis (Marcos et al., 2012, PNAS) and viscosity-gradient-induced steering (Stehnach et al., 2021, Nature Physics). While the mechanism proposed here appears distinct, a more explicit discussion of how the present work relates to these earlier studies would help readers better understand the specific conceptual advance being made.

Reviewer #1 (Public review):

Summary:

This paper presents a creative physics-based model of an ATPase-like molecular machine using mechanically coupled linkages to mimic allosteric cycles. The authors construct the complete reaction network by enumerating all mechanically allowed binding configurations and transitions between them. The resulting system contains hundreds of microstates connected through node-level binding, dissociation, intramolecular rearrangements, cleavage, and ligation reactions. Stochastic simulations are then used to study how the machine cycles between ligand-bound and substrate-bound states. Overall, the manuscript presents an interesting and creative mechanochemical framework for modeling ATPase-like allosteric cycles integrating multivalent binding, geometric exclusion through rigidity arising from binding of substrates and ligands, with stochastic simulations.

Strengths:

(1) The manuscript presents a creative mechanochemical framework that combines multivalent binding, geometric exclusion, rigidity-based coupling, stochastic kinetics, and catalysis within a unified model.

(2) The use of geometric exclusion and rigidity to generate negative allosteric coupling is elegant and provides an intuitive physical mechanism for coordinated molecular behavior.

(3) The interpretation of catalysis as a transient release of mechanical constraints is conceptually interesting and offers a novel perspective on how energy-consuming reactions can regulate state transitions.

(4) The distinction between productive and futile cycles is insightful and provides a useful framework for understanding pathway selection in molecular machines.

(5) The explicit construction of a stochastic state network allows the authors to connect microscopic binding events with emergent cyclic behavior.

(6) The work provides a conceptual platform for exploring how simple mechanical principles may give rise to allosteric regulation and mechanochemical transduction in synthetic molecular systems.

Weaknesses:

(1) The manuscript is very dense and difficult to follow. The notation and microstate labels (e.g., {S/L}:{10,5}) obscure the central ideas, and the stochastic model is not explained clearly enough. The authors should provide a simpler schematic, a mapping of state labels, and a step-by-step example of a productive cycle. The supplementary videos would also benefit from additional explanation.

(2) The framework appears most applicable to mechanically gated motor proteins and may not generalize to allosteric enzymes that operate through conformational ensembles, dynamic coupling, or entropy-driven regulation. The scope of the model should be discussed more carefully.

(3) The reported behavior appears highly dependent on specific parameter choices and rate hierarchies. A broader sensitivity analysis is needed to demonstrate robustness.

(4) The binary treatment of states as either rigid or flexible oversimplifies the continuous energy landscapes and fluctuations observed in real biomolecules. The limitations of this approximation should be discussed.

(5) The role of nonequilibrium thermodynamics is underdeveloped. The relationship between the model, ATP chemical potential, free-energy dissipation, entropy production, and the energetic cost of futile cycles should be discussed more explicitly.

(6) Although a large number of microstates are enumerated, it remains unclear which states and pathways dominate the dynamics. A more coarse-grained analysis highlighting the key states and transitions would improve interpretability and facilitate comparison with experimental systems.

Reviewer #2 (Public review):

This is an interesting study aiming to capture the fundamental principles of ATPase-like machines with an elementary model of rigid bars. While molecular motors have been the subject of many studies in statistical physics, taking very simplified approaches, these past studies generally abstract away from geometrical constraints and do not account for allosteric mechanisms. In turn, several simple physical models of allostery are now available, but most consider only long-range effects without reference to reactivity or the conversion of chemical to mechanical energy. The essential ingredient of the present model is a form of negative allostery that stems from geometrical constraints. These constraints impose the presence of hidden microstates and the connections between states that form a reaction network. Nontrivial tradeoffs can then be derived, e.g., on the catalytic rate.

One limitation of the approach is that energetic constraints, which are equally important, are not themselves derived from physical principles. This includes the different kinetic rates, the binding constants, and the mechanisms of reactivity, even though, in principle, they should follow from basic interaction energies in the context of thermal fluctuations. This is a legitimate choice of modeling level, handled notably by imposing a hierarchy between rates. It would be appreciated, however, if the overall logic of the derivation were clarified, presenting more clearly from the beginning what the fundamental hypotheses of the model are, which aspects are derived from these hypotheses, and which require additional assumptions. It seems indeed that the model involves both fundamental physical assumptions that are used to derive some emerging kinetic features (e.g., geometry imposes futile cycles) and global kinetic assumptions that are used to derive some microscopic features (e.g., a productive cycle imposes the relative values of the kinetic rates).

The conclusion ends with a proposal to generalize to more elaborate models. I was wondering, however, if the opposite would not be desirable. The current model is already quite involved (as the 7 pages of SI listing transitions between states testify). Wouldn't it be possible to obtain some of the main results, e.g., the trade-offs defining an optimal cleavage rate, from an even simpler model?

Reviewer #3 (Public review):

Summary:

In "Design of a minimal, allosteric, and ATPase-like machine using mechanical linkage," Omabegho introduces a simplified model of an allosterically-regulated molecular machine. The model machine takes inspiration from simple ATPase motors, specifically myosin or dynein, and is meant to capture the interactions between enzyme, ligand, and substrate that empower these enzymatic biomolecular machines. The model system attempts to specifically model the inhibitory allosteric regulation relevant to machine operation, following work on mechanical features of allostery in protein-analogue elastic network models. After the introduction of the model machine, the manuscript discusses the primary cycle by which the substrate serves to displace and then cyclically replace the ligand (roughly corresponding to a "recovery" and "power" stroke, respectively, in their biomolecular machine inspiration), as well as cataloguing other futile cycles or individual chemical pathways the machine may traverse. After an exhaustive enumeration of all possible states and transitions of the model machine, the actual mechano-chemical system is mapped to an abstracted stochastic chemical reaction network, which is finally studied numerically in more detail. We believe this model system is novel, interesting, and, importantly, interpretable and could prove to be useful in future modeling and rational design of simple bio-mimetic nanoscopic systems.

Strengths:

(1) Omabegho introduces a novel chemo-mechanical model system that captures the core behavior of a simple ATPase molecular machine. The model is relatively simple in construction, but, as the manuscript demonstrates, it can display very rich behavior depending on various competing chemical timescales and mechanisms. These features suggest that this system could, in fact, serve as a useful starting model if adopted by the wider community.

(2) A key feature to highlight is the mechanistic interpretability of the model. By cutting to the seemingly core functional details of an ATPase-like machine, Omebegho is able to algorithmically produce an exhaustive listing of all allowed chemical states and all possible transitions between them, enabling the study of all possible mechanistic pathways and the relative frequency of each observed path. Further, Omebegho produced very clear visualizations of these states, transitions, pathways, and cycles that again facilitate the interpretability and utility of the model. This interpretability is key to our suggestion that this model could be more widely adopted as a clear ATPase analogue model for study by the broader biophysical community.

Weaknesses:

There are some issues to note.

(1) First, although the model is inspired by ATPases, the cycle in question is not a model even for the significantly abstracted form presented in Supplemental Section 1.1, as noted in the manuscript. The allosteric regulation utilized in the model does not mandate that the ligand (a stand-in for actin, for example) displaces both products (stand-ins for ADP and P). Rather, one product (P) dissociates spontaneously, and the other, larger one (ADP) is allosterically displaced. We recognize mandating this small further detail would presumably complexify the model (i.e., it may require an additional tile in the enzyme construction), but it would also lead to a more accurate, while still simple and interpretable, picture of the biological molecular machines in question.

(2) Much as we recognize and applaud the model's structure as simple and interpretable, when trying to actually study the chemical dynamics and observed dynamical behaviors, individual chemical rates of various binding and unbinding processes appear to be quite finely tuned. There is some attempt at studying the behavior of this model in various parameter tuning regimes, but the large number of model parameters makes a truly complete numerical study prohibitive. Given this difficulty, it would be instructive to know if a comparison could be made to the actual motivating biological systems and any observed chemical rates in the experiment. Further, given the desired cyclic behavior, it would be quite interesting to see to what degree this behavior is robust to various parameter choices. Again, preliminary work was done in the manuscript by biasing rates or numerical siloing experiments, but a far more exhaustive study is certainly worthwhile.

(3) Perhaps our biggest critique of the manuscript is that, although it incorporates both mechanical and chemical aspects into the model system construction, all mechanical aspects of the model simply function to limit allowed state transitions. From our understanding, all mechanical aspects of the model are, in fact, abstracted away during any simulations. This modeling choice, of course, retains some mechanical inspiration while making the resulting system more tractable, but it is ultimately not an actual mechanical model. ATPases, especially motors such as myosin and dynein, are inherently mechanical, their fundamental features being the conversion of chemical fuel into mechanical motion. A fuller treatment, perhaps in future work, should include these physical degrees of freedom in simulation, thus truly tracking the interplay between physical enzyme mechanics and chemistry. The absence of actual mechanics as yet, beyond a strict allosteric restriction, is an inherent limitation of the model.

Reviewer #1 (Public review):

The authors aim to reconstruct a multi-layer metabolic regulatory network in Alzheimer's disease by integrating transcriptomic, proteomic, and metabolomic datasets from human brain tissue. By linking transcription factors, enzyme expression, metabolic reactions, and metabolites, the study seeks to provide a systems-level understanding of disease-associated metabolic dysregulation.

The revised manuscript has improved in clarity and includes additional analyses in response to prior comments, particularly the incorporation of cell-type proportion estimates derived from matched single-cell datasets. This represents a meaningful step toward addressing concerns about the interpretation of bulk tissue and strengthens the study's descriptive rigor.

However, several key limitations remain. First, although cell-type proportions are now estimated, this information is not integrated into downstream analyses. As a result, it remains unclear whether the observed metabolic changes reflect cell-intrinsic regulation or shifts in cellular composition. This distinction is critical for interpreting the inferred regulatory network and limits the strength of the conclusions.

Second, the biological conclusions remain largely confirmatory. The reported downregulation of energy-related pathways, including the TCA cycle and oxidative phosphorylation, is consistent with prior literature. The trans-omic framework provides a structured representation of these changes, but the manuscript does not convincingly demonstrate that this approach yields new mechanistic insight beyond existing knowledge. In particular, the network is not sufficiently leveraged to identify novel regulatory relationships or generate testable hypotheses.

Third, while the framework integrates multiple molecular layers, the contribution of upstream transcriptional regulation remains unclear. The most compelling findings appear to arise from protein and metabolite layers, and the manuscript does not clearly demonstrate how transcription factors or mRNA-level changes contribute to the interpretation of metabolic dysregulation. This weakens the claim that the study provides a fully integrated trans-omic perspective.

Fourth, concerns regarding network robustness remain. The analysis relies on partially overlapping cohorts across omics modalities, and although this limitation is acknowledged, no formal sensitivity or robustness analyses are presented. This reduces confidence in the stability and generalizability of the inferred network structure.

Finally, the handling of covariates remains limited. While the authors justify this based on data availability and prior studies, the lack of consistent adjustment for known confounders introduces uncertainty in attributing observed differences specifically to disease-related biology.

Overall, the study presents a technically sound application of a trans-omic integration framework and provides a coherent overview of metabolic dysregulation in Alzheimer's disease. However, the findings are primarily descriptive and confirmatory, and the current analyses do not fully demonstrate that the approach yields novel biological insight. The work will be of interest to researchers in systems biology and multi-omics integration, but its impact on advancing understanding of disease mechanisms is likely to be moderate.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors did an excellent job with their resubmission, politely and elegantly answering the comments from the reviewers.]

Summary:

Large language models (LLMs) have been developed rapidly in recent years and are already contributing to progress across scientific fields. The manuscript tries to address a specific question: whether LLMs can accurately infer signaling networks from gene lists.

Strengths:

The manuscript raises a good question: whether current LLMs can accurately generate signaling networks from gene lists.

Reviewer #2 (Public review):

Summary:

The authors evaluate whether commonly used LLMs (ChatGPT, Claude and Gemini) can reconstruct signalling networks and predict effects of network perturbations, and propose a pipeline for benchmarking future models. Across three phenotypes (hypertrophy, fibroblast signalling, and mechanosignalling), LLMs capture upstream ligand-receptor interactions and conserved crosstalk but fail to recover downstream transcriptional programmes. Logic-based simulations show that LLM-derived networks underperform compared to manually curated models. The authors also propose that their pipeline can be used for benchmarking future models aimed at reconstructing signalling networks.

Strengths:

The authors compare the outcomes from three LLMs with three manually curated and validated models. Additionally, they have investigated gene network reconstruction in the context of three distinct phenotypes. Using logic-based modelling, the authors assessed how LLM-derived networks predict perturbation effects, providing functional validation beyond network overlap.

Weaknesses:

The authors have used legacy models for all three LLMs, and the study would benefit from testing the current versions of the LLMs (ChatGPT 5.2, Claude 4.5 and Gemini 2.5). Additional metrics such as node coverage, node invention, direction accuracy and sign accuracy would be useful to make robust comparisons across models.

Reviewer #1 (Public review):

Summary:

Pecak et al have deciphered the conformational dynamics of a heterodimeric model ABC transporter, TmrAB, a functional homolog of the human antigen transporter TAP, using single molecule Forster resonance energy and fluorophores attached to residues at either nucleotide binding domains or periplasmic gate. The analysis not only differentiated ATP-free and bound states, but also enabled the real time monitoring of protein conformational changes precisely dissecting transport cycles and resolving transient intermediates. This study is absolutely significant in providing and establishing a general pipeline delineating the conformational dynamics in heterodimeric ABC transporters.

Strengths:

The scientific study is very well documented for experimental design, results and conclusions supported by the experimental data. Authors have determined the conformational dynamics of TmrAB across different ATP concentrations including physiological ones and resolved an outward open state and other conformational states consistent with previous cryoEM and DEER studies. Authors have also mentioned limitations in the study.

Comments on revised version.

Authors have worked on most of the revisions stated in previous feedback and included in the newer version, which has been significantly improved. Other comments have been described to be out of scope from this study.

Reviewer #2 (Public review):

In their manuscript entitled 'ATP-driven conformational dynamics reveal hidden intermediates in a heterodimeric ABC transporter', Pečak et al. use elegant single-molecule FRET experiments in detergent to investigate the heterodimeric ABC transporter TmrAB. By combining simulations of the transporter's accessible volume with elegant trapping strategies, the authors identify an unresolved outward-facing open state and conclude that it is usually obscured by a rapidly interconverting ATP-bound ensemble. Overall, the study demonstrates that smFRET can resolve the short-lived intermediate states of TmrAB and potentially other ABC transporters that are obscured in ensemble measurements.

It is a very interesting study that highlights the power of combining high-resolution structural information with spectroscopic approaches. I had three major concerns with the original version, all of which have been addressed by the authors in this revised version.

Reviewer #1 (Public review):

Summary:

This manuscript aims to test the idea that visual recognition (of faces) is hierarchically organized in the human ventral occipital-temporal cortex (VOTC). The paper proposes that if VOTC has a hierarchical organization, this should be seen in two independent features of the VOTC signal. First, hierarchy assumes that signals along the hierarchy increase in representational complexity. Second, hierarchy assumes a progressive increase in the onset time of the earliest neural response at each level of the hierarchy. To test these predictions, the authors extract high-frequency broadband signals from iEEG electrodes in a very large sample of patients (N=140). They find that face selectivity in these signals is distributed across the VOTC with increasing posterior-anterior face selectivity, hence providing evidence for the first prediction. However, they also find broadband activity to occur concurrently, therefore challenging the view of a serial hierarchy.

Strengths:

(1) The hypothesis (that VOTC is hierarchically organized) and predictions (that hierarchy predicts increases in representational complexity and increases in onset time) were clearly described.

(2) The number of subjects sampled (140) is extremely large for iEEG studies that typically involve <10 subjects. Also, 444 face selective recording contacts provide a very nice sampling of the areas of interest.

Comments on revised version:

The authors have performed additional analyses and checks and I would now rate the findings as important and compelling.

Reviewer #2 (Public review):

Summary:

This very ambitious project addresses one of the core questions in visual processing related to the underlying anatomical and functional architecture. Using a large sample of rare and high-quality EEG recordings in humans, the authors assess whether face-selectivity is organised along a posterior-anterior gradient, with selectivity and timing increasing from posterior to anterior regions. The evidence suggests that it is the case for selectivity, but the data are more mixed about the temporal organisation, which the authors use to conclude that the classic temporal hierarchy described in textbooks might be questioned, at least when it comes to face processing.

Strengths:

A huge amount of work went into collecting this highly valuable dataset of rare intracranial EEG recordings in humans. The work is worth publishing for the data alone, assuming they are shared in an easily accessible and documented format. Currently, the OSF repository linked in the article is empty, so no assessment of the data can be made. The topic is important and a key question in the field is addressed. The EEG methodology is strong, relying on a well-established and high SNR SSVEP method. The method is particularly well suited to clinical populations, leading to interpretable data in a few minutes of recordings. The authors have attempted to quantify the data in many different ways, and provided various estimates of selectivity and timing, with matching measures of uncertainty. Non-parametric confidence intervals and comparisons are provided, using resampling that preserve dependencies in a hierarchical manner, which is rare. Two types of analyses are also provided to support evidence in favour of the lack of practical significance for some of the comparisons. Collectively, the various analyses and rich illustrations provide convincing evidence in favour of the conclusions.

Comments on revised version:

The authors have addressed all my previous comments and the work is mostly limited by the lack of pre-registration and the exploratory nature of some of the analyses. However, with data and code available, other teams can assess the impact of researchers' degrees of freedom on the main outcomes.

Reviewer #1 (Public review):

Summary:

This manuscript describes the results of phylogenetic and epidemiological modeling of the PopART community cohorts in Zambia.

Comments on revised version:

Thank you for the opportunity to re-review this interesting paper.

This reviewer struggled to follow along with the author's response letter. It was challenging because responses were brief and did not list the specific changes made, leaving the reviewer to search for changes in the text. As best I could tell, there were no changes made that matched some of the highest-priority suggestions.

Critique #1 - This reviewer did not find the presentation of confidence intervals in the Abstract and other sections, which were suggested. Please note the format that was suggested in the original critique from Reviewer 1.

Critique #2 - regarding removal of unsubstantiated claims and use of a p-value to compare analysis to a null hypothesis - it seems the authors skipped over this critique and did not address it.

Regarding bias: the authors answered a different question than the one asked. The reviewer asked what proportion of transmissions were sampled; the authors stated that only communities from which phylo data was acquired were modeled. Was sampling 100% in those communities? Please provide the percentage and provide analysis that shed light on how sampling bias could impact the analysis.

Regarding "cherries" - the reviewer did not understand the author's response. The query was regarding what percent of the total number of phylogenetic pairs (denominator) were the 355 that had high confidence in directionality (numerator). The response could be expressed be a proportion.

The expectation of ART reducing the age of sources of transmission seems unrealistic to this reviewer. People on ART are not always adherent and can still transmit during gaps in adherence. ART dramatically increases life expectancy with HIV, which would have the opposite effect.

Reviewer #2 (Public review):

Summary:

The authors analyzed PopART data to better characterize the age and sex specific transmission dynamics in Zambia with a goal of allocation of resources.

Strengths:

Important analysis to hone in on key driver of HIV transmission in Zambia, which hopefully can be used to tune prevention efforts to maximize effect while limiting required resources. Two analytic approaches used, and while the phylogenetic data was markedly more limited, it mirrored the simulated epidemic. The authors did a nice job reviewing the limitations of the data and the analyses and providing analyses to support their goals and hypothesis, and this work may have more impact now that resources in SSA for HIV prevention and treatment may become more scarce.

Comments on revised version.

The revised manuscript clarifies the impact and utility of this work and better allows the comparability of the two methods. Highlighting the differences (or lack thereof) between the undiagnosed and diagnosed population) simplifies the public health approach.

Reviewer #1 (Public review):

Summary:

This manuscript describes the development of an expression system enabling up to 12 transgenes using the alternatively spliced fourth exon of *Drosophila* *Dscam* gene under the control of a UAS element. This will be a useful tool if expression is needed in *Drosophila* cells (in culture or in vivo). where *Dscam* splicing machinery is active, which limits its use.

Strengths:

The tool developed is based on a well-established genomic element. The underlying idea is relatively simple yet effective.

Weaknesses:

The authors describe the weaknesses of their system well, most importantly, depending on the presence of adequate levels of Dscam splicing factors in targeted cells. This likely limits effective use of the methodology to some cell lines (e.g., S2) and certain tissues (nervous system and innate immune system). The manuscript could do a better job in showing protein expression levels more quantitatively, either in comparison to other methods or as absolute values (transcript numbers, protein molarity, etc.).

Reviewer #2 (Public review):

Summary:

In this manuscript, Yu et al seek to develop a Drosophila genetic tool to simultaneously co-express up to 12 transgenes. They leverage the native Dscam exon 4 alternative splicing to generate a UAS to enable cell- and temporal-specific expression of transgenes. This tool is called the poly-transgene expression system (PXGS). Previous approaches to co-express transgenes have been limited to four to five genes, so PXGS would be a significant advancement, especially when examining processes that require robust expression of many genes to confer function. The authors showed that PXGS can drive expression of multiple (1) fluorescent reporters and (2) cell surface receptors in different cell types (neurons, glia, and muscles). However, there are major proof-of-principle experiments missing to demonstrate the utility of PXGS and its potential limitations. Additionally, some of the data is just not interpretable, and experimental rigor is significantly lacking.

Strengths:

Developing a genetic tool to co-express transgenes beyond what is currently available would be significant.

Weaknesses:

(1) While the authors stated that each PXGS construct can express 12 transgenes, this was not directly tested - the largest number of genes tested was in the PXGS_fluorophores, which has 4 genes inserted in 10 alternates (and therefore it can be determined if genes from all the alternates are spliced in at a meaningful level).

a. First, the authors state that they tested the expression of the fluorophores in S2 cells using RT-PCR before generating the fly line. However, this data is not shown. Also, it is possible to test expression and localization of UAS transgenes in S2 cells with a ubiquitous GAL4, similar to what they did for GFP expression in Supplemental Figure 1.

b. In the corresponding figure for this experiment (Figure 2), there are some concerning expression patterns and potential channel bleed-through/crosstalk. The nSyb-Gal4 is a pan-neuronal driver, yet expression of three fluorophores was extremely minimal. This could potentially be explained by the deterministic vs random alternative splicing. However, it is more concerning that in the GFP, RFP, and iRFP channels, the exact same tiny cluster of neurons is observed, suggesting potential bleed-through of the channels. Appropriate controls are required, including expression of a traditional fluorescent reporter with the nSyb-Gal4 they are using. And replicates would help with the experimental rigor.

c. Additionally, it would be helpful to know if genes inserted at each alternate exon are expressed at a similar efficiency (vs. some alternate exons have higher levels of expression)

(2) PXGS expression in non-neuronal cells: The authors attempt to show that fluorophores targeted to different cellular compartments can be expressed in neurons and non-neuronal cells (glia and ubiquitously).

a. In Supplemental Figure 2A, they first use S2 cells to confirm expression, which does confirm. However, they use no markers to show that the fluorophores localize to the corresponding compartments (e.g., mitochondria and nucleus). In Supplementary Figure 2B, with that magnification and resolution, it is impossible to determine if the fluorophores localize properly.

b. In Figure 3, it is impossible to know if there is any glial expression based on those images. They state that "subcellular localization of fluorophores was observed in the flight muscle", but again, that cannot be concluded from the images. Also, the schematic of the construct is the same one used in Supplementary Figure 2. Why show it again?

(3) In the functional expression of PXGS transgenes section, while the authors used RT-PCR to show that each receptor gene is transcribed in S2 cells, it was not tested if they are correctly expressed, translated, and localized in the fly. The functional outcome observed (Figure 4 b-c) could be the result of misexpression of one or multiple genes.

a. Supp Figure 3: Why does the Sli lane have so many bands?

b. Why were these genes chosen for misexpression? Is there any evidence that they are required for the wiring of the mechanosensory neuron? Does the co-expression lead to an additive effect?

c. The RT-PCR result (Supplemental Figure 3) showed variations (e.g., kek and kir being significantly dimmer than tutl; multiple products for Sli). Is there any explanation behind this, and could this be the outcome of some alternate exons being more efficiently spliced than others?

d. Figure 4: These images seem to be taken with a widefield scope and only one plane. Is it possible that some of the pSC neurons are in a different Z plane, and they are not being captured here? There definitely is part of the axon terminal out of focus in some of the images. Also, most of the figure graph axes (e.g., 4b) are extremely difficult to read. And the figure overall is not easy to interpret.

(4) Supplemental Figure 5: This figure is quickly mentioned in the Discussion without much explanation. First, this must be in the Results section since it is an experiment. Second, this needs more context because, as is, it seems like it was just thrown into the manuscript.

(5) The authors mentioned that the size of the inserted genes could be a limitation for this technique and tested cell surface receptors of different sizes. However, there was no explicit discussion in the main text.

Reviewer #3 (Public review):

This paper, by Brian Chen and collaborators, adapts the highly alternatively spliced Dscam1 gene locus for use in a system for simultaneous multi-transgene expression in a variety of insect species. Specifically, they show that the hypervariable Dscam1 exon 4 region maintains its alternative splicing when placed in a UAS expression vector, and that each of the twelve exon 4 alternates can be replaced with an exogenous gene such that co-expression of up to twelve proteins can be achieved. Since the co-expression of more than a few proteins simultaneously is difficult, this represents a significant advance with multiple use cases. The authors validated the technique by assessing expression in vitro and in vivo, and by rewiring Drosophila sensory neuron axons by simultaneously expressing several cell surface receptors within the neuron. Overall, this is a clearly written paper that describes a potentially important new system. I have no major criticisms.

Reviewer #4 (Public review):

From the Reviewing Editor:

All three reviewers recognized the conceptual originality of PXGS and its value to the Drosophila community and the broader multi-gene expression field. The core demonstration - that Dscam exon 4 mutually exclusive splicing is maintained in an exogenous UAS vector, and that individual exon alternates can be replaced with genes of interest for conditional in vivo expression - was viewed as solid and creative. The in vivo application re-wiring pSc axonal arbors using PXGS constructs loaded with cell surface receptors was noted as an encouraging functional validation.

The reviewers differed in their overall enthusiasm. Reviewer 3 found the experiments straightforward, the results clear, and the system a significant advance with broad use cases, with no major criticisms. Reviewer 1 viewed the evidence as broadly solid, with the principal limitation being a lack of quantitative expression data and a dependence on adequate Dscam splicing-factor levels that constrain the system's applicable cell types - a limitation the authors themselves describe well. Reviewer 2 was the most critical, finding the underlying concept significant but the supporting data insufficiently rigorous to conclusively establish the tool's utility. The points below reflect the areas where reviewers - principally Reviewers 1 and 2 - felt the manuscript could be strengthened, should the authors choose to revise.

(1) Quantitative characterization of expression. Reviewers 1 and 2 both noted the absence of a quantitative comparison of PXGS-driven expression - in absolute terms (transcript numbers, protein amounts) or relative to standard UAS constructs. Given that signal is inherently divided across 12 alternates per transcription event, characterizing expression efficiency and whether all alternates are spliced and expressed at comparable levels would substantially strengthen the manuscript. Reviewer 2 specifically asked whether genes at different exon 4 positions are expressed with similar efficiency.

(2) Direct demonstration of 12-transgene expression. Reviewer 2 noted that, although the manuscript claims expression of up to 12 transgenes, this was not directly tested - the largest construct placed 4 distinct genes across 10 alternates, and the largest functional test used 3 genes per construct. Either a direct demonstration with more positions occupied or a more carefully bounded claim supported by the probabilistic framework would address this.

(3) Controls and interpretability of fluorophore expression. Reviewer 2 raised concerns about Figure 2, where expression of three fluorophores under nSyb-Gal4 was minimal, and the same small neuronal cluster appeared across the GFP, RFP, and iRFP channels - raising the possibility of channel bleed-through. Appropriate controls (including a conventional single UAS-fluorophore driven by the same nSyb-Gal4) and replicates were requested. Reviewer 2 also noted that the S2 cell validation data for the fluorophore constructs, described as having been performed prior to fly line generation, are not shown.

(4) Non-neuronal expression and subcellular localization. Reviewer 2 noted that the compartment-specific localization claims (mitochondria, nucleus) in Supplemental Figure 2 and Figure 3 are not supported by co-markers, and that the magnification and resolution in key panels are insufficient to confirm proper localization, particularly in glia.

(5) Functional expression of receptor constructs. Reviewer 2 noted that, while RT-PCR confirms transcription of each receptor in S2 cells, correct translation and localization in the fly were not directly tested, so the observed phenotypes could reflect mis-expression of one or a subset of the genes. Clarification of why the specific genes were chosen, whether co-expression produces additive effects, and the cause of the variable RT-PCR band patterns (e.g., the multiple Sli products, dimmer kek and kir signals) was requested.

(6) Supplemental Figure 5 (synthetic biology / RNAi). Reviewer 2 noted that this figure is mentioned only briefly in the Discussion despite representing an experiment, and recommended moving it to the Results with appropriate context. Reviewer 1 separately queried the meaning of the two white boxes in this figure and whether the RT-PCR convincingly supports expression of all genes shown.

(7) Figure quality and labeling. Both reviewers flagged that the labels in Figure 4 (particularly panel d) and the axes in Figure 4b are too small to read. Additional labeling points were noted (alignment of "Repo-GAL4" and "brain" in Figure 3; unlabeled images in Supplemental Figures 2 and 4; clarification of whether the two lanes per group in Figure 1c are replicates or use different primers). Reviewer 1 also suggested that some figure legends describe conclusions rather than what is shown, and recommended that legends describe the data with interpretation kept to the text.

(8) Additional points. Reviewer 1 suggested showing more of the gel in Figure 1 to demonstrate the absence of non-spliced fragments; clarifying the 1/12 probability argument (or moving it to the Discussion with transcript-number context); providing sequences for the fluorophore variants and fusion tags; and minor prose corrections ("Regardless if" → "Regardless of whether"; "dependent on three things" → "dependent on three factors"). Reviewer 2 noted that the gene-size limitation, though tested, is not explicitly discussed in the main text.

Reviewer #1 (Public review):

Summary:

In their submitted work, Lee and colleagues examine the correlation between electrophysiological activity as measured by SEEG, and layer-specific activation patterns, as measured through 7T fMRI. This analysis was performed using patients undergoing monitoring for epilepsy surgery guidance, as well as healthy controls, as they both listened to music.

They find that, in general, higher-frequency SEEG activity correlated positively with the fMRI signal, while lower frequencies correlated negatively. Across cortical depth, higher-frequency activity correlated positively with middle-to-upper layers, whereas lower frequencies showed their strongest negative correlations in superficial layers.

Strengths:

This is an interesting physiological study in that, to the best of this reviewer's knowledge, it has not been done before with auditory stimuli using the combination of iEEG (as opposed to scalp EEG) and fMRI. The framework fits well with models of layer-specific feedforward versus feedback processing (e.g., Bastos et al., 2012).

Weaknesses:

Its main limitations are a lack of specificity to the acoustic stimuli, the absence of correction for venous draining, and the fact that it is largely a replication/port of prior work.

Reviewer #2 (Public review):

Summary:

The authors present an investigation of the relationship between the iEEG frequency bands signal and hemodynamic responses at different cortical depths. Based on this, the authors aim to uncover the layered origin of iEEG signals at different frequencies. The authors then interpret their results in terms of feedforward and feedback processing, arguing that the correlations between fMRI and iEEG signals reflect the interaction between both processes. In addition, the authors aim to infer the extent to which these processes are involved during naturalistic music processing.

Strengths:

This study combines the neural recording methodologies yielding the highest spatio-temporal precision achievable in humans, while using naturalistic auditory stimuli. This combination of recording methods and experimental design offers key insights regarding the precise origin of iEEG signals, which is necessary to improve the interpretability of future iEEG studies.

Weaknesses:

(1) The current framing of the paper leads the authors to interpret their findings in ways that are not warranted by the data. The main analysis of the paper consists of correlating the hemodynamic responses from different layers with iEEG signals from different frequency bands, which enables us to infer the relationship between the two signals. It does not, however, enable us to draw inferences regarding the extent of feedforward and feedback processing and the interaction between the two during naturalistic auditory processing. This would require comparing hemodynamic responses in different cortical layers or frequency bands activation against some baseline condition. Based on the presented analysis, statements such as "our frequency-specific results demonstrate that naturalistic music perception seamlessly integrates both feedforward and feedback processing streams" should be removed.

(2) The presentation of existing literature omits key details and findings, making it difficult to fully understand the research question the authors are trying to address. For example, the author mentions studies showing that feed-forward and feedback processing are segregated across cortical layers and that feed-forward and feedback processing have distinct time-frequency signatures (lines 47-58). However, the authors do not mention which cortical layer or which frequency band is associated with which kind of processing. As a result, it is difficult for the reader to determine what exact hypothesis the author is trying to test in the study. This might also relate to the confusion raised in (1).

(3) The method section omits key details. When describing the paradigm, the authors do not describe how the tones were presented, nor how the signals were synchronized. Similarly, there is no mention of the pipeline used for iEEG electrodes localization. In addition, the exact regressors that entered the generalized linear model of hemodynamic responses are not clearly stated: were all regressors (frequency bands + acoustic signal + HFA) entered together in a single model or in separate models? The mention of a cubic spline is also not sufficient for the reader to understand what was done and for which purpose. Finally, the exact tests used for some comparisons are omitted (in Figure 2, for example, no mention of the exact test used to compare betas between A1 and A2). The current structure of the method section is also quite difficult to follow: the authors switch back and forth between describing acquisition protocols and participant counts, for example.

(4) The lack of methodological details (as described in point 3 above) casts doubts about the validity of some of the statistical tests reported. Throughout the paper, the authors present quantitative statements and statistical tests comparing the fitted beta parameters between brain regions (A1 and A2) and cortical depths. However, the authors do not mention any normalization procedure taken to ensure that the scale of the signals being compared was equated. If the overall magnitude of the signals in A1 differs from that of A2, the mean of the beta distribution is expected to differ as well. Similarly, if the signal-to-noise ratio differs between brain regions or cortical layers, so should the variance of the beta parameters across subjects, which might break the homoscedasticity assumption of some tests, which might or might not be a problem depending on the exact test the authors used (hence the importance of reporting them).

Reviewer #1 (Public review):

Summary:

This manuscript examines the expression of putative chemoreceptors in CSF-contacting neurons of the larval zebrafish spinal cord. Using in situ hybridization, the authors show that sstr2a is preferentially expressed in ventral CSF-cNs, whereas grm2a, ptprna, and ldlrad2 are detected in both ventral and dorsolateral CSF-cNs, with additional expression in neighboring cells around the central canal.

Strengths:

The study provides useful anatomical information on the expression of putative chemoreceptors in CSF-contacting neurons. The experiments appear to be carefully performed, and the results are clearly presented with high-quality illustrations and informative schematics.

Weaknesses:

This work remains largely descriptive and based on mRNA expression. Therefore, the proposed roles in chemoreception, ligand sensing, lipid capture, or long-range CSF signaling remain speculative without protein-level or functional validation.

Reviewer #2 (Public review):

Summary:

Verran et al. leverage a previously published RNAseq dataset of zebrafish cerebrospinal fluid contacting neurons (CSF-cNs) to identify potential receptors involved in chemosensory signalling in these neurons. They then validate expression of the identified receptors by hybridization chain reaction (HCR) in zebrafish larvae. This way they uncover potential roles for the somatostatin receptor Sstr2a, metabotropic glutamtate receptor Grm2a, LDL receptor Ldlrad2 and the Phosphatase receptor Ptprna, suggesting the existence of numerous chemo-sensory pathways in CSF-cNs and providing a potential entry point for further investigation.

Strengths:

This is a useful resource; the provided HCR data that demonstrates expression of these receptors in CSF-cNs is convincing, and the finding that CSF-cNs express these receptors is interesting.

Weaknesses:

The overall insight provided by this manuscript is rather limited, essentially just demonstrating the expression of 4 receptors in CSF-cNs, whose expression was predicted to be enriched in these neurons anyway by a previously published dataset.

Reviewer #3 (Public review):

Summary:

The authors aimed to identify new molecular pathways that could enable long-range signaling through the cerebrospinal fluid (CSF), focusing on a specialized class of neurons called CSF-contacting neurons (CSF-cNs) in larval zebrafish.

Strengths:

Anatomical validation of transcriptomic candidates using HCR, providing high-resolution spatial mapping of chemoreceptor expression in CSF-contacting neurons and neighboring spinal cord cells. The work broadens the potential understanding of CSF-cNs and offers a resource for future functional investigations of CSF-mediated signaling.

Weaknesses:

The principal limitation of the study is that the conclusions remain largely transcriptomic and inferential. Although HCR convincingly validates mRNA expression, no protein-level evidence is provided to demonstrate receptor translation or subcellular localization, leaving uncertainty regarding functional receptor availability at the CSF interface. Moreover, the study does not establish whether the proposed ligands are present in the relevant CSF microenvironment or engage the identified receptors in vivo. As such, the functional significance of the proposed chemosensory pathways remains speculative.

Reviewer #1 (Public review):

Summary:

The Voltage-Dependent Anion Channel 1 (VDAC1) is the most abundant β-barrel protein in the outer mitochondrial membrane and the main conduit for metabolite and ion exchange between the cytosol and mitochondria. Its oligomerization has been proposed to control mitochondrion-mediated apoptosis, making it a prime target for therapeutic intervention in diseases associated with excessive cell death, such as neurodegenerative disorders and autoimmunity. VBIT-4 is a small molecule developed to inhibit VDAC oligomerization and has shown therapeutic potential in various preclinical models. Despite its widespread use, the mechanism of action of VBIT-4 has not yet been fully elucidated. In this paper, Ravishankar et al. combine a suite of biophysical approaches with computer simulations to demonstrate that VBIT-4 forms water-permeable defects in membrane bilayers without any detectable effects on VDAC1 channel properties or oligomerization. Furthermore, cytotoxicity assays revealed identical VBIT-4 IC50 values in wild-type and VDAC1-KO cells, indicating that its activity does not depend on VDAC1. Collectively, these findings cast significant doubt on the widely held assumption that VBIT-4 is a specific inhibitor of VDAC1 oligomerization. Instead, it appears that VBIT-4 functions as a membrane-active compound.

Strengths:

This is a carefully conducted and well-written study that highlights potential side effects of VBIT-4, a compound that has been used to study the role of VDAC1 in a range of physiological and pathological conditions. The work is of interest to a broad readership by showcasing the importance of a systematic assessment of drug-membrane interactions to identify potential off-target membrane-driven effects of small molecules that may be mistakenly attributed to the inhibition of specific proteins. Its strength lies in the variety of complementary approaches the authors used to rigorously challenge the effect of VBIT-4 on VDAC1 organization and function. Overall, the experimental data are compelling and of high quality.

Weaknesses:

The authors used high-speed atomic force microscopy (HS-AFM) to study the impact of VBIT-4 on VDAC1 oligomerization in real time at nanoscale resolution. Toward this end, they adsorbed POPC:POPE:cholesterol membranes reconstituted with or without VDAC1 on mica. This revealed that the addition of VBIT-4 produced small perforations in the bilayer that were independent of VDAC1. In the absence of VBIT-4, VDAC1 showed the characteristic honeycomb topography that the authors described in a previous study (Reference 17). To quantitatively assess whether VBIT-4 affects VDAC1 organization, they analyzed protein compaction within clusters using inter-protein distance measurements. This analysis revealed no significant difference in VDAC1 organization between control conditions, 1 uM and 10 uM VBIT-4, supporting a model in which VBIT-4 primarily perturbs the lipid matrix rather than VDAC1 assemblies. This conclusion is based on the assumption that VDAC channels retain some lateral mobility in bilayers adsorbed onto mica. Do the authors have evidence that this is indeed the case? Did they also perform HS-AFM on VDAC1-containing membranes treated with VBIT-4 prior to adsorption onto mica?

Reviewer #2 (Public review):

Summary:

This manuscript challenges the widely used interpretation of VBIT-4 as a specific inhibitor of VDAC1 oligomerization, arguing instead that it acts primarily as a membrane-active compound. Using high-speed atomic force microscopy, electrophysiology, liposome leakage assays, Laurdan fluorescence, microscale thermophoresis, coarse-grained molecular dynamics, and cell-based assays in wild-type and VDAC1-knockout HeLa cells, the authors show that VBIT-4 partitions into lipid bilayers, induces membrane defects and leakage, and causes VDAC1-independent cytotoxicity within a concentration range commonly used to infer VDAC1-specific effects.

Strengths:

The main strength is the convergence of several independent approaches to the same conclusion. Atomic force microscopy directly visualizes VBIT-4-induced defects in lipid regions while VDAC1 assemblies remain apparently intact. Electrophysiology separates VDAC1 channel behavior from background membrane conductance and shows that VBIT-4 does not measurably alter VDAC1 conductance or voltage gating, while increasing nonspecific membrane permeability. Lipid-only membranes, lipid nanodiscs lacking VDAC1, and VDAC1-knockout cells provide important controls supporting a VDAC1-independent mechanism.

The wild-type versus VDAC1-knockout cytotoxicity comparison is a particularly strong test of VDAC1 independence. The observations that VBIT-4 is poorly soluble, aggregation-prone, and sensitive to storage conditions are also important, as they offer a plausible explanation for variability across previous studies. The revised manuscript is further strengthened by quantitative analysis of VDAC1 organization in atomic force microscopy images and by simulations including multiple VDAC1 molecules.

Weaknesses

The main limitation is that the conclusion that VBIT-4 does not affect VDAC1 oligomerization is strongest for the specific readouts used here: atomic force microscopy measurements of cluster compaction, VDAC1 channel properties, and simulated assembly behavior. These are direct and informative measurements, but they are not identical to the chemical cross-linking readouts used in much of the prior VBIT-4 literature. Readers should therefore distinguish between VDAC1 cluster organization in membranes, as measured here, and cross-linking-defined VDAC1 proximity.

A second limitation is the uncertainty around effective VBIT-4 concentration. Because VBIT-4 is poorly soluble, aggregation-prone, pH-dependent, membrane-partitioning, and storage-sensitive, nominal added concentration may differ substantially from the concentration of active compound available in each assay. This complicates comparisons across the different in vitro, simulation, cellular, and previously published assays.

The coarse-grained simulations provide a coherent mechanistic framework for membrane partitioning, aggregation, and defect formation. However, the VBIT-4 coarse-grained model is newly parameterized and is used to support a quantitative partitioning argument. The manuscript would be easier to interpret if the coarse-grained-derived partition coefficient were reported with uncertainty, convergence information, and protonation state, and compared with a matched all-atom octanol-water partition estimate from the same atomistic model used to build the coarse-grained mapping. This matters because the partitioning argument is used quantitatively to relate micromolar aqueous VBIT-4 to millimolar concentrations in the bilayer.

Finally, the cellular data strongly support VDAC1-independent cytotoxicity, but the lower-dose mitochondrial functional phenotypes were not directly compared between wild-type and VDAC1-knockout backgrounds. VDAC1 independence is therefore more directly established for cytotoxicity than for the lower-dose mitochondrial phenotypes.

Overall, this work provides a valuable and timely reassessment of VBIT-4, and its central conclusion will be useful for researchers interpreting studies that use this compound as a probe of VDAC1 function.

Reviewer #1 (Public review):

Summary:

Many previous studies have reported inter-item biases in visual working memory tasks. These biases can be either attractive or repulsive, depending on the particular experiments. It has been difficult to explain these biases in a unifying theoretical framework. Recently, Chetverikov (the first author of the current manuscript) proposed a demixing model for explaining these biases in Ref 22. That paper shows that both attractive and repulsive biases could emerge in the demixing framework depending on the noise properties. The current manuscript seeks to test the predictions of the demixing model experimentally in a series of new experiments and find evidence supporting the demixing model.

Because previous modeling results described in reference 22 (which is a preprint) are essential in interpreting the results reported in the current manuscript, I also studied that preprint and used the results reported in that paper to help interpret the results in this paper. My comments below will also contain discussions of that modeling paper.

Strengths:

Overall, the computational model tested in the paper is novel and interesting.

The demixing framework represents an appealing hypothesis that deserves further investigation.

The current paper provides new empirical data showing that the target stimuli with the same absolute noise level can be either repelled from or attracted to non-target items, depending on the relative noise levels. The observation that biases depend on the relative noise levels is by itself an interesting one, and is consistent with the prediction of the demixing model.

Weaknesses:

While this manuscript contains interesting new experimental observations and theoretical ideas, it has several substantial problems in its current form, which limit the conclusions that can be drawn. The description of the computational model is too brief. The key modeling assumptions need to be better motivated and explained. As the computational models generate different predictions in different regimes, it is a bit difficult to evaluate how well the experimental data support the model at a more quantitative level. Also, the results focused on studying the biases in the behavior; it is unclear whether the model can fully explain the behavior data (such as error distributions or behavioral precision).

Major concerns:

(1) Concerns/suggestions regarding the computational modeling

The current paper seeks to test the predictions of the demixing-based computational model proposed in reference 22. There are several problems with the modeling component in the current paper.

(1a) The description of the model is too brief and difficult to understand. Although the model was proposed in reference 22, it would still be beneficial to provide more details of the model so that readers can understand and appreciate the strengths/limitations of the model.

The generative model and the inference procedure could be better explained to better link the model to the behavior. In particular, how was the observer's behavioral report in each trial modeled? This requires more explanation because currently the demixing procedure estimates four parameters for a given trial, yet for a given trial, only one behavioral report was produced (e.g., current Experiment 1), or two reports were produced sequentially (e.g., current Experiment 2).

(1b) Key modeling assumptions need better justification.

One such key assumption is that on a given trial, each stimulus triggers many samples (or approximately, an entire response distribution), rather than a single sample. This assumption deviates substantially from prior work on ideal observer models. It was not clear whether this assumption is realistic. For the type of stimuli used in the current experiments, perhaps one can argue that each pixel corresponds to one sample of brain activity, thus collectively each stimulus should trigger many samples of activity in the brain. If this were to be the case, it would have two implications. First, the noise parameter in the model should be directly related to the magnitude of the stimulus noise. Thus, one should be able to plug these experimentally-controlled parameter values into the model to directly generate predictions about the biases. Second, when using stimuli with no stimulus variability (e.g., simple grating stimuli), the predicted biases should change. However, it wasn't clear whether this would hold experimentally, i.e., using gratings would lead to different biases or no biases.

If the variability of the samples for a given stimulus involves neural noise, it would be useful to justify why it is reasonable to consider that many samples were generated per stimulus.

(1c) As mentioned in (1b), the model assumes that on each trial, a large number of samples was generated. It would be useful to study and report how the prediction would change when the number of samples generated per stimulus is small. In particular, what happens when each stimulus only generates one measurement? This might be useful for interpreting previous experiment results with grating stimuli.

(1d) Reference 22 studies how the predicted biases depend on the d-prime of the identifying dimension and found that the pattern of the biases varies substantially depending on the information available for the identifying dimension. However, the current paper didn't really discuss this important point. It is also unclear what parameters the authors used for the d-prime of the identifying dimension. Was it fitted directly to the data? The Methods section has some description on the "identifiability dimension", but it was a bit obscure.

Intuitively, when the d-prime of the identifying dimension is very large, the demixing problem becomes irrelevant. In this case, there should not be any biases induced by demixing. In the case of the d-prime for the identifying dimension is 0, the problem should reduce to the simplified 1-d problem studied in reference 22. If my reading of reference 22 was correct, they reported different conclusions. It would be useful to clarify these points.

In any case, the d-prime of the identifying dimension appears to be a key parameter. It would be great to constrain this parameter using the empirical data. When the d-prime of the identifying parameter is small, the observer would easily confuse the probed stimulus with the other stimulus in a given trial. This should lead to poor task performance. Thus, it may be possible to directly estimate the value of the d-prime of the identifying dimension based on the observer's performance, and then use this parameter to generate model predictions accordingly.

(1e) The current model assumes that a large number of samples are generated per stimulus and the brain can manipulate this information to perform the demixing task. It was well documented that visual working memory has a capacity limit (i.e., it can only hold information about a few items); this discrepancy needs to be clarified or addressed.

(2) How well the computational model can explain the experimental data remains not entirely clear

The authors show that there exists a parameter regime that can qualitatively explain the experimental finding. They also show that it is possible to fit the model to the data to explain the bias patterns. However, given that the model is flexible, it would be stronger if the authors could show that the same parameters that explain the biases could also explain other aspects of the behavior, for example, the magnitude of the errors.

In other words, the model is not well constrained in the way it was tested in the paper. But it should be possible to improve it. First, if the noise parameter in the model is determined by the stimulus variability, one can determine it directly based on the external noise in the stimuli (discussed also in 1b) and see what prediction it leads to. Second, from the behavioral data, it may be possible to estimate the noise for the identifying dimension. Doing so will help better constrain the model.

It would also help if the authors could report the best-fitted parameters from the experimental data. From these parameters, one can simulate synthetic data and apply the demixing model to see if the error distribution of the simulated observers is indeed similar to the experimentally measured error distribution. That way, one can check whether the fitted parameter explains the observer's behavioral performance beyond the biases.

Other comments:

(1) How does the model account for the swap errors? I am not sure I understood the way how the swap errors were treated in the paper. To me, substantial swap errors seem to be a consequence of having low d-prime values for the identifying dimension; that is, if there is only little information to discriminate the identity of the two stimuli, swap errors would be large. However, this possibility didn't seem to be mentioned in the paper.

(2) Since the solution of the demixing problem was obtained using a numerical procedure based on EM. It would be useful to check whether the initialization has affected the biases obtained.

Reviewer #2 (Public review):

Summary:

This manuscript investigates the origins of inter-item biases in visual working memory. The authors proposed a computational model where overlapping memory signals are disentangled, inducing memory biases that depend on relative noise levels across items. The key theoretical advance is the prediction that bias direction depends not only on absolute memory noise but on the relative noise levels of target and non-target representations. Using four experiments with color mosaics whose color variability manipulates memory precision, the authors report that biases reverse as a function of relative noise in a manner predicted by the model.

Strengths:

The manuscript is clearly written and theoretically motivated. The experiments are well designed and provide converging evidence for a distinctive and non-intuitive prediction of the proposed model. I found the central result compelling: independently manipulating target and non-target noise leads to qualitatively different bias patterns, consistent with the model's prediction that relative noise is a key determinant of bias direction.

Weaknesses:

The main limitation is that the evidence establishes consistency of the data with the proposed Demixing Model, but does not demonstrate that the model provides a unique explanation of the data. Although the manuscript argues that dominant theories struggle to account for the observed reversals, no formal comparison with alternative computational frameworks is presented. In addition, model fitting results are reported only briefly, making it difficult to evaluate fit quality at the level of individual observers.

Reviewer #1 (Public review):

Summary:

This paper provides interesting observations about the effects of a classical mutation in the daf-2 insulin-like receptor in male C. elegans. The observations are a contribution in and of themselves; however, the conclusions reached about these observations are not supported by the work presented. Most importantly, male-specific effects on healthspan measures are asserted without direct comparison to hermaphrodites. Perhaps more fundamentally, essential features of the methods and experimental design are lacking, which makes formal assessment of the results impossible, especially given our knowledge of negative male-male interactions, which have gone completely unacknowledged here. Indeed, there is a general lack of context for known sex differences in C. elegans, especially in terms of the core elements of longevity, which are presented here as entirely novel but in fact are not.

Major comments:

(1) The main overall criticism of the premise of the paper is that it lacks a clear hypothesis that would lead to explicit experimental tests. Instead, many of the results are observational, and the conclusions reached go beyond the actual experiments conducted. The goal should be explicit and consistent between the introduction/ discussion, and the findings should directly address the goal.

The overall focus appears to be that daf-2 males have an extended lifespan for reasons that are different from hermaphrodites. This conclusion is apparently based on the observation of lipid reserves in mutant animals. However, none of the healthspan measures were conducted in parallel with identical measures in hermaphrodites. How can the authors then claim that males are unique? This is especially problematic since other studies have demonstrated that daf-2 hermaphrodites also have altered lipid composition (Vrablik 2015 Biochim Biophys Acta; Horikawa 2010 Mol Cell Endocrin).

(2) The authors make unwarranted claims about causation from observational data that is correlative in nature. Again, they claim that male longevity is caused by increased lipid reserves. This may in fact be the case, but there is no evidence to show that this is causal, only that lipid reserves are increased in mutant animals. Causation requires an actual experiment, in this case, disrupting lipid maintenance in daf-2 males (e.g., Lapierre 2013 Autophagy). Their conclusions are consistent with their results, but their conclusions are much too strong given the nature of the evidence, especially given the concerns about proper comparisons to hermaphrodites.

(3) With these concerns in mind, all conclusions related to male-specific effects should be statistically tested using a sex-by-treatment interaction term in the statistical model. This is obviously impossible for the healthspan data, but for lifespan, this can be directly tested using (genotype x sex interaction in the CPH analysis). Further, it is unclear why each of the replicates is shown separately in Figure 1.

It is nice that the authors do not directly pool them, as most longevity studies do, but the replicate effects can be included in a more comprehensive model, which would yield an appropriate "average" effect curve.

(4) There is an inadequate review of pre-existing literature and findings that predate the observations presented here. While this is not an issue in general, the authors present their work as entirely novel when it is not.

In addition to Gems and Riddle (2000), which is tangentially cited in the discussion, the following papers should be cited and discussed in the introduction to clarify what is currently known and what remains to be explored:

Partridge and Gems (2002) Mechanisms of aging: public or private?

McCulloch and Gems (2007) Sex‐specific Effects of the DAF‐12 Steroid Receptor on Aging in Caenorhabditis elegans

Hotzi et al (2018) Sex‐specific regulation of aging in Caenorhabditis elegans

Al-Saadi et al (2025) Disruption of the insulin signaling pathway in C. elegans dramatically increases male longevity and enhances reproductive health late in life

In addition, the authors assert that the study of sex differences is unstudied. If the authors are specifically referring to the sex differences in aging research, they should explicitly state that and revise their language to reflect that it is "understudied" rather than "unstudied". But as stated below, there are many studies that look at sex-specific differences in behavior, physiology, development, etc. This is most important in the context of sexual conflict, of which there are many studies that are directly relevant to the work presented here. The authors are encouraged to review some of these papers.

(5) This is particularly important in the context of how the experiments presented here were actually conducted. The methods are inadequate to assess this, and the results would therefore be impossible to replicate in the absence of additional details. Exactly how many individuals were raised on each plate during the longevity assays (and other work) is critical to understanding the results of this study. This is because males have direct, chemically and physically mediated negative impacts on one another (see many papers from the Brunet and Murphy labs). Further, it is not even clear whether males and hermaphrodites were reared separately from one another. Males are known to leave plates without hermaphrodites, which requires appropriate inclusion of censoring criteria in studies such as these. It is unclear whether and how this was handled. Censoring is an essential feature of any longevity study and so needs to be explicitly described in the statistical methods.

The methods describe the use of heat shock to induce the production of males, but it is unclear which generation is being used here. Ordinarily, males would be induced, and then male populations would be maintained by forced mating (picking to ensure that there is a high relative frequency of males) for several generations to eliminate any carryover effects of the heatshock itself. Were the heatshock males put directly into the longevity assays? If so, were hermaphrodites subject to identical treatment? This is confusing, and a potentially critical confound is not performed correctly.

Reviewer #2 (Public review):

Summary:

The manuscript presents interesting observations regarding the exceptional longevity and improved healthspan of male daf-2 mutants. Given the comparatively limited focus on male aging in C. elegans, the study provides a potentially useful characterization of sex-specific effects associated with reduced IIS signaling.

Strengths:

The 4-fold increase in lifespan of male daf-2 mutants is a striking and unexpected observation. The altered fat metabolism between older daf-2 mutant males and hermaphrodites provides further evidence of sex-specific effects.

Weaknesses:

(1) A major limitation of the current study is that the conclusions rely primarily on a single daf-2 allele. It would strengthen the manuscript to validate at least the major observations using an independent daf-2 allele or through daf-2 RNAi. This is particularly relevant for the proposed male-specific enhancement of longevity and healthspan, as it remains unclear whether the observed effects broadly reflect reduced IIS signaling or may be influenced by allele-specific effects or background mutations.

(2) The methods for male lifespan assays require additional detail. Although the authors state that males were generated and transferred every three days, it is not clear whether males were maintained singly or in groups, how many males were placed per plate, or how many were censored by fleeing. These details are particularly important for male aging assays, as male lifespan in C. elegans is known to be influenced by social interactions. Factors such as population density can affect survival and healthspan measurements. Clarifying these procedures would improve reproducibility and interpretation of the reported male-specific lifespan effects.

(3) Because reduced IIS signaling in daf-2 mutants is known to alter metabolism, physiology, and potentially male-derived signaling, it would be interesting to determine whether the enhanced longevity of daf-2 males is influenced by altered male-male interactions or resistance to male-associated toxicity. In this context, clarification of whether lifespan assays were performed with grouped or individually maintained males would be valuable. If not already tested, lifespan analysis under isolated single-male conditions could help distinguish intrinsic longevity effects from potential contributions of population-dependent signaling or social interactions.

(4) In Figure 2D, the body-length measurements in WT males appear somewhat unexpected, particularly the apparent increase between Day 14 and Day 20. Since adult worms are not typically expected to exhibit substantial growth at advanced ages, additional clarification regarding the measurement methodology would be helpful, including confirmation that the scale bars and image scaling were applied consistently across conditions.

(5) The use of palmitic acid barriers following Beydoun et al. (2024) is appropriate; however, it would be helpful to clarify whether WT and daf-2 males exhibited comparable fleeing behavior under these assay conditions. Because male worms are highly prone to plate leaving and censoring, genotype-dependent differences in fleeing behavior could potentially influence survival analyses and the number of censored animals. In addition, as Beydoun et al. primarily characterized these barrier conditions using hermaphrodites, it would be useful to clarify whether comparable barrier effectiveness was observed in male lifespan assays.

(6) Separately, Beydoun et al. (2024) also reported that palmitic acid barrier conditions can influence body-size measurements, whereas PEG-based barriers did not show similar effects on body size. It would therefore be useful to know whether comparable body-length trends were observed under alternative barrier conditions, particularly given the unexpected increase in WT male body length at later ages.

Reviewer #3 (Public review):

This manuscript reports a striking sex-specific effect of the daf-2(e1370) mutation on C. elegans lifespan. The authors show that male daf-2 mutants exhibit dramatically extended lifespan relative to wild-type males, wild-type hermaphrodites, and daf-2 hermaphrodites. The study also demonstrates increased lipid accumulation in these long-lived males, which is increased further over time, improved late-life motility, enhanced oxidative stress resistance, and a requirement for the downstream effector of daf-2, daf-16, for the longevity phenotype.

The interest of the work is the magnitude and consistency of the lifespan effect. The authors report large increases in both median and mean lifespan in daf-2 males across independently replicated experiments. This is further supported by healthspan analyses and their finding that male daf-2 mutants maintain improved motility and stress resistance, which argues against the interpretation that lifespan extension merely reflects prolonged frailty. The genetic epistasis experiment demonstrating loss of the longevity phenotype in daf-2;daf-16 double mutants provides evidence that the effect depends on canonical insulin/IGF-1 signalling.

The main limitation is that at least the first figure is rather an incremental increase on previous work examining the lifespan of daf-2 males, although the authors do indeed show that the effects can be much larger (or more 'plastic') than those previously published. While these findings are potentially important, the manuscript would certainly benefit from a more extensive discussion of how the results compare with prior studies of daf-2 mutants and male longevity, including possible explanations for the apparent discrepancies.

The epistasis experiment shows that this exceptional longevity requires the expression of daf-16. However, in contrast to the initial experiments (Figure 1) that show three replicates of the lifespan experiment (the standard in lifespan work in this model), it appears that the daf-2;daf-16 experiment has only been performed once.

In addition, the lifespan data for hermaphrodite daf-2 mutants appear somewhat unusual. Although the mean lifespan is increased, the median lifespan is reported to be only modestly greater than that of wild-type hermaphrodites. I know that this mutant can give lifespan curves that look like this, but either the use of another allele or of the experimental conditions and how these values compare with previously published daf-2(e1370) datasets would help readers interpret the magnitude of the male-specific effect.

The lipid phenotype is intriguing. It would be interesting to expand this to examine somatic vs embryonic fat. In addition, I noted that in the methods section, the authors use palmitic acid to stop the male worms 'fleeing' the plates; is it possible to rule out the possibility that the daf-2 mutants are simply eating and metabolising/storing this fatty acid barrier differently than their wild-type counterparts? This would be worth considering and controlling for, particularly as male C. elegans have been shown to have dramatically altered metabolic transcriptional profiles. If indeed this increased lipid is responsible for the extreme longevity of the daf-2 mutant males, it would be desirable to try to link this mechanistically to the phenotype.

Overall, the evidence convincingly supports the conclusion that male daf-2(e1370) mutants are exceptionally long-lived under the conditions tested and that this phenotype requires DAF-16. The work has the potential to make an important contribution to understanding sex-specific regulation of ageing, although further contextualisation within the existing literature would strengthen the manuscript.

Reviewer #1 (Public review):

Summary

In this paper, the authors provide a systematic investigation of structural brain differences associated with congenital aphantasia (self-reported lifelong absence of voluntary visual imagery). Specifically, the authors analysed a structural neuroimaging dataset involving 18 individuals with aphantasia and 18 visualizers to test two competing hypotheses: (1) that aphantasia reflects alterations in visual pathways and early visual cortex, and (2) that it instead reflects differences in higher-order frontotemporal and cingulate systems. To test these hypotheses, the authors employed multiple analysis approaches (e.g., cortical morphometry, tractometry, graph-theoretic network analysis).

They report structural differences between the two groups in frontotemporal and cingulate systems. In contrast, they found no reliable group differences in early visual cortex or major visual tracts. On this basis, they propose that aphantasia is primarily associated with differences in higher-order systems supporting integration and conscious access to internally generated representations, rather than with deficits in sensory visual representations themselves.

Strengths

(1) The present work addresses an important gap in the mental imagery literature, providing a systematic investigation of structural neuroimaging differences in congenital aphantasia. By showing that structural differences between aphantasics and visualizers are mainly concentrated in frontotemporal and cingulate systems (rather than in visual cortex), it makes an important step toward a better understanding of individual differences in mental imagery and provides a set of candidate regions for future mechanistic work.

(2) A key strength of the study is the multimodal approach employed to address the main research question, integrating tractometry, functional region-of-interest (fROI)-based tractography, graph-theoretic network analysis, and surface-based cortical morphometry, which provide a converging assessment of structural differences between aphantasics and visualizers.

(3) The complementary use of Bayesian analyses alongside NHST to assess evidence for null results is a further strength of this work.

Weaknesses:

(1) A weakness of this work is related to aspects of the framing and, in particular, what can be confidently inferred from the results. The framing of existing accounts of aphantasia in the Introduction appears limited in that it reduces the views on aphantasia to two options (sensory strength account versus conscious access account) without acknowledging a third distinct position, namely that aphantasia reflects a specific deficit in the voluntary generation of imagery (Milton et al., 2021; Zeman et al., 2015, 2020; Whiteley, 2021; Cavedon-Taylor, 2022). Like the conscious access account, the view that aphantasia involves a deficit in the generation of sensory representation also speaks against the hypothesis of reduced sensory strength of internally generated representations. This third view could be acknowledged/discussed as it also maps quite well onto the presented results.

(2) Relatedly, I think the main weakness of the paper concerns the interpretation of results being restricted to a lack of "conscious access". The paper frames its findings as mainly evidence for a conscious access failure, the view that visual representations are generated by aphantasics but cannot be consciously accessed. However, the structural findings are equally consistent with a voluntary generation failure, especially since the same higher-order regions examined can also be implicated in the top-down generation and control of imagery. The authors themselves initially define aphantasia as "lifelong absence of voluntary visual imagery". Given the nature of structural imaging data (as opposed to functional data), it is not possible with the present study to distinguish between a lack of generation versus a lack of conscious access. As such, examining this alternative interpretation appears appropriate, and it would considerably strengthen the paper. Structural MRI alone is not sufficient to dissociate imagery generation from conscious access, as these are fundamentally functional questions.

(3) Some inconsistency and lack of clarity around the specific choice of regions/networks, which could be better motivated and explained. E.g., the "core imagery network" analysed in the white-matter connections analysis was derived from a previous 7T study (with which the sample partially overlaps) and is not necessarily the network most commonly associated with visual imagery in the literature (e.g., see Dijkstra et al., 2019; Pearson, 2019). It is, for instance, unclear why V1 was examined in the cortical thickness analysis but not in the previous one, given that both analyses are related to the visual pathway hypothesis. Related to this, in the graph-theoretic analysis, the rationale for network selection is inconsistently established in the Introduction. The attention and salience networks do have some grounding in the Introduction through the mention of specific regions such as FEF and anterior insula, though these are discussed as individual regions rather than as networks. However, the default mode network receives no motivation in the Introduction. More explicit elaboration on these choices would be appropriate.

(3) The interpretation provided in the Discussion tends to oversimplify what is in fact a heterogeneous and rich set of structural findings into a relatively coherent mechanistic account. The observed differences are spatially and directionally variable across tracts, cortical regions, and metrics: e.g., FA is reduced in the UF and posterior interparietal corpus callosum but increased in the dorsal cingulum; cortical thickness is reduced in aPFC but increased in medial temporal regions, and so forth. The Discussion acknowledges this in part (e.g., proposing increased dorsal cingulum FA as potentially compensatory) but does not address the directional heterogeneity systematically. The authors could discuss more explicitly what the opposing directions of effects mean for their overall interpretation. Relatedly, some parts of the Discussion link specific structural findings to specific imagery processes in ways that go beyond what the current data can support. The authors could more clearly distinguish between what the structural data show and what functional interpretations are taken from prior work.

Reviewer #2 (Public review):

Summary:

This paper addresses whether congenital aphantasia reflects an alteration of visual representations themselves, or rather of the systems that allow internally generated representations to reach conscious experience.

Strengths:

The study is novel and ambitious. The authors combine several complementary structural MRI approaches in a rare and well-characterised population, and the convergence of the findings toward frontotemporal and cingulate systems, with relative sparing of early visual cortex and major visual pathways, is particularly interesting because it could affect the way visual imagery is modelled and tested experimentally and clinically.

Weaknesses:

Overall, I found the manuscript conceptually and methodologically strong. My main concern regards the interpretation of the anatomical findings, rather than the findings per se. The authors discuss their results within a rich cognitive framework. However, the current dataset does not appear to include independent behavioural or neuropsychological measures that would allow the proposed cognitive interpretation to be tested in the same participants. As a result, the manuscript sometimes moves quite rapidly from 'these structural differences involve systems associated with higher-order control, salience, conscious access' to 'these structural differences may explain the cognitive mechanisms of aphantasia'. I agree that this is the most interesting interpretation, and probably the right one to explore. Although plausible, it remains indirect. The authors already acknowledge this point when discussing memory, affective control, and semantic processing. However, the same logic should be extended to the interpretation of the full set of findings. For example, if the salience/anterior insula findings are interpreted in relation to access to internally generated representations, it would be useful to know whether aphantasic participants also differ behaviourally on tasks tapping interoception or related aspects of internal monitoring. I appreciate that collecting additional behavioural data may not be feasible at this stage, especially given the difficulty of recruiting participants with such a specific manifestation. However, I think it should be acknowledged more explicitly in a dedicated limitation paragraph.

Reviewer #3 (Public review):

Summary:

The authors investigate the structural brain basis of congenital aphantasia, a condition characterised by a lifelong absence of voluntary mental imagery. They test two competing accounts: one predicting structural differences in early visual pathways, the other predicting differences in higher-order frontotemporal and cingulate systems. To do this, they combine four complementary structural imaging approaches: white-matter microstructure profiling along anatomically defined tracts, tractography seeded from functional regions of interest, whole-brain structural network analysis, and cortical thickness mapping. The main finding is that white-matter differences are selective for frontotemporal and cingulate pathways and absent in early visual pathways, which the authors interpret as support for the higher-order account.

Strengths:

The multi-modal design is a genuine strength: running four independent analyses increases the chance of detecting real effects and of identifying false positives that appear in only one stream. The statistical choices within each analysis are appropriate. Permutation-based correction with a threshold-free method is well-suited to the tract-level comparisons. The use of Bayes factors to quantify evidence for null results, rather than simply reporting non-significant tests, is particularly valuable here, since the absence of visual pathway differences is central to the argument. The robustness checks across multiple brain parcellations for the network analysis strengthen confidence in those findings.

Weaknesses:

The main limitation concerns the relationship between two of the analysis streams. The measure used to weight structural connections in the network analysis is calibrated to match fiber density estimates derived from the same diffusion signal that drives the white-matter microstructure differences. If the two groups differ in tissue organisation in certain pathways (which the microstructure analysis suggests they do), that difference will feed into both measures. The authors should acknowledge this dependency when discussing convergence across analyses.

More broadly, the imaging metrics used throughout (measures of fiber organisation and weighted connection counts) reflect what the diffusion model captures from the tissue and cannot be directly read as measures of axon number or connection strength. This is a known limitation of the field, but it is relevant to the strength of structural claims made in this paper.

The network analysis is presented without comparison to a null network. Without this, it is hard to know whether the node-level differences reflect specific network topology or simply follow from overall differences in connectivity weight or density between groups.

The study runs four separate discovery analyses on the same 36 participants, each corrected within itself but with no control across analysis streams. At 18 participants per group, this is exploratory work. Some of the language used in the abstract and discussion, like "first comprehensive characterization" and "selective structural phenotype", reads as more definitive than the data support at this sample size. Framing the results as hypotheses to be replicated would make the paper stronger.

The paper frames the results as distinguishing between two competing accounts. The positive evidence for the higher-order account is clear. The absence of differences in visual pathways is a different kind of result: it means such differences were not detected in this sample, not that visual pathways are uninvolved. The discussion at times moves toward that stronger conclusion, which the data do not support.

The cortical thickness analysis finds one cluster in the predicted direction, while the other analyses each return multiple effects. One cluster in a whole-brain search with 18 participants per group is not strong evidence and should not be presented as equivalent to the other results.

Effect sizes are reported without confidence intervals throughout. With 18 participants per group, the uncertainty around those estimates is large, and confidence intervals would give readers a more accurate sense of what can be concluded.

Reviewer #1 (Public review):

In their manuscript Arjun et al. investigate the role of the histone acetyl transferase Gcn5 in controlling drosophila blood cell homeostasis in the larval lymph gland. Using gcn5 zygotic mutants as well as targeted knock-down and over-expression of Gcn5 in various lymph gland cell populations, they show that these manipulations impact (but in a rather haphazard manner) niche cell number, blood cell progenitor maintenance, plasmatocyte differentiation, crystal cell differentiation, DNA damage accumulation. Their results suggest that Gcn5 controls autophagy and show that reducing the expression of the autophagy machinery affect blood cell differentiation. By using drugs as well as genetic approaches to modulate the mTOR pathway, they conclude that Gcn5 levels are regulated by mTOR, but that the impact of this pathway on blood cell homeostasis can override Gcn5 function.

Overall, the main conclusions are sound but interpreting several lines of experiments and results remain complicated. Consequently, the overall picture of the role of Gcn5 in Drosophila larval lymph gland development, and its relationship to mTOR and autophagy, remains unclear.

Reviewer #2 (Public review):

Summary:

Drosophila haematopoiesis has been shown to be governed by a number of signalling pathways such as JAK/STAT and Dpp. This important study shows a role for nutrient sensing and autophagy in determining blood cell differentiation. The authors show that General control non-derepressible 5 (Gcn5), a histone acetyltransferase affects blood cell differentiation. Gcn5 also negatively regulates autophagy through its effector TFEB which directly regulates autophagy genes. The authors also show that mTORC1 modulates Gcn5 levels and through it TFEB activity thus acting as a fine-tuning mechanism which maintains optimal levels of autophagy.

Strengths:

The main strength of the work lies in the interesting finding that cellular metabolic processes such as autophagy has a direct role in blood cell differentiation and has the potential to be of interest to those working on vertebrate haematopoiesis as well. The report has generated intriguing data, using promoters specific for sub sections of the lymph gland, that different cellular subsets of the lymph gland contribute differently towards haematopoiesis, but this is not followed up in detail and the final conclusions are derived from a combination of whole lymph gland perturbations as well as those from specific promoters.

Weakness:

(1) Gc5 seems to be expressed throughout the lymph gland but modulating it in the subsections do not have the same result. It is very striking that the knockdown of Gcn5 in the prohemocyte population does not have an effect on differentiation whereas overexpression does. And the modulations of Gcn5 in PSC also has variable effects across hemocyte subpopulations which is not explored in the manuscript. Interestingly, also the domain deletion constructs show differential effect on blood cell differentiation when altered solely in the prohemocytes which is not explained. While Gcn5 can be seen in all sections of the lymph gland in the first figure, under the HHLT-Gal4 and Hml-Gal4, Gcn5 looks cytoplasmic and almost completely excluded from the nucleus strikingly unlike Gcn5 expression under the Collier-Gal4 and Dome-Gal4. The rest of the experiments in the manuscript are done with multiple promoters, with autophagy flux measured by modulating Gcn5 with a pan hemocyte promoter, but the mTORC1-Gcn5 axis is explored using chemical modulators which affect the whole of the lymph gland (Fig7) or using two pro-hemocyte promoters (Fig8).

(2) The knockdown of Gcn5 seems to affect the gland size (A compared to B and C). Since mTORC1 is a central regulator of cell size, it is possible that some of the effects seen in these knockdowns are potentially through mTORC1 affecting size suggesting that the signalling axis between mTORC1 and Gcn5 might not be a one-way axis as suggested in Figure 9. Also, this would mean that in experiments where absolute cell counts of crystal cells or niche cells are used to assess blood cell differentiation, further analysis to consider total cell numbers in the lymph gland would strengthen the manuscript.

(3) A genetic manipulation of mTORC1 specifically in the pro hemocytes would strengthen the role of mTORC1 in the pathway rather than the chemical modulation which affects the whole of the lymph gland.

Comments on the revised manuscript:

Overall, the revisions make the narrative more coherent. The authors have also added data which substantiates their conclusions.

However, in some instances, the authors are not clearly able to explain the discrepancies in the data (Gen-5 depletions under the Hml-Gal4 in the whole larval lysates remove p62 completely) which is not ideal.

A query regarding the discrepancies in the immunofluorescence data: The authors have removed the IF data which suggested that there could be differences in the shuttling of Gcn5 between the nucleus and cytoplasm. The authors suggest that immunofluorescence issues are at the root of these variable results, but the reviewer wonders whether there could be further unexplored mechanisms re: shuttling that is unexplored here and would have been potentially novel.

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 weaknesses raised in the previous round of review.]

Summary:

This study examines whether gaze direction actively shapes choice during food preference decisions or whether gaze and choice evolve largely independently until the moment of commitment. The established framework in this context, the aDDM, assumes that gaze causally biases the accumulation of evidence in favour of the fixated item. The authors show convincingly that this model fails to fit key behavioural patterns across several datasets, as do other published models that make the same assumption. The authors propose an alternative model (Post-Decision-Gaze or PDG) in which gaze and decision formation are decoupled: gaze does not influence the decision process, nor is it drawn toward the ultimately chosen item, until after the decision threshold is reached. Only during the motor execution period (after commitment) is gaze directed to the chosen option. They demonstrate that this model fits several observed patterns better than the aDDM and related variants.

Strengths:

The work thoroughly considers multiple models and datasets. It advances an interesting alternative perspective on gaze-decision interactions and highlights meaningful shortcomings in existing models. The authors take the time to explain how modelling assumptions produce specific patterns in the data, which is certainly insightful to readers interested in the modelling of value-based decision making.

Weaknesses:

It is unclear to what extent the model's success relies on the way non-decision time is formalised in the model. In the proposed PDG model, non-decision time is decomposed into separate visual encoding, saccadic execution, and manual execution components. Several values (assumed or recovered) do not match known physiological or behavioural ranges. This is a common issue in the literature, and the authors may want to address it in light of broader work discussing what non-decision time consists of in both manual and saccadic actions (e.g., Bompas et al., 2024, Non decision time: the Higgs boson of decision, Psychological Review).

Reviewer #2 (Public review):

Summary:

Zylberberg et al. reanalyze eye-tracking and behavioral data to test two predictions of the attentional Drift Diffusion Model, finding that these predictions are not met. Similarly, predictions of normative models (inspired by rational inattention) are not in line with the data, and the authors propose a post-choice model of attention. This model better accounts for the two effects but also does not account for all patterns, so the authors conclude that eye movements most likely reflect both pre- and post-decisional processes.

Strengths:

A clear strength is the systematic falsification-based approach of the paper, establishing (partially) new predictions and testing to what extent these are met by extant models and by a newly developed theory. The authors do a good job in providing intuitions behind the effects and the reasons why models such as the aDDM predict them. The paper is of substantial relevance for the field, as it shows that effects pertaining to the last fixation(s) should be interpreted with caution. Another strength is the paper's transparency as the authors clearly acknowledge that their new model does not do a perfect job either.

Weaknesses:

The paper focuses on analyzing the Krajbich 2010 data, but shows that the second effect replicates in many other datasets. A more principled approach, in which both effects are analyzed and presented for all datasets, would be more convincing. The results should then be shown together for clarity/readability.

Similarly, it would be nice to show to what extent the models' predictions depend (not depend) on using the best-fitting parameter values (are there any parameter settings under which the two effects are not predicted?)

Reviewer #3 (Public review):

Summary:

In this study, the authors reanalyzed choice, RT and gaze datasets collected from human subjects performing a food-choice task. They show that models that posit a causal role for attention in shaping the decision-making process fail to account for empirical observations in the data. These include the attentional drift diffusion model (aDDM) and models that derive attention-choice associations from an optimal policy. The authors show that a model that assumes that gazes are directed towards the chosen option after decision commitment captures more (but not all) empirical findings, suggesting that attention may reflect decisions once they are made instead of contributing to their formation. However, this post-decision-gaze (PDG) model failed to capture all aspects of the data, suggesting that gaze may reflect both decisional and post-decisional operations, and existing models are still missing some features of the gaze-directing process. The authors provide convincing evidence that post-decision gaze explains a number of empirical findings in this task.

Strengths:

(1) The analyses are generally appropriate, and the conclusions are supported by the data.

(2) The study was rigorous, as the authors considered a number of alternative possible models for behavior, and evaluated their performance based on a wide range of qualitative predictions (as opposed to exclusively relying on model comparison).

(3) The proposal that gaze may largely reflect post-decisional processes is interesting, and as far as I am aware, novel.

Weaknesses:

There was limited discussion about why one might allocate attention post-decision. I would have appreciated more discussion on the potential functional consequences or implications of post-decision gaze.

Reviewer #1 (Public review):

McGaughey and Gold ask where in the decision process the flexibility of evidence accumulation arises, proposing that it is not solely a property of downstream integrators but is also supported by stimulus-specific sensory adaptation in the middle temporal area (MT). Recording single-unit activity in rhesus macaques during a motion direction-discrimination task in which an adapting stimulus of varying temporal stability precedes an identical test stimulus, they find that more rapidly changing contexts produce weaker and less discriminable MT responses to the test stimulus, which they argue accounts in part for context-dependent changes in decision-making behavior. Through session-level correlations they further identify pupil-linked arousal as a parallel, apparently separable contributor.

The main strength is the shift of perspective toward the encoding stage: rather than treating MT as a static input to flexible downstream integrators, the authors show that early sensory cortex can itself contribute adaptive, context-dependent signals that shape behavior. The conceptual advance is supported by a well-designed paradigm-total exposure to each motion direction is matched across conditions and the test stimulus is held identical-together with single-unit recordings and simultaneous pupillometry. The behavioral effect is consistent across three animals, and the fact that context-dependent differences emerge over repeated stimulus presentations within a trial, rather than as a sustained baseline offset across blocks, ties the effect convincingly to stimulus-specific adaptation.

The behavioral effect constrains the temporal dynamics of decision formation but does not uniquely identify its algorithmic basis: a leak, a saturating non-linearity, or a reduction in the gain of integration are all compatible with a shallower rise of accuracy with viewing time, and the reduced MT discriminability is itself an encoding-stage efficiency effect of this kind. The manuscript appropriately treats the algorithmic basis as unresolved, noting that distinguishing these accounts would require analyses not available here, such as reverse-correlation or motion-energy kernels with lower-coherence test stimuli.

The inference that the adaptation- and arousal-related signals operate independently rests on the absence of session-wise correlations between the neural and pupil measures and their behavioral contributions. Given the noise in the trial-wise estimates, this is best read as consistent with, rather than demonstrating, true independence, as the authors note.

Overall, the authors largely achieve their aim of showing that sensory adaptation in MT shapes the evidence available for time-dependent perceptual decisions. The evidence for a sensory-encoding contribution is convincing, while the claim of independence between adaptation and arousal is more tentative and is framed as such.

Reviewer #2 (Public review):

McGaughey and Gold trained rhesus macaque monkeys to perform a motion-direction discrimination task in which a behaviorally irrelevant adapting stimulus with either fast or slow direction alternations preceded a variable-duration test stimulus, while simultaneously recording single-unit activity in area MT and pupil diameter. They report that adaptation to the more rapidly changing stimulus was associated with reduced behavioral sensitivity, attenuated test-evoked MT responses, and larger pupil-linked arousal signals. The authors interpret these behavioral changes as evidence for context-dependent adjustments to the temporal dynamics of decision formation and argue that these adjustments are supported by both sensory adaptation in MT and arousal-related mechanisms. More broadly, they conclude that flexible evidence accumulation in dynamic environments arises from distributed adjustments across sensory encoding and neuromodulatory systems rather than solely from changes within a downstream accumulator. If correct, this interpretation has important implications not only for our understanding of perceptual decision making, but also for broader theories concerning the functional role of sensory adaptation.

The conclusions of the paper are generally supported by the data. Evidence for adaptation-induced changes in sensory encoding, behavior, and pupil dynamics is convincing, and the revised manuscript substantially strengthens the connection between the behavioral findings and the proposed decision-making framework.

Comments on revised version.

The revised manuscript provides a clearer account of how recent stimulus history influences behavioral performance. In the original version, aspects of the psychometric functions were interpreted as evidence for a more leaky evidence-accumulation process, although some of these effects could potentially have reflected alternative mechanisms, including influences of the adapting stimulus on short-duration trials. The additional analyses and discussion included in the revision clarify that information from the adapting stimulus contributes to behavior at short viewing durations and appropriately temper claims regarding the specific computational mechanism underlying the observed behavioral effects. While the data do not uniquely identify whether these effects arise from changes in leak, other nonlinearities, or related decision processes, they provide convincing evidence that recent temporal context influences the temporal dynamics of decision formation.

My original review also noted that different sections of the manuscript relied on different behavioral metrics and analytical approaches when relating behavioral changes to neural and pupil-linked measures. The revised manuscript now provides a clearer rationale for these choices, including distinctions arising from the different trial types and time windows used in the neural and pupil analyses.

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:

Kashiwagi et al. undertook a population analysis of dendritic spine nanostructure applied to the objective grouping of 8 mouse models of neuropsychiatric disorders. They report that spine morphology in cultured hippocampal neurons shows a higher similarity among schizophrenia mouse models (compared with autism spectrum disorder (ASD) mouse models) and identify an effect of Ecrg4 (encoding small secretory peptides) on spine dynamics and shape in these models.

Strengths:

The study developed a method for objectively comparing spine properties in primary hippocampal neuron cultures from 8 mouse models of psychiatric disorders at the population level using high-resolution structured illumination microscopy (SIM) imaging. This novel technique identified two distinct groups of mouse models according to the population-level spine properties: those with ASD-related gene mutations and those with schizophrenia-related gene mutations. Functional studies, including gene knockdown and overexpression experiments, identified an effect of Ecrg4 on the spine phenotype of the schizophrenia model mice.

Weaknesses:

The main weakness is that the study is wholly in vitro, using cultured hippocampal neurons. The authors present this as an advantage, however, arguing that spine morphology as measured in a reduced culture system can demonstrate direct effects of gene mutations on neuronal phenotypes in the absence of indirect influences from nonneuronal cells or specific environments.

Reviewer #2 (Public review):

Okabe and colleagues build on a super-resolution-based technique they have previously developed in cultured hippocampal neurons, improving the pipeline and using it to analyze spine nanostructure differences across 8 different mouse lines with mutations in autism or schizophrenia (Sz) risk genes/pathways. It is a worthy goal to try to use multiple models to examine potential convergent (or not) phenotypes, and the authors have made a good selection of models. They identify some key differences between the autism versus the Sz risk gene models, primarily that dendritic spines are smaller in Sz models and (mostly) larger in autism risk gene models. They then focus on three models (2 Sz - 22q11.2 deletion, Setd1a; 1 ASD - Nlgn3) for timelapse imaging of spine dynamics, and together with computational modelling provide a mechanistic rationale for the smaller spines in Sz risk models. Bulk RNA sequencing of all 8 model cultures identifies several differentially expressed genes which they go on to test in cultures, finding that ecgr4 is upregulated in several Sz models and its misexpression recapitulates spine dynamics changes seen in the Sz mutants, while knockdown rescues spine dynamics changes in the Sz mutants. Overall, these have the potential to be very interesting findings and useful for the field.

Reviewer #1 (Public review):

Summary:

This important study examines how antibiotic-resistant bacterial cells can protect neighboring sensitive cells in mixed populations that occupy both surface-associated and freely growing states. Using experiments in Enterococcus faecalis together with a mathematical model, the authors test the hypothesis that protection would be stronger in biofilm-associated populations, but instead find that resistance-mediated protection extends broadly across both population types. The work provides evidence that antibiotic efficacy depends strongly on community composition, population density, and density-dependent detoxification dynamics.

Strengths:

A major strength of the study is the close integration of experimental measurements with a relatively simple quantitative model that captures many of the observed population dynamics. In particular, the work highlights how interactions between antibiotic detoxification, cellular growth, and saturation at carrying capacity can generate nonintuitive behavior, including the reported population inversion effect. The agreement between the well-mixed model and the experimental observations is convincing, and the spatial analyses suggest that cells within the biofilm are sufficiently intermixed that large-scale spatial segregation is unlikely to dominate the observed behavior.

Weaknesses:

The mechanistic interpretation could, however, be clarified further by more explicitly emphasizing the competing timescales associated with detoxification, growth, and resource limitation. The current results suggest that when resistant cells are initially abundant, detoxification occurs rapidly relative to growth, allowing the population to approach carrying capacity after relatively few doublings, whereas slower detoxification at lower resistant fractions may permit greater expansion of sensitive cells once antibiotic concentrations decline. Additional direct measurements of antibiotic concentrations over time would also strengthen the connection between the experimental system and the modeling framework by testing whether the detoxification dynamics assumed in the model are quantitatively appropriate, although this seems very plausible.

The study also raises interesting questions regarding the role of spatial structure and exchange between planktonic and biofilm-associated populations. It would be informative to explore whether biofilm-specific protection becomes more pronounced at lower antibiotic concentrations, where local detoxification may compete more directly with antibiotic penetration into the biofilm, and in this context, the dynamics of exchange between biofilm and planktonic populations would be interesting to understand. Overall, the evidence supporting the central conclusions is convincing, and the study will likely be of broad interest to researchers studying microbial communities, antibiotic resistance, and collective population dynamics.

Reviewer #2 (Public review):

Summary:

In this manuscript, Martins et al. examined the cooperative response of E. faecalis cells to beta-lactams, in both planktonic culture and in biofilm. They found that the competition outcome between the susceptible and resistant strains is frequency dependent; they have also quantified how the competition curves change with inoculation OD and antibiotic concentration. To the authors' surprise, the competition dynamics are not that different in biofilm and in planktonic culture, which the author attributed to the unstructured nature of the thus-grown E. faecalis biofilms, quantified through correlation analysis. Using a well-mixed model capturing growth, death, and drug degradation by the resistant cells, the authors were able to quantitatively capture the experimental observation.

Strengths:

Overall, the data presented are solid. Although there is not much surprise after the understanding that the E. faecalis biofilm is unstructured, the manuscript still provides a useful "null case", so to speak, for researchers in the field when considering antibiotics in the context of biofilm. The theoretical model presented and the procedure of fitting the experimental data are useful to the research community.

Weaknesses:

One clarification the author should make is on the biofilm growth process. Specifically, could staining experiments be performed to demonstrate the secretion of the extracellular matrix? Just by looking at Figure 1b, it is hard to say. It remains a question whether the biofilm culture simply contains unstructured clusters rather than real biofilms (that are usually structured).

Reviewer #3 (Public review):

Summary:

The authors studied social aspects of antibiotic resistance by co-cultivating antibiotic-resistant and sensitive Enterococcus faecalis (an important pathogen) as biofilms to assess the extent to which sensitive cells can take advantage of the protection provided by resistant cells against both a beta-lactam antibiotic and in the presence of a B-lacatamase inhibitor. By quantifying the proportion of each cell type using fluorescence microscopy, they conclude that protection is provided equally in the biofilm and planktonically, and that the biofilm is completely unstructured with regard to the locations of the two cell types. A mathematical model is then used to show that no spatial information is needed to recapitulate the results and that the protective effect can be described completely by the growth rates of the two cell types and the affinity of the β-lactamase to the antibiotic and inhibitor. The strength of evidence is difficult to assess due to unclear descriptions of some methods, and the significance of the findings is limited by the experimental setup, where antibiotics were added very close to the time of inoculation.

Strengths:

The co-cultivation of antibiotic-resistant and sensitive bacteria allows for exploration of the social aspects of antibiotic resistance. Fluorescently-tagged strains allow for unambiguous tracking of the two cell types. The simultaneous analysis of biofilm and planktonic cells enables insight into whether these different growth modalities are influenced by social aspects of antibiotic resistance. In analyzing the structure of the biofilm, the use of a null model with randomized cell positions allows for an accurate determination of whether the observed data are due to some effect; however, as noted below, there is a caveat to this analysis. The broad observation that biofilm and planktonic populations are linked is generally supported by the data; however, this result is closely tied to the experimental setup used. The development of a mathematical model that can recapitulate results from a second set of data with values obtained from fitting a different set of data shows robustness of the model for using it to explain the results.

Weaknesses:

The observed results are tied very closely to the experimental setup of adding antibiotics very close to the time of inoculation, but this connection is not discussed. The described 'population inversion' effect is better described as frequency-dependent selection for resistant cells, but frequency-dependent selection is not discussed. Confocal microscopy was used to quantify the relative proportion of antibiotic-resistant and sensitive cells in the biofilm; however, it is unclear if the entirety of the Z stacks was used to determine these proportions. This is also the case for the analysis of whether the sensitive/resistant cells are non-randomly distributed in the biofilm: it is unclear whether the vertical distance between cells was taken into account. The authors claim that biofilm and planktonic bacteria are protected equally by the presence of resistant bacteria; however, Figure 1a and b seem to clearly show that the proportion of sensitive cells is higher in the planktonic cells compared to biofilm cells when started from an equal frequency inoculum, meaning this is not always the case. The mathematical model is used to confirm the result that no spatial components are needed to describe the results; however, this is mostly linked to the initial setup of the experiment, where antibiotics are added at the time of inoculation, and no biofilm could form before the outcome of the antibiotic-cell interactions was concluded.

Reviewer #1 (Public review):

Summary:

Lituma and colleagues investigate the role of NMD in astrocytes, an underexplored question given that prior work on NMD in the brain has focused exclusively on neurons. Using a tamoxifen-inducible, astrocyte-specific Upf2 conditional knockout (cKO) mouse, they report that loss of astrocytic NMD causes: (1) reductions in astrocyte cell volume and surface area across hippocampus, visual cortex, and prefrontal cortex; (2) decreased excitatory synapse density, reduced dendritic spine density, and impaired synaptic engulfment; (3) deficits in basal synaptic transmission and LTP, with selective impairment of mGluR-LTD; (4) elevated spontaneous calcium transients in astrocytes; and (5) anxiety-like behavior in the elevated plus maze (EPM) and contextual fear conditioning paradigms. Transcriptomic analysis of FACS-isolated astrocytes identifies 277 differentially expressed genes, ~40% of which carry canonical NMD-inducing features, implicating pathways linked to calcium signaling, phagosome formation, and glial development. A rescue experiment using the CalEx calcium extrusion pump demonstrates partial restoration of synaptic strength and anxiety behavior when astrocytic calcium is normalized.

The study addresses an important gap in our understanding of RNA regulation in glial cells, and the overall conceptual framework is well described. The experimental design is generally appropriate, and the multi-pronged approach lends the main claims a degree of validity.

Strengths:

(1) Novelty: This is the first study to systematically examine NMD function in astrocytes in vivo. The identification of astrocytic NMD targets via RNA-seq combined with an NMD-inducing feature classifier is a meaningful methodological contribution.

(2) Multi-method approach: The authors combine morphological analysis (Imaris 3D reconstruction), synaptic markers (PSD-95, LAMP2 engulfment assay), spine density measurements, acute slice electrophysiology, two-photon calcium imaging, behavioral testing, and transcriptomics. The convergence across these methods strengthens confidence in the claims.

Weaknesses:

(1) While the transcriptomic analysis is a valuable addition, the connection between specific NMD targets and the observed calcium phenotype remains largely correlational. The authors identify Gabbr2 and Adora1 as upregulated candidates with canonical NMD features and speculate that their elevated expression drives aberrant calcium signaling. However, no validation (e.g., qRT-PCR or protein-level confirmation) of these candidates is presented. The mechanistic pathway between NMD disruption and elevated calcium is thus inferred from pathway analysis rather than demonstrated. This is a significant gap between the transcriptomic and physiological arms of the study, and the authors should be more explicit about this limitation or, ideally, provide at least one validated target.

(2) The reduction in astrocyte surface area in cKO mice is interpreted as contributing to reduced synapse contact and engulfment capacity. This is a reasonable hypothesis, but the study does not directly demonstrate that reduced astrocyte territory correlates with reduced synaptic coverage at the level of individual cells or brain regions. The temporal sequence of these events is unknown. Do morphological deficits precede synaptic changes? Clarification and qualification of this causal chain in the Discussion would strengthen the manuscript.

(3) LFS-induced LTD is unaffected, while mGluR-LTD is reduced. This is intriguing and potentially informative about astrocyte contributions to distinct LTD mechanisms, but the difference receives limited discussion. Given the relevance of mGluR signaling to calcium dynamics and the identified pathway enrichments (GPCR signaling), this specificity deserves more attention.

(4) The CTRL + CalEx condition is included in the EPM experiment but not in the electrophysiology or calcium imaging experiments, making it difficult to fully assess whether CalEx itself has off-target effects on synaptic transmission or anxiety in wild-type animals. The CTRL + CalEx EPM data (Figure 7F) appears to show a modest reduction in open arm time relative to CTRL, which, if robust, would suggest that excessive calcium reduction in astrocytes is also anxiogenic. This finding would be physiologically relevant and deserves comment.

Reviewer #2 (Public review):

Astrocytes are highly responsive to their environment and play a range of critical roles in brain function. Lituma et al. theorize that one mediator of that responsiveness is the regulation of RNA stability. They therefore undertake an assessment of astrocytes missing Upf2, a protein required for mRNA degradation via nonsense-mediated decay. This is an interesting study, approaching astrocyte biology from a novel angle. The authors take on an ambitious set of experiments, spanning morphological assessment, synaptic engulfment, electrophysiology, behavior, and calcium imaging.

The authors show convincing data that knocking out Upf2 in astrocytes impairs synaptic plasticity, affects behavior, and changes the complement of astrocytic mRNA. These results, in and of themselves, are intriguing and suggest that NMD is an important biological process in astrocytes, warranting further study.

My primary concern is whether the authors may be largely studying dying cells. The idea that NMD disruption has a dramatic effect on astrocyte morphology is an intriguing idea, but it is not fully established here. The nuclei in the example cKO morphology images appear small and/or fragmented. This raises concerns that the authors did not ensure that they had the full 3D morphology of the astrocyte in the section, and the cell is in part cut off, which would compromise any data on the morphology. The authors state that the tissue was sectioned at 70 um. The diameter of an astrocyte in the adult mouse brain is typically between 50 and 70 um. Unless astrocytes are perfectly positioned in the center of the slice, at this thickness, the majority of astrocytes will almost certainly be partially cut off. More detail on how cells were chosen and what quality control metrics were implemented would alleviate concerns here. An alternative possible explanation for these small/fragmented nuclei is that cKO astrocytes may be unhealthy to the point that they are actively dying. Using the transgenic ZsGreen label, the authors state that they observe a size change (Figure S4); this is not readily apparent and is not quantified in any way. It does appear from these images that there may be a loss of some astrocytes; cell death, which would also be an interesting finding, is a fundamentally different process than morphologic restructuring in living cells. The authors do attempt to count astrocytes (Figure S6B), but do so with GFAP. This is a fundamentally flawed approach. Because GFAP is not readily detectable in most healthy astrocytes in most gray matter regions, GFAP should not be used to quantify astrocyte numbers; this experiment should be repeated with a better marker, such as Aldh1l1, Sox9, etc.

Synaptic engulfment: This is an extraordinarily high degree of engulfment in the control animals compared to many published studies, leading to concern as to the technical approach. Indeed, the overall low level of PSD-95 signal in control conditions in adult mice is concerning as to the technical accuracy of the approach. It is unclear exactly how the investigators labeled the astrocytes; presumably via the ZsGreen label, but it is never stated, and the only images shown are the highly processed Imaris renderings. The small astrocytic processes, or leaflets, that make up the vast majority of the astrocytic arbor are on the order of 100nm in diameter. The processes shown in Figure 2B are, according to the scale bar, at least 20x that size. It is difficult to have much faith in these results as currently presented.

The signal-to-noise ratio of the GCaMP experiments is worryingly low, likely responsible for the abnormally low dF/F in all conditions and the lack of significant change between control and CalEx, when control astrocytes should show a much higher GCaMP signal than any CalEx-expressing astrocyte. That said, the higher Ca++ in Upf2 KO astrocytes is intriguing. Given the roles of elevated calcium in cell death, this may reflect cells that are unhealthy to the point that they are starting to die.

The authors conduct a FACS-based analysis of astrocytic mRNA from control vs Upf2-KO, with intriguing results. An important caveat, though, is that a large amount of astrocytic mRNA is in the processes. If mRNA stability is being actively and rapidly regulated, it seems likely that the mRNA in the processes would be the most relevant population of regulated mRNA. FACS-based approaches to astrocyte purification will, as robustly shown elsewhere, strip off those processes. Particularly given that the authors have shown that the processes may be the most actively changing astrocytic compartment with Upf2 KO, this is a strange choice of technique vs. something like Ribotag that would preserve the mRNA in processes. At least, there should be some discussion regarding using FACS for this analysis and the consequences for profiling mRNA in astrocytic processes.

Minor points:

(1) The use of the Aldh1l1-CreER mouse is a strong choice and has been shown to be highly astrocyte-specific. Combining that transgenic mouse with viruses driven by different forms of the GFAP promoter is quite bizarre in several ways. First, GFAP-dependent AAVs have been shown repeatedly to have significant neuronal leak. Second, these mice are, in all cases, receiving two different viruses, driven by different forms of the GFAP promoter, and the non-Cre virus is not Cre-dependent (vs. a much more standard approach of using a Cre-dependent second virus to ensure that all analyzed cells received both viruses). The authors mention that "this experimental design ensures that phenotypes are not caused by an acute effect of tamoxifen." It is certainly true that tamoxifen is not a biologically neutral molecule. However, the mice still receive tamoxifen, both in these morphology virus experiments and in almost all other experiments. This experimental approach is not inherently bad, nor does it necessarily invalidate the data (although the near-certain neuronal contamination due to the GFAP promoter-driven viruses is a concern). It is, however, convoluted in ways that appear unnecessary. If there is a strong rationale for this approach beyond the tepid explanation already present, it should be explicitly mentioned.

(2) The characterization of the knockout is incomplete. While the authors should be applauded for their attempts to phenotype the cells in which they observe Cre-mediated recombination, there are issues with their technical approach. Most importantly, and an issue that affects other analyses in the paper as well: the vast majority of astrocytes in the healthy cortex do not express GFAP. Therefore, using GFAP to claim high astrocyte specificity and efficiency is a fundamentally flawed approach. Second, MBP is a myelin marker, not a cytoplasmic marker, and would not successfully colocalize with a cytoplasmic marker like ZsGreen even if recombination in oligodendrocytes did occur. Third, recombination at one set of LoxP sites is not a reliable indicator of recombination at other sites. Recombination efficiency is highly dependent on the spacing between the LoxP sites and cannot be reliably extrapolated to other floxed genes without validation. Finally, the most likely culprit for off-target recombination with Aldh1l1-CreERT2 (or other astrocyte-selective Cres, and certainly the GFAP-based viral promoters) is neurons, which the investigators did not test for. Neuronal Aldh1l1-CreERT2 leak is most likely to occur in the hippocampus. With the images shown in Fig S3, it is unclear whether it is possible to convincingly colocalize Upf2 staining with a cytosolic marker of all astrocytes, such as Aldh1l1 or S100b, but such data would be more appropriate. An alternative approach to validation would be in situ hybridization.

(3) Supplementary Table 2 should include gene IDs, not just Ensemble IDs.

(4) It is not fully clear what the investigators are denoting as a spine in Figure 2E; the two images do not appear to have the large degree of difference that the quantification suggests. The oversaturation of the signal complicates assessment.

(4) A more detailed discussion of the rationale behind the timeline would be helpful. What is the half-life of Upf2, and how rapidly do NMD genes build up upon Upf2 disruption? In particular, in the case of virus experiments, the timeline is quite fast: ~2.5 weeks from injection to analysis. ssAAV expression takes over a week to reach appreciable levels.

Reviewer #3 (Public review):

Summary:

The authors investigate mRNA targets of the nonsense-mediated decay (NMD) pathway in astrocytes and link the dysfunction of NMD in astrocytes to aberrant synaptic transmission that has downstream effects on behavior. Specifically, they find a link between the aberrant synaptic transmission with elevated spontaneous calcium signaling in astrocytes, and functionally they demonstrate that manipulating astrocyte calcium signaling with CalEx modulates astrocyte calcium signaling towards wildtype levels and improves anxiety behavior. They investigate the astrocyte calcium signaling changes in Upf2 conditional knockout mice in several brain regions that have been linked to anxiety behavior, including the hippocampus and prefrontal cortex. They also observe aberrant astrocyte calcium signaling in the visual cortex, demonstrating that dysfunction of the NMD pathway in astrocytes has widespread effects on synaptic transmission in various brain regions. This work identifies, through RNA-Sequencing, potential mRNA targets of NMD in astrocytes, and shows that pathway enrichment of these targets highlights calcium signaling. Altogether, this work highlights the importance of the basic cellular process of NMD in astrocytes, which are known to have extensive local translation of proteins in their perisynaptic processes. NMD may be particularly important in astrocytes due to their intimate association of processes with neuronal synapses, and the authors suggest that alterations to NMD function in astrocytes may be an important avenue for future investigation in neurodevelopmental disorders.

Strengths:

Altogether, this work is a critical foundation for future research into astrocyte contributions to neurodevelopmental disorders. The authors do a thorough characterization of astrocyte conditional Upf2 knockout mice in several brain regions. They present a complete story that connects molecular events (NMD pathway regulation of mRNA degradation) to astrocyte regulation of circuit activity to organismal behavior. The electrophysiological analysis is thorough, and the manipulation of calcium activity ties astrocyte calcium activity to anxiety behavior. The RNA-sequencing dataset is useful to the scientific community and provides a resource of candidate molecules that might be dysregulated in neurodevelopmental disorders.

Weaknesses:

The study suffers from some overstated claims and a lack of statistical rigor in some experiments, as detailed below.

(1) The title states that "Astrocytic Nonsense-mediated mRNA decay regulates calcium signaling to support synapse function and restrain anxiety". The term "restrain anxiety" implies that the NMD pathway has a direct effect on a molecular switch to control anxiety. Anxiety behavior is a complicated process, controlled by many biological phenomena and synaptic transmission in the circuit as a whole, and is not directly linked to a specific NMD mRNA target. This title is overstating the findings of the study.

(2) In general, the first figures (1-2) suffer from low power (N = 3) and statistical rigor. The statistics are inflated by analyzing individual fields of view and per-cell data rather than performing the statistics on the average of biological replicates. It is preferable to show the biological replicate data so that readers can observe the natural biological variability between replicates.

(3) The claim that astrocytes have decreased engulfment of synapses in the Upf2 conditional knockout mice is not strongly substantiated by the data. The resolution of confocal microscopy and the static nature of histological images make it difficult to measure synaptic engulfment as an active process. Additionally, the metric of quantifying the % occupancy of PSD95 puncta within the total astrocyte volume may be skewed due to overall differences in cell size (shown in Figure 1). There is not much discussion of how a decrease in astrocyte engulfment of synapses may lead to decreased synapse number. To the contrary, one might expect decreased engulfment to result in increased synapse density.

(4) The authors use Gfap as a marker to count astrocyte cell number and assess if there are changes in cell number between genotypes (Figure S6). However, Gfap does not label all astrocytes in the cortex and, in fact, is rather an aberrantly expressed marker in conditions of inflammation, as opposed to the hippocampus, where Gfap is basally expressed in all astrocytes. In the cortex, there seems to be a trend for reduced Gfap in the conditional knockout mice, which may suggest differences in astrocyte molecular signatures rather than cell numbers. Another astrocyte marker, like Aldh1L1, will be more accurate to assess this question histologically.

(5) The authors state that "Preventing abnormally high basal calcium activity in NMD-deficient astrocytes restores normal excitatory synapse function...". However, this claim is not substantiated by the data. CalEx manipulation certainly shifts the input-output curve but does not restore to wildtype baseline levels (Figure 6E). Additionally, synapse number does not appear to be restored to wildtype levels (Figure 6D - although the p-value for this comparison is now shown). The investigators do observe improvements in anxiety phenotypes, suggesting there is some modulation of circuit activity, but the claim that CalEx manipulation restores baseline synaptic transmission is not supported.

Reviewer #1 (Public review):

Summary:

The article "Nanoscale organization of beta-II spectrin within segments of the membrane-associated periodic skeleton in mouse sciatic nerve axons" by Gazal et al. looks into the organization of the spectrin scaffold in mouse sciatic nerves using super-resolution microscopy. It is now well established that axons, across species, contain a membrane-associated periodic scaffold mainly composed of circumferential actin filaments and longitudinally arranged spectrin tetramers. While super-resolution imaging of neurons in cell culture is relatively easy, exploring the ultrastructure of myelinated axons in intact nerve fibers is a daunting task. Nevertheless, the authors have attempted this by fixing and preparing cross-sections of sciatic nerves. They have then tried to quantify the fluorescence intensity patterns of specific components, especially that of labeled beta-II spectrin and have analysed its distribution.

One of the main findings is that spectrin is distributed along the axonal periphery and along the outer part of the myelin sheath. By labelling multiple cellular components and using intensity analysis, the authors show the sequence of structural organization of a few key components. They see that, unlike in the case of axons in culture, the axonal cross-sections within the sciatic nerve deviate significantly from a circular shape. They then use 3D-dSTORM to investigate the distribution of beta-II spectrin along the axonal circumference. They see that this distribution is very heterogeneous, both in the sizes of spectrin puncta and their arrangement along the periphery. The amount of spectrin scales linearly with axonal circumference.

Strengths:

Super-resolution imaging of axons of intact nerve fibers to investigate the organization of beta-II spectrin.

Weaknesses:

While most of the findings, like the spatial distribution of spectrin and related components, are reasonably well supported by data, I have concerns regarding the subsequent claims made in the article. The detection of axial periodicity based on the observation of a peak in the inter-tetramer spacing distribution is not very convincing, and a 3D representation (or a video of 3D reconstruction) would have been better. And so are the claims on characteristic spectrin spacing of 200 nm along the axonal circumference. A peak in the distribution does not imply a periodic arrangement.

Reviewer #2 (Public review):

Summary:

This is an interesting paper by the Unsain lab looking at the nanoscale organization of the membrane-associated periodic cytoskeleton in mouse sciatic nerve axons. The precise organization of the structure remains unclear, especially in vivo, and this manuscript significantly adds to our knowledge of this important structure. While some of the findings in the study are somewhat expected (though still valuable to see in an in vivo setting), an interesting observation is the presence of discrete nanoscale clusters that scale up with the size of the axon, which challenges previous assumptions.

Strengths:

Strong, convincing data; clever combination of imaging and analytical tools to make novel points; well written; excellent composition of figures.

Weaknesses:

(1) Figure 2A/3A: The large and small clusters of spectrin, as seen in cross sections, are unexpected and novel. The authors have done a clever job of combining imaging and analyses, but some things are still unclear. First, the authors should be consistent in their language when they talk about the spectrin clusters. Recommend precise language to define the small and large clusters when they first appear in the text, and then use the definitions consistently throughout the text. Second, based on the data shown, one does not get a clear idea of how the small and large clusters are organized along the longitudinal axis of the axon. In that context, are Figure 2B and C from imaging along the longitudinal axis? If not, it's unclear how the authors can conclude that the spectrin assemblies have a distance of ~170 nm along the linear axis. In general, a perceived limitation of this study is that while the authors have done a good job looking at cross sections, there is no information on the longitudinal distribution of spectrin in these axons. Looking at both cross- and longitudinal sections would also clarify details about the large spectrin clusters. For instance, are they small sausage-like structures, or long rods of spectrin running along the length of the axon? One assumes that all the analyses in Figures 3 and 4 are from the small clusters. Can the authors do a similar analyses of the large clusters? Finally, a schematic model showing both cross- and longitudinal- sections would make things clearer, but the authors would need to show the longitudinal data for that.

(2) It is interesting to think that the larger spectrin accumulations may be similar to the condensate-like structures seen by Boyer et al., as the authors mention in the discussion. In that context, it is possible that these focal accumulations are local reservoirs of spectrin that are also seen in mature axons (indeed, these accumulations were also seen in mature axons in the Boyer et al. paper, and they also speculated that these accumulations may be local reservoirs). Can the authors check if actin/adducin is also present in these larger spectrin accumulations?

(3) While talking about the nanoscale clusters, it is important to specify that the authors are talking about circumferential clusters. Though the writing is excellent, one still does not get the precise definition of "clusters" from just reading the abstract, and it would be good if the authors could work on that more (I recognize that this is not easy to do).

Reviewer #3 (Public review):

Summary:

In the presented work, the authors investigate spectral staining in axons of the sciatic nerve, where the MPS has been detected before using STED microscopy. They employ 3D-dSTORM in tissue sections and analyze the data, measuring localization of clusters on the axon perimeter and the relative distribution of those. From these data the conclude that large gaps in spectrum localizations exist and that clusters around the axon exist that are spaced at 200nm.

Major Comments:

(1) The presented data are at times overinterpreted, and the discussion lacks a critical view of the data. For example, the statement "...Unlike previous suggestions from qualitative evidence in cultured neurons (REfs), βII‑spectrin distribution in MPS segments of peripheral nerves is discontinuous, with extensive stretches of the perimeter lacking βII‑spectrin." is quite strong, given it is based on immunofluorescence staining and dSTORM microscopy in tissue. Absence of evidence of staining is not evidence of absence.

(2) The authors claim in the abstract that "The number of these clusters scales linearly with the axonal perimeter, maintaining a constant membrane occupancy of ~20% across varying axon diameters." Again, this is from a cut through an axon, while measuring the density of clusters on the perimeter. If they claim area occupancy, an area should be imaged, and the dots (clusters) should be measured in surface coverage in a 2D projection of the axonal surface.

(3) In general, this reviewer suggests being a bit more moderate in statements such as: "These findings challenge simplified models of the MPS based on cultured systems and demonstrate that the MPS in peripheral nerves is composed of discrete structural units." These statements are bold from the relatively few measurements in a single method and a single viewpoint. Especially when considering that techniques such as dSTORM depend extremely highly on labeling density, and apparent clustering of localization is highly prone to misinterpretation. If the authors desire to make such statements, working with endogenously labeled protein would be warranted. The authors should at least hedge such statements.

(4) If the authors want to make statements about general organization, why do they not compare adjacent cuts through the axon? If there are continuous spectrin filaments, the clusters should appear at the same site across repeated cuts through the axon.

Besides this, this reviewer welcomes the effort that has been made to establish dSTORM in tissue sections and to investigate the MPS in native tissue.

Reviewer #1 (Public review):

In the wild, bacteria can be found in a wide range of metabolic states, including states in which they are resource limited. Because phages heavily rely on the infected cell's molecular machinery to replicate, it is natural to wonder how phage-bacteria interactions depend on the metabolic state of the cell. In this work, Marantos et al. investigate specifically how the rate of infection of 5 different phages changes between cells grown in energy-rich conditions and cells grown in energy-depleted conditions. Their results clearly show that 4 out of the 5 phages studied display a significant reduction in infection rate in cells that are energetically depleted and provide a potential explanation for this observation by looking into the mechanisms that these phages use to irreversibly infect their host cells.

The work also tries to explain the observation using a mathematical/mechanistic model that describes infection as the sequence of two steps, where a phage first needs to bind to a cell receptor, from which it can potentially unbind, and then irreversibly infects by injecting its genome. The mechanistic interpretation offered by the model highlights an interesting trade-off between adsorbing to a metabolically active host and discriminating between active and inactive hosts that, somehow, a phage has to optimize. It would be interesting, in the future, to investigate how different phages optimize this task.

Comments on revised version.

I am happy with how the authors have addressed all the comments. The manuscript is much clearer and more readable and the previous overstated claims have been removed/clarified.

Reviewer #2 (Public review):

Summary:

The authors investigate the dependence of phage adsorption rates on host metabolic state, using 5 coliphages that differ in their infection cycles and host receptors. They find that four of the 5 phages showed significantly reduced infection under low metabolic states, with phage that generally have weaker adsorption being more strongly affected by low metabolism. The authors complement their findings with a 2-step infection model where phages can disengage from their hosts after initial adsorption. The paper illustrates the power of standardized experimental protocols for quantitative trait comparisons and highlights the dependence of phage infection success on host physiology.

Strengths:

The paper is well written and clearly structured.

The experiments are well designed and particularly commendable is the diligent use of control scenarios to allow for quantitative comparison between phages. This standardized protocol will be valuable for the entire phage community.

The authors convincingly show the impact of host physiology on phage adsorption success. This dependence has so far mainly been considered for intracellular phage replication and the paper shows that host physiology has to be taken into account at all steps of phage infection.

Reviewer #3 (Public review):

Marantos et al. showed that for some coliphages, the energetic state of the bacterial host cell has a strong impact on whether phage infection is initiated. The authors drew this conclusion from the observation that there are more free phages remaining in the medium after infection of arsenate-azide-treated cells as compared to after infection of untreated cells. These data were analyzed and reported both as ratios of the treated vs. untreated conditions and using a mass-action kinetic model of phage-cell collision in the infection mixture. The data supported the findings that for four phages infecting Escherichia coli bacteria, namely, phages λ, 𝜙80, m13, and T6, the phages are less likely to initiate infection if the host bacteria are energy depleted. However, for phage T5, the authors found that their infection propensity is not impacted.

As I have stated in the first submission of this manuscript, the data presented by the authors clearly supported the principal conclusion of the study. The five phages chosen by the authors represent different viral lifestyles and infection mechanisms, highlighting the potential applicability to other Escherichia coli phages. Finally, the authors successfully use a classic mass-action model of phage-cell collision to interpret their data. The simplicity of their experimental assay, combined with the use of this mathematical model, offers other investigators who study phage-bacterial interactions in other contexts a potentially useful toolkit to examine infection in general, and specifically, the dependence of phage infection on the host's metabolic state.

Comments on revised version.

In this revised version, the authors have successfully resolved all of my comments. I appreciate that the main text has been majorly revamped, which greatly helps the readers follow the motivation behind the experiment and analyses, and interpret the data. I agree that the revised terminology choice "commitment to infection", instead of the previous interchangeably used "adsorption"/"entry", is much more logical, considering the experimental data. I also commend the authors for writing the modeling part in a very clear, pedagogical, and instructive manner. Overall, I believe that this manuscript will be valuable to those who are interested in phage-bacterial interactions.

Reviewer #1 (Public review):

Summary:

This paper presents a toolkit for the transformation of Blastocystis. The authors have screened a number of selectable agents, promoters and reporter genes and present their findings. This resource will be of immense use to those in Blastocystsis field, as well as those seeking to establish transformation tools in other species where such tools do not yet exist. Establishing new transformation tools is extremely challenging, and the authors have done an excellent job.

Strengths:

The authors have carried out a systematic screen of promoters, reporter genes and selectable agents. They have screened numerous for each, and all the data is presented. It is good to see when things did not work as well as when things did - so this data set is extremely useful indeed.

Weaknesses:

The findings are reported by reporter gene assay (microscopy). No evidence is given using genetics. The authors claim that the DNA is maintained episomally. However, could it be possible that there is integration? No PCRS/RT-PCRs are shown (although it can safely be assumed that the DNA/RNA is present where the transformation was successful), nor are any Western blots. These would have been useful to show that the P2A ribosomal skipping had occurred, and that proteins were expressed individually rather than as a polyprotein.

Comments on revised version.

The authors have revised their manuscript to clarify that molecular analyses have not yet occurred and have resolved the technical/publication issues with the figures. I look forward to seeing these tools used in future publications to answer important questions in Blastocystsis research.

Reviewer #3 (Public review):

Summary:

The primary objective of this study was to establish a practical and functional framework for propagation of stable transgenic cell lines of Blastocystis, a common animal gut microeukaryote. Although the work focused on Blastocystis ST7-B, a subtype with relatively low prevalence in humans, this choice is justified by its association with more frequent negative health effects. Beyond their relevance to the medical field, the methodological advances described here have the potential to also expand cell biology studies of this anaerobic organism, including its unusual mitochondria and redox metabolism.

Strengths:

Prior to this work, genetic tools for Blastocystis were very limited, relying on a single strong promoter-terminator combination. The authors successfully expanded the available promoter set across a range of expression strengths by testing two dozen variants in luciferase-based assays. Critically, they developed an integrated workflow from a modular transgenic construct design to an expanded inventory of molecular components (promoters, reporters), optimized DNA delivery, stepwise antibiotic resistance-mediated clonal selection and propagation, and to reporter validation. The evaluation of several anaerobiosis-compatible labeling strategies for live (and fixed) cell optical imaging will be particularly useful, with the SNAP-tag system appearing especially promising for Blastocystis.

Weaknesses:

The presented data generally provide a solid support for the conclusions that the work reached, but clarification of reasoning and several inconsistencies, as well as amendments to visual presentation of the data would be highly beneficial, as detailed below.

(1) Episomal persistence of the construct:

The manuscript repeatedly assumes, including in its title, that constructs persist in Blastocystis in their episomal form, but no direct evidence is provided. Although this interpretation is plausible, it should be identified more clearly as provisional. Nuclear genomic integration (e.g., via NHEJ) remains a possible explanation unless supporting evidence or rationale is provided to exclude it. Testing whether the phenotype persists without drug-mediated selection in the generated transgenic cell lines would help strengthen the case for episomal maintenance.

(2) Promoters and terminators:

(2.1) There is a discrepancy between the claimed number of loci (14), from which promoters used to drive luciferase expression were derived, and those detailed as having been actually generated in Table 1 (11). This inconsistency should be corrected or explained, as it creates uncertainty around the accuracy of the dataset.

(2.2) Based on the presented evidence, constructs benchmarked in bioluminescence assays differed only in their promoter composition. Although terminator selection is mentioned in the Methods section, no additional details are provided; for instance, Table 1 and Figure 2 only list 23 promoters in total. Figure 2A likewise shows only promoter-dependent variation. If the terminator was held constant (LeguP1?), this should be stated explicitly. The authors may then consider revising the wording of having tested "23 promoter-terminator pairs" to better reflect that only promoters varied.

(2.3) Promoter benchmarking was done with a plasmid lacking a selection marker, so it is unclear how the maintenance of the luciferase construct was ensured. Without selection, the observed reporter intensity could reflect differential or stochastic plasmid retention rather than promoter strength alone. The luminescence assay was performed 16-18 hours after transfection, but the rationale for this particular timeframe should be explained. In this context, the authors should explicitly state whether the experiments shown in Fig.2A represent biological triplicates or technical triplicates from a single transfection.

(3) Figure 2:

(3.1) Several aspects of the current design may lead to ambiguity for the reader. The boxplots are colour-coded, but it is unclear whether the colours carry meaning or are purely decorative. Because the data are already spatially separated into bins, additional random colouring is redundant and may suggest distinctions that are not intended. In addition, the part A of Figure 2 is split into two panels with the scale for the left panel shown in the right panel and some of the boxplot colours falling in the range of the scale, but not in line with their counterparts in the left panel. Because the colour use is not consistent, it is difficult to tell whether the same scale should be applied to both panels or how it should be interpreted.

(3.2) The left panel of the part A uses a diverging blue-white-red colour scheme, which is most appropriate when the midpoint represents a meaningful central value such as zero. Because the values shown in this graph are only positive, a non-diverging 2-colour scale or a colour palette such as 'viridis' would make the plot easier to interpret.

(3.3) A black background should be avoided: 'B' and 'C' labels are invisible and it draws attention to a distracting design feature rather to the data themselves.

(4) Figure 3:

(4.1) Individual snapshots should be separated more clearly, either by using a white background or by adding visible borders to make the overall composition clearer. As currently displayed, some boundaries between fluorescent channels resemble image artifacts rather than intentional panel divisions.

(4.2) In the parts B-D, the legend should explain more clearly what each image shows and the figure itself would benefit from annotations. There seem to be three sub-panels in each 'condition' of part B (as well as C and D): while the middle and rightmost panel can be easily inferred to represent the fluorescent protein and bright-field image, what the leftmost panels represent is not specified. If DAPI was used to dye DNA, an explanation why mostly multiple labelled regions are visible should be provided.

(4.3) Cell morphology and appearance differ markedly between UnaG/smURFP and SNAP-tag images, which should be explained. A microscope issue is mentioned in the main text, but if that was the cause, the authors should consider replacing the images as the current distortions complicate interpretation.

Comments on revised version.

The revised version provides sufficient clarity and appropriate visual presentation. Some confusion evidently arose due to my misunderstanding, so I thank the authors for their comprehensive clarifications and patience.

Reviewer #2 (Public review):

Summary:

The manuscript titled "Latent gene network expression underlies partial re-evolution of a polyphenic trait in the worker caste of ants" by Vasquez-Correa et al. aimed to study genetic mechanisms underlying developmental plasticity, especially binary polyphenism in queen vs worker ant castes. This is an interesting question regarding the extent to which phenotypic traits were altered, lost or regained, and how molecular pathways (upstream vs. downstream) can facilitate this process.

In ants, reproductive castes (queens and males) develop wings as well as 3 ocelli for mating flights and other activities, while worker castes are wingless, and in some species, they have either no or a reduced number of ocelli. The phylogenetic analysis showed that in the Camponotini ant clade, the one-ocellus phenotype re-evolved in three species independently. The authors analyzed the conserved developmental pathways between Drosophila (well-established) and ants using HCR (a high-quality in situ hybridization technique). They found that although upstream genes for the development of ocelli (otd and hh) showed similar expression between castes, downstream genes (toy, eya, and so) had reduced or no expression in workers of C. floridanus, and this differential expression may lead to partial or complete loss of ocelli. Consistently, workers develop rudimentary tissues, suggesting that they initiate the ocellus developmental process but somehow stop it before adulthood.

Strengths:

Evo-devo approaches to reveal conserved molecular pathways of ocellus development. High-quality HCR provided convincing evidence of the expression of key genes in ocelli, eyes and antenna throughout larval development.

Using HCR, the authors showed differential expression of downstream genes in males vs. soldiers vs. minor workers of C. floridanus, which might explain phenotypic differences between castes.

Comments on revised version.

The authors have addressed the concerns in the revision. No further comments.

Reviewer #3 (Public review):

Summary:

This paper examines the loss and re-evolution of specific organs during the evolution of ants. The authors show that these organs, the ocelli, disappear and are re-evolved in different ant species, and in different ant castes within these species. The Authors show that this is linked to a conserved GRN discovered in Drosophila, that appears to underlie the development of the ocelli, and demonstrate that this GRN appears to remain active in the developing heads of ants that have no ocelli- implying that it is the evolutionary latency of this GRN that allows loss and subsequent evolution.

Strengths:

This manuscript has outstanding imaging of a very difficult developing organ, and the key data, fluorescence in situ hybridisation, is done well and clearly shows what the authors wish to demonstrate. The methods are well described and underpin the whole work.

The authors convincing demonstrate that gene expression patterns imply the conservation of the ocellus gene regulatory network from Drosophila to ants. They further show that this network is present even in ants that don't produce an adult ocellus, but do show that in those species, loss of a developing nascent ocellus (which they identify) occurs at the same time as an interruption in the expression of the key genes in the GRN. All of this data is beautifully presented and explained.

Weaknesses:

There is one key weakness in that there are no functional students that indicate that the GRN actually does make the ocellus, though the expression patterns are convincing. This applies to loss of the ocellus as well. It would be nice to see that transient loss of the ocelli GRN might lead to loss of ocelli in ant species that have them. These are very difficult things to achieve as the key genes have earlier developmental roles, such that CRISPr knockouts would not be interpretable, and transient RNAi in the head capsules of developing pupal ants would be challenging.

As the authors note in their response this is very difficult to achieve. While the addition of this data would raise this manuscript to an outstanding one, I think the data presented is solid, well-presented and provides novel insight.

Reviewer #1 (Public review):

Summary:

Cisplatin, a platinum-based chemotherapeutic agent, induces intra- and interstrand crosslinks, thereby blocking DNA replication and transcription and triggering apoptosis. The authors aim to demonstrate that DNA polymerase κ (Polκ), traditionally seen as a translesion synthesis (TLS) polymerase, able to synthesize DNA through DNA lesions, plays a non-catalytic, structural role in stabilizing replication forks and protecting cells from cisplatin-induced cytotoxicity. A key finding of this work is the identification of two novel molecular axes: PCNA-Polκ-Polδ, which facilitates efficient DNA replication; PCNA-Polκ-USP18, which stabilizes DNA damage response proteins. These findings provide actionable therapeutic targets for overcoming head and neck squamous cell carcinoma chemoresistance, a cancer with rising incidence and limited treatment options.

Strengths:

The study relies on a robust experimental design, including Polk allegedly CRISPR-Cas9 knockout, siRNA knockdown, and rescue experiments with wild-type, catalytically dead, and PCNA-interaction-deficient Polκ variants, supporting a non-catalytic role of Polκ. The work also reports a strong implication of Polk in cisplatin resistance, the identification of USP18 as a possible Polk partner and the consequences of Polk depletion on post-translational stabilisation of DNA damage response proteins.

Weaknesses:

The findings reported in this manuscript cannot be generalized to all cisplatin resistance mechanisms, as cells may develop multiple adaptive strategies to survive chemotherapy. Polκ's role varies across cancer types. For example, it is downregulated in stomach and colorectal cancers but upregulated in HNSCC, lung, and ovarian cancers. Thus, its use as a biomarker or drug target may be context-dependent.

Acute cisplatin exposure is sufficient to trigger Polκ upregulation to levels similar to those in resistant cells. However, it remains unclear how long this upregulation persists and to what extent it contributes to survival. Further, the sensitivity of cisplatin-naïve H357 or SCC9 cells (H357-S and SCC9-S) to Polκ knockdown has not been addressed. This is a critical question, as acute cisplatin exposure induces Polκ expression to levels similar to those in resistant cells. This could argue against a direct role for Polκ in mediating resistance and instead suggest indirect mechanisms (like Polκ-dependent mutations during adaptation).

The experimental design and results aimed at demonstrating the existence of a PCNA-Polκ-USP18 axis (Figure 9A) do not fully support the conclusion that these proteins form a stable complex. This set of experiments also lacks essential controls, such as the immunoprecipitated bait and the amount of immunoglobulins precipitated in all conditions. This also applies to the colocalization experiments in cells shown in Figure 9B. Images are poor and lack quantification. Further, Polk is seen mainly cytoplasmic in the upper panel, while it is nuclear in the lower panel. Discrepancies in Polk subcellular localization are also evident in the Supplementary data. USP18 is known to deubiquitinate ISG15-modified proteins (not just ubiquitin). The study does not rule out ISGylation as a contributing mechanism. The experimental design involving analysis of DNA synthesis dynamics at a single-molecule level is not appropriate. Overinterpretation of the data in several parts of the manuscript and lack of rigor in performing the experiments. Inappropriate consideration and absence of discussion of previously published literature directly related to the subject studied in this manuscript. Discrepancy with a previous report regarding the role of Polk in Chk1 phosphorylation (Tonzi et al., eLife 2018). Synergic effect of T2AA inhibitor and Cisplatin have been already described in « naive » cancer cells (Inoue et al, 2014). Another critical point is that the proliferation rate of Polk-depleted cells is slower than that of wild-type cells. Hence, the colony formation assay shown in Figure 2B can be misleading, since the observed differences can be interpreted only as a proliferation problem.

Reviewer #2 (Public review):

Summary:

Building on earlier studies, the authors report a role for pol kappa in mediated cisplatin resistance. Their data on dispensability of pol kappa catalytic activity for cisplatin resistance is consistent with previous reports. They further demonstrate that the PIP box of pol kappa is critical for cisplatin response. Based on these observations, the study concludes that targeting pol kappa and PCNA interaction can be a viable approach to overcome cisplatin resistance.

Strengths:

Indications that interaction between Pol kappa PIP box and PCNA can be targeted to overcome cisplatin resistance.

Weaknesses:

(1) The study has used a model of cisplatin resistance and found that the phenotype is specifically reliant on upregulation of Pol kappa. They also observe that in this model of cisplatin resistance, there is rapid degradation of multiple repair proteins, including ATM, ATR, HR and NHEJ proteins upon knocking out Pol kappa. However, it is unclear how the resistant model was derived. Also, since the data and almost all experiments in this manuscript were performed with a single model of cisplatin resistance, the conclusions should be taken with caution.

(2) There are also inconsistencies in findings. Increased G2 arrest and no change in origin firing are being observed despite a significant reduction in Chk1 protein levels.

Reviewer #3 (Public review):

This manuscript investigates the role of PolK in cisplatin repair. While in general it is considered that polK is not involved in the repair of cisplatin-induced DNA damage, the authors show that in a very specific scenario, namely cisplatin-resistant head and neck cancer cells, loss of PolK causes cisplatin sensitization, implying a role in cisplatin repair by polK in these cells. It is also implied that these cells acquire cisplatin resistance by overexpressing polK, but this is not really investigated. The authors then go on to show that DNA replication in the presence of cisplatin is affected by the loss of polK in these cells and also identify USP18 as a potential polK interactor in these cells with a similar phenotype. They claim that polK and USP18 form a pathway that allows cisplatin tolerance in these cisplatin-resistant head and neck cancer cells. The findings are interesting and useful to the field; however, the manuscript, in its current form, has several issues. Most importantly, the mechanism of USP18 has not been investigated. In addition, the manuscript does not flow fluidly, and instead, various experiments are put together without a clear logic. Some of the claims are not substantiated by the data shown.

(1) The experiments in Figure 1 using a few cell lines from various types of cancers are not enough to conclude that polK expression is specifically induced by cisplatin in some types of cancers but not others. Since the focus of this study is head and neck cancer, the authors should show the expression of PolK after cisplatin treatment in more head and neck cancer cell lines, and not just the two investigated.

(2) It is unclear to me why the authors include H357-S in their experiments. If the idea is that these cells acquire resistance because they overexpress polK, then the authors should investigate this by exogenously overexpressing PolK in H357-S cells and test if these cells are cisplatin resistant.

(3) In addition, the authors should create the polK knockout in H357-S cells as well and include it as a control in their experiments.

(4) Page 6, line 28: the comet assay does not measure DNA degradation, but rather DNA breaks.

(5) Figure 4B: How does the overexpression of PolK mutants compare to endogenous PolK expression? It is important to assess if this expression is similar or of much higher magnitude.

(6) Page 9, line 22: "For such a function, the catalytic domain of PolK becomes dispensable, whereas its interaction with PCNA is sufficient to drive efficient replication". I do not understand what data the authors used to make this claim. The interaction and colocalization studies should be performed with the PIP mutant. Similarly, this mutant should be used in the HU DNA fiber assays.

(7) It is unclear how USP18 acts. What are its substrates? Chk1/2, BRCA1, BRCA2? This needs to be investigated. The impact of PolK on this activity needs to be assessed as well (is PolK needed for USP18-mediated de-ubiquitination of these DSBR proteins?). As it stands, the manuscript does not address the mechanism of USP18 in DNA repair, which is billed as the main finding of the paper.

(8) Do PolK and USP18 interact directly? Experiments using recombinant proteins would be useful to address this.

Reviewer #1 (Public review):

Summary:

This is an important paper examining LTP induced by theta-burst stimulation in hippocampal slices from macaques and rats. While both species show theta-burst-late-LTP, only the non-human primate theta-burst-late-LTP showed synaptic tagging and capture that converts early-LTP into late-LTP in an independent synaptic pathway.

Strengths:

Synaptic tagging is a fundamental feature of repeated 100 Hz-tetanus-induced LTP, whereas theta-burst induction is arguably more physiologically relevant. Thus, synaptic tagging during theta-burst may differ in the two species, a distinction that may prove important in the mechanisms underlying the cognitive differences between the species.

Weaknesses:

Bursts repeated at the frequency (~5 Hz) of the endogenous theta rhythm induce strong LTP, primarily because this frequency disables feed-forward inhibition and allows sufficient postsynaptic depolarization to activate voltage-sensitive NMDA receptors. Therefore, the species differences may be due to differences in inhibition, rather than in molecular mechanisms of maintenance. One way to assess the relative strengths of this early induction mechanism in rats and macaques is to examine the "depolarization envelope" during the sequential bursts, which may be determined from the recordings already obtained. (Larson and Munkácsy, Theta-burst LTP, Brain Res 2015 Sep 24:1621:38-50. doi: 10.1016/j.brainres.2014.10.034)

Another issue is that the PKMzeta-antisense oligodeoxynucleotides block the synthesis of the kinase. However, Mei F, Nagappan G, Ke Y, Sacktor TC, Lu B (2011), BDNF Facilitates L-LTP Maintenance in the Absence of Protein Synthesis through PKMzeta. PLoS ONE 6(6):e21568, provided evidence that BDNF and theta-burst stimulation can act to increase PKMzeta by a protein synthesis-independent mechanism, presumably through decreased degradation. Therefore, the absence of an effect of the PKMzeta-antisense does not exclude the possibility that persistently increased PKMzeta is the mechanism of theta-burst-late-LTP maintenance in mice or macaques. This issue is worth discussing.

Reviewer #2 (Public review):

Summary:

This study compares theta-burst stimulation (TBS)-induced synaptic plasticity in hippocampal CA1 slices from rats and non-human primates (Macaca fascicularis). The authors report that while TBS induces persistent LTP in both species, only primate hippocampal slices exhibit synaptic tagging and capture (STC) under these conditions. They further show increased BDNF and PKMζ expression following TBS in primates and propose that a redundant BDNF/PKMζ signaling architecture supports persistent plasticity in primates, whereas rodent TBS-LTP depends primarily on BDNF. The work aims to identify species-specific specializations in associative plasticity with implications for translational neuroscience.

Strengths:

The topic is potentially important because direct comparisons of hippocampal plasticity mechanisms between rodents and primates are rare.

Weaknesses:

(1) Limited biological replication in the primate experiments

The manuscript's strongest claims rely on data obtained from 36 slices from 7 monkeys, qPCR analyses with n=3 biological replicates, and Western blot analyses with n=3 biological replicates. The effective sample size for species-level conclusions is therefore not large. The manuscript frequently treats slices as independent observations while drawing conclusions about species differences. This is particularly problematic for electrophysiological experiments because multiple slices appear to originate from the same animals. The statistical unit should be the animal, not the slice, unless nested analyses are performed.

The authors should (1) report the number of animals contributing to each experiment, (2) provide animal-level analyses, (3) use mixed-effects or hierarchical models where appropriate, and (4) clarify whether multiple slices from the same monkey contributed to the same experimental condition. Without these analyses, the evidence for species-specific mechanisms remains weaker than presented.

(2) The central STC conclusion requires stronger controls

The most important result is that TBS supports STC in primates but not rats (Figures 1F-G). However, several alternative explanations are not excluded. For example, only a single interval (30 min) between TBS and WTET is examined. Classical STC studies characterize tag duration, PRP availability window, and temporal asymmetry. The current work does not determine whether primates exhibit longer tag persistence, increased PRP synthesis, altered capture efficiency, or merely a shifted temporal window. A temporal series (e.g., {plus minus}15, {plus minus}30, {plus minus}60, {plus minus}90 min) would substantially strengthen the mechanistic interpretation.

(3) Species differences may reflect tissue quality or preparation differences

The manuscript compares 5-7 week-old rats with 5-7 year-old monkeys. These are very different developmental stages. Moreover, euthanasia methods, extraction procedures, and postmortem handling are different. These factors can affect BDNF expression, protein synthesis, LTP magnitude, and transcriptional responses. The authors should discuss these caveats more explicitly.

(4) Statistical reporting is incomplete

Many comparisons report exactly Wilcoxon p = 0.0313 and U-test p = 0.0022, across numerous experiments. This suggests very small sample sizes and discrete nonparametric distributions. The manuscript should report exact n values for each comparison, effect sizes, and confidence intervals.

Second, many genes and proteins are tested. No correction for multiple testing is described. The authors should state whether corrections were applied, and if not, justify this choice.

(5) Interpretation and significance

The study addresses an important and understudied question: whether associative synaptic plasticity mechanisms differ between rodents and primates. The finding that TBS can support STC in the primate hippocampus is potentially novel and impactful. However, the mechanistic evidence remains incomplete, the molecular analyses are underpowered, and several key controls are missing. At present, the data support the conclusion that under the specific experimental conditions tested, TBS-induced plasticity in primate hippocampal slices exhibits greater associative persistence than in rat slices.

The stronger claims regarding evolutionary specialization, fundamentally distinct plasticity rules, altered STC thresholds, and redundant BDNF/PKMζ architecture require additional experimental support.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors have undertaken an investigation of differences between two mammalian species, the brown rat and the crab-eating macaque, in the mechanisms supporting a well-established model of long-term Hebbian synaptic plasticity, Schaffer collateral to CA1 Long-term potentiation (LTP) in the hippocampus. LTP has been long-studied and deeply characterised due to its potential importance in modeling a strong candidate process for the central mechanism of learning and memory. LTP was first discovered in lagomorphs (rabbits), but has since been much more widely studied in rodents (mostly rats and mice), and there has been some complementary work revealing LTP in non-human primates and even in humans, revealing largely overlapping canonical mechanisms of induction, expression, and maintenance. More specifically, this study puts a particular focus on the fascinating associative features of this form of lasting synapse-specific modification, in which a synaptic input can be stimulated with a relatively weak induction protocol that will not produce lasting plasticity on its own, but can undergo lasting LTP if paired with stronger stimulation on a separate synaptic input to the same neuron. This associativity mechanism is particularly attractive within the Hebbian synaptic plasticity framework as it provides a candidate mechanism for associative forms of learning in which stimulus-stimulus, stimulus-reward, stimulus-punishment, or action-outcome associations are formed. A particularly attractive feature of this associative LTP is that there can also be a substantial time-lag between the strong stimulation of one pathway and the weaker stimulation of the other synaptic input, which only undergoes lasting LTP by hijacking the proteins synthesized as a result of strong stimulation elsewhere. This observation has led to the famous tagging and capture hypothesis as an explanation of how such synapse-specific change can be achieved on both stimulated inputs but not on other synaptic inputs, given the potential requirement for cell-wide protein synthesis. This theory, for which there is very strong experimental evidence, posits that a protein tag is left at synapses that have been stimulated with sufficient vigor in recent history, serving as a key mechanism to ensure that those weakly stimulated synapses will undergo change when a larger-scale LTP event occurs due to stronger stimulation elsewhere within a relevant time window. Again, this idea is attractive as it can explain how we might form associations between events that occur slightly separated in time. The manuscript goes on to show that an induction protocol that is particularly physiologically relevant, theta burst stimulation, produces this tag and capture associative effect in ex vivo slices of Macaque hippocampus, much more readily than in side-by-side ex vivo slices of rat hippocampus. Moreover, the manuscript delves into the importance of well-characterised LTP maintenance mechanisms, including PKMzeta and BDNF, which are key factors that ensure that altered synaptic change is maintained for long periods of time despite substantial molecular turnover in the neuron. The observation in this manuscript is that a degree of redundancy for these mechanisms exists in the primate species but not the rodent species, as both mechanisms need to be inhibited to return LTP to baseline in the Macaque, but only one needs to be inhibited to have that effect in the rat. A major emphasis of this study is that there may be a step-wise difference in associative learning mechanisms between rodents and primates that may contribute to their differing cognitive capacities, although I believe a lot more evidence would be required to reach that conclusion.

Strengths:

The strengths of this study are that it is technically very proficient and is from a laboratory that has a long history of seminal work on synaptic tagging and capture. The cross-species comparison, particularly involving non-human primates, is also very hard to achieve, and a major strength here is the side-by-side comparison of slices from rat and monkeys. Further strengths of the study are the use of a number of experimental strategies, including both observation and intervention, to demonstrate differential involvement of LTP maintenance mechanisms. A final major strength is conceptual, as it is undoubtedly useful not only to identify shared mechanisms of plasticity between commonly used model organisms and either humans or much more closely related species such as old world monkeys, but also to reveal differences that have the potential to contribute to differences in memory/cognition.

Weaknesses:

The findings of this study are a very useful building block for understanding how generalisable mechanisms of LTP are. However, arriving at really substantial conclusions from these findings is challenging, as there are a number of variables that are unaccounted for in this study that may explain the differences that have been observed between rats and monkeys. One example of a potential confound to these interpretations is that rats are nocturnal/crepuscular animals, and macaques are diurnal animals. Thus, to undertake a like-for-like comparison, it would be necessary for the rats to be on a reversed light-dark cycle to ensure that the wake cycle of the rat (dark) is being compared with the wake cycle of the monkey (light). It is possible that the authors have done this, but it is not mentioned in the methods section. The reason this is important is that there is a substantial body of work indicating that different mechanisms are at play in hippocampal LTP during wake and sleep. Transcripts and proteins related to synaptic function are dramatically differentially regulated during sleep-wake cycles, and phosphorylation states of key proteins involved in plasticity are also altered. Moreover, synaptic tagging and capture are specifically disrupted by sleep deprivation. Perhaps the authors have already considered this factor and appropriately reversed the light-dark cycle of their rat subjects, in which case a clarification in the manuscript would be useful. Nevertheless, I have used this as an example because there is a variety of potential confounds that may explain the difference between SC-CA1 TBS LTP in rats and monkeys, e.g., circadian rhythms, degree of enrichment, natural light vs indoor lighting, diet, degree of inbreeding, strain, etc. Thus, to make strong conclusions about the potential for differences in plasticity rules/mechanisms and how those may contribute to differences in cognition, I think it would be necessary to compare a wider variety of species, including a good representation of each order (e.g., nocturnal rats and diurnal squirrels, new and old world primates) and not just a single exemplar. I understand, of course, that this is really pushing the boundaries of practicality, but I see no other way to make a strong conclusion or to generalise to mechanisms or properties of plasticity in rodents vs primates. Thus, while I believe the manuscript presents really admirable work, I am not sure the findings are at all easy to interpret.

Reviewer #1 (Public review):

Summary:

This article describes a very ambitious metascience project aimed at testing the reproducibility of a corpus of publications conducted in Brazil. The strength of the approach lies in its systematic, multicenter replication design. The authors focus on three commonly used experimental paradigms in biology: the MTT assay, RT-PCR, and the elevated plus maze.

The effort is commendable and reveals a rather low rate of reproducibility, in line with findings from fields considered less reproducible in the life sciences, such as cancer biology.

Strengths:

The study is supported by a substantial dataset, incorporating multiple independent replication attempts and the use of stringent, well-defined protocols, which strengthens confidence in the overall conclusions.

Weaknesses:

(1) Being neither an expert in metascience nor in statistics, I cannot fully judge the methodological aspects of the article or its extensive supplementary material. I will therefore focus my comments on readability. I found the manuscript difficult to digest. The authors should improve readability if they wish to reach a broad audience of experimental biologists. In particular, they should simplify the description of protocols and highlight the key findings more clearly, using accessible language. See specific points below

(2) The article appears to oscillate between:

i) a description of the approach and the inherent challenges of such a multicenter replication program.

ii) an estimation of reproducibility.

These could potentially form two separate articles: one aimed at a broad audience emphasizing key results, and another focused on methodological aspects for a more specific metascience audience. The Results section currently contains redundancies and is difficult to follow for non-experts in statistics. I also find it challenging to extract the main findings.

A possible improvement would be to include an initial section clearly describing the protocol (replication of a single experiment, across several labs, for three types of assays), followed by a concise presentation of the main results regarding reproducibility in Brazilian science with subsections. Methodological details could be moved either to a Supplementary Information or to a more specific article, while being summarized in the Discussion.

(3) This study evaluates the reproducibility of a single experiment from each article, taken out of its broader context. While this provides an estimate of reproducibility, it does not directly contribute to resolving uncertainties within a specific field. This may represent a limitation compared to other reproducibility projects that attempt to replicate multiple key claims within a given study (e.g., in cancer biology or Drosophila immunity). I found that a weakness is that it does play a role in cleaning a field of wrong statements.

(4) The observation that external observers can predict which experiments are likely to be reproducible is interesting and should be more clearly emphasized.

(5) The manuscript frequently refers to future publications. It would be helpful to clarify what is included in the present article versus what is deferred to subsequent papers

Reviewer #2 (Public review):

Summary:

This is an important contribution to science, not only because large-scale replication studies remain rare despite their value, but also because this one focuses on research that was under represented in previous large-scale efforts. The findings reveal concerningly low replicability in this field, pointing to a problem that warrants immediate attention. Particularly noteworthy is the study's sampling strategy: by randomly selecting experiments from a wide range of publications based on methods, rather than filtering by research area, importance, or citation counts, the authors have produced results that are potentially more representative of the broader literature than those of previous large-scale replication projects in this and other fields. Overall, this is a fantastic contribution that I will be recommending and using in all my open science talks, and from which I have learned a great deal. Congratulations to the team!

Strengths:

A study of this scale inevitably requires an enormous amount of work and methodological care, and this one is clearly both robust and thoughtfully designed. I want to particularly acknowledge the considerable efforts the authors have made to ensure the robustness of their findings. The use of multiple approaches to estimate replicability, combined with a substantial battery of sensitivity analyses, including a multiverse approach on top of everything else, clearly reflects the authors' genuine commitment to understanding their results and the limits of their conclusions. The transparency and sharing of all protocols, materials, and challenges and limitations encountered is also outstanding.

Weaknesses:

There were several instances during my reading of the methodology where I felt the authors relied too heavily on the external supplementary materials, at the expense of basic detail in the main manuscript. I appreciate how overwhelming it can feel to integrate more into an already substantial paper, but without some minimum integration, the reading experience and overall comprehension are too often compromised, at times posing more questions than answers. And it is unrealistic to expect most readers to engage with the extensive supplementary materials provided. Please see the comments below for specific suggestions.

Additionally, I found the discussion rather underdeveloped. There is relatively little engagement with the broader literature, not only with replicability studies from other fields, but more generally with relevant meta-research work on publication bias, blinding, risk of bias, citation practices, etc. Some of the most novel and interesting findings in the paper also receive less attention than they deserve, and the discussion at times reads as a repetition of the results section rather than a critical engagement with them. I would encourage the authors to engage more deeply here, as the study clearly has much more to say. Doing so would further highlight why this study is important for the answers it provides and the questions it can spur. Again, please see the comments below for specific suggestions.

Specific suggestions:

Page 1, abstract: "while t values for replications were positively correlated with researcher predictions about replicability, and negatively correlated with the rate of publications by the original article's last author" - I need to address the question: why t values and not effect sizes, p values, or something else? Update after reading the study: although the authors used others, they seem to place more emphasis on t values, which is not well explained. Without a clear explanation, it just left me wonder why, given that effect sizes would, in principle, be more information.

Page 2, paragraph 2: "reproducibility (defined here as reaching the same results when analyzing a set of data)" - In my opinion, this definition is vague enough that it encompasses not only reproducibility (same data, same methods) but also robustness (same data, different methods), and I would therefore recommend providing a more precise definition. The same applies to replicability (different data, same methods), since the definition used does not highlight the importance of using the same methods, and thus also encompasses generalisability (different data, different methods). Explicitly clarifying these distinctions is particularly important as the field grows and the terms become increasingly mixed up and confusing.

Page 2, paragraph 3: "All of these issues raise concerns about the replicability of published results - something that has not been evaluated systematically in the country" - I would suggest providing more information about why those factors may lead to expected lower replicability, ideally with a couple of sentences supported by references. As it stands, less experienced readers may not follow the argumentation and may consider it speculative.

Page 3, paragraph 2: "We then opened a public call for Brazilian labs that could replicate experiments using these methods and models, advertised by email, social media and lectures in conferences and institutions, to which 73 labs initially responded" - Since recruiting is an important component of this study, I would recommend providing additional details so the reader can better assess how comprehensive and unbiased the recruitment process was. AND Page 5, paragraph 2: Please provide more information about this open call: how was it advertised, where, and when? This is needed so that the reader can assess its comprehensiveness and potential biases. Even the link provided is not specific enough to understand the process, as it only states: "Calls were open to participants > 18 years old with current or previous experience in experimental research in any field and were advertised via e-mails, lectures and social media."

Page 3, paragraph 2: "Based on the expertise of respondents and a feasibility analysis by the coordinating team, we selected 3 outcome assessment methods for replication" - Since this choice determined what was ultimately studied and who could participate, I would like to see more information to understand it: was it based on the most common expertise among respondents? How was feasibility defined and estimated?

Page 3, paragraph 3: How was the manual screening performed? Was it done by one or more people? Was there double-screening to ensure reliability of the screening protocol? Did the authors use a specific decision tree or tool? How were conflicts between observers resolved? Were any other validation steps taken to ensure reliability? The same comments apply to the data extraction (who, how many, validation, protocol, etc.).

Page 3, paragraph 3: As a non-expert, I would need more context about the expected average cost of experiments in this field; otherwise, I cannot assess how representative this sample is or whether potential biases may exist (e.g., cheaper experiments perhaps being expected to be less replicable than more expensive ones). Could expected costs also have affected the reduction in geographical coverage eventually observed in this study (Figure S3)?

Page 6, paragraph 2: "(on a scale of 1 to 5)" - Could you clarify whether 1 means no deviations and 5 means everything deviated? Is that how it was phrased to participants? Was there a threshold used by the coordinating team to decide how many deviations were acceptable? (I would briefly clarify all scales mentioned below to allow easier interpretation throughout.)

Page 6, paragraph 4: How were long-text answers (e.g., justifications) reviewed? Was this done manually by one or more members of the coordinating team, or using any text interpretation tool? What steps were taken to ensure the interpretation of these answers was as objective as possible?

Page 8, paragraph 1: "If issues were found, the lab and coordinating team reviewed them via email until the sources of errors were identified and corrected (see https://osf.io/58vsx for details)." - Could you please provide information about how often these disagreements arose and briefly explain their causes? I am struggling to understand why these discrepancies occurred and how frequently. Without more detail, the error rate presented in the next paragraph is a little concerning.

Page 8, paragraph 4: Please provide the version of any package or software used throughout, and make sure to cite R appropriately (R Core Team XXX). In addition, did the authors calculate the log ratio of means (ROM/lnRR) using escalc()? If so, please report this. If not, I would recommend doing so, as escalc() implements recommended small-sample adjustments that produce slightly different values compared to a simple manual calculation of log(mean1/mean2).

Page 10, paragraph 1: "Coefficients of variation from the original study were compared to the mean coefficient of variation of its replications using Wilcoxon's signed rank test" - I wonder how these CVs were calculated - whether simply as SD/mean or using escalc() from the R package metafor, which includes a correction for small-sample size. This may affect the fairness of the comparison, particularly since CVs from original studies are expected to be slightly overestimated given their smaller sample sizes relative to the replications. I also have concerns about using the mean CV of all replications and comparing it to a single CV value, as this ignores the uncertainty around that mean. An additional check could involve calculating the log coefficient of variation ratio (lnCVR; Nakagawa et al. 2015, Methods in Ecology and Evolution; implemented in escalc()) between the original CV and each replication CV, and running a random-effects (or multilevel) meta-analysis that accounts for shared-control non-independence. I believe this would provide a more robust approach, as it does not ignore the uncertainty around the mean CV of the replications - uncertainty that, if neglected, is expected to increase the likelihood of false positive findings. This concern would also apply to the subsequent analysis on absolute means.

Page 10, paragraph 2: The change in geographical distribution shown in Figure S3 appears rather striking, with western states disappearing step by step. Should the reader be concerned about the eventual geographical representability of the sample?

Page 15, Figure 3A: I wonder whether adding 95% CIs calculated from the sampling variance of each ratio would improve interpretation and help readers appreciate the real differences between the dots (i.e., means) - along the lines of a forest plot.

Page 17, section "Predictors of replication success": It is unclear to me how the decision was made about which results from Figure 4 to present in the text. Intuitively, given that correlations were calculated for both t values and lnRR (and other metrics), I would have expected that whenever a result is highlighted in the text, the authors also report how it changes depending on the metric used - for example, the interesting result regarding the 5-year number of publications, whose correlation is notably lower when using lnRR (−0.31 vs. −0.18). Presenting this nuance in the text would reduce the risk of inadvertently giving the impression of cherry-picking.

Page 23, paragraph 1: (this comment should have come during the first % reported, but only in the discussion I realized how important this would be for comparing estimates) I wonder whether the authors should calculate 95% confidence intervals for all their percentages (and those of Errington et al.) using the Wilson method via the function binom.confint() in R, which handles extreme proportions (0% or 100%) more gracefully. This would ensure that uncertainty around these percentages is not neglected and would aid interpretation when comparisons are made. In addition, in the next sentence, the authors are comparing correlation coefficients, at least verbally, these could in principle be transformed into Pearson's r and assigned 95% confidence intervals following meta-analytic workflows, which would better allow us to assess whether these correlations are meaningfully larger or smaller, and help avoid potentially misleading arguments.

Page 24, paragraph 2: The following result is really interesting and I would love for the authors to expand on it a little. There must be other meta-research studies that, despite not studying replicability directly, have explored a similar predictor: "Other features of the original article were generally uncorrelated with replication outcome, although large rates of publications by the last author were associated with lower replicability, suggesting that incentivizing publication volume may be counterproductive for the reliability of results."

Page 25, paragraph 1: I believe the authors could explore if there is evidence for "incorrect labeling of error bars (Cumming et al., 2007; Vaux, 2004)" by plotting log(SD) vs log(mean) across all original studies, and exploring if large outliers (i.e., points largely deviating from the positive regression) exist. That should provide some insights into whether some values reported as SD in the original studies were indeed SE, which I am assuming is what the authors of the study are referring to when they say "incorrect labelling of error bars" here.

Code: I could not engage with the data and code, but I would like to highlight that the organisation and clarity of the GitHub repository is of high quality.

Reviewer #3 (Public review):

Summary:

The authors conducted a large-scale replication effort of lab-based biomedical experiments with an emphasis on the country of origin and who conducted the replication experiments. The authors aimed to understand this context in both the outcomes produced, but also in the approach. Finally, the authors aimed to conduct multi-lab replications to provide richer data from the replications. Overall, the authors find replication rates that are like other large-scale replication efforts in the biomedical space. The authors provide rich detail into the three experimental techniques that were the focus of this effort, potential moderators of replication success, and challenges in conducting replications and coordinating a large-scale crowd-sourced effort.

Strengths:

The paper is outstanding in being transparent and calibrated in how the results are presented. While the authors were challenged by mundane aspects (e.g., difficulty with logistics), unexpected aspects (e.g., COVID pandemic), and very insightful aspects unique to conducting replications (e.g., experimental issues). The authors also provide variation in how they present the results, including confirmatory, multiverse, and exploratory analysis. A unique strength for this study is the rich in-depth insights about the process and interpretation of conducting replications, including predicting replication success in the lab-based biomedical space.

Weaknesses:

The study has weaknesses that the authors acknowledge in their discussion, such as lower number of replications than originally planned that limited the intended effort to compare multiple experiments with multiple attempts against a single original experiment. Another weakness is the limited discussion connecting these findings to the Brazilian research ecosystem.

Reviewer #1 (Public review):

Summary:

The authors used a large dataset evaluating gut carriage of Enterobacterales and ESBL organisms from children aged 6-24 months as the basis for a modeling study to investigate what factors are most important for determining the prevalence of ESBL resistance. The modeling incorporated travel, a simple model of carriage duration (short and long), fitness cost of resistance on transmission and clearance, and antibiotic use. They found that antibiotic use is the primary driver of resistance prevalence, with transmissibility of resistant strains also important for setting the prevalence. Travel, while important when prevalence is very low, plays less of a role in maintaining prevalence once it is established (in keeping with other recent work). They estimated the fitness cost of resistance (terming a reduction of 14% on the rate of transmission and an increase of 23% on the rate of clearance as "low"). While the extent of assumptions and simplifications makes me skeptical of the quantitative conclusions, the qualitative ones seem reasonable and reinforce the long-held principles of the field--reducing antibiotic pressure and interrupting transmission--and highlight the importance of understanding the biological factors that shape the duration of carriage and the likelihood of colonization.

Strengths:

This study incorporates many of the factors that might influence the carriage prevalence of ESBL Enterobacterales. This builds on the work led by this group, both in primary data collection and in theory. Overall, it's such a tough problem that I commend the authors for trying to tackle it. The authors take a thoughtful, rigorous approach, acknowledging simplifications and assumptions where they need to, so as to evaluate the various factors shaping ESBL prevalence.

Weaknesses:

Part of the reason it's such a tough problem is that we have limited data to structure and parameterize a complex model.

(1) The data are not sufficiently described.

The primary data source for this modeling exercise comes from a study of 6-24-month-old children who underwent rectal swabs and evaluation of the carriage prevalence of Enterobacterales, and then whether these Enterobacterales were ESBL; moreover, the study included data on travel and on antibiotic use. Could the authors please direct us to these primary data? Could the authors also justify the parameters in their models from these data--for example, could they please provide the distribution of antibiotic use and the associated timing? Could they also explain why they decided to treat all Enterobacterales as if they were E. coli (line 307)? Is there evidence that all Enterobacterales occupy the same niche and compete with each other?

(2) The model should be more fully described and the limitations explored/explained.

- The authors should point to the code and the ODEs.<br /> - I understand the focus on the pediatric population; the authors argue that this is reasonable because ESBL colonization is similar across age groups. But presumably, antibiotic use differs across age groups, and there is colonization pressure from within households.<br /> - The authors only consider resistance to extended-spectrum beta-lactams and use of beta-lactam antibiotics, but ESBL Enterobacterales are often resistant to other antibiotics as well. How much does the use of other antibiotics also select for Enterbacterales that happen to carry ESBL resistance? "One bug/one drug" modeling, as done here, neglects the complexities of the actual patterns of resistance and range of antibiotic use.<br /> - Do the data support the T3 or S3 compartments, which, if I understand correctly, means no exposure to antibiotics can happen during three months after either treatment or travel? What do the data say about the patterns of antibiotic use? I'd imagine that the likelihood of antibiotic use is not homogenous, but instead, there are some who use repeated rounds of antibiotics.<br /> - Why do the authors exclude individuals who used antibiotics in the prior 7 days? What justifies that cutoff? The authors speculate that the impact of excluding these individuals is likely to be minimal; why exclude them, then? Did the authors evaluate the results if they were included?<br /> - What is the basis of "niche differentiation", as described starting on line 221? Why should clearance of one strain be slower when the strain co-occurs in a host with a strain of another type?

Reviewer #2 (Public review):

Overview:

This study integrates several datasets into a unified modeling framework that incorporates several mechanisms thought to impact the spread of ESBL-resistant bacterial strains. The model accounts for tradeoffs between persistor and colonizer strains, travel rates, antibiotic treatment and strain clearance, direct competitive interactions, and, most importantly, a series of distinct costs associated with the carriage of ESBL resistance. The resulting 75-compartment model is internally consistent and structurally neutral. However, the parameter estimation is flawed in many ways, compromising the interpretations of the model.

On the usage of the Swedish infant data set to estimate colonization and persistence:

First, while other papers have taken similar approaches, the Swedish infant data set is fundamentally inadequate to estimate colonization and persistence rates. This is because very few colonies were typed per sampling event (2 to 6 colonies per event). The original authors themselves argued that strains of indistinguishable morphology would not be able to be differentiated by this method. They also provided data showing that strain identity was not directly related to colony morphology (same strain often displaying distinct morphologies).

The consequence of this is that strains present in low abundance would be missed with a high likelihood. However, if they were to be stochastically sampled, this would count as a "colonization" event, and if they were missed in subsequent samplings, this would count as a "loss" event. In other words, the statistical methods described conflate within-host dynamics (which might lead to distinct within-host abundances) with between-host dynamics (colonization and loss).

Beyond this conceptual issue, some technical aspects aren't particularly sound. The mean of the inferred posterior for the lambda and mu parameters are then used to calculate the beta, gamma, d, and epsilon parameters through a linear regression. The more technically correct way of doing this would be to directly infer these parameters from the data and obtain a full posterior for these parameters.

This highlights another issue: these parameters are passed down to the next statistical model as point estimates, with no associated uncertainty. This artificially inflates the (already low) confidence of the estimates for the cost parameters.

Finally, when this procedure generated parameters that were inconsistent with their expectations (clearance is too high to explain prevalence in France), they adjusted the parameters by discarding and recalculating their beta parameters to artificially enforce neutrality between their strains and enforce the expected prevalence. This is problematic because beta and gamma were jointly estimated, and there is no particular reason why some of them should be discarded. The more natural interpretation would be that parameters inferred from Swedish infants do not translate well to French adults, which should preclude their usage in this context.

On the estimation of costs of ESBL resistance:

The core of the second statistical model is to use prevalence data, travel data, and treatment data in conjunction with the previously inferred colonization and loss parameters to infer the costs of carrying antibiotic resistance. Therefore, the accuracy of this section is contingent on an accurate estimation of the previous parameters. However, these colonization and loss parameters are inherited with no uncertainty (just point estimates are passed down), which, as previously mentioned, generates an artificially precise posterior distribution for the resistance parameters.

However, the most severe issue with the statistics lies in the choice of priors for the cost parameters. All of them are uniform in a positive range that implies a positive cost. Importantly, the average over a positive range will always be positive; therefore, this method will ALWAYS estimate a positive mean for the costs. Note that the posterior distribution of some cost parameters seems to peak around zero and abruptly decays with no mass to the left of zero. This is caused by the choice of prior. Had delta been allowed to be negative (i.e., antibiotic resistance carried a benefit, having the prior be uniform between -1 and 1), the posterior distribution would likely be much more symmetrical, and the confidence interval would have included 0.

Restating, because the prior is a continuous function between 0 and 1, it contains infinitely more mass in the region that represents there being a cost (delta>0) than in the region representing no cost (delta=0). This means that it is a mathematical impossibility for this model to infer the absence of a cost.

Therefore, the main finding of the paper ("We found that resistance is costly") is a mathematical artifact of the prior choice and of the model structure.

Reviewer #3 (Public review):

Cotto and colleagues integrated data analysis with mathematical modeling to examine extended-spectrum beta-lactamase (ESBL)-producing E. coli in France. While ESBL prevalence has risen globally, it has stabilized at approximately 6-8% across Europe. Established risk factors for ESBL carriage include prior antibiotic exposure and travel to high-prevalence regions, most notably South-East Asia. The dataset incorporated information on ESBL-producing E. coli and travel history in young children, and the model was calibrated to ECDC surveillance data on ESBL across Europe, supplemented by literature-derived parameters on antibiotic use, E. coli biology, and transmission dynamics. The authors report that ESBL-carrying strains exhibit a 14% fitness cost in community transmission relative to susceptible bacteria, yet are cleared 23% less frequently. ESBL carriage was strongly associated with factors that prolong gut colonization. Both antibiotic treatment rates and transmission efficiency were identified as key determinants of community-level ESBL prevalence.

Strengths:

The study addresses a clinically and epidemiologically important topic. The integrated modeling approach is methodologically sound and well-suited to disentangling the relative contributions of transmission and antibiotic selection pressure.

Weaknesses:

Several concerns regarding the data used in this study warrant consideration. First, model calibration relied on ECDC surveillance data pooled across multiple European countries, several of which have substantially lower antibiotic consumption than France (ECDC ESAC-Net Annual Epidemiological Report, 2024). Given that antibiotic use is a primary driver of ESBL selection, ESBL prevalence is likely to be heterogeneous across these settings. Calibrating to a geographically diverse dataset risks introducing systematic bias into parameter estimates that may not be representative of the French context. The authors should repeat the analysis using France-specific data, or, where this is not feasible, restrict the calibration dataset to countries with comparable antibiotic consumption profiles. Second, the travel exposure data may be insufficient to adequately capture importation dynamics from South-East Asia, as the cohort consisted exclusively of young children, a demographic less likely to travel to high-prevalence regions than older age groups. This may result in an underestimation of travel-associated importation as a contributor to community ESBL prevalence, and the generalizability of these findings to the broader population should be interpreted with caution.

Reviewer #1 (Public review):

Summary:

In this work, T. Wijerathne et al. investigated and reported the agonistic effect of Yoda1 and Yoda2 over PIEZO2 function using patch clamp electrophysiology, Ca2+ imaging, and molecular dynamics. They find that Yoda1 sensitizes PIEZO2 to membrane tension, can induce Ca2+ influx, and decreases its inactivation to a lesser degree than it does to PIEZO1 channels. Additionally, their data shows that Yoda2 sensitizes PIEZO2 channels to membrane indentation to a greater extent, but it has a weaker effect on channel inactivation than Yoda1. Interestingly, they report that a mutation in a conserved arginine between PIEZO channels can be used to abolish PIEZO1-mediated Ca2+ flux in response to Yoda molecules. As a whole, the results presented here should be put into perspective against previous and future works involving systems where both PIEZO1 and PIEZO2 might be expressed. This is especially true for works where Yoda1 has been used as a basis for determining the absence of PIEZO2.

Strengths:

The authors use multiple techniques to investigate how Yoda molecules affect the three most important biophysical aspects of PIEZO channels that, when changed, result in pathophysiological responses: a) sensitivity to mechanical stimuli, b) Ca2+ entry, and c) channel inactivation. Lastly, they find a specific amino acid/region that could be exploited for drug design and/or development.

Weaknesses:

The methods and discussion sections are lacking enough detail to fully evaluate the findings and put them into perspective, respectively.

Reviewer #2 (Public review):

Summary:

This manuscript challenges the long-standing assumption that Yoda1 and Yoda2 are PIEZO1-selective activators. Using patch-clamp electrophysiology and calcium imaging in HEK293TΔPZ1 cells overexpressing PIEZO2, the authors demonstrate that Yoda1 potentiates PIEZO2 stretch-activated currents to a similar extent as PIEZO1 and slows PIEZO2 poking-current inactivation (albeit with lower efficacy). They further show that the more potent analog Yoda2 affects PIEZO2 at nanomolar concentrations and use mutagenesis and molecular dynamics simulations to propose that Yoda2's benzoic acid group forms a transient salt bridge with R1724 in the putative Yoda binding pocket, explaining its enhanced potency.

Strengths:

The authors are established Piezo/biophysics experts; the study is highly important, technically competent, and carries significant implications for the reinterpretation of prior work that used Yoda compounds as PIEZO1-selective probes.

The core finding that Yoda1 modulates PIEZO2 stretch currents is convincing and important. However, several conceptual, methodological, and presentational issues need to be addressed before acceptance, as detailed below.

Weaknesses:

(1) The abstract states that Yoda1 potentiates PIEZO2 "as efficaciously as PIEZO1." This claim is accurate only for stretch currents and single-channel open probability, but the paper itself demonstrates important asymmetries: i) Yoda molecules slow PIEZO2 poking-current inactivation ~2-fold, versus ~5-10 fold for PIEZO1 (Figure 3b and ref #60). ii) Spontaneous Ca²⁺ entry via PIEZO2 requires non-physiological conditions (high extracellular Ca²⁺, hypertonic solutions) that are unlikely to occur in native cells.

The abstract should be revised to clearly qualify where equivalence holds and where efficacy differences exist. IMO, the current wording risks overcorrecting the historical bias (PIEZO1-only) by going too far in the other direction.

(2) Related concern: the PIEZO2 Ca²⁺ signal in Figure 2 is only detectable using a Ca²⁺-boosted solution (CBS ie 30 mM Ca²⁺). Physiological extracellular Ca²⁺ and cells normally do not experience sustained hypertonicity at these magnitudes. The authors should explicitly clarify that the practical implication of their findings is primarily for electrophysiological (patch-clamp) experiments and that the Ca²⁺ imaging caveat applies only under amplified conditions. Specifically, the authors should state that in standard Ca²⁺ imaging assays with physiological buffers, PIEZO2 is unlikely to confound Yoda1 results.

Related point: Can cytochalasin D (CytoD) restore a Yoda1-dependent Ca²⁺ signal in physiological saline? This would help determine whether the weak PIEZO2 response is primarily a membrane tension issue (cytoskeletal tethering) versus intrinsically lower channel expression or permeability. The authors already have tagged PIEZO1/2 constructs and could, in principle, normalize by surface expression.

(3) The mean inactivation tau values for wild-type PIEZO2 poking currents in both DMSO and Yoda1 conditions (Figure 3b, approximately 15-40 ms range) appear substantially higher than values reported in published literature (typically 5-10 ms; eg, PMID: 20813920). This discrepancy needs to be addressed.

(4) The authors perform all MD simulations on a truncated PIEZO1 model and justify this choice by noting that the Yoda binding region is highly conserved between homologs. This is a reasonable and defensible starting point given the availability of well-validated PIEZO1 simulation set ups in their lab. A few points are nonetheless worth addressing: While PIEZO2 simulations are not strictly required, the authors are encouraged to briefly discuss whether any long-range structural differences between PIEZO1 and PIEZO2 (outside the binding site itself) could influence Yoda2 binding dynamics, particularly in light of the chimera data showing that PIEZO2 sequence in repeat A abolishes Yoda1 sensitivity. This reviewer still doesn't understand the reason behind this discrepancy despite it being acknowledged in the text.

Another MD-related comment is that three simulation replicas (which is impressive for such a big system) show markedly different salt bridge occupancy (82.6%, 49.7%, 99.8%; stated in the text). This wide variation suggests incomplete sampling in at least one replica. The authors should provide RMSD plots for ligand and protein backbone to assess convergence and possibly discuss whether the 49.7% replica represents a genuinely distinct binding mode or incomplete equilibration.

(5) The Discussion proposes that PIEZO2's weaker Ca²⁺ response to Yoda1 could partly reflect lower membrane expression. Since the authors already have fluorescently tagged PIEZO1 and 2 constructs, a simple fluorescence intensity comparison between the two (acknowledging it would reflect total rather than surface expression) could provide at least indirect support for this claim. Alternatively, if such a comparison is not feasible, the authors may consider removing membrane expression from the list of proposed explanations or explicitly acknowledging that this remains unsubstantiated speculation. The max poking currents may somewhat and roughly indicate the level expression difference too, if done exactly side by side.

(6) The abstract or concluding remarks should highlight that Dooku1 is not PIEZO1-selective in its agonist-like action on PIEZO2, and that Cmpd15/Cmpd64 appear to be better PIEZO1-selective tools. This nuance is buried in the Results section.

(7) The authors should not cite PMID 31015490. Clearly, any work on MCC13 is confounded by the overwhelming expression of PIEZO1 (PMID: 42084270). Instead, the authors should also cite the literature from others who have clearly recorded stretch currents from PIEZO2 before the cited studies (eg, PMID: 37590348).

Reviewer #3 (Public review):

Summary:

The manuscript reports that Yoda1 and Yoda2 agonize PIEZO2 in a manner similar to PIEZO1, increasing open probability and stretch sensitivity, but the mechanism underlying this sensitivity is incomplete. Mutagenesis was shown exclusively in PIEZO1, with no corresponding mutagenesis in PIEZO2, so the proposed mechanism in PIEZO2 is inferred by homology rather than directly tested. All experiments use mouse PIEZO2, and the human ortholog should be used before generalizing the proposed reinterpretation of the field.

Strengths:

The pressure-clamp electrophysiology demonstrating a shift in half-activation pressure for PIEZO2 is compelling evidence in support of the central claim.

Weaknesses:

(1) In the single-channel recordings (Figure 1a), it's unclear how many channels were present in those patches. After applying -60 mmHg pressure, multiple channels would be activated (as seen in Figure 1e). The number of channels in the patch and their inactivation rate could significantly influence the open probability in such experiments. To overcome this, in the original Yoda1 article (Syeda, Ruhma, et al. eLife 2015), no additional pressure was used. Additionally, the reported open probability comparison (n=7 Yoda1 vs n=17 DMSO patches) has an SEM nearly as large as the effect itself (0.30 {plus minus} 0.11), consistent with a small number of outliers driving this. The underlying mean open and shut times are reported without any statistical test; only the derived open probability receives a p-value. Additionally, in Figure 1a, the Yoda1 condition noise is different from the control. This should be stated if noise filtering was applied and how, given that this could affect open probability analysis.

(2) The calcium imaging data in Figure 2 raise significant concerns regarding the chemical activation claim. The calcium-boosted solution (30 mM Ca2+) is not physiological and appears to be generally stressing cells rather than specifically activating PIEZO2: the control condition under CBS already shows an elevated signal, consistent with cells being unwell at this calcium concentration, and adding Yoda1 on top of this shifted baseline raises further questions about specificity rather than confirming it. Separately, it is unclear why DMSO alone produces measurable PIEZO2-associated calcium influx in HBSS, a result that is not addressed in the text. Figure 2 should clearly indicate when DMSO/Yoda1 perfusion was initiated, and y-axis labels are missing from panels A and B.

(3) In the poke experiments, an activation threshold should be calculated and reported, and amplitude data (e.g., peak current versus indentation depth) should be shown rather than only inactivation tau values. It is also unclear why mClover3- and N-GFP-tagged constructs were used in these experiments, since electrophysiological recording already confirms channel expression without requiring a fluorescent tag.

(4) For inactivation kinetics (Figure 3b), the authors use unpaired comparisons across separate cells, whereas the deactivation experiments (Figure 3c) use paired; it should be applied to the inactivation experiments as well. Deactivation kinetics for PIEZO2 itself should be shown. If the claim is that Yoda1 acts on PIEZO2 through the same mechanism proposed for PIEZO1, then a PIEZO1/2 chimera should be expected to show a corresponding effect on deactivation tau; instead, this chimera is reported as completely Yoda1-insensitive despite both parental channels being Yoda1-sensitive, as shown in this study.

(5) Given that this reflects a different experimental paradigm for Yoda EC50, PIEZO1 should be included within Figure 4b. Additionally, EC50 bar plots should be present on this figure. The inactivation time constant for PIEZO2 without Yoda1 is inconsistent across figures, below 20 ms in Figure 3b but above 20 ms in Figure 4c.

(6) Finally, the modeling is performed exclusively on PIEZO1, whereas the manuscript's central focus is PIEZO2. It is therefore unclear whether the proposed structural mechanism, including the basis for Yoda2's reduced efficacy on PIEZO2, can be directly extrapolated to PIEZO2.

Reviewer #1 (Public review):

Summary:

In this study, the authors describe an early diverging vertebrate KCNE gene present in jawless lampreys that they denote KCNE0.

Three forms of the protein are isolated from different lampreys, which have 95% homology to each other, but only moderate homology to KCNE1-6.

Co-expression with lamprey KCNQ1 produced a non-inactivating current, whereas co-expression with mammalian KCNQ1 resulted in less modulation. Introduction of a tetra-leucine motif from KCNE4 into KCNE0 reduced current on co-expression with KCNQ1, conferring an inhibitory effect.

Strengths:

This is an interesting and uncontroversial report of a new KCNE isoform from lower vertebrates that gives insight into the evolutionary progression of the sequence and functional properties of the accessory protein.

Weaknesses:

(1) No error bars visible for lamprey Q1 isoforms (open symbols) in Figure 2G. No statistical comparison was provided to indicate whether lamprey Q1 isoform V1/2s are significantly different (nor in Supplementary Table 1).

(2) There is the same issue in Figures 3 and 4. No appropriate statistical comparison is made between V1/2s for different truncations of PmKCNE0 (Figure 3), or between KCNQ1 species isoforms with and without PmE0.

Reviewer #2 (Public review):

Summary:

This study functionally characterizes a single KCNE-like gene, kcne0, from a jawless vertebrate. The authors conducted multiple experiments, including TEVC, VCF, RT-PCR, and RNA-seq to show that KCNQ1 and kcne0 exhibited a broadly overlapping organ distribution in lamprey species, and KCNE0 produced a constitutively active current when co-expressed with lamprey KCNQ1, similar to the effects of human KCNE3 on KCNQ1. This modulation was species-specific, as co-expression of KCNE0 with other species' KCNQ1 was less effective. Moreover, the authors found that truncating the N-terminal had a more significant reduction of the modulatory effects than truncating the C-terminal of KCNE0. Interestingly, the introduction of the tetra-leucine motif from human KCNE4 into KCNE0 conferred KCNE0 with comparable effects of human KCNE4 on KCNQ1.

Strengths:

The authors clearly introduced an early-diverging member of the KCNE family, and convincingly demonstrated the function of this gene, KCNE0. The results are supported by experiments of multiple approaches and are clearly written. The work is significant and will interest readers from the extended research area.

Weaknesses:

No major concerns were identified with the manuscript in general.

Reviewer #1 (Public Review):

The manuscript by Boudjema et al. describes the cellular events underlying centriole amplification and apical migration to allow the assembly of hundreds of motile cilia in multi-ciliated cells. For this, they use cell culture models in combination with fixed and live cell imaging using antibody staining and fluorescence from endogenously tagged centriole and deuterostome markers, respectively. The work is largely descriptive and functional analyses are restricted to treatment with the microtubule depolymerizing drug nocodazole. The imaging is state-of-the-art including confocal microscopy, live imaging with optical sectioning and high optical and temporal resolution, as well as super-resolution imaging by ultra-expansion microscopy.

The study does a good job of providing a very detailed description of the dynamics of centrioles and deuterostomes that lead to centriole amplification and apical migration in multiciliated cells. This detailed view was missing in previous work. It also reveals the involvement of microtubules at multiple steps: the formation of a cloud of deuterostome precursors, the nuclear envelope tethering of newly formed centrioles, their separation, and their migration to the apical surface.

It would have been useful to expand the analysis of the role of microtubules by including analyses of the requirement for specific microtubule motors, for a better understanding and additional evidence that microtubule-based transport is involved. A weak point is that there is no visualization of microtubules together with deuterosomes and centrioles at the different steps of centriole amplification and migration, to directly address how these structures may interact with and move along microtubules.

Overall, apart from experimental aspects and since this is largely a descriptive study, the manuscript would benefit from more precise language and a better description of the complex events underlying centriole amplification and movements.

Comments on revised version.

The authors have significantly improved the manuscript, by refocusing it, introducing text and figure changes, and by adding new data including functional analyses. The revised version now has convincing data that support the claims. All my remaining concerns have been addressed.

Reviewer #3 (Public review):

Summary:

In this manuscript, Boudjerna and Balagé et al. aim to elucidate the spatial origin of centriole amplification and the mechanisms behind the formation of an apical basal body patch in multiciliated cells (MCCs). To this end, they focused on the role of microtubules and developed new tools for spatiotemporal and high-resolution analysis of different stages of centriole amplification, including the centrosome stages, A-stage, G-stage, MCC-stage. Among these tools, the MEF-MCC cells grown on micropatterns stands out for its versatility as it is not tissue-specific and does not require epithelial cell-to-cell contact for differentiation. Additionally, the Cen2-GFP; mRuby-Deup1 knock-in mouse model was used to study different stages of centriole amplification in physiological brain MCCs. This model offers an advantage over the previously described Cen2-GFP model by enabling the resolution of early events in centriole amplification through the visualization of Deup1-positive structures and their dynamics. Finally, the authors leveraged powerful imaging techniques, including super-resolution microscopy, the U-ExM and high-resolution live cell imaging in order to detect and track centriole amplification, elongation, disengagement, and migration.

By combining the MEF-MCC and knock-in mouse model with spatiotemporal imaging in control and nocodazole-treated cells(treated acutely or chronically), the authors define the sequence of events during centriole amplification, revealing the critical roles of microtubules for the first time. Initially, the centrosome-mediated microtubule network forms, organizing a pericentrosomal nest from which procentrioles and deuterosomes emerge. Their findings indicate the importance of microtubules in recruiting and maintaining pericentriolar material clouds that contain DEUP1, PCNT, SAS6, PLK1, PLK4, and tubulins. Following the amplification stage, the procentrioles mature, leading to cells displaying numerous MTOCs, as demonstrated by regrowth experiments. Mature centrioles then disengage from deuterosomes, attach to the nuclear envelope, and migrate to the apical surface facilitated by microtubules.

Strengths:

The manuscript provides new insights into the regulatory function of microtubules and microtubule-based transport in different stages of differentiation in brain MCCs. Addressing the role of microtubules during different stages of centriole amplification required development of new tools to study brain MCCs, which will be useful in future studies of MCCs. A notable strength of this manuscript is the authors' thorough and quantitative spatiotemporal analysis of highly dynamic processes in MCCs. The precision and detail in describing these dynamic events are impressive and are further strengthened in the revised version through additional analysis and adoption of new methods. This comprehensive analysis advances our understanding of MCC biology regarding the involvement of microtubules.

Comments on revised version.

The revised manuscript is substantially improved, and given the scope, it is appropriate that it primarily establishes a detailed spatiotemporal framework. That said, a few points would further strengthen clarity and impact. First, several observations naturally raise follow-up mechanistic questions, for example whether additional cytoskeletal systems such as actin contribute to steps like centriole apical migration. A slightly more detailed framing of these open questions would help guide future work. Second, some terminology introduced to label observed microtubule-based structures (for example "nest") may not be essential. Finally, while the authors have increased quantification, some analyses would benefit from super plot-style displays with replicate-level comparisons, particularly for intensity-based readouts.

Reviewer #1 (Public review):

This work convincingly shows that, rather than gradually "evolving" throughout interphase, global chromatin architecture undergoes unexpectedly sharp remodeling at G1-S (and to a lesser extent, S-G2) transitions. By applying "standard" Hi-C analyses on carefully sorted cells, the authors provide an excellent temporal view of how global chromatin architecture is changed throughout the cell cycle. They show a surprisingly abrupt increase in compartmentation strength (particularly interactions between the "active" A compartments) at G1-S transition, which is slightly weakened at S-G2 transition. Follow-up experiments show convincingly that the compartment "maturation" does not require the DNA synthesis accompanying S phase per se, but the authors have not identified the responsible factors (work for future publications). The possible biological ramifications of these architectural changes (setting up potential replication "factories", and/or facilitating transcription-replication conflict resolution, both more pertinent for the active A compartments, which are most affected) have been well discussed in the article, but still remain speculative at this stage.

My major criticism of this article is aimed more at the state of the field in general, rather than this specific article, but it should be discussed to give a more balanced view: what actually is a chromatin compartment? Chromosomal tracing and live tracking experiments have shown that the majority of "structures" identified from Hi-C experiments are statistical phenomena, with even "strong" interactions only being infrequent and transient. A-B compartments are "built up" from multiple very low-frequency "interactions", so ascribing causal effects for genome functions is even tougher. As a result, I have very little confidence in the results of the authors' polymer simulations and their inferred "peninsula" A compartment structures without any other supporting experimental data.

Comments on revised version.

The authors have included orthogonal DNA FISH evidence to support their claims which greatly strengthens the manuscript. Their further precisions within the discussion have answered all of my previous concerns with the manuscript.

Reviewer #2 (Public review):

Summary:

This manuscript by Choubani et al presents a technically strong analysis of A/B compartment dynamics across interphase using cell-cycle-resolved Hi-C. By combining the elegant Fucci-based staging system with in situ Hi-C, the authors achieve unusually fine temporal resolution across G1, S, and G2, particularly within the short G1 phase of mESCs. The central finding that A/B compartment strength increases abruptly at the G1/S transition, stabilizes during S phase, and subsequently weakens toward G2 challenges the prevailing view that compartmentalization strengthens monotonically throughout interphase. The authors further propose that this "compartment maturation" is triggered by S-phase entry but occurs independently of active DNA synthesis, and that it involves a consolidation and large-scale reorganization of A-compartment domains.

Strengths:

Overall, this is a thoughtfully executed study that will be of broad interest to the 3D genome community. The data are of high quality, and the analyses are extensive, albeit not completely novel. In particular, previous work (Nagano et al 2017 and Zhang et al 2019) has shown that compartments are re-established after mitosis and strengthened during early interphase, and single-cell Hi-C studies have reported changes in compartment association across S phase. In particular, Nagano et al show that DNA replication correlates with a build-up of compartments, similar to what is presented here, with the authors' conclusion that compartment strength peaks in early S. The idea that it weakens toward G2, rather than continuing to strengthen, appears to be novel and differs from the prevailing framing in the literature.

Comments on revised version.

The authors have responded constructively to my major conceptual concerns. The distinction between DNA synthesis and replication initiation has been clarified appropriately. The additional insulation analysis substantially strengthens the argument that compartment maturation is not simply a consequence of changing loop extrusion dynamics, although I would encourage slightly more cautious wording regarding "independence" from cohesin-mediated extrusion. The peninsula model is now framed appropriately as a heuristic interpretation and supported by orthogonal imaging data. Finally, the discussion of conservation across cell types has been appropriately tempered. Overall, I believe the manuscript has been significantly improved.

Reviewer #1 (Public review):

Summary:

The manuscript by Lu and colleagues demonstrate convincingly that PRRT2 interacts with brain voltage-gated sodium channels to enhance slow inactivation in vitro and in vivo. The work is interesting and rigorously conducted. The relevance to normal physiology and disease pathophysiology (e.g., PRRT2-related genetic neurodevelopmental disorders) seems high. Some simple additional experiments could elevate the impact and make the study more complete.

Strengths:

Experiments are conducted rigorously including experimenter blinding and appropriate controls. Data presentation is excellent and logical. The paper is well written for a general scientific audience.

Comments on revised version.

The manuscript by Lu and colleagues has been revised sufficiently to address all my prior concerns.

Experiments are conducted rigorously including experimenter blinding and appropriate controls. Data presentation is excellent and logical. The paper is well written for a general scientific audience.

Reviewer #2 (Public review):

Summary:

As a member of DspB subfamily, PRRT2 is predominantly expressed in CNS and has been associated with various paroxysmal neurological disorders. Previous studies have shown that PRRT2 interacts with Nav and Cav channels, modulating channel properties and neuronal excitability.

In this manuscript, Lu et al. demonstrate that PRRT2 is a potent regulator of Nav channel slow inactivation, promoting the development of Nav slow inactivation and impeding the recovery from slow inactivation. This effect is highly conserved in PRRT2s across species as well as among DspB family members (TRARG1 and TMEM233). The authors further confirmed the interaction between Nav channels and PRRT2 in heterologous expression systems as well as in Prrt2-V5 knock-in mice. Prrt2-mutant mice, which lack PRRT2 expression, require lower stimulation thresholds for evoking after-discharges when compared with WT mice.

Overall, this is a well-executed and methodologically comprehensive study. This work offers valuable insight into the physiological functions of PRRT2 and reveals a potential pathogenic mechanism underlying PRRT2-associated neurological disorders.

The revised manuscript has addressed most of the concerns raised by the reviewers and has been substantially strengthened, although I still have several concerns regarding the discussion section.

Strengths:

(1) Overall, this is a well-executed and methodologically comprehensive study. The electrophysiological data strongly support the conclusion that PRRT2 is a potent regulator of Nav channel slow inactivation. The observation that this regulation is conserved in PRRT2 across species and among DspB family members raises the possibility that altered regulation of Nav channels may also contribute to the pathogenesis of TRARG1- or TMEM233-associated disorders.

(2) Co-immunoprecipitation assay performed using brain tissue from genetically modified Prrt2-V5 knock-in mice provides convincing in vivo evidence for the interaction between PRRT2 and Nav1.2 channels.

(3) Prrt2-V5 KI mice show markedly reduced PRRT2 protein expression and display phenotypes similar to those observed in Prrt2-mutant mice, supporting an important role of PRRT2 in regulating neuronal and network excitability.

Weaknesses:

(1) Nav1.6 is also highly expressed in cortical neurons and is widely regarded as a major contributor to action potential initiation and sustained high-frequency firing. Given that PRRT2 similarly regulates the fast and slow inactivation of Nav1.6 and Nav1.2 channels, the potential contribution of Nav1.6 regulation to neuronal and network excitability should be discussed.

(2) Slow inactivation is generally considered to develop over timescales ranging from hundreds of milliseconds to seconds or longer. Therefore, the statement in Discussion (Page 13, line 381-382) that "slow inactivation develops on a timescale of tens of milliseconds to seconds" may not accurately reflect the conventional kinetic definition of slow inactivation and should be clarified.

(3) Page 14, line 417-430: "question about how Nav channel slow inactivation is regulated in cells that do not express PRRT2".<br /> PRRT2 is unlikely to be the sole regulator of Nav channel slow inactivation. Other molecules and signaling pathways may regulate Nav channel and contribute to neuronal excitability. In addition, neuronal excitability can also be regulated through modulating other Nav properties, such as long-term inactivation or slow recovery from inactivation, as well as through modulating the activity of other ion channels, for example, Kv7.2 and Kv7.3 channels. Therefore, PRRT2-negative cells may utilize alternative mechanisms to fine-tune neuronal excitability. In its current form, this paragraph somewhat overstates the role of PRRT2 and would benefit from a more balanced discussion.

(4) Page 50, Figure 7-figure supplement 2: It would be helpful to include representative traces of the 1st and the last (20th) compound APs in panels B and C.

Reviewer #3 (Public review):

This paper reveals that the neuronal protein PRRT2, previously known for its association with paroxysmal dyskinesia and infantile seizures, modulates the slow inactivation of voltage-gated sodium ion (Nav) channels, a gating process that limits excitability during prolonged activity. Using electrophysiology, molecular biology, and mouse models, the authors show that PRRT2 accelerates entry of Nav channels into the slow-inactivated state and slows their recovery, effectively dampening excessive excitability. The effect seems evolutionarily conserved, requires the C-terminal region of PRRT2, and is recapitulated in cortical neurons, where PRRT2 deficiency leads to hyper-responsiveness and reduced cortical resilience in vivo. These findings extend the functional repertoire of PRRT2, identifying it as a physiological brake on neuronal excitability. The work provides a mechanistic link between PRRT2 mutations and episodic neurological phenotypes.

Comments:

(1) The precise structural interface and the molecular basis of gating modulation remain inferred rather than demonstrated.

(2) The in vivo phenotype reflects a complex circuit outcome and does not isolate slow-inactivation defects per se.

(3) Expression of PRRT2 in muscle or heart is low, so the cross-isoform claims are likely of limited physiological significance.

(4) The mechanistic separation between trafficking of PRRT2 and its gating effects is not clearly resolved.

(5) Additional studies with Nav1.6 should be carried out.

Comments on revised version.

These comments have been addressed in the revised version.

Reviewer #1 (Public review):

Summary:

This study offers a careful and technically strong look at how surface stickiness changes whisker-surface interactions and how that information reaches peripheral sensory neurons. The authors use 3D whisker tracking to capture bending, twisting, rolling, and tip motion during contact with surfaces that differ in stickiness, coarseness, and position. They show that sticky surfaces, especially silicone, broaden the range of whisker deformation, produce stronger but less frequent stick-slip events, and change firing rates in some trigeminal ganglion neurons. Overall, the study is valuable because it goes beyond standard 2D tracking and shows that out-of-plane motion and roll are important for understanding how whiskers encode texture.

Strengths:

The study is technically strong and well motivated. Its main strength is the use of 3D whisker tracking to show that surface stickiness affects whisker deformation in ways that standard 2D tracking would miss, including torsion, roll, out-of-plane motion, and stick-slip dynamics. The authors also connect these mechanical effects to TG activity, providing evidence that stickiness information is available in peripheral sensory responses. Overall, the work expands the study of whisker-based texture sensing beyond coarseness and provides a richer biomechanical framework for understanding tactile encoding.

Weaknesses:

The main weakness is that stickiness is not formally defined early in the manuscript, even though it is the central experimental variable. Several methodological choices also need clearer justification or validation, including the use of 2D measures as comparators for torsion and roll, the thresholds used for stick-slip detection, the degree-5 polynomial fit, the reference ROI, and aspects of the 3D surface reconstruction. The neural evidence should also be interpreted cautiously because the TG sample is small, only a subset of units discriminated silicone, and the correlation between strain sensitivity and silicone discrimination is suggestive rather than definitive.

Reviewer #2 (Public review):

The authors explore the sensation of stickiness from the point of view of whisker exploration and encoding in the trigeminal ganglion. In doing so, they develop methods for 3D whisker tracking to describe stick-specific parameters such as stick-slip rates and strain. Overall, the methods are strong, and the authors present the results appropriately. Overall, I think exploration of the sensation of stickiness is a great question.

My main criticism is in relation to the chosen stimuli, and I wonder whether the authors may have room to explore more naturally sticky materials and what this may mean for the animal.

(1) Chosen stimuli for stickiness:

Four different materials are used, with the aim of presenting animals with graded measures of stickiness. The results show that silicone stands out against the others; it's less clear whether the intermediate textures (Delrin and resin) may be truly intermediate in stickiness.

I wonder if the stimuli chosen were truly representative of the aim of providing a gradient of stickiness. Did the materials differ in other features, such as surface temperature, texture, etc., which could explain some results? The authors discuss this in terms of coefficients of friction and how these estimates are not quantified in relation to whiskers themselves.

Measures of stick-slip and strain with silicone vs other materials make intuitive sense. Could the authors add additional naturally sticky stimuli to exemplify the results? For example, adhesive, glue, or a sugary substance.

(2) Tracking methods and quantification:

The 3D tracking methods, which incorporate whisker twists, strain, and other fine features of whisker exploration, present an advance in terms of analysis of how whiskers may explore more complex, natural features of environments. The analyses and quantifications are all solid and robust. The technical approaches are well-prepared to take the work a step further in terms of stimulus choice.

(3) Peripheral coding of stickiness:

The authors report that some units respond preferentially to whisking on silicone and that this has to do with strain on the whisker. Is there a possibility to understand the nature or anatomy of these units and why they might be preferential for the sticky sensation? Can the location in the follicle be assigned? And/or would the methodology allow for assignment of where the specifically sticky-tuned units project centrally?

(4) Relationship to natural stimuli:

A piece missing from the paper is more discussion and exploration of why stickiness may be important for sensory coding, as well as potentially more naturally sticky stimuli. One could imagine that a mouse navigating the world could find stickiness attractive, if it were a source of sweet food, for example, or it could potentially be a sensation the animal prefers to avoid. Stickiness could also indicate contamination or a sticky trap, to be avoided. If the authors are able to add naturally sticky stimuli, the whisker exploration and encoding could potentially provide further cues towards the valence of stickiness for mice.

Reviewer #3 (Public review):

This paper tackles an underexplored dimension of whisker-based texture sensing: while surface coarseness encoding has been extensively characterized in rodents, the mechanical and neural basis for stickiness sensing has not previously been examined. The authors make two intertwined contributions that together represent a substantial advance: a methodological one - a 3D whisker tracking pipeline operating at 4000 fps, capable of capturing torsion, roll, and out-of-plane whisker motion - and a scientific one - a first characterization of how whisker mechanics and primary trigeminal afferent responses differ between surfaces of high and low stickiness. The work is technically solid, the dataset is large, and the question is well motivated both by the multidimensional nature of tactile texture perception and by the practical advantages of the whisker system for studying touch mechanics.

Strengths.:

The 3D tracking system is a timely advance over existing tools, particularly in its handling of non-planar whisker shapes and the full automation required for the sub-millisecond resolution needed to detect stick-slip events. The mechanical dataset is extensive. The finding that whisking against silicone expands the sampled whisker strain space and produces stronger but less frequent stick-slip events is clearly demonstrated and internally consistent with the proposed mechanism of greater strain accumulation before frictional release - a physically intuitive result. The open release of the tracking code considerably increases the value of this work to the broader community.

Weaknesses:

A few aspects of the paper, if sharpened, would considerably strengthen the evidence and the clarity of the conclusions.

The central claim - that "stickiness information is available to the whisker system" - does not capture the precision of what the paper demonstrates. As stated, the finding is close to guaranteed: any variation in surface friction will produce some change in whisker mechanics, so the presence of mechanical differences between materials is expected rather than surprising. The more valuable question the paper is well positioned to answer is which specific dimensions of the whisker mechanical response are most informative about surface stickiness. The paper reports effects on strain distribution breadth, stick-slip amplitude, and stick-slip rate, but does not synthesize which of these - or which sub-dimensions (bending, twisting, or rolling) - carry the most discriminating information. Identifying the salient dimensions of the mechanical response and relating them to the proposed frictional mechanism would sharpen the paper's conclusions substantially.

A related but distinct limitation is the absence of direct force measurements during whisker-surface contact. The authors acknowledge this openly, and I recognize it is not easily remedied within the current experimental setup. It does, however, constrain interpretation: without knowing the actual forces generated at the whisker-surface interface, the assumed stickiness ordering of the tested materials cannot be validated, and - importantly - the relative contribution of surface friction and material compliance to the observed mechanical differences cannot be determined. This is an important direction for future work in this area.

The paper argues carefully that 2D tracking is insufficient for capturing the full mechanical picture of whisker-surface interactions, and the figure currently in the supplementary material (Figure S2) makes this case convincingly through multiple analyses. This argument is the core justification for the paper's methodological contribution and deserves a place in the main manuscript. Furthermore, while the mechanical case for 3D over 2D tracking is well made, it has not yet been tested at the neural level: the regression model used to predict neural firing incorporates 3D variables, but its performance is not compared against an equivalent model restricted to 2D variables. Such a comparison would directly demonstrate whether torsion and roll - the signals inaccessible to 2D tracking - carry neural predictive value, and would elegantly unite the paper's methodological and scientific contributions.

Finally, the three-dimensional plots in Figure 3 are the paper's primary representation of its main mechanical result, and there is a real opportunity to make them considerably more informative. The whisker deformation probability distributions (panel B) are rendered in 3D from a single viewing angle, making it difficult to assess the shape or anisotropy of the distributions - and in particular to see which dimensions expand most for silicone relative to the other materials. This is precisely the information needed to identify the most salient dimensions of the stickiness signal, and two-dimensional representations would make it directly readable.

Reviewer #1 (Public review):

Summary:

Using Mendelian randomisation on available GWAS data, the investigators identified eGenes associated with prostate cancer and applied the data to define relevant immune cell types involved. Additional analysis was performed to explore potential candidate targets and agents from licensed medicines.

This is an interesting approach as the investigators have expertise in other research fields, applied here to prostate cancers. The use of three different datasets is significant, and the approach to further analyse implicated eGenes in drug target analysis is relevant and timely.

A particular strength is taking putative genes from Mendelian randomisation analysis to target and potential drug agents.

Some aspects of the study would need to be clarified to enable interpretation of the findings in the context of the prostate gland and prostate cancers: expanding the descriptions of the supporting Supplementary Data and Tables, explanations of the analysis for the general reader, and clarification of the selection of eGenes (Figure 5).

Reviewer #2 (Public review):

Summary:

This study integrates bulk and single-cell transcriptomic-derived eQTLs from two separate consortia (PRACTICAL and Finngen) to identify immune-cell-specific therapeutic targets in prostate cancer. Mendelian randomization and Bayesian colocalization have been used to produce druggable eGene modules through STRING and DrugBank.

This is an interesting study that is attempting to address risk-associated, immune-specific transcriptomic repertoires in prostate cancer. It is knitting together concepts of drug repurposing and prostate cancer immunogenicity. This is an entirely computational study, which would benefit from some wet lab experimental validation.

It is very tricky to attribute cell-type-specific responses, especially when the majority of genes involved represent cytoskeletal or stress responses, which are ubiquitous throughout the prostate microenvironment. This point is relevant for the drug repurposing section: if these drugs are targeting immune cell-specific repertoires, what would the response be of the entire environment? It would be useful to contextualize the validity of each proposed therapy in a specific prostate cancer context and the involvement of AR antagonism or radiotherapy.

Strengths and limitations of this study:

Strengths:

This is a scientifically interesting and potentially impactful study, particularly in its attempt to integrate immune-cell-specific transcriptomics, causal inference, and drug repurposing in prostate cancer. The methodology is well described, and the data (albeit limited) are well analyzed.

Limitations:

The central weakness is the overstatement of the conclusions regarding immune-cell-specific causality, without sufficiently contextualizing the biological meaning of the findings.

Highlighted genes, such as LMNA, XBP1, histone-related genes, and stress-response markers, are ubiquitous regulators involved in fundamental cellular processes, including ageing, unfolded protein response (UPR), integrated stress response (ISR), chromatin remodeling, proliferation, and metabolism. It is unclear whether these signatures truly represent immune mechanisms, or instead reflect broader inflammatory and age-associated biology expected within an ageing glandular organ such as the prostate.

Immune cell identity alone may not be sufficient to infer biological relevance because immune state characterization (e.g., exhausted versus functional T cells, or distinct macrophage/myeloid phenotypes) is largely absent from the current analysis. The assertion that specific immune populations are correlated with prostate cancer susceptibility is probably an overstatement unless the nature of these cells can also be characterized.

The interpretation of "causal variants" is not always specified, i.e., what phenotype is being associated: prostate cancer susceptibility, recurrence, progression, or treatment response (e.g. is there direct causality from immune-cell variants to prostate cancer?).

Overall, there is a need for stronger biological and translational contextualization: how do the identified pathways relate to ageing-associated inflammation, PIN, microbiome-driven inflammatory changes, and stress-response biology in the prostate gland? While the manuscript identifies network hubs and enriched pathways, it often stops short of explaining what these modules biologically represent or how they may influence prostate cancer development, progression, treatment resistance, or immune evasion.

There are additional publicly available spatial transcriptomic or single-cell datasets which could be used to validate whether the purported immune-cell-specific genes are genuinely enriched in immune populations adjacent to tumour cells. In the drug repurposing analyses, the current study does not explicitly handle prostate cancer subtypes such as HSPC, CRPC, NEPC, or DNPC and co-treatment with androgen receptor antagonism or radiotherapy.

Reviewer #1 (Public review):

Summary:

The manuscript- "Cell cycle-dependent variation in endocytosis drives phenotypic diversity in M. tuberculosis" by Subhash et al. demonstrates how host cell heterogeneity shapes intracellular pathogen phenotypes. The central and novel finding of this study (G2-phase cells have higher endocytic capacity and harbour more oxidised Mtb) highlights that a host cell cycle (interphase-driven) changes in endocytic capacity regulate bacterial redox states.

Strengths:

Overall, the study is well-executed and conceptually rich, establishing a causal link between host cell cycle progression, endocytic heterogeneity, and M. tuberculosis phenotypic diversity.

The combination of multiple modalities, including live-cell imaging, flow cytometry, scRNA-seq, and redox-sensitive bacterial reporters, supports these findings and substantially strengthens the biological relevance of the work.

The writing is generally clear, and the figures are well-organised.

This work will be of interest to readers across cell biology, microbiology, and infection biology

Weaknesses:

However, several central claims are only partially supported, the mechanistic depth is limited, and several experimental and analytical concerns need to be addressed.

Major Comments:

(1) The authors demonstrate a correlation between the G2 phase and elevated endocytic capacity. However, the mechanistic link (upstream molecular mechanism) between the cell cycle and endocytic upregulation remains largely unaddressed. The authors speculate that membrane biogenesis during volumetric expansion may drive increased endocytosis and note that lipid biosynthesis genes are upregulated in high-endocytic cells. It would substantially strengthen the paper to test this directly, by examining whether inhibition of lipid biosynthesis (e.g., with fatostatin or cerulenin) selectively reduces the G2-associated increase in endocytic capacity. Alternatively, cyclin-CDK axis perturbations (e.g., CDK1 inhibition with RO-3306 to specifically block G2/M entry) could be used to ask whether cells arrested in G2 maintain elevated endocytosis, helping distinguish cell-cycle-position-dependent from cell-cycle-progression-dependent effects.

(2) The current data show a clear association between high endocytic capacity and more oxidised Mtb, and the authors (consistent with their prior work) hint at lysosomal delivery as the likely mechanism. However, direct evidence for this in the current paper is limited. An experiment examining phagosomal pH or lysosomal fusion (e.g., using a pH-sensitive reporter or lysotracker) specifically in high- and low-endocytic-capacity cells after infection would help confirm this.

(3) Temporal resolution of Mtb redox dynamics. The plasticity experiment (Figure 6C-D) is elegant and shows that Mtb redox states revert as host cells divide and daughters enter G1. However, the experiment compares day 0 and day 3 post-sorting, which spans multiple cell divisions. While a finer time resolution (spanning 24h) would establish the causal relationship, the authors could discuss the possibility and consequences of multiple cell divisions between day 0 and day 3 used in the present study.

(4) Relevance of G2 percentages in differentiated macrophages. In Figure 7 and Supplementary Figure S7, only 4.4-5.7% of THP-1-derived macrophages and 5.7% of BMDMs are in G2. While the authors demonstrate statistically significant differences in Mtb redox states between G1 and G2 macrophages, the biological significance of such a small G2 fraction in a non-dividing population deserves discussion specifically with respect to: a) Are these cells re-entering the cycle? b) Is the G2 designation capturing a distinct functional state rather than active cycling? The authors should include additional markers (e.g., phospho-histone H3 for mitotic cells or BrdU incorporation to test for active S-phase) to characterise this population and clarify its identity and origin in differentiated macrophages, thereby meaningfully informing interpretation.

In conclusion, this is an important mechanism-driven study that highlights an important link in host-driven bacterial phenotypic heterogeneity. The experiments are thorough, the model is well-supported, and the study has implications for infection biology.

Reviewer #2 (Public review):

In this manuscript, the authors utilize a combination of techniques to show that macrophage endocytic capacity is partially dictated by cell-cycle stage, that Mycobacterium tuberculosis (Mtb) more readily infects macrophages that are in G2/M -phases, and that bacteria that are internalized by macrophages at different stages of the cell-cycle experience different levels of intracellular stress (as reported by the redox state of the bacteria). Furthermore, the authors provide evidence that terminally differentiated macrophages retain memory of the cell-cycle stage that they were in prior to differentiation, at least in the context of endocytic capacity.

This work provides evidence for the growing idea that fundamental heterogeneity in both host and bacterial organisms can alter the host-pathogen relationship in important ways. However, based on the current data, I am not convinced that the manuscript establishes endocytic capacity as the causal link between macrophage cell-cycle stage and bacterial state. The main issue is that fluorescence-based sorting for cell-cycle stage is likely to covary with cell size. Larger cells, including those later in the cell cycle, may be more likely to fall into the "high" fluorescence gate, while smaller cells may be enriched in the "low" population. Therefore, the observed phenotypes may still be cell-cycle-associated, but the causal determinant could be a correlated feature of cell-cycle progression rather than endocytic capacity itself. This is a significant caveat because nearly all the data, including the live-cell imaging following individual cells, rely on 'total' fluorescence, which will scale strongly with cell size.

If the authors' conclusion that endocytic capacity is cell-cycle regulated holds true after appropriate controls, this would significantly advance our understanding of the causal interplay between host cell-cycle state, endocytosis, and Mtb physiology. However, an alternative interpretation is that the observed differences in Mtb uptake and bacterial redox state are associated with cell-cycle stage but are not caused directly by differences in endocytic capacity. For example, they could instead reflect other cell-cycle-linked changes in macrophage physiology, such as cell size, intracellular volume, metabolic state, or some other mechanism important for Mtb pathogenesis. If the authors find that their data are best explained by cell-cycle stage independent of endocytic capacity, this would still represent an important advance. However, in that case, the manuscript should clearly distinguish the association with cell-cycle state from the downstream effector mechanisms, which would remain to be determined.

Strengths:

The authors utilize various macrophage models for their studies, which is important considering the variability in macrophage behavior, as well as the growing evidence that differences between mouse and human macrophages are relevant for Mtb infection.

Weaknesses:

The most important caveat is the covariance between fluorescence-based reporters and cell size. This concern applies to both the sorting experiments, which directly measure total fluorescence, and the time-lapse microscopy experiments, in which the authors show total fluorescence rather than mean, area-normalized fluorescence in Figure 3C. This could be explained by biomass accumulation alone, rather than by a specific cell-cycle-dependent increase in endocytic capacity. Without distinguishing total signal from concentration or activity per unit cell area/volume, it is difficult to conclude that endocytosis itself is regulated by cell-cycle stage rather than simply scaling with cell size.

Although the authors provide some evidence that the mean GFP intensity, which more closely reflects concentration, differs between the sorted populations in Figure 3B, they do not report statistics for this comparison. Moreover, this control is not carried through the rest of the manuscript, including in key experiments such as Figure 2B. As a result, it remains difficult to determine whether the observed differences between "high" and "low" populations reflect cell-cycle state specifically or instead reflect differences in total reporter fluorescence driven entirely by cell size.

The evidence for cell-cycle-dependent effects would be more convincing if the authors included additional controls. For example, they could:

(1) Plot both mean GFP intensity and total GFP intensity in Figure 3B, ideally alongside an unrelated fluorescent reporter that does not vary across the cell cycle. This would help distinguish changes in reporter concentration from changes driven by cell size or total fluorescence.

(2) Sort cells based on an unrelated fluorescent marker and test whether the same phenotypes - infectivity, dextran uptake, bacterial redox state, etc. - differ between high- and low-fluorescence populations. If these phenotypes are specific to the cell-cycle reporter and not observed with an unrelated marker, this would strengthen the conclusion that the effects are linked to cell-cycle state rather than to fluorescence intensity, cell size, or sorting artifacts.

Reviewer #1 (Public review):

Summary:

Torpor can be induced by chemogenetic activation of the medial preoptic area. This activation leads to protection from myocardial infarction in an isolated heart preparation despite normalization of the ambient temperature, thus, in principle, uncoupling hypothermia from torpor-induced neuroprotection. Putative pathways of protection are suggested by proteomic studies.

Strengths:

(1) Elegant strategy for inducing torpor in rats.

(2) Appropriate controls for verifying the neuron transducer.

(3) Cardiac protection is significant and appears independent of hypothermia.

(4) Interesting omic strategy to begin to find established and novel pathways mediating organ autonomous torpor-induced protection.

Weaknesses:

(1) The study would benefit from using inhibitory chemogenetics of the same neurons to demonstrate that this might make cardiac response to ischemia worse.

(2) Infecting an area of the brain not known to be involved in torpor would be a useful control.

(3) In vivo cardio protection seems essential as the validation of the strategy requires support that is in the intact animal.

(4) The assumption that the positive effects of torpor are mediated via a phosphoproteomic change rather than a translational or transcriptional control mechanism is not established.

(5) A 40 percent reduction in infarct size may work for genetically identical rats with no co-morbidities, but is unlikely to be significant enough to weather the variability that emerges in humans because of these differences and more. The question is not what the mechanism is, but how do we make it more robust? Overall, this is at best a preliminary data set that requires more experiments to deliver on its immense promise.

Reviewer #2 (Public review):

Summary:

Elley and colleagues induced a synthetic torpor-like state in rats (a non-hibernating species) by chemogenetically activating neurons in the medial preoptic area of the hypothalamus. They show that this state substantially reduced cardiac infarct size in an ex vivo ischemia-reperfusion model. They further report that protection persisted when ambient temperature was raised to prevent hypothermia, and used exploratory phosphoproteomics to identify candidate cardioprotective signaling pathways.

Strengths:

This is the first demonstration that a torpor-like state is cardioprotective in a species that does not naturally enter torpor, which meaningfully advances the potential clinical utility of synthetic torpor. The experimental design is logical, and the controls are generally appropriate. The characterisation of the responsible neuronal population using ISH against QPLOT markers adds mechanistic depth and supports the cross-species conservation argument. The phosphoproteomic analysis, though exploratory, generates plausible and biologically coherent hypotheses grounded in the hibernation literature.

Weaknesses:

The primary weakness is that the central conclusion - that hypothermia is not necessary for cardioprotection - exceeds the evidence. The thermoneutral groups were not demonstrably normothermic (36.4 vs 37.05{degree sign}C, p=0.44 with n=6), core temperature telemetry was absent in the majority of control animals contributing to the infarct endpoint, and the decisive test, i.e., a correlation between individual nadir temperature and infarct size, was never performed. Additional weaknesses include the absence of sex-stratified analysis despite known estrogenic contributions to torpor

Reviewer #3 (Public review):

Summary:

The manuscript by Elley and colleagues describes experiments on the effects of synthetic torpor on ex vivo heart ischemia. The key aspect of the study was the use of viral-vector mediated manipulation of the hypothalamic medial preoptic area (MPA) in rats. They used AAV-CaMKIIa-hM3D(Gq). The authors report that chemogenetic activation of the MPA prior to an ex vivo heart ischemia-reperfusion insult induces cardio protection against infarct size that is independent of prior in vivo hypothermia. Phosphoproteomic analysis of cardiac tissue suggested changes in cell survival and death pathways.

Strengths:

This study has important strengths. The idea is novel. The experimental design is appropriately rationalized and fascinating. The manuscript is written and presented concisely.

Weaknesses:

The study has important weaknesses in the experimental design and validation of the model.

(1) The study is based on the use of a DREADD-designed viral vector (AAV-CaMKIIa-hM3D(Gq) -mCherry) that is activated by 2 mg/kg IP injection of CNO. The rationale is to putatively activate the MPA. The authors show no evidence for chemogenetic activation of neurons in the MPA. This could be done using a variety of different approaches, even phosphoproteomics.

(2) The stereotaxic injections are difficult to precisely and locally place, particularly bilaterally. Figure 2F is only a schematic. It would be better to show actual low magnification brain sections (bregma +0.12 to -0.48) from a representative rat to show the placement of the AAV.

(3) The control rats were injected with AAV-CaMKIIa-EGFP. Why was EGFP used instead of mCherry for the control?

(4) Ideally, a mutant non-activatable variant of AAV-CaMKIIa-hM3D(Gq) should have been used for a better control.

(5) The authors should comment on whether there is any neurotoxicity in the MPA associated with the forced AAV expression of hM3D-Gq.

(6) Is there any inflammatory pathology seen in the MPA with AAV transduction?

(7) There are no experiments to show that the systemic torpor is specifically associated with the MPA region. Experiments should be done with injections of AAV-CaMKIIa-hM3D(Gq)-mCherry placed in other brain regions, for example, the nearby nucleus accumbens.

(8) The mapping of the distribution of neurons responsible for synthetic torpor is not mechanistic enough and is not directly to the point. While excitatory and inhibitory markers are examined, a more interesting and deeper approach would have been to use glutamate receptor antagonists to manipulate the torpor response.

(9) The ischemia and reperfusion aspects of the Lagendorff method need to be clarified. The isolated hearts are already ischemic after their removal from the rat. The reperfusion aspect is caused by reflow of blood to generate oxidative stress, but in the ex vivo model, is there really reperfusion injury?

(10) The authors show that whole animal oxygen consumption is reduced in the torpor state. The measurement is crude and most likely reflects the inactivity of the animal's skeletal muscle in the torpor state. A more relevant and direct experiment would be to do oxygen consumption (or Seahorse) assays on extracts of the isolated hearts.

(11) The authors report that the synthetic torpor induces bradycardia. There is no follow-up on this important observation. The MPA-heart connection is not analyzed. (A) Is the link through cardiovascular centers in the brainstem? (B) Is the torpor-induced bradycardia mediated through increased parasympathetic or decreased sympathetic autonomic tone? Pharmacological experiments could also be done.

Reviewer #1 (Public review):

The work corroborates the idea, recently suggested by Rosenthal et al. (2025), that spreading depolarization is involved in the mechanisms of electroconvulsive therapy. Using a mouse model of electroconvulsive therapy and various sophisticated approaches to visualize cortical activity, the authors provide an extensive description of traveling calcium waves induced by electroconvulsive stimulation. The study confirms that the calcium events have properties typical of cortical spreading depolarization and seeks to show that the calcium/SD waves mediate therapeutic and neuroplastic effects of electroconvulsive therapy. The authors find that after electroconvulsive stimulation associated with calcium/SD waves, Fos expression increases widely; in the cortex, this increase is localized to the hemisphere affected by calcium waves. They show that some EEG predictors of the beneficial effects of electroconvulsive therapy correlate with the occurrence of calcium/SD waves. Despite the solid methodology and the study's interesting, its conclusions are not fully supported by the data.

In particular:

(1)The title of the paper claims that "electroconvulsive stimulation drives cortical spreading depolarization dependent immediate early gene expression". However, immunohistochemical staining shows that Fos expression increases not only in the cortex but also in many subcortical regions, including the hippocampus and amygdala (Figure 5A). Really, conventional electroconvulsive therapy stimulates nearly the entire brain volume and induces generalized seizure activity that can trigger SD not only in the cortex but also in other brain sites. Therefore, regions beyond the cortex can also drive the effects of electroconvulsive therapy. Next, the authors use Fos staining as a marker of neuronal plasticity. However, Fos is also a marker of preceding neuronal activation. As electroconvulsive stimulation, seizures, and SD are associated with high neural activity, it is unclear whether the observed Fos upregulation results from the prior activation or heralds the subsequent plastic changes. Other markers of neuroplasticity (e.g., BDNF) should also be examined.

(2) Postictal EEG suppression is one of the most promising correlates of positive clinical outcomes after electroconvulsive therapy. Cortical SD is also tightly coupled with suppression of neuronal activity in affected regions. Although the authors report that postictal suppression is stronger after stimulations with cortical SDs than without SDs, the cortices affected (ipsi) and unaffected (contra) by unilateral cortical calcium/SD events exhibit identical suppression (Figure 6F). The result contradicts established knowledge in the field. If the calcium events are cortical SDs, they should induce EEG suppression only in the affected hemisphere.

(3) The study states a beneficial role of calcium/SD waves in ECS effects. However, SD alters numerous aspects of brain function, leading to a range of effects that can underlie side effects as well. Assessment of the behavioral effects of stimulation with and without calcium/SD waves can help clarify the issue.

The results of the work suggest that cortical SD can contribute to electroconvulsive therapy-related mechanisms and help to optimize the stimulation parameters to achieve maximal therapeutic effect.

Reviewer #2 (Public review):

Summary:

This manuscript addresses the question of mechanisms underlying the therapeutic effects of electroconvulsive therapy (ECT). Clinical efficacy of ECT in major depression (and other disorders) is well established and has often been assumed to be a direct consequence of seizure activity generated by the current application. However, as the authors point out, this explanation is unsatisfactory. A recent study (Rosenthal et al., 2025) provided evidence that ECT generates a wave of cortical spreading depolarization (CSD) in mice, and initial evidence that similar events were generated in patients undergoing ECT. Based on their observations, Rosenthal et al. proposed that CSD, rather than seizure, may engage plasticity mechanisms that contribute to the brain's clinical response to ECT. The current study adds to that prior work by reporting other consequences of CSD, in addition to sustained Ca2+ elevations. The current study also links EEG characteristics immediately following the ECT with the likelihood of generating a CSD, which can help optimize ECT parameters.

Strengths:

An important research topic, linking a large set of rodent studies with a limited clinical EEG data set.

The data acquisition and analyses appear to be of very high quality, and the main results are well illustrated.

Association between EEG characteristics linked to good clinical outcome matched by mouse EEG data linked to CSD.

Characterization of multiple consequences of CSD following ECT in the mouse brain.

Weaknesses:

The main characterization of CSD propagation comes from GCaMP Ca2+ measurements, as previously reported (Rosenthal et al., 2025). That prior study also provided key electrophysiological evidence of CSD with a DC shift after ECT in mice (supplemental data). Given the prior evidence for ECT-CSD, the additional measures shown in the current manuscript are fully expected. Thus, the 2-photon imaging of Ca2+ elevations following CSD (Figure 4) is consistent with prior 2-photon imaging studies of CSD, and the complex hemodynamic and pH changes are expected to contribute to propagation of EGFP fluorescence changes (Supplemental Figure 5). These data are well presented, but, contrary to the results section here, these results appear confirmatory rather than necessary to build a case that the key event generated by ECT is a CSD.

The authors state that "our conclusion that CSD is the primary driver of plasticity is based on its role in driving Fos expression" (line 472). Related to the point above, there is already a very well-established literature showing that CSD leads to rapid and robust Fos expression in rodent cortex, so this is fully consistent with prior work. The prior work, CSD-fos work, should be summarized and/or cited more clearly in the manuscript. Showing that Fos increases only in the hemisphere where there is a large CSD-Ca2+ wave is a clear demonstration of this. While Fos increases can certainly be well linked to plasticity in some experimental paradigms, the implication that Fos increases underlie CSD-induced plasticity and possibly therapeutic effects of ECT is not appropriate. Fos increases after CSD are a reliable marker of the very strong neuronal activation that occurs, but Fos increases are not specific for plasticity and can be activated by challenges that do not generate synaptic plasticity. A range of other gene expression changes have been identified with CSD and may contribute to adaptive plasticity; these could be mentioned alongside speculation about Fos. To support the main conclusions of this paper about CSD driving plasticity via Fos, Fos knockout or knockdown studies are needed, as has been used in prior plasticity studies.

Reviewer #3 (Public review):

Summary: