Reviewer #2 (Public review):

Summary:

This population-based cohort study found no evidence that physical activity, whether self-reported or objectively measured, positively influenced brain structure (hippocampal volume or BrainAGE) or cognitive function (Trail Making Test scores). Notably, longitudinal analyses suggested the opposite temporal relationship: a higher BrainAGE at baseline predicted higher physical capacity at follow-up, more in line with reverse causation rather than a neuroprotective effect of physical activity.

Strengths:

The study's statistical approach is thorough and well-documented, and the inclusion of two measurements of physical activity (self-report questionnaire and objective accelerometer data) is a strength. The longitudinal aspect also represents a strength.

Weaknesses:

Several aspects of the measurement timing warrant consideration. Physical activity was assessed over 7-day periods, creating a potential mismatch with (commonly less dynamic) brain outcomes examined (hippocampal volume, BrainAGE), which may reflect cumulative exposures over longer timescales. Additionally, the asynchronous measurement protocol (cognitive testing preceding accelerometry, and the MRI occurring weeks after baseline visits) may introduce time lags that attenuate associations. The observed null associations may be influenced by timing misalignment rather than reflecting the absence of consistent effects of physical activity on brain health and cognition.

Other measurement characteristics also warrant consideration when interpreting the null findings. Physical activity was assessed using short-form self-report questionnaires and averaged accelerometer MET/day values, both of which have limited reliability. Additionally, the modest accelerometer subsample size and low/insufficient variation in activity levels observed in this cohort increase the likelihood of missing effects. These factors collectively raise the possibility that true physical activity-brain health associations may have been obscured.

The study's conclusions regarding brain health, structure, and cognitive functioning are broad despite the scope of the selection of outcomes examined. The analyses focus on hippocampal volume, BrainAGE (a global aging metric), and Trail Making Test performance (processing speed and executive function), while omitting other important neuroimaging markers such as cortical thickness, functional connectivity, or white matter microstructure. The null findings presented here cannot exclude positive effects of physical activity on broader constructs of brain health or cognitive functioning.

While the authors appropriately note the use of different physical activity instruments across time points (IPAQ at baseline, VSAQ at follow-up) in the limitations section, the discussion should more explicitly address the interpretive challenges this creates. The observed association between higher baseline brain age gap and lower follow-up physical activity may reflect: (1) a true temporal relationship, (2) an artifact of switching from behavior-focused (IPAQ) to capacity-focused (VSAQ) measurement, or (3) some combination of both. This ambiguity substantially limits causal inference.

Reviewer #2 (Public review):

Summary:

This paper presents a new approach for explicitly transforming B-cell receptor affinity into evolutionary fitness in the germinal center. It demonstrates the feasibility of using likelihood-free inference to study this problem and demonstrates how effective birth rates appear to vary with affinity in real-world data.

Strengths:

(1) The authors leverage the unique data they have generated for a separate project to provide novel insights into a fundamental question.

(2) The paper is clearly written, with accessible methods and a straightforward discussion of the limits of this model.

(3) Code and data are publicly available and well-documented.

Weaknesses (minor):

(1) Lines 444-446: I think that "affinity ceiling" and "fitness ceiling" should be considered independent concepts. The former, as the authors ably explain, is a physical limitation. This wouldn't necessarily correspond to a fitness ceiling, though, as Figure 7 shows. Conversely, the model developed here would allow for a fitness ceiling even if the physical limit doesn't exist.

(2) Lines 566-569: I would like to see this caveat fleshed out more and perhaps mentioned earlier in the paper. While relative affinity is far more important, it is not at all clear to me that absolute affinity can be totally ignored in modeling GC behavior.

(3) One other limitation that is worth mentioning, though beyond the scope of the current work to fully address: the evolution of the repertoire is also strongly shaped by competition from circulating antibodies. (Eg: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3600904/, http://www.sciencedirect.com/science/article/pii/S1931312820303978). This is irrelevant for the replay experiment modeled here, but still an important factor in general repertoires.

Reviewer #2 (Public review):

Summary:

This paper presents a new approach for explicitly transforming B cell receptor affinity into evolutionary fitness in the germinal center. It demonstrates the feasibility of using likelihood-free inference to study this problem and demonstrates how effective birth rates appear to vary with affinity in real-world data.

Strengths:

• The authors leverage the unique data they have generated for a separate project to provide novel insights to a fundamental question.
• The paper is clearly written, with accessible methods and straightforward discussion of the limits of this model.
• Code and data are publicly available and well-documented.

Weaknesses:

• No substantial weaknesses noted.

Reviewer #2 (Public Review):

Summary:

The authors combine a clever use of historical clinical data on infection duration in immunologically naive individuals and queuing theory to infer the force of infection (FOI) from measured multiplicity of infection (MOI) in a sparsely sampled setting. They conduct extensive simulations using agent-based modeling to recapitulate realistic population dynamics and successfully apply their method to recover FOI from measured MOI. They then go on to apply their method to real-world data from Ghana before and after an indoor residual spraying campaign.

Strengths:

(1) The use of historical clinical data is very clever in this context.

(2) The simulations are very sophisticated with respect to trying to capture realistic population dynamics.

(3) The mathematical approach is simple and elegant, and thus easy to understand.

Weaknesses:

(1) The assumptions of the approach are quite strong and should be made more clear. While the historical clinical data is a unique resource, it would be useful to see how misspecification of the duration of infection distribution would impact the estimates.

(2 )Seeing as how the assumption of the duration of infection distribution is drawn from historical data and not informed by the data on hand, it does not substantially expand beyond MOI. The authors could address this by suggesting avenues for more refined estimates of infection duration.

(3) It is unclear in the example how their bootstrap imputation approach is accounting for measurement error due to antimalarial treatment. They supply two approaches. First, there is no effect on measurement, so the measured MOI is unaffected, which is likely false and I think the authors are in agreement. The second approach instead discards the measurement for malaria-treated individuals and imputes their MOI by drawing from the remaining distribution. This is an extremely strong assumption that the distribution of MOI of the treated is the same as the untreated, which seems unlikely simply out of treatment-seeking behavior. By imputing in this way, the authors will also deflate the variability of their estimates.

- For similar reasons, their imputation of microscopy-negative individuals is also questionable, as it also assumes the same distributions of MOI for microscopy-positive and negative individuals.

Reviewer #2 (Public review):

Summary:

The manuscript describes the structure of the Mycobacterium tuberculosis (MmpS4)3-(MmpL4)3 hetero-heximeric transporter complex. The structure was obtained by cryogenic electron microscopy using an engineered construct that cross-links MmpS4 to MmpL4 via a disulfide bond. The position of the disulfide bond was determined using an Alphafold2 model of the hetero-heximer. Although Alphafold2 predicts a symmetric hetero-heximer, the author found that the structure of the coiled-coil domain (CCD) is asymmetric, tilted at about 60° relative to the membrane domains, and only contains two of the three alpha helical hairpins, with the third being disordered.

Strengths:

The strategy of using Alphafold2 models to guide construct design for experimental structure determination is state-of-the-art, and this work provides a great example of its applications and limitations. I.e., the experimental structure does not fully recapitulate the prediction but provides unexpected results.

The comparisons between the authors' structures and the previously published structures of the MmpL4 monomer and MmpL5 trimers strengthen the authors' findings.

Weaknesses:

A more detailed description of the current mechanistic hypothesis would strengthen the manuscript. The authors state that the two periplasmic domains "are expected to undergo rigid body movements that allow substrate transport through these periplasmic domains similar to the conformational changes observed in the E. coli multidrug efflux pump AcrB". A schematic of the proposed transport cycle, as a supplemental figure that shows the current hypothesis regarding transport, would be beneficial for understanding the previous structures and putting the current structure in context. Outside of "the mechanistic basis of how these conformational changes are coupled to protonation of the DY-pairs", what are the major controversies/open questions regarding the mechanism?

The authors provide evidence that the cysteine-depleted S4L4 construct is functional, but do not show that the construct with the introduced disulfide bond #5 (D39C MmpS4 and S434C MmpL4) is also functional. Demonstrating this would allow the authors to better interpret their resulting structures.

The analysis presented in Figure 5 and Supplementary Figure 7 seems to suggest that the authors are proposing that the CCD central cavity acts as a transport pathway for the transported substrate, but I am not sure that this hypothesis is explicitly stated. This makes the reasoning behind the analysis presented unclear. Clarity could be improved by stating that the hypothesis of direct transport of substrate through the CCD central channel is being examined using the structure prediction, and what the implications are for the structure solved with the incompletely formed CCD.

Given that the results emphasize the flexibility of the CCD, the manuscript would be strengthened by 3D variability analysis either in cryoSPARC or using cryoDRGN (or both). This would allow the authors to better quantify the degree of motion in the CCD and how it may correlate to flexibility in other regions. Further 3D flex reconstruction in cryoSPARC may improve the map quality of the CCD.

Reviewer #2 (Public review):

Summary:

This is an inspired study that merges the concept of individuality with evolutionary processes to uncover a new strategy that diversifies individual behavior that is also potentially evolutionarily adaptive.

The authors use time-resolved measurement of spontaneous, innate behavior, namely handedness or turn bias in individual, isogenic flies, across several genetic backgrounds.

They find that an individual's behavior changes over time, or drifts. This has been observed before, but what is interesting here is that by looking at multiple genotypes, the authors find the amount of drift is consistent within genotype i.e., genetically regulated, and thus not entirely stochastic. This is not in line with what is known about innate, spontaneous behaviors. Normally, fluctuations in behavior would be ascribed to a response to environmental noise. However, here, the authors go on to find what is the pattern or rule that determines the rate of change of the behavior over time within individuals. Using modeling of behavior and environment in the context of evolutionarily important timeframes such as lifespan or reproductive age, they could show when drift is favored over bet-hedging and that there is an evolutionary purpose to behavioral drift. Namely, drift diversifies behaviors across individuals of the same genotype within the timescale of lifespan, so that the genotype's chance for expressing beneficial behavior is optimally matched with potential variation of environment experienced prior to reproduction. This ultimately increases fitness of the genotype. Because they find that behavioral drift is genetically variable, they argue it can also evolve.

Strengths:

Unlike most studies of individuality, in this study, authors consider the impact of individuality on evolution. This is enabled by the use of multiple natural genetic backgrounds and an appropriately large number of individuals to come to the conclusions presented in the study. I thought it was really creative to study how individual behavior evolves over multiple timescales. And indeed this approach yielded interesting and important insight into individuality. Unlike most studies so far, this one highlights that behavioral individuality is not a static property of an individual, but it dynamically changes. Also, placing these findings in the evolutionary context was beneficial. The conclusion that individual drift and bet-hedging are differently favored over different timescales is, I think, a significant and exciting finding.

Overall, I think this study highlights how little we know about the fundamental, general concepts behind individuality and why behavioral individuality is an important trait. They also show that with simple but elegant behavioral experiments and appropriate modeling, we could uncover fundamental rules underlying the emergence of individual behavior. These rules may not at all be apparent using classical approaches to studying individuality, using individual variation within a single genotype or within a single timeframe.

Weaknesses:

I am unconvinced by the claim that serotonin neuron circuits are regulating behavioral drift, especially because of its bidirectional effect and lack of relative results for other neuromodulators. Without testing other neuromodulators, it will remain unclear if serotonin intervention increases behavioral noise within individuals, or if any other pharmacological or genetic intervention would do the same. Another issue is that the amount of drugs that the individuals ingested was not tracked. Variable amounts can result in variable changes in behavior that are more consistent with the interpretation of environmental plasticity, rather than behavioral drift. With the current evidence presented, individual behavior may change upon serotonin perturbation, but this does not necessarily mean that it changes or regulates drift.

However, I think for the scope of this study, finding out whether serotonin regulates drift or not is less important. I understand that today there is a strong push to find molecular and circuit mechanisms of any behavior, and other peers may have asked for such experiments, perhaps even simply out of habit. Fortunately, the main conclusions derived from behavioral data across multiple genetic backgrounds and the modeling are anyway novel, interesting and in fact more fundamental than showing if it is serotonin that does it or not.

To this point, one thing that was unclear from the methods section is whether genotypes that were tested were raised in replicate vials and how was replication accounted for in the analyses. This is a crucial point - the conclusion that genotypes have different amounts of behavioral drift cannot be drawn without showing that the difference in behavioral drift does not stem from differences in developmental environment.

Comments on the latest version:

The changes to the manuscript sufficiently addressed my few comments. I do not have anything else substantial to add to my review and I am comfortable with my initial assessment.

Reviewer #2 (Public review):

Summary:

The main objective of the study was to link the changes in brain state due to anesthesia to consequences on visual neural processing, particularly effects on spatial frequency tuning. This is accomplished by 2-photon imaging of excitatory and inhibitory neurons (separating PV- and SST-positive subtypes) in mouse visual cortex during full-field visual stimulation with gratings, and tracking neuronal tuning for spatial frequency before, during, and after isoflurane anesthesia. The main finding is that anesthesia induces lower spatial frequency preferences in excitatory neurons, and this leads to poorer population representations (decoding) of higher spatial frequency responses during anesthesia. A second main finding is that anesthesia impacts inhibitory neuron subtypes in distinct ways, with the most pronounced effects of anesthesia on somatostatin inhibitory neurons.

Strengths:

(1) A main strength is that the study is that it is straightforward, and reassuringly, the results confirm multiple previous studies showing anesthesia's effects on the amplitude of cortical responses: larger and less selective responses in excitatory neurons (versus awake responses); strongly reduced responses in somatostatin inhibitory neurons (versus awake responses) (Fig. 5I-L), with less differences across anesthetized and awake states on response amplitude of PV neurons.

(2) These confirmations of prior observations (on the amplitude of responses) establish good ground for the new results on spatial frequency tuning. For excitatory neurons, spatial frequency selectivity shifts to higher values in awake versus anesthetized conditions; this is because anesthesia induces larger responses to lower spatial frequencies. In somatostatin neurons, instead, wakefulness reduces the lower spatial frequency responses present in anesthesia, and dramatically increases the overall amplitude of responses and medium and higher spatial frequencies. This is consistent with prior work showing that in awake states, somatostatin neurons exert broad inhibition in V1; this study extends that finding to the tuning of spatial frequencies.

Weaknesses:

(1) A first weakness of the study is the lack of examination of changes to single neuron receptive field sizes and/or surround suppression across conditions, and how these may relate to the effects on spatial frequency tuning with full field gratings. There is a well-known relationship between the size of the receptive field and the resulting selectivity for spatial frequencies (i.e., large receptive fields prefer lower spatial frequency stimuli). Likewise, there are many studies showing how surround suppression / spatial integration is impacted by anesthesia (and arousal). A more detailed examination of all these related quantities on an individual neuron basis would provide a greater understanding of the factors underlying the effects on spatial frequency tuning. One could imagine that receptive field changes, and/or changes in surround suppression, influence the selectivity to full-field gratings.

(2) A second weakness is the lack of examination/insight into the temporal dynamics of the effects. The experimental paradigm records activity across control, anesthesia, and recovery epochs in a single duration (~40 mins) session. The epochs are simply binned together ("Awake", "Anes.", "Recover"). It is not clear how the start of the anesthesia bin is defined, nor is it clear how the recovery period is defined. It is also not clear what the changes are to motor tone, brain state, etc., that are also strong influences on visual responses in mouse V1. Presumably, these onset/offset effects are similar enough across mice and sessions that they affect all the bins in the same way, but greater examination of the temporal effects in excitatory, PV, and SOM neurons could shed light on interactions driving the changes. Is there some temporal dependence of anesthesia on selectivity changes across the cell types? For example, at the onset of anesthesia, are SOM neurons losing broadband frequency responses before the excitatory neurons gain low frequency responses? Do PV neurons also show effects after the changes in SOM neurons (suggesting strong SOM -> PV inhibition)? Such analysis might shed light on the timing/causality of the effects among these 3 neuron types.

(3) A third weakness concerns the interpretation of the low and high arousal conditions during awake states (Figure 6). It is not clear how movement (or lack of movement) impacts the high arousal epochs, nor is it clear how the low arousal condition compares to the brain state during anesthesia. For example, deep versus light anesthesia can lead to synchronized or asynchronous states, respectively, and low arousal in wakefulness can show strong low-frequency oscillations of activity, which could promote a lower excitability state than light anesthesia. Without some more detail about commonly measured brain state or body/face motion metrics, it is difficult to know what brain states are represented by the bins and how to interpret the comparisons.

Overall, the study uses adequate methods and experimental design to demonstrate solid support for the (somewhat narrow) central finding that anesthesia lowers the spatial resolution of mouse V1 responses.

Since this is a very well-examined topic, the findings here are not totally surprising, but confirmatory and slightly extend prior findings (a good thing). As such, the study will likely have most relevance to specialists in the mouse visual system, but if the study could address some of the remaining questions discussed above, this would potentially broaden the implications of the study to general insights about the operation of cortical circuitry.

Reviewer #2 (Public review):

This paper by Kleinman et al. tackles an increasingly discussed biosecurity scenario, namely the possibility that "mirror bacteria" could evade key elements of host immunity and therefore demand bespoke medical countermeasures. The authors experimentally probe two such countermeasure concepts: (1) whether existing chiral antibiotics might still work against mirror bacteria (this is tested indirectly by measuring the activity of antibiotic enantiomers against natural-chirality bacteria), and (2) whether D-peptide antigens can be made immunogenic. Briefly, the authors show that enantiomers of four approved antibiotics have little to no activity in MIC assays, argue this implies the parent drugs would likely fail against mirror bacteria, report limited single-dose tolerability data for the enantiomers in mice, and show that selected bacterially derived D-peptides can elicit strong binding antibody titers when conjugated to a carrier protein and given with adjuvant.

Overall, the study is quite interesting but constrained by the fact that D-peptide immunogens and related ideas have been explored for decades, by prior literature showing that D-enantiomeric peptides can themselves be strongly antimicrobial vs conventional bacteria, and by a number of conceptual and experimental limitations outlined below.

(1) A blanket statement indicating that flipping chirality makes antibiotics ineffective cannot be true across all classes. Indeed, there is extensive precedent for "mirror" (D-amino-acid) peptides that retain, or even improve, antimicrobial activity against natural bacteria.

(2) The paper's key claim ("parent antibiotics won't work on mirror bacteria") is based on the observation that the enantiomers of chloramphenicol/linezolid/tedizolid/aztreonam largely lose activity against natural bacteria. This is a reasonable proxy experiment given the absence of mirror organisms, but it remains an inference and should be described as such.

(3) The chiral purity needs to be documented more rigorously. The methods mention structural confirmation by NMR and >95% purity by LC-MS/HPLC for enantiomeric compounds, but this is not the same as demonstrating high enantiomeric excess or excluding low-level contamination by the active parent enantiomer.

(4) The residual activity of ent-aztreonam is quite interesting. The authors report slight activity for ent-aztreonam (MIC of 32-128 µg/mL in a subset), still far weaker than aztreonam but nonzero.

(5) For antibiotics, MIC is a starting point, but further experiments are needed. To justify countermeasure relevance, it would help to include at least one additional pharmacodynamic readout (time-kill kinetics, post-antibiotic effect, inoculum effect, or activity in the presence of human serum).

(6) The acute toxicity study is limited (single-dose, short follow-up, small n, one sex/strain, and no histopathology).

(7) The Discussion leans on human equivalent dosing logic to reassure feasibility. Given the lack of PK, bioavailability, metabolism, and repeat-dose data, these comparisons risk overreach.

(8) The readout is ELISA endpoint binding (IgG; and IgA in BALF for one antigen), which is fine for an initial immunogenicity screen. But the manuscript then drifts toward "vaccine strategy" claims without showing any antibody functionality (opsonophagocytosis, complement deposition, neutralization, blocking adhesion, and so on) or even binding to a more native-like antigen format (e.g., D-peptide displayed on particles; D-protein fragments; or any surrogate that goes beyond plate-bound peptide).

(9) The methods report peptide conjugates containing ~10-200 EU/mL endotoxin. That is not trivial and could materially amplify immunogenicity, and should be discussed.

(10) The authors should report how many technical/biological replicates were performed for MIC determinations and for ELISAs.

Reviewer #2 (Public review):

Summary:

In this study, Zhou et al investigated the expression and function of AIRE in B cells in peripheral lymphoid tissues. First, they found the expression of AIRE protein in mature B cells in the follicles in human tonsils and spleens from healthy donors. Flow cytometry analyses using human samples as well as Aire-reporter mice demonstrated AIRE expression in germinal center B cells. The expression of Aire in B cells was induced by CD40 signals. Then, to investigate the impact of AIRE deficiency on B-cell function, the authors used a method of transplanting bone marrow cells from Aire-KO and WT mice into B-cell-deficient mice, comparing B-cell development and function reconstituted in the recipient mice. Their results showed that Aire-deficient B cells strongly responded to immunization with antigens, exhibiting enhanced class switching and somatic hypermutation of antibodies compared with WT B cells. The same phenomena were observed in CRISPRed B cell lines lacking Aire. The authors successfully utilized the Aire-deficient B cell line to demonstrate that Aire suppresses antibody class switching and somatic hypermutation via its interaction with AID. Finally, using B cell transfer into B cell-deficient mice demonstrated that mice harboring Aire-deficient B cells produced high levels of autoantibodies against Th17 cytokines and exhibited reduced resistance to Candida infection. This mirrors characteristic symptoms in AIRE-deficient patients. The findings of this study not only reveal an unexpected function of AIRE in B cells but also have the potential to contribute to understanding the pathogenesis of APECED and to offering a new direction for developing therapies.

Strengths:

The strength of this study lies in demonstrating the expression of the function of AIRE in B cells in both mice and humans. It also revealed the direct interaction between AIRE and AID, along with its binding mode (requiring CARD and NLS domains of AIRE), and showed that this interaction is crucial for AIRE function in B cells. It is also significant that the study demonstrated how B-cell-intrinsic dysfunction of AIRE leads to autoantibody production against cytokines.

Weaknesses:

As for loss-of-function analysis of Aire in B cells, in addition to the B cell transfer from Aire-KO mice performed in this study, generating B cell-specific Aire-deficient mice using Aire-flox mice (Dobes et al, Eur J Immunol 2018) would further reinforce the conclusions of this study. Furthermore, the relationship with Aire function in thymic B cells reported by previous studies remains unclear, posing an unresolved challenge. This study also failed to address whether Aire deficiency affects gene expression in GC B cells, in particular, whether it induces the expression of various self-antigens as reported in thymic B cells or mTECs.

Reviewer #2 (Public review):

Synesthesia is a neurological condition where stimulation of one sensory channel leads to involuntary, automatic, and consistent experience of another, unrelated percept. For example, Sir Francis Galton (1880, Nature) famously described the robust tendency of some individuals (synesthetes) to associate numerals with a distinct color. Ever since, synesthesia has continued to attract a broad interest in the cognitive neurosciences in light of its implications for the study of domains such as perception, consciousness, and brain connectivity, among others.

Strauch, Leenaars, and Rouw measured pupil size in a group of 16 grapheme-color synesthetes and two matched control groups. The participants were presented with gray digits - that is, visual stimuli having identical physical properties in terms of brightness. Each participant subsequently rated the corresponding evoked color and brightness: unlike controls, synesthetes did so in a very consistent and reliable fashion. Accordingly, this was also shown in their pupils: despite the same objective luminance, digits associated with brighter percepts caused their pupils to constrict, and digits associated with darker percepts caused their pupils to dilate more than controls. These results highlight how crossmodal correspondences are deeply rooted in synesthetes, and put forward pupillometry as a particularly appealing biomarker for some phenomenological experience (at least those grounded in "brightness").

Further strengths of the technique are its temporal resolution and its responsiveness to several constructs. Across several tasks, the authors show, for example, that responses to synesthetic light are somewhat slower than responses to real light (i.e., they are likely mediated), but at the same time faster than responses to mental imagery. The role of mental imagery can also be reasonably dismissed when considering the second feature of pupil size: its responsiveness to mental effort and cognitive load. The pupils tend to dilate with demanding, challenging tasks, and this was the case when control participants were asked to report the color of a digit for which they did not consistently experience a synesthetic association. The same task was, instead, seemingly effortless for synesthetes, again speaking in favor of the automaticity of number-color correspondences in their case.

Overall, the findings by Strauch, Leenaars, and Rouw are highly significant for the field and likely to be impactful. The strength of their evidence, when accounting for the relatively small sample size and the inherent variability of both phenomenology (color perception and subjective reporting) and physiology (pupil size), is adequate and sufficiently convincing.

Reviewer #3 (Public review):

Summary:

The authors utilized ChIP-seq on strains containing tagged transcription factor (TF)-overexpression plasmids to identify binding sites for 172 transcription factors in P. aeruginosa. High-quality binding site data provides a rich resource for understanding regulation in this critical pathogen. These TFs were selected to fill gaps in prior studies measuring TF binding sites in P. aeruginosa. The authors further perform a structured analysis of the resulting transcriptional regulatory network, focusing on regulators of virulence and metabolism, in addition to performing a pangenomic analysis of the TFs. The resulting dataset has been made available through an online database. While the implemented approach to determining functional TF binding sites has limitations, the resulting dataset still has substantial value to P. aeruginosa research.

Strengths:

The generated TF binding site database fills an important gap in regulatory data in the key pathogen P. aeruginosa. Key analyses of this dataset presented include an analysis of TF interactions and regulators of virulence and metabolism, which should provide important context for future studies into these processes. Experimental validation has been included in the revised version. The online database containing this data is well organized and easy to access. As a data resource, this work should be of significant value to the infectious disease community.

Weaknesses:

Drawbacks of the study, which have been mitigated in a revised version, include 1) challenges interpreting binding site data obtained from TF overexpression due to unknown activity state of the TFs on the measured conditions (discussed by the authors), and 2) remaining challenges in the practical utilization of the TRN topological analysis.

Reviewer #3 (Public review):

Summary:

Varani et al present important findings regarding the role of distinct cerebellothalamic connections in motor learning and performance. Their key findings are that: 1) cerebellothalamic connections are important for learning motor skills, 2) cerebellar efferents specifically to the central lateral (CL) thalamus are important for short-term learning, 3) cerebellar efferents specifically to the ventral anterior lateral (VAL) complex are important for offline consolidation of learned skills, and 4) that once a skill is acquired, cerebellothalamic connections become important for online task performance. The authors went to great lengths to separate effects on motor performance from learning, for the most part successfully. While one could argue about some of the specifics, there is little doubt that the CN-CL and CN-VAL pathways play distinct roles in motor learning and performance. An important next step will be to dissect the downstream mechanisms by which these cerebellothalamic pathways mediate motor learning and adaptation.

Strengths:

(1) The dissociation between on-line learning through CN-CL and offline consolidation through CN-VAL is convincing.

(2) The ability to tease learning apart from performance using their titrated chemogenetic approach is impressive. In particular, their use of multiple motor assays to demonstrate preserved motor function and balance is an important control.

(3) The evidence supporting the main claims is convincing, with multiple replications of the findings and appropriate controls.

(4) The retrograde tracing experiments (Supplementary Figure 5) demonstrate convincingly that the CN-VAL and CN-CL projections are almost entirely segregated,

Weaknesses:

(1) Despite the care the authors took to demonstrate that their chemogenetic approach does not impair online performance, there is (as they acknowledge in the Discussion) impaired rotarod performance at fixed higher speeds in Supplementary Figure 4f for CN-VAL projections, suggesting that there could be subtle changes in motor performance below the level of detection of their assays. There is also a trend in the same direction that did not pass significance for CN-CL at higher speeds, suggesting that part of the effects could be related to subtle deficits in performance.

Reviewer #2 (Public review):

The authors hypothesized that chemostat propagated viromes could modulate the GM and reduce NEC lesions while avoiding potential side effects, such as the earlier onset of diarrhea. This is interesting.

Major revision

(1) As authors said, the aim of the research is 'We hypothesized that chemostat propagated viromes could modulate the GM and reduce NEC lesions while avoiding potentialside effects, such as earlier onset of diarrhea'.

(a) For the efficacy, in Fig 5, there are no significance in stomach pathology and enterocolitis between groups, even between the control group and the experimental groups, is it because of the low incidence of NEC? This may affect the statistical power of the conclusions. And how can you draw the conclusion that chemostat can reduce NEC lesions?

(b) Lack of gross view pictures of animal tissues or any other pathological pictures is not convincing.

(c) For the safety, such as body weight development, FVT had no statistical significance with control, CVT and CVT-MO, so how can you draw the conclusion that chemostat can avoiding potentialside effects?

(d) The evidence to prove the decrease of eukaryotic viruses are not enough and quantitative.

(2) Fig 3F,

(a) How can a medium have 'the baseline viral content' ?

(b) Statistical significance of relative abundance of specific eukaryotic viral contigs between different times is unkown.

(c) Some of listed eukaryotic viruses, their hosts are not pigs, piglets or even human, so what's the meaning if these eukaryotic viruses decreased?

(3) In this study, pH 6.5 was selected as the pH value for chemostat cultivation, but considering the different adaptability of different bacteria to pH, it is recommended to further explore the effect of pH on bacteria and virus groups. In particular, it was optimized to maintain the growth of beneficial bacteria such as Lactobacillaceae and Bacteroides in order to improve the effect of chemostat cultivation.

(4) In some charts, the annotation of error lines, statistical significance markers (even 'ns' should be marked), etc., should be more standardized and clearer. And in your results section, the combination of pictures is messy, thus maybe you should do some recombination.

Comments on revisions:

(1) At the design level, the study posited "reduction of necrotizing enterocolitis (NEC)" as the primary hypothesis and endpoint. Yet neither of the two in-vivo experiments demonstrated any NEC-protective signal; Experiment 2 even showed a trend toward more severe gastric lesions. Although delayed onset of diarrhea can be listed as a secondary endpoint, its clinical significance is limited. The work remains a safety proof-of-concept and falls short of efficacy validation, yielding insufficient scientific value for publication.

(2) The manuscript postulates a link between the loss of Lactobacillaceae phages and the absence of NEC protection, but no reverse verification (e.g., re-introducing these phages or optimizing culture to retain them) was performed within the study.

(3) Culturing intestinal microbiota ex vivo is inherently challenging, owing to oxygen sensitivity, pH drift, nutrient depletion, and other factors. This study not only failed to demonstrate stable congruence between the cultured community and the original fecal inoculum, but also documented a marked loss of Lactobacillaceae and a 75 % drop in viral diversity. In the absence of any NEC-protective efficacy, the authors likewise provide no functional validation of phage viability (lysis assays, MOI determination, etc.). Consequently, the data are inadequate to support expectations of therapeutic benefit in vivo.

Reviewer #2 (Public review):

Summary:

Endowing protein language models with an ability to predict the function of antibodies would open a world of translational possibilities. However, antibody language models have yet to achieve the breakthrough success, which large language models have achieved for the understanding and generation of natural language. This paper elegantly demonstrates how training objectives imported from natural language applications lead antibody language models astray on function prediction tasks. Training models to predict masked amino acids teaches models to exploit biases of nucleotide-level mutational processes, rather than protein biophysics. Taking the underlying biology of antibody diversification and selection seriously allows disentangling these processes, through what the authors call deep amino acid selection models. These models extend previous work by the authors (Matsen MBE 2025) by providing predictions not only for the selection strength at individual sites, but also for individual amino acids substitutions. This represents a practically important advance.

Strengths:

The paper is based on a deep conceptual insight, the existence of multitude of biological processes that affect antibody maturation trajectories. The figures and writing a very clear, which should help make the broader field aware of this important but sometimes overlooked insight. The paper adds to a growing literature proposing biology-informed tweaks for training protein language models, and should thus be of interest to a wide readership interested in the application of machine learning to protein sequence understanding and design.

Weaknesses:

Proponents of the state-of-the-art protein language models might counter the claims of the paper by appealing to the ability of fine-tuning to deconvolve selection and mutation-related signatures in their high-dimensional representation spaces. Leaving the exercise of assessing this claim entirely to future work somewhat diminishes the heft of the (otherwise good!) argument. In the context of predicting antibody binding affinity, the modeling strategy only allows prediction of mutations that improve affinity on average but not those which improve binding to specific epitopes.

Comments on revisions:

We thank the authors for clarifying the description of the methods and for adding additional discussion of important directions for future work.

Reviewer #2 (Public review):

Summary:

This manuscript reports the identification of ZNF-236 as a key regulator that maintains quiescence of heat shock inducible genes in C. elegans. Using a forward genetic screen for constitutive activation of an endogenous hsp-16.41 reporter, the authors show that loss of znf-236 leads to widespread, HSF-1-dependent expression of inducible heat shock proteins (iHSPs) and a subset of prion-like stress-responsive genes, in the absence of proteotoxic stress. Transcriptomic analysis reveals that znf-236 mutants partially overlap with the canonical heat shock response, selectively activating highly inducible iHSPs rather than the full HSR program. iHSP transgenes integrated throughout the genome generally become de-repressed in znf-236 mutants, whereas the same constructs on extrachromosomal arrays or inserted into the rDNA locus re insensitive to znf-236 loss. Using a newly developed method, Transcription Factor Deaminase Sequencing (TFD-seq), the authors show that ZNF-236 binds sparsely across the genome and does not associate with iHSP promoters, supporting an indirect mode of regulation. Physiologically, znf-236 mutants exhibit increased thermotolerance and maintain iHSP expression during aging.

Strengths:

This is a carefully executed and internally consistent study that identifies a new regulator of stress-induced gene quiescence in C. elegans. The genetics are clean and the phenotypes are robust.

Weaknesses:

The manuscript is largely descriptive. It would be substantially strengthened by deeper mechanistic insight into what ZNF-236 does beyond being required for default silencing.

Reviewer #2 (Public review):

Summary:

The question of how caloric and taste information interact and consolidate remains both active and highly relevant to human health and cognition. The authors of this work sought to understand how nutrient sensing of glucose modulates sweet sensation. They found that glucose intake activates hugin signaling to AstA neurons to suppress feeding, which contributes to our mechanistic understanding of nutrient sensation. They did this by leveraging the genetic tools of Drosophila to carry out nuanced experimental manipulations, and confirmed the conservation of their main mechanism in a mammalian model. This work builds on previous studies examining sugar taste and caloric sensing, enhancing the resolution of our understanding.

Strengths:

Fully discovering neural circuits that connect body state with perception remains central to understanding homeostasis and behavior. This study expands our understanding of sugar sensing, providing mechanistic evidence for a hugin/AstA circuit that is responsive to sugar intake and suppresses feeding. In addition to effectively leveraging the genetic tools of Drosophila, this study further extends their findings into a mammalian model with the discovery that NMU neural signaling is also responsive to sugar intake.

Weaknesses:

The effect of Glut1 knockdown on PER in hugin neurons is modest in both fed and starved flies, suggesting that glucose intake through Glut1 may only be part of the mechanism. Additionally, many of the manipulations testing the "brake" circuitry throughout the study show similar effects in both fed and starved flies. This suggests that the focus of the discussion and Supplemental Figure 16 on a satiety-specific "brake" mechanism may not be fully supported by the data.

Reviewer #3 (Public review):

Summary:

The authors propose a method for estimating the spatial power spectrum of cortical activity from irregularly sampled data and apply it to iEEG data from human patients during a delayed free recall task. The main findings are that the spatial spectra of cortical activity peak at low spatial frequencies and decrease with increasing spatial frequency. This is observed over a broad range of temporal frequencies (2-100 Hz).

Strengths:

A strength of the study is the type of data that is used. As pointed out by the authors, spatial spectra of cortical activity are difficult to estimate from non-invasive measurements (EEG and MEG) and from commonly used intracranial measurements (i.e. electrocorticography or Utah arrays) due to their limited spatial extent. In contrast, iEEG measurements are easier to interpret than EEG/MEG measurements and typically have larger spatial coverage than Utah arrays. However, iEEG is irregularly sampled within the three-dimensional brain volume and this poses a methodological problem that the proposed method aims to address.

Weaknesses:

Although the proposed method is evaluated in several indirect ways, a direct evaluation is lacking. This would entail simulating cortical current source density (CSD) with known spatial spectrum and using a realistic iEEG volume-conductor model to generate iEEG signals.

Comments on revisions:

I would like to clarify two points:

(1) In their response, the authors frame the role of simulations primarily as a means of assessing the effects of volume conduction. However, the purpose of evaluating a proposed estimation method through simulations extends beyond this specific issue. More generally, simulations are essential for establishing that the proposed method-particularly given the multiple non-trivial transformations applied to the observed data-produces accurate and reliable estimates under controlled conditions.

(2) The authors seem to interpret my use of the term current source density as referring to the current source density (CSD) method, which is an approach to mitigating volume conduction by inverting Poisson's equation. This was not my intention: current source density refers to the physical quantity (i.e., the spatial density of current sources) underlying macroscopic brain activity, and is independent of any specific estimation or inversion technique.

Reviewer #2 (Public review):

Summary:

This paper presents a novel transformer-based neural network model, termed the epistatic transformer, designed to isolate and quantify higher-order epistasis in protein sequence-function relationships. By modifying the multi-head attention architecture, the authors claim they can precisely control the order of specific epistatic interactions captured by the model. The approach is applied to both simulated data and ten diverse experimental deep mutational scanning (DMS) datasets, including full-length proteins. The authors argue that higher-order epistasis, although often modest in global contribution, plays critical roles in extrapolation and capturing distant genotypic effects, especially in multi-peak fitness landscapes.

Strengths:

(1) The study tackles a long-standing question in molecular evolution and protein engineering: "how significant are epistatic interactions beyond pairwise effects?" The question is relevant given the growing availability of large-scale DMS datasets and increasing reliance on machine learning in protein design.

(2) The manuscript includes both simulation and real-data experiments, as well as extrapolation tasks (e.g., predicting distant genotypes, cross-ortholog transfer). These well-rounded evaluations demonstrate robustness and applicability.

(3) The code is made available for reproducibility.

Weaknesses:

(1) The paper mainly compares its transformer models to additive models and occasionally to linear pairwise interaction models. However, other strong baselines exist. For example, the authors should compare baseline methods such as "DANGO: Predicting higher-order genetic interactions". There are many works related to pairwise interaction detection, such as: "Detecting statistical interactions from neural network weights", "shapiq: Shapley interactions for machine learning", and "Error-controlled non-additive interaction discovery in machine learning models".

(2) While the transformer architecture is cleverly adapted, the claim that it allows for "explicit control" and "interpretability" over interaction order may be overstated. Although the 2^M scaling with MHA layers is shown empirically, the actual biological interactions captured by the attention mechanism remain opaque. A deeper analysis of learned attention maps or embedding similarities (e.g., visualizations, site-specific interaction clusters) could substantiate claims about interpretability.

(3) The distinction between nonspecific (global) and specific epistasis is central to the modeling framework, yet it remains conceptually underdeveloped. While a sigmoid function is used to model global effects, it's unclear to what extent this functional form suffices. The authors should justify this choice more rigorously or at least acknowledge its limitations and potential implications.

(4) The manuscript refers to "pairwise", "3-4-way", and ">4-way" interactions without always clearly defining the boundaries of these groupings or how exactly the order is inferred from transformer layer depth. This can be confusing to readers unfamiliar with the architecture or with statistical definitions of interaction order. The authors should clarify terminology consistently. Including a visual mapping or table linking a number of layers to the maximum modeled interaction order could be helpful.

Comments for the revision:

I want to thank the authors for their efforts in revising the manuscript. Most of the concerns raised in the initial review have been adequately addressed.

However, one important issue remains. I previously asked the authors to benchmark their method against stronger baselines. The authors declined, arguing that these alternatives are "not directly applicable to the types of analyses." I am not persuaded by this rationale. In my view, these baseline methods target essentially the same underlying problem, and at least some, if not all, should be included in a comparative evaluation (or the manuscript should provide a clearer, more technically grounded explanation of why such comparisons are not feasible or not meaningful).

DOI: 10.1016/j.isci.2026.115231

Resource: None

Curator: @areedewitt04

SciCrunch record: RRID:ZFIN_ZDB-ALT-130404-2

What is this?

Reviewer #2 (Public review):

Summary:

This paper starts with a large-scale yeast two-hybrid (Y2H) screen using Set1 (full-length and smaller parts) and other Set1C/COMPASS subunits as bait. There are hundreds of possible interactions identified, but only a small number are given any follow-up. While it's useful to document all the possible interactions, the unfocused and preliminary nature of the results makes the paper feel scattered and incomplete.

Strengths:

The Y2H screen was very comprehensive, producing lots of interesting possible leads for further experiments.

Weaknesses:

The results are useful but incomplete because only a small subset of the Y2H interactions is further examined. Even in the case of those that were further tested, the validating experiments are only partial or inconclusive.

Reviewer #2 (Public review):

Summary:

The authors measure the directional consistency of water diffusion in white matter (functional anisotropy: FA) to stratify depression subtypes across young adults. These findings are significant in that they highlight white matter as an underappreciated aspect of neural heterogeneity in major depressive disorder. While the evidence for meaningful, lower-dimensional structure in depression heterogeneity within their Nanjing cohorts is strong, claims that their subtypes are characterized by specific clinical symptom profiles and reflect neuroplasticity reserve are not supported by the same strength of evidence.

Strengths:

Circumscribing analyses to a simple white matter measure, across a sparse skeleton, with explicit sparsity-promoting algorithms yielded heterogeneity subdivisions that are much more interpretable than most depression heterogeneity clustering papers. Replication of their 3-cluster solution in an external dataset bolsters confidence in the existence of these 3 clusters, although generalizability to more diverse populations remains untested. The authors also tested a wide variety of treatment outcomes, which is difficult data to aggregate but ultimately critical for validating the utility of depression subtypes.

Weaknesses:

sCCA and SVR results were less interpretable. In part, this is due to core features of these methods (broad distribution of weights, instability across iterations). However, these inherent components of sCCA and SVR opacity were exacerbated by the opacity surrounding several analytic choices made by the authors and intermediate results associated with them. Without more transparency, it's unclear how these results extend the neuroclinical differentiation established (or not established) by their original NMF analyses.

To be more specific, a central claim of the paper is that their biotypes are "pathophysiologically distinct" and demonstrate "symptom-specific neurobiological substrates". However, only 3/18 pairwise symptom differences generalize across both datasets (Figures 1 and 2), implying that these biotypes have more symptom overlap than distinction. Brain-based distinctions are real and replicable, but because their NMF approach specifically optimizes for separating clusters on the basis of brain features, this is more of a methodological validation than a scientific finding. While several brain-symptom relationships reported later using sCCA and SVR are interesting, it is not currently possible to evaluate the robustness of these relationships and whether or not these relationships are nested within NMF-derived clusters or exist regardless of subtype.

To be clear, the heterogeneity problem in depression is extremely difficult to solve and beyond the scope of this manuscript. Despite the scale of this problem, the authors do report tangible progress in this aim, largely through finding an interpretable set of white matter features distinguishing patient clusters. These findings may lead researchers to meaningfully incorporate white matter features into heterogeneity analyses more in the future. However, many of the claims made are not fully supported, particularly surrounding clinical specificity and neuroplasticity reserve.

Reviewer #2 (Public review):

In this paper, Hamid et al present 40 genomes from the Faroe Islands. They use these data (a pilot study for an anticipated larger-scale sequencing effort) to discuss the population genetic diversity and history of the sample, and the Faroes population. I think this is an overall solid paper; it is overall well-polished and well-written. It is somewhat descriptive (as might be expected for an explorative pilot study), but does make good use of the data.

The data processing and annotation follows a state-of-the-art protocol, and at least I could not find any evidence in the results that would pinpoint towards bioinformatic issues having substantially biased some of the results, and at least preliminary results lead to the identification of some candidate disease alleles, showing that small, isolated cohorts can be an efficient way to find populations with locally common, but globally rare disease alleles.

I also enjoyed the population structure analysis in the context of ancient samples, which gives some context to the genetic ancestry of Faroese, although it would have been nice if that could have been quantified, and it is unfortunate that the sampling scheme effectively precludes within-Faroes analyses.

Comments on the revision:

I appreciate the authors' detailed and thoughtful response to my review. They have addressed all my concerns to my satisfaction and I have no additional comments.

Reviewer #3 (Public review):

Henshall et al. study invasion of human erythrocytes by Plasmodium falciparum merozoites and report knockout of PfMSP2, a critical merozoite surface protein with unknown function. They describe conservation of MSP2 in P. falciparum and key avian malaria parasites, unabated growth of two knockout lines (∆MSP2) produced in divergent 3D7 and Dd2 strains, no differences in expression of key invasion-associated genes, no effect on invasion kinetics (with or without protease treatment of erythrocytes), nonsignificant effects of knockout on parasite growth inhibition by antibodies directed against key invasion-associated antigens, and do find a significant effect on potentiating AMA1 invasion inhibitory antibodies. The studies are interesting and have potential for directing vaccine design targeting erythrocyte invasion, a critical step in bloodstream expansion of malaria parasites.

Major points:

(1) Much of the manuscript describes negative results and this reviewer found it arduous to get through many negative or nonsignificant results before finally getting to the significant effect on AMA1 inhibitory antibodies, not presented until Figure 6! Computational studies in Fig. 1 could be a supplementary figure. Figs. 2 and 3. demonstrate knockout in 3D7 and Dd2, respectively and could be assembled into a single figure. (Notably Fig. 2A and 3A are almost identical with use of some different primers.) Fig. 2E, 2F, 3D-H, all of Fig. 4, most of Fig. 5 are all negative or insignificant results that could also be moved to supplementary data. As MSP4, MSP5, and SUB1 are presumably included in the whole genome RNA-seq experiments shown in Fig. 4C, it makes sense to remove Fig. 4A data from the paper fully. These consolidating changes would help highlight the key finding of improved binding and block of AMA1's role in invasion.

(2) The potentiating effects on anti-AMA1 antibodies are shown with rabbit sera and purified antibodies, mouse monoclonal antibodies, and smaller i-bodies inspired by shark antibody-like receptors but not with human monoclonal antibodies (hmAbs). As naturally acquired hmAbs targeting AMA1 have been identified and characterized (PMIDs: 39632799, 40020675), would it not be important to test these antibodies in the ∆MSP2, especially as the authors emphasize the importance of their model in designing better human malaria vaccines?

(3) Fig. 7 presents quantitative fluorescence microscopy to measure anti-AMA1 binding and support a model where MSP2 serves to sterically hinder antibody access to AMA1 on individual merozoites. I understand that the negative WD33 control is useful to contrast to the positive WD34 antibody (both bind AMA1 but only WD34 exhibits parasite growth inhibitory effects), but it seems that use of smaller i-bodies rather than conventional larger mouse or ideally human monoclonal antibodies may compromise demonstration of steric hindrance by MSP2 because smaller i-bodies may be less hinder.

(4) Some explanation for why WD33 fails to inhibit growth despite targeting the same antigen as WD34 is needed. Are the epitopes known? Does one bind further from the RON2 binding pocket?

Reviewer #2 (Public review):

Summary:

The authors used the Drosophila heart tube to model Retinal vasculopathy with the goal of building a model that could be used to identify druggable targets and for testing chemical compounds that might target the disease. They generated flies expressing human TREX1 as well as a line expressing the V235G mutation that causes a C-terminal truncation that has been linked to the disease. In humans, this mutation is dominant. Heart tube function was monitored using OCM; the most robust change upon overexpression of wild-type or mutant TREX1was heart tube restriction, and this effect was similar for both forms of TREX1. Lifespan and climbing assays did show differential effects between wt and mutant forms when they were strongly and ubiquitously expressed by an actin-Gal4 driver. Unfortunately, these types of assays are less useful as drug screening tools. Their conclusion that the primary effect of TREX is on neuronal function is inferential and not directly supported by the data.

Strengths:

The authors do not show that CG3165 is normally expressed in the heart. Further fly heart tube function was similarly restricted in response to expression of either wild-type or mutant TREX1. The fact that expression of any form of human TREX1 had deleterious effects on heart function suggests that TREX1 serves different roles in flies compared to humans. Thus, in the case of this gene, it may not be a useful model to use to identify targets or use it as a drug screening tool.

The significant effects on lifespan and climbing that did show differential effects required ubiquitous overexpression using an actin-gal4 driver that does not allow the identification of tissue-specific effects. Thus, their assertion that the results suggested a strong positive correlation between Drosophila neuromotor regulation and transgenic hTREX1 presence and a negative impact from hTREX1 V235G" is not supported by these data. Also worrisome was the inability to identify the mutant TREX1 protein by Western blot despite the enhanced expression levels suggested by qPCR analysis. Mutant TREX1 cannot exert a dominant effect on cell function if it isn't present.

There are also some technical problems. The lifespan assays lack important controls, and the climbing assays do not appear to have been performed correctly. It is unclear what the WT genetic background is in Figure 1-3, so it is unclear if the appropriate controls have been used. Finally, the lack of information on the specific statistical analyses used for each graph makes it difficult to judge the significance of the data. Overall, the current findings establish the Retinal vasculopathy disease model platform, but with only incremental new data and without any mechanistic insights.

Reviewer #2 (Public review):

This study presents a comprehensive genetic dissection of the role of IKK signaling in the development and maintenance of lymphoid gd T cells. By employing a variety of conditional and mutant mouse models, the authors demonstrate that IKK-dependent NF-κB activation is essential for the generation of type 1 gd T cells, while adaptive gd T cells require this pathway primarily for long-term survival. The use of multiple complementary genetic strategies, including IKK deletion and modulation of RIPK1 and CASPASE8 activity, provides robust mechanistic insight into subset-specific regulation of gd T cell homeostasis. Overall, the study provides mechanistic insight for IKK-dependent regulation of gd T cell development and peripheral maintenance.

Comments on revisions:

Thank you for your comments and clarifications.

Reviewer #2 (Public review):

Summary:

This manuscript investigates the protein composition and functional role of the C2a projection of the central apparatus (CA) in vertebrate motile cilia. Using three knockout mouse models (Ccdc108, Mycbpap, and Cfap70), the authors demonstrate that these genes - homologs of Chlamydomonas FAP65, FAP147, and FAP70 - are required for normal motile cilia function in ependymal and tracheal multiciliated cells. Specifically, the authors show that:

(1) Knockout mice for each gene exhibit primary ciliary dyskinesia phenotypes (hydrocephalus and sinusitis), accompanied by abnormal ciliary motion and reduced ciliary beat frequency.

(2) CCDC108, MYCBPAP, and CFAP70 physically interact and localize to the axonemal central lumen, consistent with the C2a projection.

(3) Loss of any one of these proteins destabilizes the others and disrupts CA integrity in a tissue-specific manner.

(4) ARMC3 and MYCBP are C2a-associated proteins.

Strengths:

(1) Clarity: the results are presented in a coherent sequence that facilitates understanding of both the rationale and conclusions.

(2) Genetic rigor: three independent knockout mouse lines that exhibit consistent motile cilia phenotypes provide in vivo support for the proposed role of these proteins.

(3) Integration of structural and functional analyses: combination of ultrastructural (TEM) and immunofluorescence data with CBF measurements provides convincing correlation between structural defects and impaired ciliary function.

(4) Mutual dependency model: reciprocal destabilization of CCDC108, MYCBPAP, and CFAP70 supports their interdependence in the C2a assembly.

(5) Expansion of the vertebrate C2a proteome: the identification of ARMC3 and MYCBP as C2a-associated proteins provides a foundation for future mechanistic studies.

Weaknesses:

(1) Mechanistic depth: the data show a convincing correlation between C2a and ciliary function, but the cell type-specificity of CCDC108, MYCBPAP, and CFAP70 knockout effects is underdeveloped. This is an interesting observation that raises mechanistic/structural questions not addressed in the study, such as what is the role of C2a in CP nucleation, maintenance, or mechanical stabilization? Is C2a composition different in different cell types?

(2) Cell model choice: co-immunoprecipitation was performed using mouse testis lysates. While this is a reasonable source of CA proteins from flagellated cells, the functional analyses in this study focus on ependymal and tracheal multiciliated cells. It would therefore be helpful for the authors to clarify the extent to which these interactions are expected to be conserved across ciliated cell types, and to discuss potential tissue-specific differences in CA assembly.

(3) Statistical analysis: the manuscript states "Statistical significance was defined as P < 0.5", which is likely a typo, but should be P < 0.05. In general, the statistical methods require more clarification. In several figures (e.g., 2B, 2D, 5J, 5K), multiple knockout genotypes are compared with WT, yet unpaired t-tests are reported. When more than two groups are analyzed, multiple pairwise t-tests inflate Type I error unless appropriately corrected; a one-way ANOVA with post hoc comparisons (e.g., Dunnett's test for WT-referenced comparisons) would be more appropriate. Furthermore, the analysis of ciliary movement modes (Figure 2D) involves categorical data, for which a t-test is not statistically appropriate. These comparisons could instead be evaluated using chi-square or Fisher's exact tests. Addressing these issues is important to ensure accurate statistical inference.

(4) Methods section: does not sufficiently describe how image-based quantifications were performed. For example, the criteria used to define cilia number, basal body number, and rotational beating are not specified, nor is how CBF measurements were analyzed. The authors should also provide details regarding analysis software and imaging parameters used (and whether they were kept constant across genotypes).

Reviewer #2 (Public review):

Summary:

In the manuscript "Primordial Cardiomyocytes orchestrate myocardial morphogenesis and vascularization but are dispensable for regeneration", Sun et al. identify a novel marker of primordial cardiomyocytes and use it to visualize and ablate the population during development and regeneration. The role of the primordial layer has not been investigated because the tools to manipulate this population have not existed. The manuscript is straightforward, easy to understand, and addresses an important question that has not been explored.

While the manuscript provides important insights into the role of primordial CMs, backed by a convincing methodology, the authors should clarify their requirements for heart development and maturation. Specifically, is the primordial layer required for the fish to survive? Do primordial CMs regenerate when ablated during development, and do the defects observed (in trabecular and compact CMs and coronary vessels) resolve after 10 days post-treatment when they were detected?

Strengths:

The major strengths are the identification of a marker that enables manipulation of primordial cardiomyocytes and the tools generated by the team.

Weaknesses:

The major weakness is not considering the longer-term consequences of primordial layer ablation during development, as it is unclear whether the animals succumb to the acute cardiac defects observed or fully recover.

Reviewer #2 (Public review):

The manuscript "Alternative splicing of PIF4 regulates plant development under heat stress" by Niño-González et al. describes a heat-responsive alternative splicing (AS) event in PIF4 in Arabidopsis and its potential impact on seedling development. The authors observe that etiolated ings exposed to heat respond with a more photomorphogenic developmental behaviour, as reflected, for example, by increased cotyledon opening and reduced hypocotyl elongation. They propose that the AS event in PIF4 may contribute to this response, due to reduced formation of the full-length PIF4 protein and an increase in the shorter PIF4 protein with potentially dominant negative functions.

Expressing the individual variants in a pif4 mutant background was used to further examine their function. In the case of the full-length PIF4 variant, some of the heat-induced phenotypes were suppressed. For the lines overexpressing the shorter PIF4 variant, heat responses were not examined.

The authors describe an interesting phenotype and present an appealing model of how AS of PIF4, a well-known key regulator of developmental processes including light- and temperature responses, might be involved. However, I don't think that the authors provide strong evidence for their model, and the unaltered heat response of pif4 mutants argues against a major role of this gene and its AS event under these conditions. Regarding the heat responses, it remains open how distinct those are from thermomorphogenesis.

Weaknesses:

(1) In the manuscript, it is emphasized that previous studies on PIFs' role in temperature responses have mainly focused on thermomorphogenesis under high ambient temperature and not under hot temperatures causing heat stress. How do the authors know that the effects they are looking at are specific to hot temperatures and do not also occur at more moderate temperature increases? So, what would PIF4 splicing look like upon a shift from 22{degree sign}C to 28{degree sign}C (instead of 37{degree sign}C as used in the manuscript)?

(2) The potential role of PIF4 and its AS event in the heat response is the key point of this manuscript, as also reflected by the title. As summarized above, I don't see direct evidence for this and a functional characterization of the AS event is lacking. First, the pif4 mutant doesn't show an altered response, which argues against its requirement under these conditions, and in particular against the proposed model that a shortened version of PIF4 acts in a dominant negative manner. Second, the impact of AS on PIF4 protein levels remains open. Antibodies against PIF4 exist and have been used before, e.g. in Lee et al. (2021), Nat Comm, and Fan et al. (2025), Nat Comm - both studies address the role of PIF4 in thermomorphogenesis and should also be discussed in this manuscript. Detecting PIF4 proteins would allow testing if indeed both PIF4 protein variants are detectable and whether, upon heat stress, the longer variant decreases while the shorter variant increases. This could be expected based on transcript data; however, due to regulation at multiple steps, a correlation between transcript and protein levels might not exist. Third, the transgenic lines expressing either the short or long PIF4 variant do not really reflect the situation in the wild type and might be/are overexpression lines. Specifically, constructs for both variants lack the UTRs according to the description in the method section. Furthermore, is the short version expressed as GFP fusion, as I understood from the method description? The PIF4-L mutants have similar PIF levels as the WT (SFig. 9); however, this refers to total transcripts, which makes a difference in the wild type, in particular under heat stress. Comparing here only the PIF4-L levels would be more informative. Accordingly, the transgenic lines may overexpress PIF4-L compared to the wild type. All the PIF4-S lines show 4 to 5-fold overexpression (again for total transcripts) compared to WT. Including lines with lower overexpression levels would be needed for a direct comparison to the wild type. Moreover, immunoblot analysis of the PIF4 protein would be needed for a direct comparison between the wild type and the two types of mutants.

(3) Apart from the question of what level of (over)expression the transgenic lines have, several aspects of the phenotyping experiments are not in line with a simple model of PIF4 regulation or have not been addressed. Expressing the long PIF4 variant in the pif4 mutant background suppresses some of the heat-induced changes, but not the hypocotyl shortening, suggesting that the hypocotyl effect is not caused by a heat-induced lack of PIF4.

When expressing the short variant, the authors observe increased cotyledon opening in darkness, consistent with a suppression of skotomorphogenesis due to a negative function of PIF4-S, at least when it is overexpressed. For hypocotyl length, no consistent difference between wild type and PIF4-S lines was observed: seedlings grown for 3 d in darkness had identical lengths, for 4-d-old seedlings, the PIF4-S lines did not give consistent results: PIF4S.1 (which has highest transgene expression) had same length as wild type; a pronounced difference was only seen for PIF4-S.3, which is the line with lowest expression. Have the experiments been reproduced with independent seed badges? I'm also wondering why the authors haven't performed the heat stress experiments with these PIF4-S lines, as they did for the PIF4-L mutants. According to the authors' model, the PIF4-S lines might show an opposite response compared to the PIF4-L lines, i.e. an even more pronounced heat effect compared to the wild type.

(4) Why was the heat effect on AS of PIF6 not further analysed? Previous work showed the role of PIF6 in seed development and germination; in line with this, PIF6 expression is particularly high in embryos and seeds, but it is also expressed and alternatively spliced in other tissues and conditions, as shown in Figure 1 and SFigure 2. From the data in Figure 1, it looks like the AS pattern in heat might also be different from other conditions. So, it would be interesting to see how AS of PIF6 changes in the control and heat samples that the authors analysed for PIF4 AS, in particular, if this response is distinct for PIF4 versus PIF6.

(5) The presentation of the RNA-seq data is incomplete. According to the method section, WT, pif4-101, PIF4-L.1 and PIF4-L.2 seedlings upon 3 h heat/control treatment were analysed. Why are DE and DAS genes and comparisons of different genotypes not shown? The FC data displayed in Figure 2E and the overlap between heat-regulated genes (Fig. 3D; only in WT) and PIF regulation show only some aspects of the data.

Reviewer #2 (Public review):

Aims:

The authors sought to optimize SHARE-seq, a multimodal single-cell method, to improve the simultaneous profiling of gene expression and chromatin accessibility. Their goal was to enhance barcode design for better sequencing efficiency and cost savings, while improving overall data quality. They then applied their optimized method, easySHARE-seq, to study liver sinusoidal endothelial cells (LSECs) to demonstrate its utility in examining gene regulation and spatial zonation.

Strengths:

The improved barcode design is an advance, increasing the proportion of sequencing reads dedicated to biological information rather than barcode identification. This modification offers practical benefits in terms of sequencing costs and read length, potentially reducing alignment errors. The method also demonstrates improved RNA detection compared to the original SHARE-seq protocol. The biological applications showcase how simultaneous measurement of both modalities enables analyses that would be practically impossible with single-modality approaches, particularly in examining how chromatin states change along developmental or spatial trajectories.

Weaknesses:

There is a notable reduction in chromatin accessibility detection compared to the original SHARE-seq method, likely limiting the broad use of the method. While the authors are transparent about this tradeoff, additional discussion would be helpful regarding how this affects data interpretation. Comparisons showing consistency between easySHARE-seq and SHARE-seq chromatin accessibility patterns at the single-cell level would strengthen confidence in the method.

Overall:

The authors achieve their aim of creating an optimized protocol with improved barcode design and enhanced RNA detection. The method represents a useful advance for specific experimental contexts where the tradeoffs are appropriate.

Reviewer #2 (Public review):

Howard et al. describe a set of deep mutational scanning (DMS) experiments applied to TYK2, which is a drug target implicated in autoimmune disease. By assaying protein abundance (stability) effects as well as immune signaling, the authors are able to disentangle variant effects that may be directly involved in protein activity (and therefore potentially druggable) from variant effects that are due to loss of protein or general structural instability. By performing these assays under multiple conditions, including the presence of various concentrations of small molecules, they develop a clear picture of which sites in TYK2 may be most relevant for intervention or targeting. Overall, the work represents a very compelling example of DMS for understanding protein biology and candidate drug mechanisms.

The work is very thorough, with multiple DMS assays described and compared/contrasted. This greatly enhances the impact and interpretability of any individual assay performed.

The authors have made improvements to the state of the art in terms of wet-lab assay design as well as the analysis of FACS-based deep mutational scans.

The potential mechanism of loss of protein abundance in TYK2 being protective for autoimmune disease is clear, but the estimates of the effect size in more physiologically relevant settings vary quite a bit and might be quite small. Are there examples that could be cited of other similar disease mechanisms where a 10% loss in abundance is associated with a clinical phenotype?

Reviewer #2 (Public review):

Summary:

The study by Robben et al., show 3D beta-cell spheroid platform, a valuable tool allowing high-throughput monitoring of cytoplasmic Ca concentrations and insulin secretion, with Ca signals comparable to those recorded in primary islets. The authors demonstrate a solid method to culturing MIN6 cells in a 3D culture system, recording Ca signals in a high-throughput format and characterizing these Ca signals using pharmacological tools, including TRPM3 channel and K-ATP channel modulators. This highlights the utility of the 3D beta-cell spheroid for screening new ion channel modulators in beta-cells of the pancreas.

Strengths:

- The study shows that the MIN-6-based 3D beta-cell model is better to study Ca-signaling and insulin secretion compared to 2D culture of single MIN-6 cells.

- The method allows imaging of Ca signaling in many spheroids in parallel followed by collecting medium to measure insulin release and correlate both effects.

- The authors demonstrate that this system is suitable for screening new pharmacological modulators and used as an agonist of the ATP-sensitive potassium channel (diazoxide) and the agonist and antagonist of the TRPM3 channel.

Weaknesses:

- The study is based on only one cell line, the MIN6 insulinoma cells, which may not fully mimic the pancreatic beta-cells within the islet.

- The authors show only spheroids cultured overnight. A long-term culture is missing to assess beta-cell viability long term function.

- The authors tested their platform using only two compounds. Testing a larger compound library is necessary to make a clear conclusion about the suitability of the platform for high-throughput screening.

Reviewer #2 (Public review):

Summary:

In this paper, the authors leverage single-cell approaches to delve deeper into the host responses and immune cells involved in immunopathogenesis of influenza virus infection in aged mice. The dynamics of gene expression and immune cell frequencies were also tracked at multiple time-points to examine the acute and chronic changes in young and aged mice after influenza virus infection. Their analyses demonstrated that the immune cell frequencies and gene signatures differed in young and aged mice, especially macrophages, T cells and B cells. Furthermore, interferon pathways were found to be differentially regulated in the young and aged mice, and blocking the interferon pathway with monoclonal antibodies led to improvement in lung respiratory functions and reduced inflammation.

Strengths:

A strength of this study is that multiple time points are considered for analyses, allowing assessment of temporal changes in gene expression and immune cell frequencies after virus infection during the acute and chronic phases of the disease. The data presented could also serve as a potential resource for other researchers interested in understanding the host responses to the influenza virus, especially in aged mice. Another interesting finding was that blocking interferon signalling can reduce the chronic severe symptoms caused by the influenza virus in aged mice.

Weaknesses:

The manuscript could greatly benefit from more rigorous approaches, particularly in the statistical analyses and data visualisation. Moreover, the scientific rationale and logic for several parts of the manuscript can be improved. Finally, the authors did not adequately dissect whether the contribution of host responses was from virus infection or from bystander effects. Specifically, my major comments are as follows:

(1) While it is interesting to compare the difference in host responses between aged and young mice, the authors should also more deeply characterise the differences in phenotypic and infection kinetics between aged and young mice, so that the readers can better appreciate the effects of virus infection and host immune tolerance to viral infection. For instance, what are the differences in virus infection kinetics between the aged and young mice? Are the levels of infection different? Are the virus dynamics and kinetics different between aged and young mice? Besides lung tissue damage, are there also tissue damage or inflammatory responses beyond lung tissues that differ between aged and young mice?

(2) Figure 1B: Could the authors quantify the extent of tissue damage in aged and young adults? It is challenging to interpret the extent of tissue damage, especially across the different time points.

(3) Figure 1D: The authors claim that the senescence signatures are higher in aged mice, justifying that the pathway analyses are consistent with ageing signatures. However, it is also important to note that the senescence signatures were insignificant in aged mice after day 14. Is this expected?

(4) Figure 1E: The stacked bar charts are difficult to read. It is unclear if the cell type frequencies or proportions are significantly changed, especially as the authors are showing these changes with averaged values. Moreover, the authors should keep the colours of the bar charts consistent with the UMAP.

(5) Figure 1F-M: The charts show increased frequencies of innate and adaptive immune cells in aged mice. How about the young mice? Which type of cells are increased to allow these mice to be more tolerant to infection?

(6) Figure 2D and Figure S2C: Besides showing the dynamics of the different clusters, the authors should also display the statistics for individual mice. If the analyses have to be pooled for the single-cell analysis, the authors should declare the challenges and show the statistical comparisons for the flow cytometry.

(7) Figure 3E: The authors should not claim differences in somatic hypermutation based on gene expression. This will require BCR sequencing and evidence for clonal expansion to confirm that there are differences in somatic hypermutation. Moreover, the authors did not measure the quality and quantity of antibody responses between aged and young mice. The claims for the antibody responses are thus extrapolated, and the B cell identities cannot be identified without any functional or phenotypic readouts.

(8) Figure 4H. Why did the authors not perform the experiments for aged mice with a higher virus dose? Also, the spider plots do not display the variability between individual mice, making it challenging to interpret whether the changes were statistically different between the conditions.

(9) Figure 5A. Is the interferon pathway the only pathway that was significantly enriched in the aged mice? Is it the top pathway? The authors should also show the other pathways that were significantly enriched in aged mice. Did the authors also analyse whether the differences in interferon pathways were caused by infected cells or by bystander cells?

(10) Figure 5B: Based on the pathway analyses, the peak responses for interferon are at day 9 post-infection. However, the interferon treatment is performed on day 14, where differences were less apparent. Why did the authors choose to do the interferon treatment at day 14 instead?

(11) Figure 6: How about interferon-mediated cell-cell interactions? The authors should consider using established libraries such as Cell Chat to determine if there are any cell-cell communications that lead to differences in interferon responses and signaling.

(12) Throughout the whole manuscript, the authors kept emphasising that the aged mice displayed uncoordinated immune responses, yet, based on the pathway analyses and phenotypic characterisation, it appears that only interferon was mainly dysregulated. I would thus like to recommend that the authors adjust the tone of the manuscript to tailor it to the results obtained from their investigations.

Reviewer #2 (Public review):

I have reviewed both the original and revised version of this manuscript and while no additional experiments were added, I find the interpretations and discussion of the limitations of the study have improved. This is appreciated.

My original concern regarding the mixture treatments largely remains. Figure 4 nicely shows that the mixtures are more potent than the average of all single compounds. However, Fig S3 shows that the effects of mixtures are not significantly different from effects of at least one, single N,S compound (voruscharin or uscharin) across all measured growth/sequestration responses. Essentially, the effects of single N,S compounds is similar to mixtures (which also contain N,S compounds).

While the current results are certainly interesting as presented, in my view the main takeaway of the manuscript would be more compelling if it could be demonstrated that it isn't simply the presence of N,S compounds in the mixtures driving the observations. For example, does a mixture of all compounds except voruscharin or uscharin still have stronger growth/sequestration effects compared to single non-N,S compounds?

Reviewer #2 (Public review):

Summary:

In this manuscript, Sheidaei et al. reported on their study of chromosome congression during the early stages of mitotic spindle assembly. Building on their previous study (ref. #15, Booth et al., eLife, 2019), they focused on the exact role of the actin-myosin-based contraction of the nuclear envelope. First, they addressed a technical issue from their previous study, finding a way to specifically impair the actomyosin contraction of the nuclear membrane without affecting the contraction of the plasma membrane. This allowed them to study the former more specifically. They then tracked individual kinetochores to reveal which were affected by nuclear membrane contraction and at what stage of displacement towards the metaphase plate. The investigation is rigorous, with all the necessary controls performed. The images are of high quality. The analyses are accurate and supported by convincing quantifications. In summary, they found that peripheral chromosomes, which are close to the nuclear membrane, are more influenced by nuclear membrane contraction than internal chromosomes. They discovered that nuclear membrane contraction primarily contributes to the initial displacement of peripheral chromosomes by moving them towards the microtubules. The microtubules then become the sole contributors to their motion towards the pole and subsequently the midplane. This step is particularly critical for the outermost chromosomes, which are located behind the spindle pole and are most likely to be mis-segregated.

Significance:

While the conclusions are somewhat intuitive and could be considered incremental with regard to previous works, they are solid and improve our understanding of mitotic fidelity. The authors had already reported the overall role of nuclear membrane contraction in reducing chromosome mis-segregation in their previous study, as mentioned fairly and transparently in the text. However, the reason for this is now described in more detail with solid quantification. Overall, this is good-quality work which does not drastically change our understanding of chromosome congression but contributes to improving it. Personally, I am surprised by the impact of such a small contraction (of around one micron) on the proper capture of chromosomes and wonder whether the signalling associated with the contraction has a local impact on microtubule dynamics. However, investigating this point is clearly beyond the scope of this study.

Reviewer #2 (Public review):

Summary:

In this study, the authors present the latest improvement of their previously published methods, pMAGIC and nMAGIC, which can be used to engineer mosaic gene expression in wild-type animals and in a tissue-specific manner. They address the main limitation of MAGIC, the lack of gRNA-marker transgenes, which has hampered the broader adoption of MAGIC in the fly community. To do so, they create an entire toolkit of gRNA markers for every Drosophila chromosome and test them across a range of different tissues and in the context of making Drosophila species hybrid mosaic animals. The study provides a significant and broadly useful improvement compared to earlier versions, as it broadens the use-cases for transgenic manipulation with MAGIC to virtually any subfield of Drosophila cell biology.

Strengths:

Major improvements to MAGIC were made in terms of clone induction efficiency and usability across the Drosophila model system, including wild-type genotypes and the use in non-melanogaster species.

Notably, mosaic mutants can now be created for genes residing on the 4th chromosome, which is exciting and possibly long-awaited by 4th chromosome gene enthusiasts.

Selection of the standard set of gRNA markers was done thoughtfully, using non-repetitive conserved and unique sequences.

The authors demonstrate that MAGIC can be used easily in the context of interspecific hybrids. I believe this is a great advancement for the Drosophila community, especially for evolutionary biologists, because this may allow for easy access to mechanistic, tissue-specific insight into the process of a range of hybrid incompatibilities, an important speciation process that is normally difficult to study at the level of molecular and cell biology.

In the same way, because it is not limited to usage in any particular genetic background, genome-wide MAGIC can be potentially used in wild-type genotypes relatively easily. This is exciting, especially because natural genetic diversity is rarely investigated more mechanistically and at the scale/resolution of cells or specific tissues. Now, one can ask how a particular naturally occurring allele influences cell physiology compared to another (control) while keeping the global physiological context of the particular genetic background largely intact.

Reviewer #3 (Public review):

Summary:

In the submitted manuscript the authors investigate the role of Synaptotagmins (Syt1) and (Syt7) in MR1 presentation of Mtb antigens. By using Syt1 and Syt7 knock down the authors determine that these molecules are required to effectively control Mtb infection.

Strengths:

In the first series of experiments, the authors determined that knocking down Syt1 and Sy7 in antigen-presenting cells decreases IFN-γ production following cellular infection with Mtb. These experiments are well performed and controlled.

Comments on revisions:

The revised manuscript offers further support to the role of Synaptogamins 1 and 7 in MR1 trafficking during MT infection

Reviewer #2 (Public review):

Summary:

In this study, the authors identify the N-glycosylation factor B4GALT1 as an important regulator of CD8 T-cell function.

Strengths:

The use of complementary ex vivo and in vivo CRISPR screens is commendable and provides a useful dataset for future studies of CD8 T-cell biology.

The authors perform multiple untargeted analyses (RNAseq, glycoproteomics) to hone their model on how B4GALT1 functions in CD8 T-cell activation, as well as the use of a CD8-CD3 to narrow down the effects of B4GALT1, which is a broad-acting enzyme.

B4GALT1 is shown to be important in both in vitro T-cell killing assays and a mouse model of tumor control, reinforcing the authors' claims.

Weaknesses:

The authors did not verify the efficiency of knockout in their single gene KO lines, although they mention a plan to include such data in a future version of the manuscript.

The specific N-glycosylation sites of TCR and CD8 are not identified, and would be helpful for site-specific mutational analysis to further the authors' model.

The study or future studies could benefit from further in vivo experiments testing the role of B4GALT1 other physiological contexts relevant to CD8 T cells, for example autoimmune disease or infectious disease.

Comments on revisions:

The paper improved after revision.

Reviewer #2 (Public review):

The authors present a comparative genomic and phylogenetic analysis aimed at elucidating the functions of nickel-dependent carbon monoxide dehydrogenases (Ni-CODHs) and hybrid-cluster proteins (HCPs). By examining gene neighborhoods, phylogenetic relationships, and co-occurrence patterns, they propose functional hypotheses for different CODH clades and highlight those with the greatest potential for biotechnological applications.

A major strength of this work lies in its systematic and conceptually clear approach, which provides a rapid and low-cost framework for predicting the functional potential of newly identified CODHs based on sequence data and genomic context. The analysis is careful in minimizing false positives and offers valuable insights into the diversity and distribution of CODH enzyme clades.

Reviewer #2 (Public review):

Summary:

Fu and colleagues have shown that VALOR, a model of multimodal and dynamic stimulus features, better predicts brain responses compared to unimodal or static models such as AlexNet, WordNet, or CLIP. The authors demonstrated robustness of their findings from generalizing encoding results to an external dataset. They demonstrated the models' practical benefit by showing that semantic mappings were comparable to another model that required labor-intensive manual annotation. Finally, the authors showed that the model reveals predictive coding mechanisms of the brain, which held meaningful relationship with individuals' fluid intelligence measure.

Strengths:

Recent advances in neural network models that extract visual, linguistic, and semantic features from real-world stimuli have enabled neuroscientists to build encoding models that predict brain responses from these features. Higher prediction accuracy indicates greater explained variance in neural activity, and therefore a better model of brain function. Commonly used models include AlexNet for visual features, WordNet for audio-semantic features, and CLIP for visuo-semantic features; these served as comparison models in the study. Building on this line of work, the authors developed an encoding model using VALOR, which captures the multimodal and dynamic nature of real-world stimuli. VALOR outperformed the comparison models in predicting brain responses. It also recapitulated known semantic mappings and revealed evidence of predictive processing in the brain. These findings support VALOR as a strong candidate model of brain function.

Weaknesses:

The authors argue that this modeling contributes to better understanding how the brain works. However, upon reading, I am less convinced how VALOR's superior performance than other models tell us more about the brain. VALOR is a better model of the audiovisual stimulus because it processes multimodal and dynamic stimuli compared to other unimodal or static models. If the model better captures real-world stimuli, then I almost feel that it has to better capture brain responses, assuming that the brain is a system that is optimized to process multimodal and dynamic inputs from the real world. The authors could strengthen the manuscript if the significance of their encoding model findings is better explained.

In Study 3, the authors show high alignment between WordNet and VALOR feature PCs. Upon reading the method together with Figure 3, I suspect that the alignment almost has to be high, given that the authors projected VALOR features to the Huth et al.'s PC space. Could the authors conduct non-parametric permutation tests, such as shuffling the VALOR features prior to mapping onto Huth et al.'s PC space, and then calculating the Jaccard scores? I imagine that the null distribution would be positively shifted. Still, I would be convinced if the alignment is higher than this shifted null distribution for each PC. If my understanding about this is incorrect, I suggest editing the relevant Method section (line 508) because this analysis was not easy to understand.

In Study 4, the authors show that individuals whose superior parietal gyrus (SPG) exhibited high prediction distance had high fluid cognitive scores (Figure 4C). I had a hard time believing that this was a hypothesis-driven analysis. The authors motivate the analysis that "SPG and PCu have been strongly linked to fluid intelligence (line 304)". Did the authors conduct two analyses only-SPG-fluid intelligence and PCu-fluid intelligence-without relating other brain regions with other individual differences measures? Even if so, the authors should have reported the same r value and p value for PCu-fluid intelligence. If SPG-fluid intelligence indeed hold specificity in terms of statistical significance compared to all possible scenarios that were tested, is this rationally an expected result and could the authors explain the specificity? Also, the authors should explain why they considered fluid intelligence to be the proxy of one's ability to anticipate upcoming scenes during movie watching. I would have understood the rationale better if the authors have at least aggregated predictive scores for all brain regions that held significance into one summary statistics and have found significant correlation with the fluid intelligence measure.

Comments on revisions:

The revision has addressed these concerns.

Reviewer #2 (Public review):

Summary:

Huang et al recorded anterior cingulate cortex activity in mice while they performed a shuttle escape task. The task utilized two auditory cues, each of which informed the mice to stay or escape depending on which side they were on, and incorrect responses were punished by shock administration. Analyses focused on ACC neurons that fired when mice crossed the shuttle box in either direction (A-->B or B-->A), coined "action state", or when mice crossed in one direction but not the other, coined "action content". The authors characterized these populations, and ACC firing changes mostly occurred around the time of shuttle crossing. This work will likely be of broad interest to those who are interested in neocortical neurophysiology broadly, anterior cingulate cortex specifically, and their contributions to learning about actions. The task is well-designed and provides a nice background for neurophysiological recordings. The authors leveraged these strengths in characterizing the neural populations that fire to shuttle crossings in both directions vs one direction.

Strengths:

The factorial design nicely controls for sensory coding and value coding, since the same stimulus can signal different actions and values.

The figures are well presented, labeled, and easy to read.

Additional analyses, such as the 2.5/7.5s windows and place-field analysis, are nice to see and indicate that the authors were careful in their neural analyses.

The n-trial + 1 analysis where ACC activity was higher on trials that preceded correct responses is a nice addition, since it shows that ACC activity predicts future behavior, well before it happens.

The authors identified ACC neurons that fire to shuttle crossings in one direction or to crossings in both directions. This is very clear in the spike rasters and population scaled color images. While other factors such as place fields, sensory input, and their integration can account for this activity, the authors discuss this and provide additional supplemental analyses.

Weaknesses:

Some of the neural analyses could use the necessary and sufficient comparisons to strengthen the authors' claims.

Comment on revised version:

I think the authors did a very admirable job revising the manuscript. It is much improved. However, I believe a formal analysis of action-state versus action-content neurons on A-->B versus B-->A crossing is still warranted. I appreciate the fact that this analysis may not be as reliable with smaller ensemble sizes, but with careful pseudo-ensemble and resampling approaches, such an analysis would go a long way towards increasing the strength of evidence.

Reviewer #2 (Public review):

Summary:

The authors are attempting to advance understanding of the role of unconventional PKCs, PKCM𝛇, and PKC𝜄/𝝀 in maintenance of late-phase LTP. Their results help to clarify the interplay between "structural" and "biochemical/enzymatic" mechanisms of LTP and learning in the hippocampus.

Strengths:

A strength is the use of conditional knock-outs of PKCM𝛇 and PKC𝜄/𝝀 to assess the role of these two enzymes in maintaining long-term potentiation and in compensating for each other when one of them is conditionally knocked out in the adult.

Weaknesses:

The paper is extremely difficult to read because the abstract does not clearly state the advances made over earlier studies by the use of conditional KO mutation. For example, in line nine of the abstract, the authors state, "Here, we found PKC𝜄/𝝀 persists in LTP and long-term memory when PKM𝛇 is genetically deleted." This is confusing because it sounds as though the experiments have repeated earlier published experiments in which the gene encoding PKM𝛇 is deleted in the embryo. The authors are not clear throughout the manuscript that they are using conditional KO of the two enzymes in the adult animal, rather than deletion of the gene. The term "genetically deleted" does not mean "conditionally deleted in the adult." The final sentences of the abstract are: "Whereas deleting PKM𝛇 and PKC𝜄/𝝀 individually induces compensation, deleting both aPKCs abolishes hippocampal late-LTP. Hippocampal 𝜄/𝝀-𝛇 -double-knockout eliminates spatial long-term memory but not short-term memory. Thus, in the absence of PKM𝛇 , a second persistent biochemical process compensates to maintain late-LTP and long-term memory." These sentences do not convey a clear logical conclusion. The Discussion does a better job of stating the importance of the experiments.

Reviewer #2 (Public review):

Summary:

Here, the authors attempt to demonstrate that a simple model of multicellularity - snowflake yeast - exhibits key ecologically relevant changes in the regulation of the cell cycle. By examining the effects of the ace2 mutation in environments where multicellularity is not directly selected for or against, and combining it with mutations in key cell cycle regulators, they hope to show that mutations driving simple multicellularity can be selectively favored due to their effects on the release from quiescence rather than their effects on multicellularity itself.

Strengths:

The experiments performed are extensive and thorough. The yeast genotypes examined are judiciously chosen, so as to map out a functional model of the relationship between alterations to cell cycle control and changes to multicellularity phenotypes. Multiple possible interactions are examined, with the causal link and model of the relationship between the multicellular passenger phenotype and the selectable quiescence-release phenotype being well-supported. There are extensive controls demonstrating the separation between the 'passenger' multicellular phenotype and the cell cycle regulation phenotypes examined, including haploid/diploid strains with different multicellular phenotypes but similar cell cycle regulation phenotypes, and phenocopy strains in which downstream enzymes are deleted rather than key central regulators.

Weaknesses:

My only concerns about these results relate to the focus on selection on cell cycle control being examined in a model of multicellularity with key core cell cycle mutations rather than in a wild-type background, as this is a somewhat artificial system.

I believe, however, that the authors convincingly make their case that this work on the multicellular phenotypes of yeast represents a potent proof-of-concept that simple multicellularity can be driven into existence or selected for as a passenger phenotype due to pleiotropic effects of mutations under selection from real-world ecological pressures. They are able to connect this phenotype back to known mutations of particular cell cycle regulators (RB) in other multicellular lineages and demonstrate that ecologically relevant changes to the cell cycle are connected to multicellular phenotypes. As a proof of concept of the connection between these phenotypes, rather than a study of a particular event in the past of a living lineage, it makes a strong case.

A longstanding question in the field of multicellularity is the selective pressures that can drive simple multicellularity into existence and then act on simple multicells to drive their increased size and complexity. This work brings to the table tangible evidence of the possibility that, instead of being selected for on its own, simple multicellularity can be a side-effect of selection on other key phenotypes.

This separates the question of the origins of multicellularity and the forces that drive its further evolution. This separation can reframe how the field is studied, especially in the context of the apparent dichotomy between dozens of origins of 'simple' multicellularity across the tree of life and a few origins of 'complex' multicellularity in the history of Earth. Especially in light of other evidence that multicellularity is connected to changes in cell cycle regulation, I believe that this is an important insight that will alter the way we think about the origins of this key evolutionary transition.

Reviewer #2 (Public review):

Summary:

This manuscript addresses an important and timely question in TDP-43 biology by systematically identifying regulators of TDP-43 anisosome formation, with a particular focus on nuclear export via XPO1. Using a combination of unbiased chemical screening, genetic perturbation, and advanced imaging approaches, the authors propose that inhibition of nuclear export modulates the abundance and biophysical properties of TDP-43 anisosomes. The study is conceptually innovative and has potential relevance for neurodegenerative diseases characterized by TDP-43 pathology. However, significant concerns regarding experimental controls, reporting transparency, and model translatability currently limit the strength of the conclusions and the interpretability of several key findings.

Strengths:

(1) The study employs an unbiased, hypothesis-free compound screen to identify regulators of TDP-43 anisosome formation, which is a major strength and reduces confirmation bias.

(2) The authors combine chemical and genetic screening approaches, providing orthogonal validation of key pathways and increasing confidence in the biological relevance of top hits.

(3) The focus on biophysical properties of TDP-43 assemblies, assessed through imaging and FRAP, moves beyond simple presence/absence of aggregates and provides mechanistic insight into the biophysical states of TDP-43.

(4) The use of multiple experimental modalities, including live-cell imaging, FRAP, pharmacological perturbation, and transcriptomic analysis, reflects a technically sophisticated and ambitious study design.

(5) The authors attempt to extend findings beyond immortalized cancer cell lines by incorporating organoid models, demonstrating awareness of disease relevance and translational importance.

Overall, the manuscript is clearly written and logically structured, making complex experimental workflows accessible and the central hypotheses easy to follow.

Weaknesses:

Despite its strengths, the manuscript has several major limitations that affect data interpretation and confidence in the conclusions.

(1) Lack of appropriate controls for overexpression experiments:

A central concern is the absence of proper controls for TDP-43 and XPO1 overexpression. Prior studies (including those cited by the authors, Archbold et al.2018) show that overexpression of WT TDP-43 alone is toxic to neurons. Thus, the experimental system itself may induce anisosome formation independently of the mechanisms under study. Similarly, XPO1 overexpression lacks a suitable control (e.g., mCherry alone or mCherry fused to a protein known to be independent of TDP-43). The near-complete colocalization of XPO1 with TDP-43 anisosomes upon overexpression raises the possibility that these structures reflect non-physiological protein accumulation rather than regulated assemblies.

2) Insufficient experimental and analytical transparency:

The manuscript frequently lacks clear reporting of experimental details. In multiple figures, the stated number of independent experiments does not match the number of data points shown, making it difficult to assess statistical validity. Concentrations used in the compound screen are not clearly defined, nor is it stated whether multiple concentrations were tested. It is unclear how many wells, cells, or independent cultures were analyzed. The criteria used to reduce 1,533 screening hits to 211 candidates via STRING analysis are not explained. Knockdown and overexpression efficiencies are not reported.

(3) RNA-seq concerns:

The RNA-seq experiments are particularly problematic. The number of biological replicates per condition is not stated, and heatmaps suggest that only one sample per group may have been used, which would preclude statistical analysis. No baseline comparison between WT and mutant TDP-43 is shown. Given that TDP-43 is an RNA-binding protein, splicing analyses would be far more informative than gene expression alone, yet no splicing data are presented. Moreover, nuclear retention of TDP-43 does not preclude nuclear aggregation, which may still impair its splicing function.

(4) Limited translatability to neuronal biology:

All anisosome analyses are performed in a cancer cell line, raising concerns about relevance to post-mitotic neurons. While organoids are used as a secondary model, the assays performed do not overlap with those used in cancer cells, making it difficult to assess whether anisosome-related mechanisms are conserved. Neuronal toxicity, a critical outcome given known TDP-43 biology, is not assessed. Prior work has shown that WT TDP-43 overexpression alone is toxic to neurons, yet this is not addressed.

(5) Conceptual and interpretational gaps:

The authors quantify anisosome number but also report conditions in which anisosome number decreases while size increases. The biological interpretation of larger anisosomes is not discussed, and whether this reflects improvement or worsening of pathology is unclear. Compounds targeting the same mechanism (e.g., nuclear export inhibition) are inconsistently used across experiments (KPT compounds, verdinexor, leptomycin B), raising concerns about reproducibility. In organoids, the experimental paradigm shifts to long-term treatment (35 days vs. 16 hours), further complicating interpretation.

(6) Overinterpretation of rescue effects:

Although the authors state that they aim to test whether nuclear export inhibition rescues neuronal defects, no functional neuronal readouts are provided (e.g., viability, morphology, axon outgrowth, or electrophysiological measures). RNA-seq alone is insufficient to support claims of rescue.

(7) Finally, the model does not appear to exhibit cytosolic TDP-43 aggregation at baseline. It remains unclear whether longer induction would produce cytosolic gel-like assemblies and whether these would be prevented by nuclear export inhibition. Long-term data are shown only in organoids, yet anisosome formation is not assessed there.

This is surprising because I thought research papers should mostly focus on sources. I didn’t realize the writer’s own ideas are actually the most important part.

This part is interesting because it shows that many of the people who were detained were normal community members. It makes the situation feel more real and personal.

This is troubling because only a small number of accounts created most of the hate. It shows that a few people or bots can make the internet feel negative.

Reviewer #2 (Public review):

Summary:

This study addresses an important and timely question in colorectal cancer biology by systematically examining the effects of the common driver mutations APC, KRAS G12D, and TP53 in murine colorectal organoids, with particular emphasis on how the order of APC and TP53 acquisition influences tumor phenotype. These mutations are well known to be frequent, truncal, and often co-occurring in colorectal cancer. While it is increasingly appreciated that mutational order can shape tumor behavior, studies directly comparing the phenotypic consequences of alternative APC-TP53 mutation orders remain rare. This work, therefore, addresses a relevant and timely question.

Strengths:

A major strength of the study is its focus on previously unexplored biology, combined with the generation of multiple isogenic murine organoid models with controlled mutational sequences. The authors employ careful and robust quality control of the CRISPR-mediated alterations, and the inclusion of both in vitro and in vivo experiments strengthens the relevance of the work.

Weaknesses:

There are, however, several limitations that should be considered when interpreting the findings. First, KRAS G12D activation is used as the initiating alteration, whereas APC loss is generally believed to be the initiating event in most human colorectal cancers. Second, the analysis is restricted to comparing only two mutation orders (KAT versus KTA), which limits the breadth of conclusions that can be drawn about mutation ordering more generally. Finally, key RNA-sequencing and in vivo experiments rely on a single isogenic line, which substantially constrains interpretability.

The aim of the study was to systematically investigate how mutation accumulation and order influence colorectal cancer initiation. While the data suggest that the relative timing of APC and TP53 loss may be particularly important for tumor initiation, the absence of biological replication makes it difficult to draw robust conclusions. Engraftment efficiency and tumor behavior can be influenced by many factors for a single clone, including additional passenger mutations acquired during culturing, as well as epigenetic differences that are independent of the engineered mutations.

Reviewer #2 (Public review):

Summary:

The authors introduce a generalised HGF featuring (1) volatility coupling (rate of change), value coupling (phasic or autoregressive drift) [and 'noise coupling', which is a volatility parent of an outcome state] (2) parameters: volatility coupling κ, tonic volatility ω, value coupling α, tonic drift ρ, {plus minus}auto-regressive drift λ (3) inputs at irregular intervals (but still discrete time steps, unlike continuous time belief evolution in predictive coding) (4) states with multiple parents or parents with multiple child states (5) value parents by default have a volatility parent, and volatility parents have a value parent (or none) (6) linear or non-linear (including ReLU) functions (7) also beliefs can be any exponential family distribution (incl binary, categorical), hence can also model POMDPs

They describe the 3 steps involved in updating (for both value and volatility): (1) prediction (2) update posterior (entails passing both pwPE and prediction precision from lower to upper node - the latter is not found in other predictive coding schemes) (3) prediction error NB this makes the network modular, so nodes can be added/removed without recomputing all the update equations.

They give some examples of models working using simulated data: (1) sharing of parent nodes can generalise an update from one context to another (2) sharing of child nodes enables multisensory cue combination (e.g. auditory-visual, or interoceptive-exteroceptive).

The authors further discuss a potential shortcoming of the HGF - its discretisation of timesteps - which is less naturalistic but nevertheless makes it very amenable to fitting trial-wise experimental data. They propose to extend the HGF to modelling within-step dynamics in future, which could make testable continuous time neuronal predictions.

Strengths:

Overall, I think the paper is excellent - it contributes an important extension to a popular modelling tool which substantially increases the number of potential applications. It is well written, and I have almost no criticisms to make.

Weaknesses:

The authors state that this generalised HGF will "make it easy to build large networks with considerable hierarchical depth", comparable to neural network architectures. The examples they give are extremely simple; however, it would be good to see a more complex one.

Reviewer #2 (Public review):

Summary:

The manuscript by Pierre Despas and co-workers, reports the biochemical characterization of LppB a peculiar Lpp (Braun's lipoprotein) homolog found in Salmonella enterica. S. enterica encodes two Lpp homologs LppA and LppB: while LppA and Lpp function similarly, the role of LppB is less clear. LppB shares with Lpp the C-terminal Lys needed for covalent attachment to peptidoglycan (PG) but diverges in residues that precede the terminal Lys featuring a Cys residue at the penultimate position. By using E. coli as a surrogate model, the authors show that LppB can be covalently linked to PG via the terminal Lys residues and that the penultimate Cys residue can be used to form homodimer species when expressed alone and heterotrimeric complexes when co-expressed with Lpp. Interestingly, LppB expressed in E. coli seems to be stabilized at acidic pH a condition Salmonella encounters in macrophage phagosomes. Finally, based on decreased intensity of LppB-PG crosslinked bands as LppB expression increases the authors suggest that LppB is able to negatively modulate the outer membrane-peptidoglycan connectivity.

Strengths:

The manuscript is interesting, describes a novel strategy employed by bacteria to fine tuning outer membrane-PG attachment and provides new insights into how envelope remodeling processes can contribute to bacterial fitness and pathogenicity.

Weaknesses:

The analysis and quantification of muropeptides formed in E. coli strains overexpressing LppB would strengthen the main conclusion of the manuscript.

Reviewer #2 (Public review):

Summary:

The manuscript by Foucault, Weber, and Hunt examines human learning behavior across change-point and continuously changing environments. The authors suggest that humans normatively adjust their learning dynamics to the current environmental dynamics. Moreover, they argue that humans not only track the means of the outcome-generating process, but also the variance, which extends recent work in this domain. The present results suggest that human learners are well able to distinguish the two moments and adjust their behavior accordingly.

Strengths:

(1) The paper is clearly written, and the figures demonstrate the results well. The authors clearly explain the two key results and their implications for the field.

(2) The paper uses a common modeling framework for the two environments. This makes it less likely that differences in learning behavior between the two environments are driven by general model properties rather than the specific learning mechanisms.

Weaknesses:

(1) Interpretation in terms of normative learning

(1.1) Perseveration and paddle movement

The model presented in the main manuscript is equipped with a response-probability mechanism that controls whether the paddle is updated. Especially on smaller prediction errors, the paddle is often not updated (perseveration). I wonder whether this mechanism truly reflects normative updating behavior or rather a heuristic strategy. Not moving the paddle is non-normative. A fully Bayesian model would hardly ever show a learning rate of exactly zero (one could argue only when the error is itself zero or after a massive amount of trials). This is partly apparent in Supplementary Figure 1, where the lowest learning rates are around alpha = 0.2 (change-point environment) and 0.5 (random walk).

Supplementary Figure 1 shows the learning rate for the normative model without the response-probability mechanism. Primarily in the random-walk environment, but to some extent also in the change-point condition, the shape of the learning rate changes quite dramatically compared to Figure 4. In the random-walk environment, the learning rate appears relatively stable, with a value slightly larger than 0.5. In the change-point case, the learning rate is somewhat higher in the range of smaller prediction errors. Doesn't this speak against the interpretation that the model in the main manuscript is really behaving in a purely normative fashion? The tendency to perseverate might reflect a simplified strategy, which is sometimes described as "satisficing". That is, in line with the authors' description of the mechanism, perseveration occurs when it seems "good enough" (Simon, 1956), which has been demonstrated in a belief updating context before (Bruckner et al., 2025; Gershman, 2020; Nassar et al., 2021).

Supplementary Figure 3 suggests that humans show quite a lot of this type of behavior. It indicates that in the change-point condition, in only 20% of the trials in the minimal prediction error range, participants update their prediction (i.e., in 80% of these trials, they perseverate on the previous prediction). This update probability increases as a function of the prediction error. In the random-walk condition, update probabilities are higher, starting at around 40% and also increasing as a function of the error.

Indeed, Supplementary Figure 4 suggests that the shape of the learning rate for true update trials is much shallower for humans and the "perseverative" model compared to the model in Supplementary Figure 1. This suggests that the curve in Figure 4 (main manuscript), hinting at a continuous increase in the learning rate, could be the result of a mixture of perseveration (alpha = 0) and higher learning rates compared to the normative model without the response-probability mechanism.

(1.2) Control models

One might reply that the response-probability mechanism just adds noise, while the actual learning mechanism is still normative. However, a standard Rescorla-Wagner model with the same response-probability mechanism might also show increasing apparent learning rates as a function of prediction error (when perseveration trials and regular update trials are averaged as a function of the prediction error).

Therefore, I suggest adding a control analysis with a Rescorla-Wagner model. One version with the same response mechanism yielding perseveration, and one standard Rescorla-Wagner model without this mechanism. This should help identify how well the present analyses can distinguish true learning-rate dynamics from averaging artifacts due to perseveration.

(1.3) Discussion of the possibility of non-normative learning mechanisms

Given the considerations above, I suggest a more balanced discussion of potential non-normative influences on learning, in particular, perseveration. Several previous papers have similarly shown that perseveration prominently characterizes human learning and decision-making (Bruckner et al., 2025; Gershman, 2020; Nassar et al., 2021), and in my opinion, it would be relevant to discuss how normative and non-normative mechanisms might jointly shape learning.

(2) Model description

The Bayesian model is quite central to the paper. However, the mathematical details are sparse, and I did not fully understand the differences between the model variants and how they were implemented. In particular, what approximations were used to make the model tractable? And how does the variance inference work? Is the learning rate directly computed, similar to the Nassar model, or is it derived from updates and prediction errors?

(3) Apparent learning rates in humans

The main learning-rate analyses compute the fraction of updates and prediction errors. For quality assurance, it would be useful to see a few supplementary histograms of the apparent learning rates. It would be great to have one plot across all participants and a few example plots for single participants. These analyses will reveal the distribution of learning rates and the proportion at the boundaries, which can sometimes be a source of bias.

References:

Bruckner, R., Nassar, M. R., Li, S.-C., & Eppinger, B. (2025). Differences in learning across the lifespan emerge via resource-rational computations. Psychological Review, 132(3), 556-580. https://doi.org/10.1037/rev0000526.

Gershman, S. J. (2020). Origin of perseveration in the trade-off between reward and complexity. Cognition, 204, 104394. https://doi.org/10.1016/j.cognition.2020.104394.

Nassar, M. R., Waltz, J. A., Albrecht, M. A., Gold, J. M., & Frank, M. J. (2021). All or nothing belief updating in patients with schizophrenia reduces precision and flexibility of beliefs. Brain, 144(3), 1013-1029. https://doi.org/10.1093/brain/awaa453.

Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63(2), 129-138. https://doi.org/10.1037/h0042769.

Reviewer #2 (Public review):

Summary:

This manuscript addresses a clear and widely relevant question: how ongoing fluctuations in alertness during wakefulness relate to large-scale patterns of coordinated brain activity. The authors combine high-field magnetic resonance imaging with simultaneous pupil measurements, and they compute an edgewise measure of arousal-related coupling for every pair of regions. Their main contribution is to show that arousal-related coupling is low-dimensional and organized into seven reproducible "connectivity communities", each with characteristic network pair compositions. A secondary contribution is the observation that these communities exhibit systematic but community-specific hemispheric asymmetries, including a striking left/right dissociation within the ventral attention network, where the left side participates broadly across communities while the right side forms a more cohesive, segregated arousal-responsive module. A final contribution is cross-context generalization: the same organizational structure and lateralization signatures are largely preserved during naturalistic movie watching.

Strengths:

(1) The paper moves beyond state contrasts and quantifies arousal-related modulation continuously within wakefulness, directly addressing a gap highlighted in the Introduction.

(2) The hemispheric asymmetry result is not framed as a crude global dominance effect; the authors explicitly test and argue that the key signal lies in structured spatial heterogeneity rather than mean shifts.

(3) The cross paradigm replication in movie watching is a strong design choice and supports the claim that the organizational motifs are not limited to unconstrained rest.

Weaknesses:

(1) Arousal effects on BOLD signals and on pupil size can have different delays, so it would be valuable to test lagged relationships (for example, shifting the pupil series forward and backward) to show that the main community structure and lateralization results are not sensitive to an arbitrary temporal alignment.

(2) Pupil diameter covaries with blinks, eye closure, and other factors that can covary with head motion and physiological noise. The Methods include substantial quality control and denoising, including motion regression and scrubbing, plus exclusions for eye closure.

(3) The dataset is described in terms of runs retained (for example, 485 resting runs), and runs are treated as observations in clustering after z-scoring across runs. If multiple runs come from the same individuals, the manuscript would benefit from explicitly showing that results replicate at the participant level (for example, community structure stability within participant across runs, and participant-level summary statistics used for inference), rather than relying primarily on pooled run-level patterns.

(4) Time-resolved connectivity is estimated using a 30-second sliding window and 5 second step. It is reasonable to wonder whether the same conclusions hold with alternative estimators that do not rely on fixed windows. The Discussion acknowledges this limitation, but adding a small robustness analysis would make the paper more definitive.

Reviewer #2 (Public review):

Summary:

The manuscript introduces Neuroplex, a pipeline that integrates miniscope Ca²⁺ imaging in freely moving mice with multiplexed confocal and spectral imaging to infer projection identities of recorded neurons. This technical approach is promising and could broaden access to projection-resolved population imaging. However, the core quantitative analyses apply a winner-take-all single-label assignment per neuron even when multiple fluorophores exceed threshold, with additional labels treated descriptively as "secondary hits." While the authors acknowledge and simulate dual labeling, the extent to which this single-label decision rule affects subtype fractions and behavioural comparisons remains uncertain without a multi-label (or probabilistic) sensitivity analysis and propagation of classification uncertainty.

Strengths:

(1) Conceptual advance and practicality: Decoupling acquisition from identity readout constitutes an innovative approach that is, in principle, applicable in laboratories currently using single-color miniscopes.

(2) Engineering thoroughness: The manuscript offers detailed consideration of GRIN optics, spectral libraries, registration procedures, and simulations that address signal-to-noise ratio, background, and class imbalances.

(3) Immediate community value: If demonstrated to be robust, the pipeline could enable projection-resolved analyses without reliance on specialized multicolor miniscopes.

Weaknesses:

(1) Single-label assignment in the main analyses: When multiple fluorophores exceed threshold for a neuron/ROI, the workflow applies a winner-take-all rule and assigns a single label (the fluorophore with the largest standardized beta), while additional above-threshold fluorophores are retained only as "secondary hits." This is a reasonable specificity-first choice, but because cortical excitatory neurons can collateralize, collapsing dual-threshold ROIs to one identity may under-represent dual-projecting cells and could bias estimated subtype fractions and behavioural comparisons.

(2) Dual-label detection is acknowledged but remains descriptive in vivo: the manuscript explicitly discusses the possibility of dual projection, evaluates dual-fluorophore detection in simulations (including performance under realistic noise/background), and reports in vivo rates of secondary hits. However, these dual-threshold events are not incorporated as co-identities in the main statistical analyses, making it difficult to judge how robust the principal biological conclusions are to the single-label decision rule.

(3) Uncertainty is not propagated: False-positive/false-negative rates from simulations and uncertainty from registration/segmentation are not carried forward into quantitative confidence bounds on subtype proportions or behaviour-by-subtype effects.

Reviewer #2 (Public review):

This manuscript investigates how people's perceptual reports are influenced by events and trials in the past, and how this long-range dependence relates to broader learning across locations in a visual learning task. The authors present clear and internally consistent analyses showing that extended temporal integration is associated with greater generalization of learning. The study is thought-provoking and may contribute meaningfully to understanding how short-term influences and long-term improvement interact, although several interpretational points would benefit from clarification.

Strengths:

(1) The manuscript identifies unusually long-range perceptual biases extending up to ten trials back, which is a striking and potentially important finding.

(2) The association between strong long-range dependence and greater learning generalization is clearly documented and supported by consistent analyses.

(3) The dataset is large and rich, and the authors apply repeated and well-controlled analyses that give confidence in the stability of the effects.

(4) The writing is generally clear, and the manuscript raises interesting conceptual links between temporal integration and generalization of learning.

Weaknesses / Points Requiring Clarification:

(1) The manuscript repeatedly equates generalization with increased efficiency, but this relationship is not universally true. In some populations or tasks, excessive generalization can reduce task-specific efficiency. The authors should discuss this context-dependence to clarify when generalization is beneficial versus detrimental.

(2) Serial dependence is also present, though smaller, in the central fixation task. It remains unclear whether this bias could contribute to the serial dependence observed in the main task. The authors should clarify whether the two biases are independent or whether the central-task bias might partially influence orientation judgments in the main task.

(3) Several figure captions and labels contain minor inconsistencies in formatting and terminology. Careful proofreading would improve clarity.

Reviewer #2 (Public review):

Summary:

The authors set out to determine whether people can adjust how narrowly or broadly they focus attention in advance based on expectations about how difficult an upcoming visual task will be. Specifically, they aimed to test whether expecting a more demanding search leads to a narrower focus of attention or instead strengthens attention at the relevant location without changing its spatial extent.

Strengths:

The study addresses a timely and interesting question about how expectations influence the preparation of attention before a task begins. The experimental design is well-suited to isolating anticipatory effects by manipulating expectations about task difficulty independently of moment-to-moment stimulus information. The manuscript is clearly written, and the methods are described in sufficient detail to support transparency and reproducibility.

Weaknesses:

Despite the strengths of the design and the merit of the work, I have a few concerns regarding the analysis and the interpretation of the results.

(1) I was somewhat confused by aspects of the behavioural analysis. I may be mistaken, but fixed effects in generalised mixed-effects models are more commonly reported using Wald statistics with beta coefficients rather than F statistics, and the very large degrees of freedom reported here are difficult to interpret. In particular, they appear closer to trial counts than to the number of participants, which raises questions about how statistical uncertainty is being estimated. This concern is compounded by the fact that different statistical approaches appear to yield different conclusions: the generalised mixed-effects models and the pairwise t-tests reported in the figure caption do not fully align. Moreover, the latter are not described in the Methods, and the justification for using them in the figure is not provided. Taken together, this makes it difficult to assess the strength of the behavioural evidence. The reported effects of expectation on behaviour also appear small, and there is no clear cost at uncued locations. This limited behavioural footprint makes it difficult to determine how robust the proposed preparatory mechanism is. It also complicates the interpretation of the neural findings as reflecting a general strategy for optimising task preparation.

(2) A central premise of the study is that, if observers proactively narrow their attentional focus when expecting difficult search, this should be reflected in sharper spatial tuning profiles. This prediction is presented as a diagnostic test of whether expectations modulate attentional scope. However, the absence of such sharpening is later taken as evidence that expectations do not alter spatial extent and instead operate exclusively through gain modulation. This inference may be stronger than the data allow. The lack of an observed difference in tuning width does not necessarily rule out changes in attentional scope, particularly if such changes are subtle, temporally limited, or not well captured by the spatial resolution of the approach. As a result, while the findings are consistent with a gain-based account, they do not definitively exclude the possibility that expectations also influence spatial extent, and the logic linking the original prediction to the final conclusion would benefit from a more cautious interpretation.

(3) The difference between easy and hard searches in the CTF slope is taken as evidence for enhanced preparatory spatial attention under high expected difficulty. However, these differences could also reflect broader changes in alertness or motivational state between blocks. The behavioural results show a small overall increase in accuracy in expect-hard blocks, which may be consistent with a more general increase in task engagement rather than a spatially specific preparatory mechanism. Although the authors decompose slope differences into amplitude and width parameters, the interpretation still relies on ruling out alternative, more global explanations for enhanced signal strength or reduced variability. This leaves some ambiguity as to whether the observed modulation reflects a specific adjustment of preparatory attention or a more general change in task state.

Reviewer #2 (Public review):

Summary:

The authors investigate single-neuron activity in rhesus macaques during model-based (MB) and model-free (MF) reinforcement learning (RL). Using a well-established two-step choice task, they analyze neural correlates of MB and MF learning across four brain regions: the anterior cingulate cortex (ACC), dorsolateral PFC (DLPFC), caudate, and putamen. The study provides strong evidence that these regions encode distinct RL-related signals, with ACC playing a dominant role in MB learning and caudate updating value representations after rare transitions. The authors apply rigorous statistical analyses to characterize neural encoding at both population and single-neuron levels.

Strengths:

(1) The research fills a gap in the literature, which has been limited in directly dissociating MB vs. MF learning at the single unit level and across brain areas known to be involved in reinforcement learning. This study advances our understanding of how different brain regions are involved in RL computations.

(2) The study used a two-step choice task Miranda et al., (2020), which was previously established for distinguishing MB and MF reinforcement learning strategies.

(3) The use of multiple brain regions (ACC, DLPFC, caudate, and putamen) in the study enabled comparisons across cortical and subcortical structures.

(4) The study used multiple GLMs, population-level encoding analyses, and decoding approaches. With each analysis, they conducted the appropriate controls for multiple comparisons and described their methods clearly.

(5) They implemented control regressors to account for neural drift and temporal autocorrelation.

(6) The authors showed evidence for three main findings:

(a) ACC as the strongest encoder of MB variables from the four areas, which emphasizes its role in tracking transition structures and reward-based learning. The ACC also showed sustained representation of feedback that went into the next trial.

(b) ACC was the only area to represent both MB and MF value representations.

(c) The caudate selectively updates value representations when rare transitions occur, supporting its role in MB updating.

(7) The findings support the idea that MB and MF reinforcement learning operate in parallel rather than strictly competing.

(8) The paper also discusses how MB computations could be an extension of sophisticated MF strategies.

Weaknesses:

(1) There is limited evidence for a causal relationship between neural activity and behavior. The authors cite previous lesion studies, but causality between neural encoding in ACC, caudate, and putamen and behavioral reliance on MB or MF learning is not established.

(2) There is a heavy emphasis on ACC versus other areas, but is unclear how much of this signal drives behavior relative to the caudate.

(3) The authors mention the monkeys were overtrained before recording, which might have led to a bias in MB versus MF strategy.

(4) The authors have responded to the weaknesses appropriately in the manuscript.

Reviewer #2 (Public review):

Summary:

A particular challenge in treating infections caused by the parasite Toxoplasma gondii is to target (and ultimately clear) the tissue cysts that persist for the lifetime of an infected individual. The study by Maus and colleagues leverages the development of a powerful in vitro culture system for the cyst-forming bradyzoite stage of Toxoplasma parasites to screen a compound library for candidate inhibitors of parasite proliferation and survival. They identify numerous inhibitors capable of inhibiting both the disease-causing tachyzoite and the cyst-forming bradyzoite stages of the parasite. To characterize the potential targets of some of these inhibitors, they undertake metabolomic analyses. The metabolic signatures from these analyses lead them to identify one compound (MMV1028806) that interferes with aspects of parasite mitochondrial metabolism. In the revised version of the manuscript, the authors present convincing evidence that MMV1028806 targets the mitochondrial electron transport (ETC) chain of the parasite (although they don't identify the actual target in the ETC). The revised manuscript also nicely addresses my other criticisms of the original version. Overall, the study presents an exciting approach for identifying and characterizing much-needed inhibitors for targeting tissue cysts in these parasites.

Strengths:

The study presents convincing proof-of-principle evidence that the myotube-based in vitro culture system for T. gondii bradyzoites can be used to screen compound libraries, enabling the identification of compounds that target the proliferation and/or survival of this stage of the parasite. The study also utilizes metabolomic approaches to characterize metabolic 'signatures' that provide clues to the potential targets of candidate inhibitors. In addition to insights into candidate bradyzoite inhibitors, the study also provides new insights into the physiological role of the mitochondrial electron transport chain of bradyzoites, and raises a host of interesting questions around the functional roles of mitochondria in this stage of the parasite.

Weaknesses:

In the revised manuscript, the authors have included additional oxygen consumption rate data that indicate that MMV1028806 targets the mitochondrial electron transport chain (ETC). These data are convincing. On line 481, the authors state that "treatments with ATQ, BPQ, MMV1028806, and antimycin A resulted in substantially reduced oxygen consumption levels relative to the DMSO control and suggest indeed a blockage of the mETC consistent with the inhibition of the bc1-complex." The OCR assay the authors use is still only an indirect measure of bc1 activity. Given that most OCR-inhibiting compounds in T. gondii are bc1 inhibitors, it is possible (and perhaps likely) that MMV1028806 is targeting this complex. However, the data cannot rule out that it is targeting another component of the ETC (or potentially even a TCA cycle enzyme). Without a direct test that MMV1028806 inhibits bc1 complex activity, the authors should be more cautious in their interpretation (e.g. by acknowledging the limitations of their conclusion, or acknowledging other possible targets). Similarly, the conclusion on line Line 622 that "... we confirmed the bc1-complex as a target" is overstating the findings. The phrasing on lines 683-695 is more appropriate: "... suggesting that it also targets complex III or a functionally linked site within the mitochondrial electron transport chain."

Reviewer #2 (Public review):

Mansingh et al., investigate the impact of voluntary wheel training and acute physical exercise on the transcriptomic and proteomic profile of spinal cord tissues from young adult mice. They first describe the proteomic and transcriptomic differences between sedentary mice and mice provided with running wheels for voluntary exercise. They show that voluntary physical exercise induces changes at a transcriptional level as well as at a proteomic level, with most of these effects restricted to glial cells. They further analyze the putative cell interactions that are induced in the context of physical training and describe the specificity of transcriptional changes in the different cell populations. Using the same multi-omics pipeline, the authors assess dynamic changes in sedentary and trained mice 6 and 24 hours following a bout of physical exercise until exhaustion. Importantly, they demonstrate that the impact of this single bout to exhaustion is modified in mice that have access to running wheels compared with sedentary mice, with a reduced amplitude of the reaction and a faster resolution of changes caused by exercise until exhaustion.

Altogether, this study provides a useful description of the transcriptional changes at play following voluntary physical training and, importantly, uncovers the role of this training in shaping future transcriptomic reactions to a stressful bout of exercise until exhaustion. However, the conclusions of the manuscripts would be strengthened by the clarification of the methods, a better use of the proteomic data regarding the transcriptomic datasets, and a cross-validation of the main claims currently based solely on transcriptomic datasets.

(1) In this study, the housing strategy used is key as it will impact both the proteome and transcriptome of cells in the central nervous system. It can be difficult to measure the running activity of individual mice if they are not housed individually. Yet, individual housing has a major impact on the nervous system and notably on glial cells. Therefore, a better description of the housing strategy for the sedentary and trained group during the 6 weeks of training is required.

(2) In the first part of the paper that uses the results from the first set of multi-omics data, the protocol used is not clear. From Figure 1A, it seems that the mice went through a max performance test before and after the 6-week period in which the two groups had different life experiences (voluntary running versus sedentary). Since in the methods the maximal test protocol is effectively an exercise until exhaustion, it is difficult to understand why the authors defined this first experiment as the one allowing them to test "molecular remodeling in the spinal cord at rest". Also, it is not clear how long after the max performance test the tissues were collected. If indeed the mice went through the max endurance test before tissue collection, it is not a condition at rest, and this first protocol in some way looks like a duplication of a subpart of the second experiment. If mice did not go through this max performance test, it needs to be clarified both in the text and in the figure.

(3) One of the strengths of this study is its multi-omics approach assessing changes at both transcriptomic and proteomic levels. Yet, the use by authors of the proteomic datasets is minimal, and there are no comments on how the proteomic and transcriptomic datasets support each other. Changes at the transcriptional level do not necessarily translate into changes at the protein level. Therefore, it would improve the quality of the study if authors could use the bulk proteomic data in relation to the transcriptomic dataset. The fact that the proteomic datasets do not provide the identity of the cells from which the changes originate should not prevent authors from putting them in perspective with transcriptomic results.

(4) None of the results from the single-nucleus RNA sequencing are cross-validated with, for instance, in situ hybridizations. It would improve the strength of the claim if some findings, in particular regarding the dynamics of the changes 6 vs 24h after exhaustion bout, were cross-validated.

(5) Although the authors note as a limitation that cholinergic neurons were underrepresented in their dataset, since one of the main claims of the manuscript relates to them, it calls for some additional comments on the identity of the cholinergic neurons present in their dataset. There are different populations of spinal cholinergic neurons with very different functions. It would greatly improve the strength of this result if the authors could identify which cholinergic neurons show these changes (or at least which proportion of the different cholinergic population is present in their datasets). For instance, which proportion of cholinergic neurons are expressing classical markers of motor neurons versus markers of cholinergic interneurons (for instance, from the V0c population).

Reviewer #2 (Public review):

Summary:

This manuscript investigates the mechanisms by which visual working memory (WM) interacts with perceptual judgements, using continuous mouse-tracking to dissociate putative attentional capture from representational shift. Across two experiments, participants maintained a color in WM while performing an intervening perceptual matching task. Analyses of mouse trajectories revealed bidirectional influences with distinct dynamics of attentional capture and representational shift components. For WM's influence on perceptual judgments, trajectories showed a fast and endpoint-inconsistent deviation (interpreted as attentional capture by WM-matching features), followed by a slower and sustained drift that closely matched the final perceptual bias. In contrast, when perceptual judgments influenced subsequent WM recall, trajectory dynamics were dominated by the sustained drift component, with minimal capture-like deviation. Together, these findings are interpreted as evidence that WM shapes perceptual decisions through at least two temporally distinct processes.

Strengths:

I find the paradigm to be cleverly designed and the analyses rigorous. A major strength of this work is the use of continuous mouse-tracking and time-resolved analyses to dissociate transient influences from sustained biases within single trials. The trajectory decomposition provides an elegant way to separate early deviations from later drift, which would be difficult to achieve using traditional measures that only measure the final recall. I find the observation particularly compelling that trajectories initially deviate toward WM-matching information and then correct back toward the task-relevant target, highlighting the dynamic interplay between transient priority signals and the final decision.

Weaknesses:

(1) The early curvature in the mouse trajectory, inconsistent with the endpoint, is interpreted as fast attentional capture. However, this signal may also reflect competition among multiple responses driven simultaneously by the WM representation and the perceptual matching item. While the current interpretation is plausible, it would be helpful if the authors could more clearly articulate why this component should be solely interpreted as attentional capture rather than early response competition.

(2) The mouse trajectories show a clear correction back toward the target later in the movement, particularly when the cursor enters the color wheel (Figure 3a), where the correction appears most pronounced. I wonder how this corrective phase should be interpreted. For example, does this correction reflect disengagement from an initial WM-driven priority signal, increasing influence of task demands and sensory evidence, or some other control process?

Relatedly, movement onset latency modulated the overall AUC but did not influence the final perceptual error. I wonder whether the time courses of the capture and shift components (as revealed by the destination-vector transformation) differ between early-onset and late-onset trials, and if so, when those differences emerge. Explicitly showing these comparisons would help further clarify how early capture is corrected while the endpoint bias remains stable. It may also be informative to include representative raw trajectory paths for early- and late-onset trials, as Figure 3a is currently the only figure showing raw trajectories, whereas most subsequent results are derived measures.

(3) The contrast in destination-vector dynamics between the perceptual matching response and the WM recall response (Figure 8) is interesting. For the representational shift component, the effect appears to increase sharply after movement onset. Conceptually, one might expect the shift in WM representation to have already occurred following perceptual judgment, rather than emerging during the response itself. It would be helpful if the authors could clarify why the shift is expressed primarily during the movement phase. Additionally, although weak, there appears to be a small capture-like deviation in the WM recall trajectories. Was this effect statistically significant? It may be informative to apply the same cluster-based permutation analysis directly comparing the capture effects against zero, in addition to the paired comparisons currently reported.

Reviewer #2 (Public review):

This paper investigates the latent dynamic brain states that emerge during memory encoding and predict later memory performance in children (N = 24, ages: 8 -13 years). A novel computational approach (Bayesian Switching Dynamic Systems, BSDS) discovers latent brain states from fMRI data in an unsupervised and parameter-free manner that is agnostic to external stimuli, resulting in 4 states: an active-encoding state, a default-mode state, an inactive state, and an intermediate state. The key finding is that the percentage of time occupied in the active-encoding state (characterized by greater activity in hippocampal, visual, and frontoparietal regions), as well as greater transitions to this state, predicts memory accuracy. Memory accuracy was also predicted by the mean lifetime and transitions to the default-mode state (characterized by greater activity in medial prefrontal cortex and posterior cingulate cortex) during post-encoding rest. Together, the results provide insights into dynamic interactions between brain regions that may be optimal for encoding novel information and consolidating memories for long-term retention.

The approach is interesting and important for our understanding of neural mechanisms of memory during development, as we know less about dynamic interactions between memory systems in development.

Moreover, the novel methodology may be broadly useful beyond the questions addressed in this study. The manuscript is well-written and concise. Nonetheless, there are several areas for improvement:

(1) The study focuses on middle childhood, but there is a lack of engagement in the Introduction or Discussion about what is known about memory development and the brain during this period. Many of the brain regions examined in this study, particularly frontoparietal regions, undergo developmental changes that could influence their involvement in memory encoding and consolidation. The paper would be strengthened by more directly linking the findings to what is already known about episodic memory development and the brain.

(2) A more thorough overview of the BSDS algorithm is needed, since this is likely a novel method for most readers. Although many of the nitty-gritty details can be referenced in prior work, it was unclear from the main text if the BSDS algorithm discovered latent states based on activation patterns, functional connectivity, or both. Figure 1F is not very informative (and is missing labels).

(3) A further confusion about the BSDS algorithm was whether it necessarily had to work on the rest data. Figure 4A suggests that each TR was assigned one of the four states based on the maximum win from the log-likelihood estimation. Without more details about how this algorithm was applied to the rest data, it is difficult to evaluate the claim on page 14 about the spontaneous emergence of the states at rest.

(4) Although the BSDS algorithm was validated in prior simulations and task-based fMRI using sustained block designs in adults, it is unclear whether it is appropriate for the kind of event-related design used in the current study. Figure 1G shows very rapid state changes, which is quantified in the low mean lifetime of the states (between 1-3 TRs on average) in Figure 4C. On the one hand, it is a strength of the algorithm that it is not necessarily tied to external stimuli. On the other hand, it would be helpful to see simulations validating that rapid transitions between states in fMRI data are meaningful and not due to noise.

(5) The Methods section mentions that participants actively imagined themselves within the encoded scenes and were instructed to memorize the images for a later test during the post-encoding rest scan. This detail needs to be included in the main text and incorporated into the interpretation of the findings, as there are likely mechanistic differences between spontaneous memory replay/reinstatement vs. active rehearsal.

(6) Information about the general linear model used to discover the 16 ROIs that showed a subsequent memory effect are missing, such as: covariates in the model (motion, etc.), group analysis approach (parametric or nonparametric), whether and how multiple-comparisons correction was performed, if clusters were overlapping at all or distinct, if the total number of clusters was 16 or if this was only a subset of regions that showed the effect.

Reviewer #2 (Public review):

This work studies the self-association behavior of 109 human Death Fold Domains (DFD) in eukaryotic cells and its connection to their function in innate immune signalosomes.

Using an amphifluoric FRET (DAmFRET) method previously developed by the authors, self-association is monitored as a function of protein concentration by Förster Resonance Energy Transfer in the cell.

Several DFDs are found to be in a supersaturable state and are considered energy reservoirs necessary for signal amplification.

The revised manuscript addresses most of the original concerns, resulting in a significant improvement.

The following observations are made:

(1) A group of DFDs shows a bimodal FRET distribution of no FRET and high FRET values at low and high protein concentration, which indicates a nucleation barrier. This conclusion is corroborated by the modification from a discontinuous to a continuous FRET transition by expressing a structural template or seed. The authors find that DFDs displaying discontinuous FRET behavior are supersaturated, and those that retain their discontinuous behavior in the context of the full-length protein correspond to protein adaptors of innate immune signalosomes.

(2) The authors indicate that the adaptors of inflammatory signalosomes act as energy reservoirs for signal amplification. This is not demonstrated, but it is assumed that the energy stored in the supersaturated state is released upon polymerization.

(3) This work also includes evidence showing that nonsupersaturable and supersaturable constructs of caspase-9 form puncta that dissolve or persist, respectively, upon apoptosome stimulation. The supersaturable construct also induces massive cell death, in contrast to the nonsupersaturable form. Although not demonstrated, these results could be related to the level of signal amplification.

(4) The cell's lifespan depends on the supersaturation levels of certain DFDs.

(5) Polymerization nucleated by interaction between DFDs from different pathways (different signalosomes) is rare.

(6) The study demonstrates the presence of nucleation barriers, inferred from supersaturable conditions, in the adaptor orthologs of zebrafish (Danio rerio) and the model sponge Amphimedon queenslandica, which indicates that this characteristic is conserved.

Reviewer #3 (Public review):

Xiaoyu Wu and colleagues examined a potential role in sleep of a Drosophila ribosomal RNA methyltransferase, mettl5. Based on sleep defects reported in CRISPR generated mutants, the authors performed both RNA-seq and Ribo-seq analyses of head tissue from mutants and compared to control animals collected at the same time point. A major conclusion was that the mutant showed altered expression of circadian clock genes, and that the altered expression of the period gene in particular accounted for the sleep defect reported in the mettl5 mutant. In this revision, the authors have added a more thorough analysis of clock gene expression and show that PER protein levels are increased relative to wild type animals a specific times of day, indicating increased stability of the protein. Given that PER inhibits its own transcription, the per RNA is low in the mutants. Efforts toward a more detailed understanding of how clock gene expression was altered in the mutants, as well as other clarification of sleep phenotypes throughout is appreciated. As noted above, a strength of this work is its relevance to a human developmental disorder as well as the transcriptomic and ribosomal profiling of the mutant. However, there still remain some minor weaknesses in the manuscript. This reviewer is not in agreement with the interpretation of the epigenetic experiments. Specifically, co-expression of Clk[jrk] or per[01] with the mettl5 mutant recovered the nighttime sleep phenotype, but was additive to the daytime sleep phenotype such that double mutants showed higher sleep. This effect should be acknowledged and discussed. Overall, this is an interesting paper that indicates a molecular link between mettl5 and the circadian clock in regulation of sleep.

Reviewer #2 (Public review):

Summary:

In this study, performed in human patients, the authors aimed at dissecting out the role of cholinergic modulation in different types of memory (recollection-based vs familiarity and novelty-based) and during different memory phases (encoding and retrieval). Moreover, their goal was to obtain the electrophysiological signature of cholinergic modulation on network activity of the hippocampus and the entorhinal cortex.

Strengths:

Authors combined cognitive tasks and intracranial EEG recordings in neurosurgical epilepsy patients. The study confirms previous evidence regarding the deleterious effects of scopolamine, a muscarinic acetylcholine receptor antagonist, on memory performance when administered prior the encoding phase of the task. During both encoding and retrieval phases scopolamine disrupts the power of theta oscillations in terms of amplitude and phase synchronization. These results raise the question on the role of theta oscillations during retrieval and the meaning of scopolamine effect on retrieval-associated theta rhythm without cognitive changes. The authors clearly discussed this issue in the discussion session.

A major point is the finding that scopolamine-mediated effect is selective for recollection-based memory and not for familiarity- and novelty-based memory.

The methodology used is powerful and the data underwent a detailed and rigorous analysis.

Reviewer #2 (Public review):

The revised data support the conclusion that methodological differences can influence apparent receptor localization. However, key claims regarding functional surface engagement of TfR and hydrodynamic clearance remain based largely on indirect evidence and model-based interpretation. These conclusions should therefore be phrased more cautiously.

I thank the authors for their careful rebuttal and the additional experiments included in the revised manuscript. The new fixation comparisons and transferrin competition assays substantially strengthen the technical basis of the study and address several of the original concerns.

However, some conclusions remain more inferential than directly supported by the data. While the fixation and washing controls demonstrate that methodology influences apparent TfR localisation, they do not directly establish that previous protocols quantitatively redistribute surface TfR into the flagellar pocket. Statements implying such redistribution should therefore be phrased more cautiously.

Similarly, the added transferrin binding controls argue against non-specific interactions, but functional engagement of surface-exposed TfR in intact bloodstream-form parasites remains supported mainly by indirect evidence. The proposed explanation involving rapid on/off rates and newly arriving receptors is plausible but should be more clearly identified as an inference.

Reviewer #2 (Public review):

Summary:

The posterior parietal cortex (PPC) has been identified as an integrator of multiple sensory streams and guides decision making. Hira et al observe that dissection of the functional specialization of PPC subregions requires simultaneous measurement of neuronal activity throughout these areas. To this end, they use widefield calcium imaging to capture the activity of thousands of neurons across the PPC and surrounding areas. They begin by delineating the boundaries between the primary sensory and higher visual areas using intrinsic imaging and validate their mapping using calcium imaging. They then conduct imaging during a visually guided task to identify neurons that respond selectively to visual stimuli or choice. They find that vision and choice neurons intermingle primarily in the anterior medial (AM) area, and that AM uniquely encodes information regarding both the visual stimulus and the previous choice, positioning AM as the main site of integration of behavioral and visual information for this task.

Strengths:

There is an enormous amount of data and results reveal very interesting relationships between stimulus and choice coding across areas and how network dynamics relate to task coding.

Weaknesses:

The enormity of the data and the complexity of the analysis makes the manuscript hard to follow. Sometimes it reads like a laundry list of results as opposed a cohesive story.

Comments on revisions:

The authors have addressed our concerns.

Reviewer #2 (Public review):

Summary

Briola and co-authors have performed a structural analysis of the human CTF18 clamp loader bound to PCNA. The authors purified the complexes and formed a complex in solution. They used cryo-EM to determine the structure to high resolution. The complex assumed an auto-inhibited conformation, where DNA binding is blocked, which is of regulatory importance and suggests that additional factors could be required to support PCNA loading on DNA. The authors carefully analysed the structure and compared it to RFC and related structures.

Strength & Weakness

Their overall analysis is of high quality, and they identified, among other things, a human-specific beta-hairpin in Ctf18 that flexible tethers Ctf18 to Rfc2-5. Indeed, deletion of the beta-hairpin resulted in reduced complex stability and a reduction in the rate of primer extension assay with Pol ε. Moreover, the authors identify that the Ctf18 ATP-binding domain assumes a more flexible organisation.

The data are discussed accurately and relevantly, which provides an important framework for rationalising the results.

All in all, this is a high-quality manuscript that identifies a key intermediate in CTF18-dependent clamp loading.

Reviewer #2 (Public review):

Summary:

Mohr and Kelly report a high-density EEG study in healthy human volunteers in which they test whether correlations between neural activity in primary visual cortex and choice behavior can be measured non-invasively. Participants performed a contrast discrimination task on large arrays of Gabor gratings presented in the upper left and lower right quadrants of the visual field. The results indicate that single-trial amplitudes of C1, the earliest cortical component of the visual evoked potential in humans, predict forced-choice behavior over and beyond other behavioral and electrophysiological choice-related signals. These results constitute an important advance for our understanding of the nature and flexibility of early visual processing.

Strengths:

The findings suggest a previously unsuspected role for aggregate early visual cortex activity in shaping behavioral choices.

The authors extend well-established methods for assessing covariation between neural signals and behavioral output to non-invasive EEG recordings.

The effects of initial afferent information in primary visual cortex on choice behavior is carefully assessed by accounting for a wide range of potential behavioral and electrophysiological confounds.

Caveats and limitations are transparently addressed and discussed.

Weaknesses:

Due to the inherent limitations of scalp-recorded visual evoked potentials, the results cannot be directly compared to invasive recordings in animal models.

Reviewer #2 (Public review):

Summary:

- This is a complicated research topic that touches on a few sub-fields of biology, and thus to make the paper more approachable I would recommend a careful edit of the text for clarity and precision of language.<br /> - Authors point out that this is a decades-old field; it would make sense to use terminology established within the field rather than inventing their own. Allelic imbalance has been referred to as AI, MAE (monoallelic expression), RMAE (random monoallelic expression) etc. The paper whose mouse data the authors make use of uses Asynchronous Stochastic Replication Timing (ASRT) instead of VERT to refer to the same phenomenon. Creating unnecessary jargon makes the paper more difficult to read and adds needless complexity to an already complex field.<br /> - Methods do not provide sufficient detail to fully evaluate or reproduce these experiments.<br /> - It is helpful to show representative loci as the authors do in Fig 1F and G and Fig 2, but these panels are very densely rendered and thus difficult to process visually - even the cartoon version (1D) is thick with overlapping lines. The point that allelic imbalance is enriched in VERTs would be enhanced if the authors could present the allelic ratio for all genes found in all VERTs, demonstrating how replication timing on either chromosome affects the allelic ratio.<br /> - The authors make the important point that VERTs are unlikely to be shared among different cell types and tissues (Fig 1i) but then find an enrichment for neuronal and immune genes in VERT regions identified in ACPs. It follows that these same genes are unlikely to be in such regions in the tissues where they are relevant. Some of the GO terms presented are too broad to suggest any biological significance to the result, even if there is statistical significance (for example, the top term for LCL clones 'Cytoplasm' is associated with 12,000 genes, and the second term for mouse clones 'Membrane' is associated with 10,000). It would be helpful to focus on GO terms lower in the GO hierarchy.<br /> - Figure 3 highlights the association of related gene clusters with VERTs but the VERTs are assigned based on variable replication timing in just 1 or 2 clones. This is an interesting observation, but to make the point that "VERT regions frequently coincide with gene clusters in the human genome" there needs to be a systematic assessment of replication timing at all gene clusters across all clones, and a statistical test for significance.<br /> - It is an interesting hypothesis that VERTs are conserved between species at synentic loci. If such regions are really conserved, one would expect that replication timing at these sites would be consistently asynchronous. However, the data presented shows that in human clones these VERTs can be specific to an individual donor (as in 5A) or an individual clone (as in 5H).<br /> - Again, the finding that VERTs coincide with neurodevelopmental disease genes in immune and cartilage cells is at odds with the previous statements and data about the tissue specificity of VERTs. In order to support the claim that neurodevelopmental disease associated genes reside in asynchronously replicating regions, and are thus more prone to allelic imbalance, the authors would need to demonstrate this phenomenon in neuronal cells.

Significance:

The authors pair analysis of replication timing and allele-specific expression in clonal populations of primary human cells. They combine these data with previously published data on clones from transformed human cell lines. They identify a number of genomic regions that display asynchronous replication timing in at least one clone and correlate these regions with allele-specific expression of genes within them. They also observe that several interesting gene sets, including genes that are associated with human diseases, map to asynchronously replicating regions. This is a good experimental approach that builds on already published data demonstrating the connection between allelic imbalance and replication timing. However, the authors consistently lean on thin evidence (i.e. a single clone) within a modestly sized dataset (4 clones from 2 donors each) to propose a new model for haploinsufficiency in human disease. The consistent focus on limited elements in the data and perhaps an overreach in the interpretation makes it difficult to appreciate what is in fact a very good experiment.

Reviewer #2 (Public review):

Summary:

This manuscript describes novel BK channel concatemers as a tool to study the stoichiometry of gamma subunit and mutations in modulation of the channel. Taking the advantage of modular design of BK channel alpha subunit the authors connected S1-S6/1st RCK as two- and four-subunit concatemers and coexpressed with S0-RCK2 to form normal function channels. These concatemers avoided the difficulty that the extracellular N-terminus of S0 was unable to connect with the cytosolic C-terminus of the alpha or gamma subunit, allowing a single gamma subunit to be connected to the concatemers. The concatemers also helped reveal the required stoichiometry of mutant BK subunits in modulating channel function. These include L312A in the deep pore region that altered channel function additively with each additional subunit harboring the mutation, and V288A at the selectivity filter that altered channel function cooperatively only when all four subunits being mutated. These results demonstrate that the concatemers are robust and effective in studying BK channel function and molecular mechanisms related to stoichiometry. The different requirement of the gamma subunit and the mutations stoichiometry for altering channel function is interesting, revealing fundamental mechanisms of how different motifs of the channel protein control function.

Strengths:

The manuscript presents well designed experiments with high quality data, which convincingly demonstrate the BK channel concatemers and their utility. The results are clearly written.

Weaknesses:

This reviewer did not identify any major concerns with the manuscript.

Editors' note: We thank you for addressing some of the concerns, adding clarifications and more complete discussions, including further details about experimental protocols. The revised version is significantly improved. Some concerns linger that the biophysical/structural mechanisms underlying the observed phenotypes remain unclear and in some ways are phenomenological. However, the current study is more about the methodology and the mechanisms underlying the stoichiometry dependent effects are perhaps left for a separate study, with more detailed exploration. Congratulations for the excellent work.

Reviewer #2 (Public review):

Summary:

The work titled "Geomagnetic and visual cues guide seasonal migratory orientation in the nocturnal fall armyworm, the world's most invasive insect" provided experimental evidence on how geomagnetic and visual cues are integrated, and visual cues are indispensable for magnetic orientation in the nocturnal fall armyworm.

Strengths:

It has been demonstrated that the Australian Bogon moth could integrate global stellar cues with the geomagnetic field for long distance navigation. However, data are lacking for other insects. This study suggested that the integration of geomagnetic and visual cues may represent a conserved navigational mechanism broadly employed across migratory insects.

Weaknesses:

The visual cues used in the indoor experimental system designed by the authors may have some limitations in ecological relevance. The author may need more explanations on this experimental system.

In the revised manuscript, the authors have added explanations in the discussion section. I am fine with the revision.

Reviewer #2 (Public review):

Summary:

In this article, Laaker et al described diverse populations of macrophages and dendritic cells found in and around the cribriform plate in the context of a neuroinflammation caused by an autoimmune disease (EAE). The authors utilize elegant histochemical staining and a nifty approach to sort doublets to interrogate cells that are in contact with one another, presumably in vivo. Notably, they uncover a population of CD11c+CD11b+ cells interacting with M2 macrophages and PDPN+ fibroblasts and lymphatics. These cells are heterogenous but some of these DCs express PD-1, and transcriptional profiling suggests they may have immunosuppressive behavior. Altogether, this article explains well the complexity of cell populations found around the cribriform plate during inflammation, and is suggestive of different interactions that trigger these different phenotypes from immune cells.

Strengths:

Beautiful images of a unique CNS: peripheral interface that support a novel scRNA approach to understanding how different cell populations engage in functional interactions in vivo.

Weaknesses:

It's currently unclear how the sorted populations reflect in vivo interactions or a propensity to form aggregates during ex vivo processing. The authors address both podoplanin-expressing cells as stromal cells and as lymphatic endothelial cells, but at times it's unclear which of these two populations is being analyzed and which is the most relevant. While novel observations, most of these findings are descriptive and lack functional correlates, and in places, the potential implications could use further discussion.

Reviewer #2 (Public review):

Summary:

Almansour et al. investigate whether the proximity of TAD boundaries is directly linked to gene activity. The authors use high-throughput imaging to simultaneously measure the gene activity and physical distances between boundary regions in an allele-specific manner. Using transcriptional inhibitors, expression induction, and acute depletion of CTCF and cohesin, they test whether proximity of boundaries affects, or is affected by, gene activity.

Strengths:

The combined use of DNA and RNA imaging enabled simultaneous measurement of boundary proximity and transcriptional status at individual alleles. This allows single-allele correlation between boundary proximity and gene activity at multiple loci across thousands of alleles.

The use of both transcription inhibitors and transcription stimulation provides compelling and consistent evidence that boundary proximity can be disconnected from a gene's activity. The data convincingly support the conclusion that stable proximity between boundary regions is not required for ongoing transcription at the loci and timescales examined.

This work strengthens the emerging view that genome organization at the level of domain boundaries does not impose a deterministic control over transcription.

Weaknesses:

In untreated cells, the distribution of distance measurements between boundary probes is exceptionally narrow. While depletion of RAD21 clearly demonstrates an ability to detect changes in this distribution, this tight baseline distribution may limit sensitivity to more subtle changes (like those one might expect from transcriptional influences). In addition, the correlation analysis is asymmetric, primarily stratifying by transcriptional status and then comparing boundary distances. Given the central claim that boundary architecture does not influence gene activity, the analysis should be done from the opposite perspective (stratifying by boundary distance).

Strong disruption of boundary distances is only observed upon depletion of cohesin. Notably, this corresponds with the largest changes in gene activity. In contrast, depletion of CTCF actually had minimal impact on boundary distances and also had minimal impact on gene activity. This makes sense in light of previous work, where live cell imaging demonstrated that cohesin is more important for domain-structure, whereas CTCF is only important for blocking cohesin from continuing on, such that the fully formed loop occurs in a very small percentage of cells. Therefore, the fact that disruption of cohesin (more important for internal domain structure) affects gene activity while disruption of CTCF does not is exceptionally interesting but is lacking from the discussion.

On a related note, this approach primarily tests the role of boundary interactions rather than domain organization as a whole, and it should be acknowledged that internal domain structures are not directly assessed.

The comparison to work in other organisms (particularly the comparisons made to Drosophila) should be handled with care. The mechanisms underlying domain formation differ substantially across these systems, particularly regarding the differences in CTCF's role.

Reviewer #2 (Public review):

Summary:

Okatsu et al report the cryoEM structure of the PINK1-HSP90-CDC37 complex at 3.08A. To do so, they mutated the PARL cleavage site (F104M) and removed the N-terminal 103 a.a. The construct was co-expressed with HSP90beta and CDC37 in insect cells, as performed previously for other kinase-HSP90-CDC37 complexes (e.g. Raf1). Molybdate was added to prevent cycling between open and closed HSP90 conformations. The initial characterization by single particle cryoEM reveals two HSP90 conformations: closed with CDC37 dissociated, and open with the CTD of HSP90 separated. Thus, the authors crosslinked the complex, which yielded a more homogenous closed structure with clearly visible density for HSP90, CDC37, and PINK1. The structure shows an immature or partially folded kinase domain conformation for PINK1, with the C-lobe bound to HSP90 and the N-lobe unfolded. The C-lobe binds to HSP90 via the HPNI motif in CDC37, which mimics the HPNI motif found in the N-lobe of kinases, and which is conserved across kinases. The main novelty here is the interaction between the C-terminal extension (CTE) of PINK1, which must adopt another conformation than in the folded state, which would otherwise clash with HSP90. The interaction with the CTE is notably mediated by the flexible charged linker (FCL) of HSP90, which is partially disordered. In this conformation, HSP90 would clash with TOM20 binding.

Strengths:

Overall, this is well-executed structural biology work, which brings insight into the elements required to fold PINK1. The protein engineering used in this study is of great value and will help others in the field explore the function of PINK1 folding. Understanding the mode of activation of PINK1 is important, and this work brings forward hypotheses that are worthy of testing.

Weaknesses:

In the absence of functional assays, the study does not bring much novelty or biological insights. Furthermore, there are already several structures of HSP90-CDC37 bound to partially folded kinases, and a simple superposition of these structures on the model of HsPINK1 allows similar conclusions to be drawn, i.e. that it would bind a folded C-lobe and unfolded N-lobe. Furthermore, a very similar structure of PINK1 bound to HSP90-CDC37 (and FKBP5) was published in Nature Communications in December 2025 by another group. The main novelty from this work (and the paper published in December) is that the CTE adopts a different conformation compared to the mature form, but the implications of this are not explored. Furthermore, the authors propose that HSP90 would compete with TOM20, but what dictates the outcome of this competition? More importantly, how do these results help understand how PINK1 become active? Again, this is not explored.

Reviewer #2 (Public review):

Aging poses a significant challenge to the regenerative capacity of oligodendrocyte precursor cells (OPCs) to differentiate and myelinate neuronal axons. Myelin abnormalities accumulate with age, and it is likely that the ability of OPCs to differentiate into myelinating oligodendrocytes becomes progressively impaired during aging, leading to inefficient turnover of damaged myelin and oligodendrocytes, as well as reduced adaptive myelination. Understanding the molecular mechanisms underlying the compromised capacity of aged OPCs is therefore critical for addressing age-related white matter decline.

This study aims to decipher the intrinsic molecular changes that occur in aged OPCs. By profiling differentially expressed transcription factors (TFs) between young and aged OPCs, and by employing a novel bioinformatic tool to identify key TFs that undergo dynamic changes across distinct stages of OPC differentiation, the authors identify Bcl11a as a potential regulator. Bcl11a is highly expressed in young OPCs but markedly reduced in aged cells. Functional experiments further demonstrate that while Bcl11a does not affect OPC proliferation, it significantly promotes the differentiation of aged OPCs. Importantly, this effect is also observed in vivo following demyelinating injury in aged mice.

While the study provides compelling evidence that BCL11A represents a limiting factor for OPC differentiation during ageing, the downstream targets and molecular mechanisms through which BCL11A exerts its effects are not directly addressed. As such, the work should be interpreted primarily as identifying a key regulatory node rather than a fully defined molecular pathway.

Overall, this study offers valuable insights into the age-related loss of regenerative capacity in the central nervous system and introduces a computational framework that may be broadly useful for investigating dynamic gene regulation in other biological contexts.

Major Points:

(1) MACS mouse anti-A2B5 microbeads are not OPC-specific and may also label astrocyte precursor cells or immature astrocytes. How do the authors justify this caveat? Could some of the claimed "OPC-specific" switch genes in fact be enriched in astrocyte lineage cells?

(2) Overall, Figures 1 and 2 are not very informative in terms of biological insight. The authors should provide more detail in the main figures regarding the enriched gene sets associated with each of the Type 1-4 switch categories. For example, summarizing the top Gene Ontology terms for each switch type would greatly enhance interpretability.

(3) A similar issue applies to Figure 3. The authors should explicitly specify the transcription factors in the main figure, particularly the 27 TFs identified through the ENCODE/ReMap2 analysis.

(4) Have the authors validated Bcl11a expression across different CNS cell types and between young and aged conditions using independent methods such as qPCR, immunofluorescence, or western blotting?

(5) Regarding OPC aging, an open question is whether the reduced differentiation capacity of aged OPCs is an intrinsic property of the cells themselves or whether it results from prolonged exposure to an aging environment that induces non-cell-autonomous epigenetic or genetic changes, thereby rendering OPCs less efficient at differentiating. It would be helpful if the authors could expand on this point in the Discussion, with reference to relevant previous studies and experimental evidence.

(6) Do the authors observe a change in the number or density of OPCs between young and aged mice?

(7) The in vivo characterization of Bcl11a overexpression using the AAV-based approach appears incomplete. Do aged mice overexpressing Bcl11a in Sox10⁺ cells exhibit reduced age-related myelin degeneration under baseline conditions? In the LPC model, do the authors observe differences in lesion size and/or remyelination efficiency?

(8) Are the authors presenting gSWITCH for the first time in this manuscript? Given that the gSWITCH framework is novel and central to the study, its conceptual contribution could be emphasized more strongly. A brief comparison with existing trajectory- or pattern-based methods-ideally in the main text around Figure 1-would help readers better appreciate its novelty.

(9) The evolutionary analysis also appears somewhat disconnected from the rest of the study. Could the authors leverage available public datasets to test whether a similar Bcl11a expression trajectory is observed in human oligodendrocyte lineage cells?

Reviewer #2 (Public review):

Summary

This manuscript focuses on the role of social responsibility and guilt in social decision making by integrating neuroimaging and computational modeling methods. Across two studies, participants completed a lottery task in which they made decisions for themselves or for a social partner. By measuring momentary happiness throughout the task, the authors show that being responsible for a partner's bad lottery outcome leads to decreased happiness compared to trials in which the participant was not responsible for their partner's bad outcome. At the neural level, this guilt effect was reflected in increased neural activity in the anterior insula, and altered functional connectivity between the insula and the inferior frontal gyrus. Using computational modeling, the authors show that trial by trial fluctuations in happiness were successfully captured by a model including participant and partner rewards and prediction errors (a 'responsibility' model), and model-based neuroimaging analyses suggested that prediction errors for the partner were tracked by the superior temporal sulcus. Taken together, these findings suggest that responsibility and interpersonal guilt influence social decision making.

Strengths

This manuscript investigates the concept of guilt in social decision making through both statistical and computational modeling. It integrates behavioral and neural data, providing a more comprehensive understanding of the psychological mechanisms. For the behavioral results, data from two different studies is included, and although minor differences are found between the two studies, the main findings remain consistent. The authors share all their code and materials, leading to transparency and reproducibility of their methods.

The manuscript is well-grounded in prior work. The task design is inspired by a large body of previous work on social decision making, and includes the necessary conditions to support their claims (i.e., Solo, Social, and Partner conditions). The computational models used in this study are inspired by previous work, and build on well-established economic theories of decision making. The research question and hypotheses clearly extend previous findings, and the more traditional univariate results align with prior work.

The authors conducted extensive analyses, as supported by the inclusion of different linear models and computational models described in the supplemental materials. Psychological concepts like risk preferences are defined and tested in different ways, and different types of analyses (e.g., univariate and multivariate neuroimaging analyses) are used to try to answer the research questions. The inclusion and comparison of different computational models provides compelling support for the claim that partner prediction errors indeed influence task behavior, as illustrated by the multiple model comparison metrics and the good model recovery.

The authors did a good job acknowledging other factors that could differ between the conditions, including the role of other emotions (like empathy) or agency in the decision making process. These additional analyses and nuances strengthen the manuscript and the interpretability of the findings.

Weaknesses

As the authors already note, they did not directly ask participants to report their feelings of guilt. The authors clearly describe this limitation, and also note that in addition to guilt, other emotions like empathy could also be at play in interpersonal decisions. Despite this limitation, this study provides insights into the neural and behavioral mechanisms of responsibility and guilt in social decision making, and how they influence behavior.

Reviewer #2 (Public review):

In this paper, Rayan et al. report that RNA influences cytotoxic activity of the staphylococcal secreted peptide cytolysin PSMalpha3 versus human cells and E. coli by impacting its aggregation. The authors used sophisticated methods of structural analysis and described the associated liquid-liquid phase separation. They also compare the influence of RNA on the aggregation and activity of LL-37, which shows differences from that on PSMalpha3.

Strengths:

That RNA impacts PSM cytotoxicity when co-incubated in vitro becomes clear.

Weaknesses:

I have two major and fundamental problems with this study:

(1) The premise, as stated in the introduction and elsewhere, that PSMalpha3 amyloids are biologically functional, is highly debatable and has never been conclusively substantiated. The property that matters most for the present study, cytotoxicity, is generally attributed to PSM monomers, not amyloids. The likely erroneous notion that PSM amyloids are the predominant cytotoxic form is derived from an earlier study by the authors that has described a specific amyloid structure of aggregated PSMalpha3. Other authors have later produced evidence that, quite unsurprisingly, indicated that aggregation into amyloids decreases, rather than increases, PSM cytotoxicity. Unfortunately, yet other groups have, in the meantime, published in-vitro studies on "functional amyloids" by PSMs without critically challenging the concept of PSM amyloid "functionality". Of note, the authors' own data in the present study, which show strongly decreased cytotoxicity of PSMalpha3 after prolonged incubation, are in agreement with monomer-associated cytotoxicity as they can be easily explained by the removal of biologically active monomers from the solution.

(2) That RNA may interfere with PSM aggregation and influence activity is not very surprising, given that PSM attachment to nucleic acids - while not studied in as much detail as here - has been described. Importantly, it does not become clear whether this effect has biologically significant consequences beyond influencing, again not surprisingly, cytotoxicity in vitro. The authors do show in nice microscopic analyses that labeled PSMalpha3 attaches to nuclei when incubated with HeLa cells. However, given that the cells are killed rapidly by membrane perturbation by the applied PSM concentrations, it remains unclear and untested whether the attachment to nucleic acids in dying cells makes any contribution to PSM-induced cell death or has any other biological significance.

Overall, the findings can be explained in a much more straightforward way with the common concept of cytotoxicity being due to monomeric PSMs, and the impact of nucleic acids on cytotoxicity being due to lowering of the concentration of that active form by RNA attachment. Further limiting the significance of the findings, whether this interaction has any biological significance on the physiology or infectivity of the PSM producer remains largely unexplored.

Reviewer #2 (Public review):

The authors argue that the Emiliano Aguirre Korongo (EAK) assemblage from the base of Bed II at Olduvai Gorge shows systematic exploitation of elephants by hominins about 1.78 million years ago. They describe it as the earliest clear case of proboscidean butchery at Olduvai and link it to a larger behavioral shift from the Oldowan to the Acheulean.

The manuscript makes a valuable contribution to the Olduvai Gorge record, offering a detailed description of the EAK faunal assemblage. In particular, the paper provides a high-resolution record of a juvenile Elephas recki carcass, associated lithic artifacts, and several green-broken bone specimens. These data are inherently valuable and will be of significant interest to researchers studying Early Pleistocene taphonomy.

Comments on previous round of revisions:

The revised manuscript does a good job of using less definitive language, particularly by adding "possible" qualifiers to several interpretations. This addresses the concern about overstatement.

The main issue raised in the original review, however, remains unresolved. Only two elephant bone specimens at EAK show green-bone breakage interpreted as anthropogenic, and the diagnostic basis for that interpretation is not demonstrated clearly on the EAK material itself. The manuscript discusses a suite of fracture attributes described as diagnostic of dynamic percussive breakage, but these attributes are not explicitly documented on the EAK specimens. Instead, the diagnostic traits are illustrated using material from other Olduvai contexts, and that behavior is then extrapolated to make similar claims at EAK. For a paper making a potentially important behavioral argument, the key diagnostic evidence is not clearly demonstrated at the focal assemblage.

This problem is evident in the presentation of the EAK specimens. In their response, the authors state that one EAK specimen shows "overlapping scars" and constitutes a "long bone flake"; however, these features are not clearly identifiable in the figures or captions as currently presented. The authors state that Figures S21-S23 clearly indicate human agency, including a long bone flake with overlapping scars and a view of the medullary surface, but it is unclear which specimens or surfaces these descriptions refer to. Figure S21 does appear to show green fracture and is described only as an "elephant-sized flat bone fragment with green-bone curvilinear break." Figure S22 shows the same bone and cortical surface in a different orientation, providing no additional information. In Figure S23, I cannot clearly identify a medullary surface or evidence of green-bone fracture from this image. None of these images clearly demonstrates overlapping scars, and the figures would be substantially improved by explicitly identifying the features described in the text. Even if both EAK specimens are accepted as green-broken, they do not demonstrate the co-occurrence of multiple diagnostic fracture traits such as multiple green breaks, large step fractures, hackle marks, and overlapping scars that the authors state is required to attribute dynamic percussive activity to hominins and address equifinality.

I appreciate that the authors are careful to state that spatial association between stone tools and fossils alone does not demonstrate hominin behavior, and that they treat the spatial analyses as supportive rather than decisive. While the association is intriguing, the problem is downstream: spatial association is used to strengthen an interpretation of butchery at EAK that still depends on fracture evidence that is not clearly documented at the assemblage level.

The critique concerning Nyayanga is not addressed in the revision. The manuscript proposes alternative explanations for the Nyayanga material but does not demonstrate why these are more plausible than the interpretation advanced by Plummer et al. (2023). I am not arguing that the Nyayanga material should be accepted as butchery; rather, showing that trampling is possible does not establish it as more probable than cut marks. In contrast, the EAK material is treated as evidence of butchery on the basis of evidence that, in my opinion, is more limited and less clearly demonstrated. Even if this is not the authors' intention, the uneven treatment removes an earlier megafaunal case from the comparison and strengthens the case for interpreting EAK as marking a behavioral shift toward megafaunal butchery by excluding other early cases.

While I remain concerned about how the EAK evidence is documented and interpreted, I think the manuscript is appropriate for publication and will generate useful discussion. Readers can then assess for themselves whether the available evidence supports the strength of the behavioral claims.

[Editors' note: the authors are encouraged to make this version the Version of Record.]

Reviewer #2 (Public review):

Summary:

King et al. present several sets of experiments aimed to address potential impact of UV irradiation on human mitochondrial DNA as well as possible role of mitochondrial TFAM protein in handling UV irradiated mitochondrial genomes. The carefully worded conclusion derived from the results of experiments performed with human HeLa cells, in vitro small plasmid DNA, with PCR-generated human mitochondrial DNA and with UV-irradiated small oligonucleotides is presented in the title of the manuscript: "UV irradiation alters TFAM binding to mitochondrial DNA". Authors also interpret results of somewhat unconnected experimental approaches to speculate that "TFAM as a potential DNA damage sensing protein in that it promotes UVC-dependent conformational changes in the [mitochondrial] nucleoids, making them more compact. They further propose that such a proposed compaction might trigger removal of UV-damaged mitochondrial genomes as well as facilitates replication of undamaged mitochondrial genomes.

Strengths:

(1) Authors presented convincing evidence that a very high dose (1500 J/m2) of UVC applied to oligonucleotides covering the entire mitochondrial DNA genome alleviates sequence specificity of TFAM binding (Figure 3). This high dose was sufficient to cause UV-lesions in a large fraction of individual oligonucleotides. The method has been developed in the lab of one of the corresponding authors (ref. 74) and is technically well refined. This result can be published as is or in combination with other data.

(2) Manuscript also presents AFM evidence (Figure 4) that TFAM, which was long known to facilitate compaction of mitochondrial genome (Alam et al., 2003; PMID 12626705 and follow up citations), causes in vitro compaction of a small pUC19 plasmid and that approximately 3 UVC lesions per plasmid molecule results in slight albeit detectable increase in TFAM compaction of the plasmid.

Both results are discussed in line of a possible extrapolation to in vivo phenomena. The revised version of the discussion includes a clear statement that no in vivo support was provided within the set of experiments presented in the manuscript.

Weaknesses:

The experiments presented on Figures 3 and 4 may support the speculation that TFAM can carry protective role of eliminating mitochondrial genomes with bulky lesions by way of excessive compaction and removal damaged genomes from the in vivo pool, however extensive additional studies that would go well beyond the experiments described in this paper are needed to fill the gap between this set of results and the proposed explanations.

Reviewer #2 (Public review):

Summary:

The manuscript by Chen et al addresses an important aspect of pathogenesis for mycobacterial pathogens, seeking to understand how bacterial effector proteins disrupt the host immune response. To address this question the authors sought to identify bacterial effectors from M. tuberculosis (Mtb) that localize to the host nucleus and disrupt host gene expression as a means of impairing host immune function. Their revised manuscript has strengthened their observations by performing additional experiments with BCG strains expressing tagged MgdE.

Strengths:

The researchers conducted a rigorous bioinformatic analysis to identify secreted effectors containing mammalian nuclear localization signal (NLS) sequences, which formed the basis of quantitative microscopy analysis to identify bacterial proteins that had nuclear targeting within human cells. The study used two complementary methods to detect protein-protein interaction: yeast two-hybrid assays and reciprocal immunoprecipitation (IP). The combined use of these techniques provides strong evidence of interactions between MgdE and SET1 components and suggests the interactions are in fact direct. The authors also carried out rigorous analysis of changes in gene expression in macrophages infected with MgdE mutant BCG. They found strong and consistent effects on key cytokines such as IL6 and CSF1/2, suggesting that nuclear-localized MgdE does in fact alter gene expression during infection of macrophages. The revised manuscript contains additional biochemical analyses of BCG strains expressing tagged MgdE that further supports their microscopy findings.

Reviewer #2 (Public review):

This manuscript examines how disease-associated hyperphosphorylation disrupts tau's role as a cooperative microtubule-binding regulator of intracellular transport. Using in vitro reconstitution assays and live-cell imaging in iPSC-derived neurons, the authors employ phosphomutant tau constructs (E14 to mimic hyperphosphorylation, AP to prevent phosphorylation) at 14 disease-associated residues to isolate phosphorylation effects independent of expression system-dependent PTM heterogeneity. The results show that hyperphosphorylated tau fails to form cooperative envelope-like structures on microtubules, instead binding diffusely and dissociating rapidly. In contrast, wild-type and phospho-resistant tau form cohesive envelopes that regulate motor protein access. At the single-molecule level, hyperphosphorylation reduces KIF5C inhibition while maintaining or enhancing KIF1A inhibition through altered processivity and detachment rates. In live neurons, hyperphosphorylated tau phenocopies tau knockout conditions, weakening tau-mediated inhibition of lysosome transport and increasing processive motility. The authors quantify tau binding using Gaussian mixture model-based image analysis and measure tau kinetics via FRAP, demonstrating that hyperphosphorylation-induced loss of cooperative binding correlates with dysregulated organelle transport. These findings establish a mechanism by which phosphorylation-driven disruption of tau's gatekeeper function on microtubules compromises axonal transport prior to aggregation in tauopathies. The paper provides interesting new knowledge for the field, but there are outstanding concerns that could be further addressed by the authors to strengthen and clarify the current manuscript:

(1) Lack of Phosphatase-Treated Control and Explicit WT Phosphorylation Quantification

Wild-type tau expressed in insect and mammalian cells is known to be phosphorylated by endogenous kinases (eg, GSK3, CDK5, MARK). The manuscript acknowledges this in the Discussion but provides no phosphatase-treated lysate control or quantification of endogenous phosphorylation on WT tau via phospho-specific Western blots. This leaves ambiguity about whether observed differences between WT and E14 reflect purely the introduced mutations or confounding baseline differences in phosphostate content.

(2) Limited Normalization of Motor Effects to Measured Tau Lattice Occupancy

Although kinesin trajectories are classified inside vs. outside tau envelopes (inherently normalizing to local tau density), motor parameters are not systematically reported as functions of tau fluorescence intensity across all constructs. Co-purifying MAPs or microtubule-modifying enzymes in cell lysates is not quantified or excluded, leaving residual uncertainty about tau-specificity of observed motor inhibition. This should be at least acknowledged in the results section.

(3) Insufficient Citation of Prior Neuronal Tau Envelope Evidence

In the Introduction, the authors state, "it was an open question if tau forms envelopes in neurons," but this understates existing evidence. Tan et al. (2019) report tau neuronal staining consistent with envelope formation, while Siahaan et al. (2021) provide more direct evidence in non-neuronal cells. The framing should acknowledge and integrate these prior findings.

(4) Unclear Wording on Expression System-Dependent Phosphorylation

The sentence "The phosphostate of tau is strongly dependent on the expression system" requires rewording. It is ambiguous whether this refers to the final phosphostate achieved after expression or the inherent phosphorylating capacity of each system. Clearer language would strengthen the methodological justification.

(5) Insufficient Quantification of Motor and Lysosome Transport Effect Magnitudes in Results Section

The data on molecular motor motility and lysosome transport are densely described. The magnitude of effects (fold-changes, percentage differences) should be explicitly stated in the Results section when first presenting findings to orient readers to biological significance. For example, effect magnitudes for lysosome run lengths, velocities, and directional bias should be quantified in text, not left to figure inspection.

(6) Incomplete Discussion of Projection Domain Necessity for Envelope Formation

The Discussion states the projection domain is "a critical regulator of both tau-tau and tau-microtubule interactions," but does not engage with prior domain dissection work. Tan et al. (2019) found that the entire projection domain is not necessary for envelope formation in vitro. The authors should discuss which projection domain regions are specifically regulated by phosphorylation vs. required for cooperativity, providing a more nuanced interpretation than implied by their current framing.

Reviewer #2 (Public review):

Summary:

To discover peptides that interact with autophagy-related protein LC3B and profile the key binding determinants, the authors screened a library of ~500,000 36-residue peptides derived from the human proteome using bacterial cell-surface display. Analysis of the screening data revealed exceptions to the reported LIR motif and a strong preference for negatively charged residues adjacent to the LIR.<br /> These results support a refinement of the LIR motif definition and expand the network of candidate LC3B interaction partners.

Strengths:

High-throughput approach.

Weaknesses:

Lack of in vitro data and molecular dynamics simulations.

Reviewer #2 (Public review):

Summary:

In this paper, the authors have characterized Rv2577 as a Fe3+/Zn2+ -dependent metallophosphatase and a nucleomodulin protein. The authors have also identified His348 and Asn359 as critical residues for Fe3+ coordination. The authors show that the proteins encode for two nuclease localization signals. Using C-terminal Flag expression constructs, the authors have shown that MmpE protein is secretory. The authors have prepared genetic deletion strains and show that MmpE is essential for intracellular survival of M. bovis BCG in THP-1 macrophages, RAW264.7 macrophages and mice model of infection. The authors have also performed RNA-seq analysis to compare the transcriptional profiles of macrophages infected with wild type and mmpE mutant strain. The relative levels of ~ 175 transcripts were altered in mmpE mutant infected macrophages and majority of these were associated with various immune and inflammatory signalling pathways. Using these deletion strains, the authors proposed that MmpE inhibits inflammatory gene expression by binding to the promoter region of vitamin D receptor. The authors also showed that MmpE arrests phagosome maturation by regulating the expression of several lysosome associated genes such as TFEB, LAMP1, LAMP2 etc. These findings reveal a sophisticated mechanism by which a bacterial effector protein manipulates gene transcription and promotes intracellular survival.

Strength:

The authors have used a combination of cell biology, microbiology and transcriptomics to elucidate the mechanisms by which Rv2577 contributes to intracellular survival.

Weakness:

The authors should thoroughly check the mice data and show individual replicate values in bar graphs.

Comments on revisions:

Thanks to the authors for addressing the concerns raised during the review of the original manuscript. The data is now presented with clarity, and discrepancies in mouse experiments have also been addressed with additional experiments.

Reviewer #3 (Public review):

Summary:

Metabolic dysfunction associated liver disease (MASLD) describes a spectrum of progressive liver pathologies linked to life style-associated metabolic alterations (such as increased body weight and elevated blood sugar levels), reaching from steatosis over steatohepatitis to fibrosis and finally end stage complications, such as liver failure and hepatocellular carcinoma. Treatment options for MASLD include diet adjustments, weight loss, and the receptor-β (THR-β) agonist resmetirom, but remain limited at this stage, motivating further studies to elucidate molecular disease mechanisms to identify novel therapeutic targets.

In their present study, the authors aim to identify early molecular changes in MASLD linked to obesity. To this end, they study a cohort of 109 obese individuals with no or early-stage MASLD combining measurements from two anatomic sides: 1. bulk RNA-sequencing and metabolomics of liver biopsies, and 2. metabolomics from patient blood. Their major finding is that GTPase-related genes are transcriptionally altered in livers of individuals with steatosis with fibrosis compared to steatosis without fibrosis.

Major comments:

(1) Confounders (such as (pre-)diabetes)

The patient table shows significant differences in non-MASLD vs. MASLD individuals, with the latter suffering more often from diabetes or hypertriglyceridemia. Rather than just stating corrections, subgroup analyses should be performed (accompanied with designated statistical power analyses) to infer the degree to which these conditions contribute to the observations. I.e., major findings stating MASLD-associated changes should hold true in the subgroup of MASLD patients without diabetes/of female sex and so forth (testing for each of the significant differences between groups).

Post-rebuttal update: The authors have performed the requested sub-group analysis and find the gene signatures hold for the non-diabetic sub-cohort, but not the diabetic subgroup. They denote a likely interaction between fibrosis and diabetes, that was not corrected for in the original analysis.

Post-post-rebuttal update: I thank the authors for having added Figure 5-figure supplement 2 to show this analysis.

(2) External validation

Additionally, to back up the major GTPase signature findings, it would be desirable to analyze an external dataset of (pre)diabetes patients (other biased groups) for alternations in these genes. It would be important to know if this signature also shows in non-MASLD diabetic patients vs. healthy patients or is a feature specific to MASLD. Also, could the matched metabolic data be used to validate metabolite alterations that would be expected under GTPase-associated protein dysregulation?

Post-rebuttal update: The authors confirm that with the present data, insulin resistance cannot be fully ruled out as a confounder to the GTP-ase related gene signature. They however plan future mouse model experiments to study whether the GTPase-fibrosis signature differs in diabetic vs. non-diabetic conditions.

(3) 3D liver spheroid MASH model, Fig. 6D/E

This 3D experiment is technically not an external validation of GTPase-related genes being involved in MASLD, since patient-derived cells may only retain changes that have happened in vivo. To demonstrate that the GTPase expression signature is specifically invoked by fibrosis the LX-2 set up is more convincing, however, the up-regulation of the GTPase-related genes upon fibrosis induction with TGF-beta, in concordance with the patient data, needs to be shown first (qPCR or RNA-seq). Additionally, the description of the 3D model is too uncritical. The maintenance of functional PHHs is a major challenge (PMID: 38750036, PMID: 21953633, PMID: 40240606, PMID: 31023926). It cannot be ruled out that their findings are largely attributable to either 1) the (other present) mesenchymal cells (i.e., mesenchyme-derived cells, such as for example hepatic stellate cells, not to be confused with mesenchymal stem cells, MSCs), or 2) related to potential changes in PHHs in culture, and these limitations need to be stated.

Post-rebuttal update: To address the concern of other cells than hepatocytes contributing to the observed effects in culture, the authors performed TGF-beta treatment in independent mono-cultures (Figure R4): LX-2 and hepatocytes, and the spheroid system. Surprisingly, important genes highlighted in Figure 6E for the spheroid system (RAB6A, ARL4A, RAB27B, DIRAS2) are all absent from this qPCR(?) validation experiment. The authors evaluate instead RAC1, RHOU, VAV1, DOCK2, RAB32. ­In spheroids, RHOU and RAB32 are down-regulated with TGF-B. In hepatocytes DOCK2 and RAC seemed up-regulated. They find no difference in these genes in LX-2 cells. Surprisingly, ACTA2 expression values are missing for LX-2 cells. Together, it is hard to judge which individual cell type recapitulates the changes observed in patients in this validation experiment, as the major genes called out in Figure 6E are not analyzed.

Post-post-rebuttal update: I thank the authors for having added Figure 6-figure supplement 5 to show qPCR results for this question.

Unfortunately, the 3D liver spheroid model used (as presente­d in PMID39605182) lacks important functional validation tests of maintained hepatocyte identity in culture (at the very least Albumin expression and secretion plus CYP3A4 assay). This functional data (acquired at the time point in culture when the RNA expression analysis in 6E was performed) is indispensable prior to stating that mature hepatocytes cause the observed effects.

Post-post-rebuttal update: I thank the authors for having added more references, I still think a quick functional validation of the system (at the time point in culture when the RNA expression analysis in 6E was performed) would be beneficial.

(4) Novelty / references

Similar studies that also combined liver and blood lipidomics/metabolomics in obese individuals with and without MASLD (e.g. PMID 39731853, 39653777) should be cited. Additionally, it would benefit the quality of the discussion to state how findings in this study add new insights over previous studies, if their findings/insights differ, and if so, why.

Post-rebuttal update: The authors have included the studies into their discussion.

Overall post-post-rebuttal update: I thank the authors for having added more data, important discussion points, and references, and have no further requests.

Reviewer #2 (Public review):

Summary:

This paper uses an optogenetic approach to either activate or inhibit separate neural pathways projecting to the ventral CA1 hippocampal subregion, from either CA3 or the entorhinal cortex. The authors report that manipulation of the vCA3→vCA1 pathway affected behavioural performance on a number of tasks: elevated plus maze, open field, Vogel conflict test and freezing behaviour to both context and a trace CS cue. In contrast, optogenetic manipulation of neural activity in the EC→vCA1 pathway only affected behaviour on the trace CS/context fear memory test but had no effect on the elevated plus maze, open field or Vogel conflict test. The authors suggest different roles for these two ventral hippocampal pathways in fear versus anxiety.

Strengths:

This is an interesting study addressing an important question in a highly topical subject area. The experiments are well conducted and have generated interesting and important data.

Weaknesses:

While I am broadly sympathetic to the overall narrative of the paper, I have some questions/comments around the specific interpretation of the results presented. In my view, the authors' claims may not be completely supported by their data, but the data are interesting nonetheless.

In terms of the framework presented by the authors for interpreting their data, many would argue that freezing (or at least reduced activity/behavioural inhibition) to the context provides a readout of conditioned anxiety rather than fear. In this sense, the context is a signal of potential threat (i.e. the context becomes associated with both shock and with the absence of shock) and thus generates anxiety rather than fear. Likewise, the trace CS cue could be considered as an ambiguous predictor of shock in that the shock doesn't occur straight away. In contrast, a punctate CS cue which co-terminates with shock would be a reliable signal of imminent threat and thus generates a fear response. Thus, it might be argued that all of the assays adopted by the authors are readouts of anxiety (albeit comprising tests of both conditioned and unconditioned anxiety). For example, from the authors' perspective, it is not clear a priori why the Vogel conflict test is considered anxiety, but contextual freezing is considered fear? Indeed, in the Discussion, the authors mention another study in which the data from the Vogel conflict test align with fear assays rather than anxiety tests. Can the authors elaborate on their distinction? I appreciate that, in practice, it might be difficult to distinguish between fear and anxiety at the behavioural level in rodents (although opposing effects of fear and anxiety on pain responses might be one option). At the very least, this issue merits further discussion.

Another question is whether rather than representing a qualitative difference between the contributions of the vCA3→vCA1 and EC→vCA1 pathways to different aspects of fear/anxiety behaviours, the different results reflect a quantitative difference between the magnitude of effects in vCA1 that are generated from optogenetic manipulation of the two pathways, coupled with the possibility that behaviour on the trace CS/context fear memory task is more sensitive to manipulation than the "anxiety tests". The possibility that vCA3→vCA1 stimulation is more effective is potentially supported by the c-fos measurements in vCA1. vCA3→vCA1 stimulation produced a much bigger vCA1 c-fos response (approx. 350% c-fos cell activation; see Figure 1E) compared to activation of the EC→vCA1 pathway (approx. 170% c-fos cell activation; see Figure 4E).

Furthermore, in some studies, there seem to be quite large differences between the laser OFF conditions for the different groups (which presumably one would not expect to be different). For example, compare laser OFF for the Inhibition group for time in open arms of EPM in Figure 5C (> 40%) versus laser OFF for the Inhibition group for time in open arms of EPM in Fig. 2C (< 20%). This could potentially result in ceiling effects, such that it is very hard to see a further increase in time in the open arms from a level already above 40% when the laser is then switched on. This could complicate the interpretation of the laser ON condition.

Likewise, there is a big difference between the behavioral performance of the two SHAM groups in Figure 3 (compare SHAM in 3 B, C and SHAM in 3 D, E). How is this explained? Could this generate a ceiling effect? This may also merit some discussion. More details on the SHAM procedure(s) in the main manuscript may also be helpful.

According to Figure 3A, the test of freezing response to the trace Tone CS is conducted in a different context from the conditioning context. The data presented in Figure 3 for tone fear are the levels of freezing during the presentation of this cue in the different contexts. It would be important to present both pre-CS and CS freezing levels here to determine how much of the freezing is actually driven by the punctate tone CS. The pre-CS freezing levels in this different context would also provide a nice control for the contextual fear conditioning.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors identify Leiomodin-1 (LMOD1) as a key regulator of early myogenic differentiation, demonstrating its interaction with SIRT1 to influence SIRT1's cellular localization and gene expression. The authors propose that LMOD1 translocates SIRT1 from the nucleus to the cytoplasm to permit the expression of myogenic differentiating genes such as MYOD or Myogenin.

Strengths:

A major strength of this work lies in the robust temporal resolution achieved through a time-course mass spectrometry analysis of in vitro muscle differentiation. This provides novel insights into the dynamic process of myogenic differentiation, often under explored in terms of temporal progression. The authors provide a strong mechanistic case for how LMOD1 exerts its role on muscle differentiation which opens avenues to modulate.

Weaknesses:

In the revised manuscript, the authors begin to translate their in vitro findings to an in vivo context by examining SIRT1 expression across a regeneration time course (Fig. 4I). They observe an increase in SIRT1 expression concomitant with LMOD1, supporting a potential role for SIRT1 in myogenic differentiation. Future studies will be required to provide deeper mechanistic insight into SIRT1 function in vivo.

Discussion:

Overall, the study emphasizes the importance of understanding the temporal dynamics of molecular players during myogenic differentiation and provides valuable proteomic data that will benefit the field. Future studies should explore whether LMOD1 modulates the nuclear-cytoplasmic shuttling of other transcription factors during muscle development and how these processes are mechanistically achieved. Investigating whether LMOD1 can be therapeutically targeted to enhance muscle regeneration in contexts such as exercise, aging, and disease will be critical for translational applications. Additionally, elucidating the interplay among LMOD1, LMOD2, and LMOD3 could uncover broader implications for actin cytoskeletal regulation in muscle biology. The authors have nicely updated their discussion.

Reviewer #2 (Public review):

This manuscript by Carmona, Zagotta, and Gordon is generally well-written. It presents a crude and incomplete structural analysis of the voltage-gated proton channel based on measured FRET distances. The primary experimental approach is Förster Resonance Energy Transfer (FRET), using a fluorescent probe attached to a noncanonical amino acid. This strategy is advantageous because the noncanonical amino acid likely occupies less space than conventional labels, allowing more effective incorporation into the channel structure.

Fourteen individual positions within the channel were mutated for site-specific labeling, twelve of which yielded functional protein expression. These twelve labeling sites span discrete regions of the channel, including P1, P2, S0, S1, S2, S3, S4, and the dimer-connecting coiled-coil domain. FRET measurements are achieved using acridon-2-ylalanine (Acd) as the acceptor, with four tryptophan or four tyrosine residues per monomer serving as donors. In addition to estimating distances from FRET efficiency, the authors analyze full FRET spectra and investigate fluorescence lifetimes on the nanosecond timescale.

Despite these strengths, the manuscript does not provide a clear explanation of how channel structure changes during gating. While a discrepancy between AlphaFold structural predictions and the experimental measurements is noted, it remains unclear whether this mismatch arises from limitations of the model or from the experimental approach. No further structural analysis is presented to resolve this issue or to clarify the conformational states of the protein.

The manuscript successfully demonstrates that Acd can be incorporated at specific positions without abolishing channel function, and it is noteworthy that the reconstituted proteins function as voltage-activated proton channels in liposomes. The authors also report reversible zinc inhibition of the channel, suggesting that zinc induces structural changes in certain channel regions that can be reversed by EDTA chelation. However, this observation is not explored in sufficient depth to yield meaningful mechanistic insight.

Overall, while the study introduces an interesting labeling strategy and provides valuable methodological observations, the analysis appears incomplete. Additional structural interpretation and mechanistic insight are needed.

Major Points

(1) Tryptophan and tyrosine exhibit similar quantum yields, but their extinction coefficients differ substantially. Is this difference accounted for in your FRET analysis? Please clarify whether this would result in a stronger weighting of tryptophan compared to tyrosine.

(2) Is the fluorescence of acridon-2-ylalanine (Acd) pH-dependent? If so, could local pH variations within the channel environment influence the probe's photophysical properties and affect the measurements?

(3) Several constructs (e.g., K125Tag, Y134Tag, I217Tag, and Q233Tag) display two bands on SDS-PAGE rather than a single band. Could this indicate incomplete translation or premature termination at the introduced tag site? Please clarify.

(4) In Figure 5F, the comparison between predicted FRET values and experimentally determined ratio values appears largely uninformative. The discussion on page 9 suggests either an inaccurate structural model or insufficient quantification of protein dynamics. If the underlying cause cannot be distinguished, how do the authors propose to improve the structural model of hHV1 or better describe its conformational dynamics?

(5) Cu²⁺, Ru²⁺, and Ni²⁺ are presented as suitable FRET acceptors for Acd. Would Zn²⁺ also be expected to function as an acceptor in this context? If so, could structural information be derived from zinc binding independently of Trp/Tyr?

(6) The investigated structure is most likely dimeric. Previous studies report that zinc stabilizes interactions between hHV1 monomers more strongly than in the native dimeric state. Could this provide an explanation for the observed zinc-dependent effects? Additionally, do the detergent micelles used in this study predominantly contain monomers or dimers?

(7) hHV1 normally inserts into a phospholipid bilayer, as used in the reconstitution experiments. In contrast, detergent micelles may form monolayers rather than bilayers. Could the authors clarify the nature of the micelles used and discuss whether the protein is expected to adopt the same fold in a monolayer environment as in a bilayer?

Reviewer #2 (Public review):

Summary:

The paper by Stephens and co-workers provides important mechanistic insight into how hyaluronan synthase (HAS) coordinates alternating GlcNAc and GlcA incorporation using a single Type-I catalytic centre. Through cryo-EM structures capturing both "proofreading" and fully "inserted" binding poses of UDP-GlcA, combined with detailed biochemical analysis, the authors show how the enzyme selectively recognizes the GlcA carboxylate, stabilizes substrates through conformational gating, and requires a priming GlcNAc for productive turnover.

These findings clarify how one active site can manage two chemically distinct donor sugars while simultaneously coupling catalysis to polymer translocation.

The work also reports a DDM-bound, detergent-inhibited conformation that possibly illuminates features of the acceptor pocket, although this appears to be a purification artefact (it is indeed inhibitory) rather than a relevant biological state.

Overall, the study convincingly establishes a unified catalytic mechanism for Type-I HAS enzymes and represents a significant advance in understanding HA biosynthesis at the molecular level.

Strengths:

There are many strengths.

This is a multi-disciplinary study with very high-quality cryo-EM and enzyme kinetics (backed up with orthogonal methods of product analysis) to justify the conclusions discussed above.

Comments on revisions:

The suggestions made in the initial comments have all been responded to very well.

Reviewer #3 (Public review):

This manuscript presents a macroevolutionary approach to identification of novel high-level antibiotic resistance determinants that takes advantage of the natural genetic diversity within a genus (mycobacteria, in this case) by comparing antibiotic resistance profiles across related bacterial species and then using computational, molecular, and cellular approaches to identify and characterize the distinguishing mechanisms of resistance. The approach is contrasted with "microevolutionary" approaches based on comparing resistant and susceptible strains of the same species and approaches based on ecological sampling that may not include clinically relevant pathogens or related species. The potential for new discoveries with the macroevolution-inspired approach is evident in the diversity of drug susceptibility profiles revealed amongst the selected mycobacterial species and the identification and characterization of a new group of rifamycin-modifying ADP-ribosyltransferase (Arr) orthologs of previously described mycobacterial Arr enzymes. Additional findings that intra-bacterial antibiotic accumulation does not always predict potency within this genus, that M. marinum is a better proxy for M. tuberculosis drug susceptibility than the commonly used saprophyte M. smegmatis, and that susceptibility to semi-synthetic antibiotic classes is generally less variable than susceptibility to antibiotics more directly derived from natural products strengthen the claim that the macroevolutionary lens is valuable for elucidating general principles of susceptibility within a genus.

There are some limitations to the work. The argument for the novelty of the approach could be better articulated. While the opportunities for new discoveries presented by identification of discrepant susceptibility results between related species is evident, it is less clear how the macroevolutionary approach is further leveraged for the discovery of truly novel resistance mechanisms. The example of the discovery of Arr-X enzymes presented here relied upon foundational knowledge of previously characterized Arr orthologs. There is less clarity about what the pipeline would look like for discovery of previously unknown determinants when one is agnostic to putative mechanisms. From the point at which interspecies differences in susceptibility are noted, does the framework still remain distinct from other discovery frameworks and approaches?

While the experimentation and analyses performed are generally well designed and rigorous, there are a few instances in which broad claims are based on inferences from sample sets or data sets that are, at present, too limited to provide robust support. For example, the claim that rifampicin modification, and precisely ADP-ribosylation, is the dominant mechanism of resistance to rifampicin in mycobacteria is still a bit premature or at least an over-generalization, as other enzymatic modification mechanisms and other mechanisms such as helR-mediated dissociation of rifampicin-stalled RNA polymerases, efflux, etc were not examined. CRISPR interference was used in a demonstrative example to support this assertion, but would need to be applied more systematically to be more conclusive. The general claim that intra-bacterial antibiotic accumulation does not predict potency in mycobacteria may be another over-generalization based on the limited set of drugs and species studied.

Comments on revisions:

Discussion, lines 321-323: "We found that resistance to these antibiotics in mycobacteria do not correlate with by uptake/efflux mechanisms in the species tested..." is an over-generalization and conflicts with the following statement on lines 199-201: "for BDQ we could observe some correlation between antibiotic potency and [BDQ]IB which could be indicative of efflux playing a role in antibiotic efficacy. Given that the current statement in the Discussion only applies to 2 of 3 drugs tested, a more specific or nuanced interpretation seems warranted.

Reviewer #2 (Public review):

Summary:

In this manuscript, submitted to Review Commons (journal agnostic), Coward and colleagues report on the role of insulin/IGF axis in podocyte gene transcription. They knocked out both the insulin and IGFR1 mice. Dual KO mice manifested a severe phenotype, with albuminuria, glomerulosclerosis, renal failure and death at 4-24 weeks.

Long read RNA sequencing was used to assess splicing events. Podocyte transcripts manifesting intron retention were identified. Dual knock-out podocytes manifested more transcripts with intron retention (18%) compared wild-type controls (18%), with an overlap between experiments of ~30%.

Transcript productivity was also assessed using FLAIR-mark-intron-retention software. Intron retention w seen in 18% of ciDKO podocyte transcripts compared to 14% of wild-type podocyte transcripts (P=0.004), with an overlap between experiments of ~30% (indicating the variability of results with this method). Interestingly, ciDKO podocytes showed downregulation of proteins involved in spliceosome function and RNA processing, as suggested by LC/MS and confirmed by Western blot.

Pladienolide (a spliceosome inhibitor) was cytotoxic to HeLa cells and to mouse podocytes but no toxicity was seen in murine glomerular endothelial cells.

The manuscript is generally clear and well-written. Mouse work was approved in advance. The four figures are generally well-designed, bars/superimposed dot-plots.

Methods are generally well described.

Comments on revised version:

Coward and colleagues have done an excellent job of responding to all the reviewer comments.

Reviewer #3 (Public review):

Summary:

The authors revisit the role of DR6 in axon degeneration following physical injury (Wallerian degeneration), examining both its effects on axons and its role in regulating the Schwann cell response to injury. Surprisingly, and in contrast to previous studies, they find that DR6 deletion does not delay the rate of axon degeneration after injury, suggesting that DR6 is not a mediator of this process.

Overall, this is a valuable study. As the authors note, the current literature on DR6 is inconsistent, and these results provide useful new data and clarification. This work will help other researchers interpret their own data and re-evaluate studies related to DR6 and axon degeneration.

Strengths:

(1) The use of two independent DR6 knockout mouse models strengthens the conclusions, particularly when reporting the absence of a phenotype.

(2) The focus on early time points after injury addresses a key limitation of previous studies. This approach reduces the risk of missing subtle protective phenotypes and avoids confounding results with regenerating axons at later time points after axotomy.

Comments on revisions:

I thank the authors for their thorough responses to my previous comments. The revisions have addressed the points raised and have improved the clarity and overall quality of the manuscript. I appreciate the effort taken to strengthen the presentation of the work.

Reviewer #2 (Public review):

Summary:

In this study, the authors set out to determine how a contact-dependent bacterial antagonistic system contributes to the ability of specific bacterial strains to persist within a complex, native gut community derived from wild animals. Rather than focusing on simplified or artificial models, the authors aimed to examine this system in a biologically realistic setting that captures the ecological complexity of the gut environment. To achieve this, they combined controlled laboratory experiments with animal colonization studies and sequencing-based tracking approaches that allow individual strains and mobile genetic elements to be followed over time.

Strengths:

A major strength of the work is the integration of multiple complementary approaches to address the same biological question. The use of defined but complex communities, together with in vivo experiments, provides a strong ecological context for interpreting the results. The data consistently show that the antagonistic system is not required for initial establishment but plays a critical role in long-term strain persistence. This insight that moves beyond traditional invasion-based views of microbial competition. The observation that transferable genetic elements can confer only temporary advantages, and may impose longer-term costs depending on community context, adds important nuance to current understanding of microbial fitness.

Weaknesses:

Overall, there is not a lack of evidence, but a deliberate trade-off between ecological realism and mechanistic resolution, which leaves some causal pathways open to interpretation.

Reviewer #2 (Public review):

Summary:

The manuscript by Aranaz-Novaliches describes a study of Tent5a knockout (KO) mice. The authors demonstrate a severe enamel phenotype in these mice, characterized by hypoplastic enamel with markedly disturbed organization of enamel rods. Additionally, they report that Amelx expression is reduced in the mutant compared to wild type (WT) at both mRNA and protein levels. The authors also examine the distribution and co-localization of Amelx and Ambn in ameloblasts and the enamel matrix. These findings are novel and provide important insights into the role of polyadenylation in regulating enamel matrix protein translation and its downstream effects on protein trafficking, secretion, and enamel formation. However, I have multiple concerns regarding the data and its analysis that need to be addressed.

Specific comments:

(1) Introduction

The structure of the introduction is unconventional. The first sentence of the third paragraph states that the goal of this study is to investigate the role of TENT5A in enamel formation, but the rest of the paragraph focuses on enamel in general. The following paragraph claims that the authors discovered the effects of Tent5a deficiency on enamel formation for the first time, yet most of the paragraph discusses enamel proteins and amelogenesis. The choice of references is problematic. The authors cite Sire et al. (2007), which focuses on the origin and evolution of enamel mineralisation genes, a poor fit for this context. A more appropriate source would be a recent review, e.g., Lacruz R et al., Physiol Rev. 2017;97(3):939-993. Ambn constitutes ~5% of the enamel matrix, not 10%. Reference 16 (Martin) is not ideal for murine enamel; more detailed studies exist, e.g., Smith CE et al., J Anat. 2019;234(2):274-290. References on protein-protein interactions (17-19) are also off: Wald et al. studied Ambn-Ambn and Amelx-Amelx interactions separately; Fang et al. focused on Amelx self-assembly only; Kawasaki and Weiss addressed gene evolution. The authors should cite work from Moradian-Oldak's lab, which clearly demonstrates Amelx-Ambn interactions. The last paragraph contains confusing statements, e.g., "TENT5a localized in rER promotes the expression of AmelX and other secreted protein transcripts." Also, the manuscript does not convincingly show disruption of self-assembly beyond overall enamel disorganization.

(2) Results

(a) microCT

Quantitative microCT analyses of WT and KO enamel are needed. At a minimum, enamel thickness and density should be measured from at least three biological replicates per genotype. Severe malocclusion in KO mice is not discussed. The mandibular incisor appears abraded, while the maxillary incisor is overgrown. Is maxillary enamel as affected as mandibular? The age of the mice is not specified. High-resolution scans of isolated mandibular incisors described in Materials and Methods should be included.

(b) SEM

The term "disorganized crystal structure" is incorrect - SEM cannot reveal crystal structure. This requires electron/X-ray diffraction or vibrational spectroscopy. Likely, the authors meant disorganized rods and interrod enamel. The phrase "weak HAP composition" is unclear. Can the increase in interprismatic matrix volume and reduction in rod diameter be quantified? Since rods are secreted by distal Tomes' processes and interrod by proximal Tomes' processes, an imbalance may indicate alterations in the ameloblast secretory apparatus. TEM studies of demineralized incisors are recommended to assess ameloblast ultrastructure.

(c) EMP expression

There is a discrepancy between WB images and data in Figure S2a. In Figure 2b, Amelx band is stronger than Ambn (expected, as Amelx is ~20× more abundant), but in Figure S2a, Ambn appears higher. How was protein intensity in Fig. S2a calculated? Optical density? Was normalization applied? Co-localization in Figure 2d was performed on LS8 cells, which lack a true ameloblast phenotype. Amelx expression in LS8 cells is ~2% of actin (Sarkar et al., 2014), whereas in murine incisors, it is ~600× higher than actin (Bui et al., 2023). Ambn signal is weaker than Amelx, which may affect co-localization results.

(d) Splicing products in Figure 2e

All isoforms except one contain exon 4. The major functional splice product of Amelx lacks exon 4 (Haruyama et al. J Oral Biosci. 2011;53(3):257-266), and there are some indications that the presence of exon 4 can lead to enamel defects. Can it be that the observed phenotype is due to the presence of exon 4?

(e) Co-localization studies

The presented co-localization studies do not demonstrate self-assembly defects; they reflect enamel microstructural defects observed by SEM. Self-assembly occurs at the nanoscale and cannot be assessed by light microscopy except with advanced optical methods. Conclusions based on single images are weak. The authors should perform experiments at least on three biological replicates per genotype, quantify results (e.g., total gray values per ROI of equal pixel size), and use co-localization metrics such as Mander's coefficient. Claims about alternative secretory pathways require much stronger evidence.

The authors should avoid implying that mRNA is inside the ER lumen. It is likely associated with the outer rER surface, which is expected. The resolution of the methods used is insufficient to confirm ER lumen localization.

DOI: 10.1016/j.celrep.2026.116971

Resource: None

Curator: @areedewitt04

SciCrunch record: RRID:ZFIN_ZDB-ALT-040601-2

What is this?

DOI: 10.1016/j.celrep.2026.116971

Resource: None

Curator: @areedewitt04

SciCrunch record: RRID:ZFIN_ZDB-ALT-120828-2

What is this?

Reviewer #2 (Public review):

Summary:

The authors studied cognitive control and attention in response to mnemonic prediction errors (MPEs): situations in which the external reality violates internal memory-based predictions. The behavioral task first established strong versus weak predictions, and then either confirmed or violated these predictions. The authors examined markers of cognitive control (frontal theta) and attention (posterior alpha suppression, pupil response) while strong and weak predictions were confirmed or violated. They found increased cognitive control (frontal theta) for strong MPEs, which correlated with subsequent memory. Markers of attention (alpha suppression, pupil response) also accompanied strong MPEs but did not correlate with subsequent memory. Pupil response was investigated using an interesting approach that decomposes the response into different components, finding that different components respond earlier or later and show different correlations with MPEs and their strength. The authors also investigated how EEG, reaction time, and pupil responses correlated with one another, providing further insight into the mechanism underlying the response to MPEs. Together, the study points toward multiple control and attention mechanisms involved in MPE response and memory.

Strengths:

The study has a clear behavioral paradigm with multiple measures - behavioral, EEG, and pupillometry that offer an investigation into different aspects of MPE response and memory.

The study is also very comprehensive in looking at multiple phases in processing MPEs: the prediction phase (prior to the violation), the response to MPEs, and subsequent memory of MPEs, all within one study. Specifically, the link between neural mechanisms and subsequent memory is a major advancement, as most prior studies did not include this component. Mechanisms underlying subsequent memory of MPEs are theoretically important, as a primary function of MPEs is to promote learning and memory. As the authors mention, the different neural and pupillary signals are not robustly correlated, suggesting multiple mechanisms underlying MPE detections, which is interesting, offers avenues for future research, and can facilitate a better theory of how MPEs are processed in the brain. Finally, the decomposition of pupil response into different components and their correlation with behavior (RT during match/MPE detection) is interesting.

Weaknesses:

The methods are rigorous, and the claims are mostly supported by the data, but there are a few weaknesses or places that could be improved:

(1) The authors conduct PCA analysis to identify different components of the pupillary response to MPE and relate them to behavior. Specifically, the authors identify components PC3 and PC4, which they interpret as related to MPE. However, some parts of the interpretation could be clearer or better justified:

(a) The authors refer to PC4 as "post-decision cognitive processing". But, given that RT was between .5-.7s, and PC3 peaked after more than 1s, wouldn't it be cautious to interpret PC3 as post-decision as well?

(b) MPEs overall elicit longer RTs in this study, suggesting that long RT is a behavioral marker of MPE. Nonetheless, the authors argue on p. 12: "Altogether, these findings indicate that when stronger mnemonic predictions (as indexed by shorter RTs) were violated." And, PC3 is correlated with shorter RTs for mismatches, meaning that behaviorally, these trials were more similar to matches. Thus, how do the authors interpret shorter versus longer RTs for MPEs, and what processes do these RT reflect?

(2) The brain to pupil relationship (p. 13-14): If I understand correctly, this was done on a trial-by-trial basis, but the high temporal resolution allows doing the analysis in a time-resolved manner - does brain activity at a certain time point preceding/following the pupil response correlate with the pupil response? It might be that cognitive control influences attention mechanisms or vice versa (because there is some overlap in the response). Although not testing causality, this temporally resolved correlation would be an interesting way to start probing how signals might influence each other.

(3) The relationships the authors find between brain measures and pupil components were largely not specific to mismatches/matches. However, are they specific to this task? I think it would benefit the paper to show that these relationships are potentially specific to making match/mismatch memory decisions, versus, e.g., any stimulus processing. For example, the authors could run the same analyses locked to stimuli in the study phase, anticipating a different pattern, if indeed these findings are specific to the associative memory task.

(4) During memory retrieval (i.e., before the probe), the authors find that frontal theta, a marker of cognitive control, was associated on a trial-by-trial basis with more posterior alpha (i.e., less alpha suppression, potentially reflecting less attention), and that this association was stronger for weaker predictions. The authors interpreted this as weaker predictions necessitating more cognitive control, and that more cognitive control was recruited specifically in trials where retrieval included less content (memory reinstatement) to attend to. Generally, cognitive control is recruited to facilitate memory retrieval. If so, one possible interpretation is that this correlation reflects cognitive control effort that has failed to produce enough memory reinstatement. The other possibility is that this correlation reflects more specific retrieval of the correct probe, without retrieval of interfering items (i.e., overall less content). I believe that the former explanation predicts that this correlation would be associated with longer RTs (more difficult decisions), while the latter predicts shorter RTs (easier decisions due to successful retrieval), at least for matches.

(5) In section 3, the authors found a positive relationship between alpha during memory retrieval and PC3 during MPE. If I understood correctly, this means that less attention during retrieval (less suppression) is correlated with a stronger PC3 response. How do the authors interpret this? Maybe along the same lines as in (5), specifically retrieving the correct information (i.e., less retrieved content to attend to) means a stronger prediction, leading to a stronger MPE, and a stronger MPE response, as reflected by PC3?

(6) The results with subsequent memory are important and address a major gap in the field that largely did not relate neural effects of MPE to subsequent memory. However, one major limitation of the study is that the authors did not test memory for matches. I understand the logic of avoiding testing matches. Because matches were repeated more times in the study, it's not a fair comparison, and could change participants' overall criterion for old/new decisions. However, one possibility would have been to test only the weak prediction; this could have given some specificity to the neural subsequent memory findings.

(7) The authors nicely characterized the different PC of pupillary MPE response. But, with respect to subsequent memory, they only present pupil size. Unless there is some methodological reason that prevents testing subsequent memory on the PC, I think this will be very informative about the potential mechanisms underlying memory of MPE.

(8) This paper includes many interesting findings, and I am not sure how they all come together into a cohesive mechanistic understanding of MPE response and subsequent memory. I think the paper would benefit from either a conceptual mechanism figure or, in the Discussion, have a summary of a proposed mechanism integrating the findings together.

(9) Relatedly, the section "Immediate, strength-sensitive neurocognitive impacts of MPEs" does not link the arguments to specific data points, so it's hard to follow which data specifically the authors are interpreting.

(10) If I understand correctly, the authors did not find improved memory for strong compared to weak MPE. First, I think this behavioral result should be incorporated in the main paper and in the interpretation of the results. Second, given that the neural effects the authors tested either correlated with memory for strong MPE or did not show a relationship with memory, what neural/pupil response could explain memory for weak MPE?

Reviewer #2 (Public review):

Summary:

The manuscript proposes interesting synaptic plasticity rules grounded in experimental data. Its main features are:

(1) plasticity depends on local calcium concentration driven by presynaptic activity and is independent of somatic action potentials,

(2) the rules incorporate metaplasticity, and (3) they demonstrate how a single neuron could address the feature-binding problem at the dendritic level.

The work extends a previous study (https://doi.org/10.7554/eLife.97274.2), to which the author also contributed.

The author models two calcium thresholds (LTP/LTD) from two different calcium sources (NMDA/VGCC), and these thresholds are flexible (metaplasticity rule, similar to BCM), which is claimed to be necessary for successful learning of both FBP and NFBP (linear and nonlinear feature binding problem with 1 or 2 patterns). The role of each threshold seems to be opposite and complementary. One extra condition has been added: an upper threshold for LTP. This threshold serves to stop synaptic strengthening once synapses are strong enough to evoke a plateau. With that, synapses are not strengthened to the maximal value, avoiding strong supralinear integration for irrelevant patterns.

Strengths:

The current model implements not only local synaptic plasticity but also metaplasticity and solves the FBP at the dendrite level. Another strong aspect of the model is that metaplasticity in the LTD threshold protects strengthened synapses from weakening. In this way, as the author mentioned, metaplasticity is able to protect learned patterns from being forgotten or weakened and prevent irrelevant patterns from being stored. This is a nice modelling example of metaplasticity being helpful in preventing the catastrophic interference or forgetting (as has been explicitly discussed in a recent article https://doi.org/10.1016/j.tins.2022.06.002 ). The author might want to briefly mention or emphasize this aspect of the model, which might be interesting also for the AI community.

Weaknesses:

(1) What is novel in the current paper as compared to Khodadadi et al. eLife 2025? That is not completely clear and should be made clearer. Is it only a minor difference related to the fact that the new learning rule has metaplasticity in both calcium thresholds and is simpler? This seems to be just an incremental increase in knowledge/methods. Can the author defend his paper against this point from the „devil's advocate"? How is the conclusion of the author in the abstract that „metaplasticity in both thresholds is necessary" reconcilable with his previous publication (Khodadadi et al. eLife 2025), in which only metaplasticity in one threshold was successful in solving the nonlinear feature binding problem?

(2) As far as I can judge without testing the model, metaplasticity causes thresholds to monotonically increase during systematic pattern presentation, which stabilizes weights and allows pattern separation. Due to the closed-loop nature of the current implementation, where metaplasticity only happens if plasticity happens, this also effectively locks patterns in place. However, flexible learning is an essential mechanism for survival. Imagine a mutation event takes place and bananas suddenly become red and/or strawberries turn yellow. It seems that the current model would be unable to adapt to these new patterns even if rewards were to be shifted. While out of the scope of the study, due to its importance, I feel that pattern shifting/relearning should at least be briefly discussed. How could the model be improved to allow relearning?

Reviewer #2 (Public review):

Summary:

This manuscript reports the application of a combined targeted therapeutic approach to gastric cancer treatment. The RTK, FGFR2 and the phosphatase, SHP2 are targeted with existing drugs; AZD457 and SHP099, respectively. Having shown increased mRNA levels of FGFR2 and SHP2 in a patient population and highlighted the issue of resistance to single therapies the combination of inhibitors is shown to reduce cancer-related signalling in two gastric cell lines. The efficacy of the dual therapy is further demonstrated in a single patient case study and mouse xenograft models. Finally, the rationale for SHP2 inhibition is shown to be linked to immune response.

Strengths:

The data is generally well presented, and the study invokes a novel patient data set which could have wider value. The study provides additional evidence to support the combined therapeutic approach of RTK and phosphatase inhibition.

Weaknesses:

Combined therapy approaches targeting RTKs and SHP2 have been widely reported. Indeed, SHP099 in combination with FGFR inhibitors has been shown to overcome adaptive resistance in FGFR-driven cancers. Furthermore, the inhibition of SHP2 has been documented to have important implications in both targeting proliferative signalling as well as immune response. Thus, it is difficult to see novelty or a significant scientific advance in this manuscript. Although the data is generally well presented, there is inconsistency in the interpretation of the experimental outcomes from ex vivo, patient and mouse systems investigated. In addition, the study provides only minor or circumstantial understanding of the dual mechanism.

Using data from a 161 patient cohort FGFR2 was identified as displaying amplification of FGFR2 in ~6% with concomitant elevation of mRNA of patients which correlated with PTPN11 (SHP2) mRNA expression. The broader context of this data is of value and could add a different patient demographic to other data on gastric cancer. However, there is no detail on patient stratification or prior therapeutic intervention.

Comments on revisions: This has been attended to in the revised version

In SNU16 and KATOIII cells the combined therapy is shown to be effective and appears to be correlated with increase apoptotic effects (i.e. not immune response).

Fig 2E suggests that the combined therapy in SNU16 cells is little better than FGFR2-directed AZD457 inhibitor alone, particularly at the higher dose.

The individual patient case study described via Fig 3 suggests efficacy of the combined therapy (at very high dosage), however the cell biopsies only show reduced phosphorylation of ERK, but not AKT. This is at odds with the ex vivo cell-based assays. Thus, it is not clear how relevant this study is.

The mouse xenograft study shows a convincing reduction in tumor mass/volume and a clear reduction in pAKT, whilst pERK remains largely unaffected by the combined therapeutic approach. This is in conflict with the previous data which seems to show the opposite effect.

Comments on revisions: The authors have clarified this point

In all, the impact of the dual therapy is unclear with respect to the two pathways mediated by ERK and AKT.

Finally, the authors demonstrate the impact of SHP2 on PD-1 expression and propose that the SHP099/AZD4547 combination therapy significantly induces the production of IFN-γ in CD8+ T cells. This part of the study is unconvincing and would benefit from an investigation of the tumor micro-environment to assess T cell infiltration.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors combined coarse-grained structure-based model simulation, optical tweezer experiments, and AI-based analysis to assess the knotting behavior of the TrmD-Tm1570 protein. Interestingly, they found that while the structure-based model can fold the single knot from TrmD and Tm1570, the double-knot protein TrmD-Tm1570 cannot form a knot itself, suggesting the need for chaperone proteins to facilitate this knotting process. This study has strong potential to understand the molecular mechanism of knotted proteins, supported by many experimental and simulation evidence. However, there are a few places that appear to lack sufficient details, and more clarification in the presentation is needed.

Strengths:

A combination of both experimental and computational studies. The authors have addressed my questions in their revised manuscript. I appreciate their efforts.

Reviewer #2 (Public review):

Summary:

This is a mechanistic study that provides new insights into the inhibition of SARS-CoV-2 Mpro.

Strengths:

The identification of dimer interface stabilization/destabilization as distinct inhibitory mechanisms and the discovery of C300 as a potential allosteric site for ebselen are important contributions to the field. The experimental approach is modern, multi-faceted, and generally well-executed.

Weaknesses:

The primary weaknesses relate to linking the biophysical observations more directly to functional enzymatic outcomes and providing more quantitative rigor in some analyses. While the study is overall strong, addressing its weaknesses and limitations would elevate the impact and translational relevance of the current manuscript.

(1) Correlation with Functional Activity:

The most significant gap is the lack of direct enzymatic activity assays under the exact conditions used for MS and HDX. While EC50 values are listed from literature, demonstrating how the observed dimer stabilization (by peptidomimetics) or dimer disruption (by ebselen) directly correlates with inhibition of proteolytic activity in the same experimental setup would solidify the functional relevance of the biophysical observations. For instance, does the fraction of monomer measured by native MS quantitatively predict the loss of activity? Also, the single inhibitor concentration used in each MS experiment needs to be specified in the main text and legends. A discussion on whether the inhibitor concentrations required to observe these dimerization effects (in native MS) or structural dynamics (in HDX-MS) align with EC50 values would be helpful for contextualizing the findings.

(2) For the two Cys residues found to be targeted by ebselen, what are their respective modification stoichiometry related to the ebselen concentration? Especially for the covalent binding site C300, which is proposed in this study to represent a novel allosteric inhibition mechanism of ebselen, more direct experimental evidence is needed to support this major hypothesis. Does mutation or modification of C300 affect the Mpro dimerization/monomer equilibrium and alter the enzymatic activity? If ebselen acts as a covalent inhibitor linked to multiple Cys, why is its activity only in the uM range?

(3) For the allosteric inhibitor pelitinib with low-uM activity, no significant differences in deuterium uptake of Mpro were observed. In terms of the binding affinity, what is the difference between pelitinib and ebselen? Some explanations could be provided about the different HDX-MS results between the two non-peptidomimetic inhibitors with similar activities.

(4) Native MS Quantification:

The analysis of monomer-dimer ratios from native MS spectra appears qualitative or semi-quantitative. A more rigorous and quantified analysis of the percentage of dimer/monomer species under each condition, with statistical replicates, would strengthen the equilibrium shift claims. For native MS analysis of each inhibitor, the representative spectrum can be shown in the main figure together with quantified dimer/monomer fractions from replicates to show significance by statistical tests.

(5) Changes of HDX rates in certain regions seem very subtle. For example, as it states 'residues 296-304 in the C-terminal region of M pro were more flexible upon ebselen binding (Figure 4c)', the difference is barely observable. The percentage of HDX rate changes between two conditions (with p values) can be specified in the text for each fragment discussed, and any change below 5% or 10% is negligible.

Reviewer #2 (Public review):

Summary:

The authors conducted a brain-wide survey of Avp (arginine vasopressin) and its Avpr1a gene expression in the mouse brain using RNAscope, a high-resolution in situ hybridization method. Overall, the findings are useful and important because they identify brain regions that express the Avpr1a transcript. A comprehensive overview of Avpr1a expression in the mouse brain could be highly informative and impactful. The authors used RNAscope (a proprietary in situ hybridization method) to assess transcript abundance of Avp and one of its receptors, Avpr1a. The finding of Avp-expressing cells outside the hypothalamus and the extended amygdala is novel and is nicely demonstrated by new photomicrographs in the revised manuscript. The Avpr1a data suggest expression in numerous brain regions. In the revised manuscript, reworked figures make the data easier to interpret.

Strengths:

A survey of Avpr1a expression in the mouse brain is an important tool for exploring vasopressin function in the mammalian brain and for developing hypotheses about cell- and circuit-level function.

[Editors' note: The authors have substantially addressed all the reviewers' concerns and comments.]

Reviewer #2 (Public review):

This is an interesting study that shows that mRNA acetylation at synapses is dynamically regulated at synapses by spatial memory in the mouse hippocampus. The dynamic changes of ac4C-mRNAs regulated by memory were validated by methods including ac4C dot-blot and liquid 13 chromatography-tandem mass spectrometry (LC-MS/MS).

Reviewer #2 (Public review):

Summary:

The authors performed a genetic screen using deficiency lines and identified Uev1a as a factor that protects nurse cells from RasG12V-induced cell death. According to a previous study from the same lab, this cell death is caused by aberrant mitotic stress due to CycA upregulation (Zhang et al.). This paper further reveals that Uev1a forms a complex with APC/C to promote proteasome-mediated degradation of CycA.

In addition to polyploid nurse cells, the authors also examined the effect of RasG12V-overexpression in diploid germline cells, where RasG12V-overexpression triggers active proliferation not cell death. Uev1a was found to suppress its overgrowth as well.

Finally, the authors show that the overexpression of the human homolog, UBE2V1 and UBE2V2, suppresses tumor growth in human colorectal cancer xenografts and cell lines. Notably, these genes' expression correlates with the survival of colorectal cancer patients carrying Ras mutation.

Strength:

This paper presents a significant finding that UBE2V1/2 may serve as a potential therapy for cancers harboring Ras mutations. The authors propose a fascinating mechanism in which Uev1a forms a complex with APC/C to inhibit aberrant cell cycle progression.

Comments on revisions:

The authors have addressed several of the major concerns, including the addition of new data and improved figure presentation. However, some issues remain insufficiently resolved, particularly regarding control reuse (Major Comment 3) and experimental interpretation (Major Comments 5 and 8).

Regarding Major Comment 5, the authors state that UAS copy number affects the frequency of egg chamber degradation in Fig. 2D, and thus explains the reduced phenotype in RasG12V + GFP-RNAi compared to RasG12V alone. However, this explanation is not consistent with other data in the manuscript. UAS-RasG12V combined with UAS-lacZ in Fig. 2G shows a phenotype comparable to UAS-RasV12 alone, despite also increasing the UAS copy number. This suggests that the effect is not simply due to copy number.

I understand that the authors used UAS-RasG12V + GFP-RNAi as a control for the RNAi experiments and UAS-RasG12V + lacZ for the overexpression experiments. I suggest examining the phenotype frequency of UAS-RasG12V + UAS-GFP, to figure the reason out. Overall, these results indicate that there is a spectrum of phenotype frequencies, and therefore appropriate controls should be included for each experiment rather than reusing the same dataset across different experiments, as also noted in Major Comment 3.

Reviewer #2 (Public review):

Summary:

The authors performed bioinformatic analyses to trace the genomic history of the clinically relevant pT181 plasmid. Specifically, they:

(1) tracked the presence of pT181 across different S. aureus strain backgrounds through time. It was first found in one, later multiple strains, though this may reflect changes in sampling over time.

(2) estimated the mutation rate of the chromosome and plasmid.

(3) estimated the plasmid copy number of pT181, and found that it decreased over time. The latter was supported by two sets of statistical analyses, first showing that the number of single-copy isolates increased over time, and second, that the multicopy isolates demonstrated a lower PCN over time.

(4) reported the different integration sites at which pT181 integrated into the genome.

As a caveat, they mentioned that identical plasmid sequences have variable plasmid copy numbers across different genomes in their dataset.

Strengths:

This is a very solid, well-considered bioinformatic study on publicly available data. I greatly appreciate the thoughtful approach the authors have taken to their subject matter, neither over- nor underselling their results. It is a strength that the authors focussed on a single plasmid in a single bacterial species, as it allowed them to take into account unique knowledge about the biology of this system and really dive deep into the evolution of this specific plasmid. It makes for a compelling case study. At the same time, I think the introduction and discussion can be strengthened to demonstrate what lessons might be drawn from this case study for other plasmids.

Weaknesses:

The finding that the pT181 copy number declined over time is the most interesting claim of the paper to me, and not something that I have seen done before. While the authors have looked at some confounders in this analysis, I think this could be strengthened further in a revision.

For the flow of the storyline, I also think the estimation of mutation rates (starting L181) and integration into the chromosome (starting L255) could be moved to the supplement or a later position in the main text.

Clearly, the use of publicly available data prevents the authors from controlling the growth and sequencing conditions of the isolates. It is striking that they observe a clear signal in spite of this, but I would have loved to see more discussion of the metadata that came with the publicly available sequences and even more use of that metadata to control for confounding.

Reviewer #2 (Public review):

Summary:

This manuscript studies the impacts of knocking out a protein known to be involved in synapse maturation in mice, measuring their ability to hunt prey items (and to discriminate simple visual patterns) under binocular and monocular viewing conditions. The main results are that the mice with this protein knocked out are impaired when performing visual tasks with binocular viewing, but are actually better when they perform monocularly. The interpretation is that the knocked-out protein has affected binocular visual integration.

Strengths:

Overall, the attempt to connect a protein to behavior/perception, via known mechanistic effects on synapse development and visual critical periods, is admirable.

The use of multiple visual conditions and behavioral paradigms (binocular/monocular, cricket hunting/orientation discrimination, light/dark) strengthens and enriches the results.

Weaknesses:

The primary interpretation - that binocular integration is affected in the PSD-95 knockouts- is not supported by the behavioral evidence. Using behavior to isolate a particular stage in visual processing (and further, to distinguish it from elements of generating the behavioral response and/or acquiring the visual information in the first place) is notoriously difficult. Such attempts are, of course, the domain of psychophysics. In fact, the most classical and loveliest success is in the domain of binocular integration- Bela Julesz's "psychoanatomy" that used random dot stereograms to isolate stereoscopic computations.

I mention this example because it is, in fact, directly relevant to my primary concern about the evidence used as support for the favored interpretation here. Julesz's stimuli were extremely clever in isolating binocular mechanisms (i.e., binocular mechanisms MUST be used to perform the task), and any perceptual/behavioral reports are very straightforward to interpret (i.e., a stereoscopically-defined shape can be identified, or not).

Now compare this to the work described in this manuscript. KO (knockout) mice are worse than wild types at chasing prey items or at moving towards a rewarded orientation, but they get better when performing this task monocularly. No argument that that is an interesting bit of scientific phenomenology to characterize. However, the behaviors do not require binocular integration, the freely-moving paradigms involve a variety of gaze and body-movement strategies, and the metrics used to quantify performance are similarly high-dimensional. Bottom line, it is not possible to glean whether the KO's intriguing binocular-vs-monocular differences are due to binocular integration per se, or something better thought of as fundamentally sensorimotor in origin. The tasks do not isolate visual from sensorimotor processing, and the behaviors and associated metrics cannot definitely adjudicate between a multitude of possible specific interpretations.

More specifically, the KO mice may have abnormal patterns of binocular coordination. Eye movements were not tracked in these studies, despite the availability of such instrumentation and their successful application in many preceding studies of mouse prey capture. If the KO mice do not coordinate their eye movements (in task-specific/task-relevant ways), they might receive binocular input that is abnormal. Under monocular conditions, that mismatched or inappropriately coordinated binocular input is absent, which would relieve them of the confusing visual information. That is rather different than having an impairment of binocular integration, as it is basically a question of whether the visual system is impaired, or whether the inputs to the visual system are abnormal due to differences in binocular coordination.

It is also possible that the binocular deficit, as measured in behavior,r occurs in a distinct part of the sensorimotor loop. Even if the binocular eye movements are normal, and binocular visual integration is normal, PSD-95 KO mice may be confused or distracted by the larger visual field that comes from binocular viewing (quite profound in species with mostly lateralized eyes). Such a "post-sensory" interpretation related to target selection (from what could be a totally normal visual representation) is difficult to rule out as well.

In summary, this reviewer appreciates the value of trying to connect this molecular mechanism to sensory processing and behavior. The use of naturalistic tasks and freely-moving paradigms is also something to commend. However, the sorts of visual stimuli and behavioral paradigms used here are not well-suited to supporting the rather specific interpretation that has been put forth in this manuscript.

Reviewer #2 (Public review):

Summary:

The basic helix-loop-helix transcription factor TCF4 (also known, as ITF2, SEF2, or E2-2) is a protein involved in the development and functioning of many different cell types. TCF4 plays important roles in the nervous system, both in health and disease. Its importance in the nervous system is underlined by its association with common and rare cognitive disorders. Specifically, variants of the TCF4 gene are implicated in increased susceptibility to schizophrenia, and mutations in the TCF4 gene cause Pitt-Hopkins syndrome (PTHS) or mild to moderate non-syndromic intellectual disability.

In this manuscript, the authors have studied whether reinstating TCF4 later in postnatal development in juvenile PTHS model mice could reverse behavioral phenotypes, thereby simulating gene therapy. Previous research by the same group has demonstrated that restoring TCF4 during embryonic or neonatal stages, corresponding to prenatal or neonatal periods in humans, improved phenotypes in a PTHS mouse model. In the current study, a conditional TCF4 reinstatement mouse model, Tcf4-lox-stop-lox (Tcf4-LSL), previously developed and characterized by their lab, where Cre-mediated recombination removes a floxed transcriptional stop cassette downstream of exon 17, leading to reinstatement of all TCF4 isoforms at appropriate levels in neurons, was used. The study showed that this later intervention failed to correct most phenotypes, suggesting that perinatal reinstatement of TCF4 holds the greatest potential to treat behavioral symptoms of PTHS. However, the study also suggests that some cognitive behaviors may still be responsive to TCF4 reinstatement later in life.

Strengths:

This is a very important study aimed at developing gene therapy for PTHS. The study is technically very well performed and written.

Weaknesses:

The only weakness is that a human disease is modelled in a mouse, which is evolutionarily not the closest mammal to humans. Hopefully, in the future, similar studies will also be performed in a nonhuman primate model, for example rhesus macaque.

Reviewer #2 (Public review):

Summary:

The authors derived a time-specific signature of reactogenicity from mouse muscle following exposure to vaccines /TLRs for capturing the reactogenicity patterns. They tested this reactogenicity signature in mouse blood, and then they applied the reactogenicity signature to human blood from subjects having received different vaccines. They identified biomarkers in mouse muscle which are also observed in mouse and human blood and could be used as a reactogenicity signature in mice, instead of CRP.

Strengths:

(1) The authors used transcriptomic response following vaccination and used common genes to human and mice for defining a reactogenic signature.

(2) As the authors used different formulations in mice, the model was trained across a broad reactogenicity spectrum, which has the advantage of being used for evaluating new vaccines/vaccine platforms.

Weaknesses:

(1) The muscle gene signature reflects local reactogenicity. Systemic reactogenicity is not specifically addressed, except where overlapping gene signatures are observed for both local and systemic reactogenicity.

(2) In the same logic, could we find additional genes in the blood which are not captured in the muscle?

(3) The peak of the reactogenicity is usually 24h; it is not certain that additional TPs have helped the findings. If they have, the authors should explain.