Reviewer #1 (Public review):

Summary:

Using a computational modeling approach based on the drift diffusion model (DDM) introduced by Ratcliff and McKoon in 2008, the article by Shevlin and colleagues investigates whether there are differences between neutral and negative emotional states in:

(1) The timings of the integration in food choices of the perceived healthiness and tastiness of food options between individuals with bulimia nervosa (BN) and healthy participants.

(2) The weighting of the perceived healthiness and tastiness of these options.

Strengths:

By looking at the mechanistic part of the decision process, the approach has the potential to improve the understanding of pathological food choices. The article is based on secondary research data.

Weaknesses:

I have two major concerns and a major improvement point.

The major concerns deal with the reliability of the results of the DDM (first two sections of the Results, pages 6 and 7), which are central to the manuscript, and the consistency of the results with regards to the identification of mechanisms related to binge eating in BN patients (i.e. last section of the results, page 7).

(1) Ratcliff and McKoon in 2008 used tasks involving around 1000 trials per participant. The Chen et al. experiment the authors refer to involves around 400 trials per participant. On the other hand, Shevlin and colleagues ask each participant to make two sets of 42 choices with two times fewer participants than in the Chen et al. experiment. Shevlin and colleagues also fit a DDM with additional parameters (e.g. a drift rate that varies according to subjective rating of the options) as compared to the initial version of Ratcliff and McKoon. With regards to the number of parameters estimated in the DDM within each group of participants and each emotional condition, the 5- to 10-fold ratio in the number of trials between the Shevlin and colleagues' experiment and the experiments they refer to (Ratcliff and McKoon, 2008; Chen et al. 2022) raises serious concerns about a potential overfitting of the data by the DDM. This point is not highlighted in the Discussion. Robustness and sensitivity analyses are critical in this case.

The authors compare different DDMs to show that the DDM they used to report statistical results in the main text is the best according to the WAIC criterion. This may be viewed as a robustness analysis. However, the other DDM models (i.e. M0, M1, M2 in the supplementary materials) they used to make the comparison have fewer parameters to estimate than the one they used in the main text. Fits are usually expected to follow the rule that the more there are parameters to estimate in a model, the better it fits the data. Additionally, a quick plot of the data in supplementary table S12 (i.e. WAIC as a function of the number of parameters varying by food type in the model - i.e. 0 for M0, 2 for M1, 1 for M2 and 3 for M3) suggests that models M1 and potentially M2 may be also suitable: there is a break in the improvement of WAIC between model M0 and the three other models. I would thus suggest checking how the results reported in the main text differ when using models M1 and M2 instead of M3 (for the taste and health weights when comparing M3 with M1, for τS when comparing M3 with M2). If the differences are important, the results currently reported in the main text are not very reliable.

(2) The second main concern deals with the association reported between the DDM parameters and binge eating episodes (i.e. last paragraph of the results section, page 7). The authors claim that the DDM parameters "predict" binge eating episodes (in the Abstract among other places) while the binge eating frequency does not seem to have been collected prospectively. Besides this methodological issue, the interpretation of this association is exaggerated: during the task, BN patients did not make binge-related food choices in the negative emotional state. Therefore, it is impossible to draw clear conclusions about binge eating, as other explanations seem equally plausible. For example, the results the authors report with the DDM may be a marker of a strategy of the patients to cope with food tastiness in order to make restrictive-like food choices. A comparison of the authors' results with restrictive AN patients would be of interest. Moreover, correlating results of a nearly instantaneous behavior (i.e. a couple of minutes to perform the task with the 42 food choices) with an observation made over several months (i.e. binge eating frequency collected over three months) is questionable: the negative emotional state of patients varies across the day without systematically leading patients to engage in a binge eating episode in such states.

I would suggest in such an experiment to collect the binge craving elicited by each food and the overall binge craving of patients immediately before and after the task. Correlating the DDM results with these ratings would provide more compelling results. Without these data, I would suggest removing the last paragraph of the Results.

(3) My major improvement point is to tone down as much as possible any claim of a link with binge eating across the entire manuscript and to focus more on the restrictive behavior of BN patients in between binge eating episodes (see my second major concern about the methods). Additionally, since this article is a secondary research paper and since some of the authors have already used the task with AN patients, if possible I would run the same analyses with AN patients to test whether there are differences between AN (provided they were of the restrictive subtype) and BN.

Reviewer #2 (Public review):

Summary:

Binge eating is often preceded by heightened negative affect, but the specific processes underlying this link are not well understood. The purpose of this manuscript was to examine whether affect state (neutral or negative mood) impacts food choice decision-making processes that may increase the likelihood of binge eating in individuals with bulimia nervosa (BN). The researchers used a randomized crossover design in women with BN (n=25) and controls (n=21), in which participants underwent a negative or neutral mood induction prior to completing a food-choice task. The researchers found that despite no differences in food choices in the negative and neutral conditions, women with BN demonstrated a stronger bias toward considering the 'tastiness' before the 'healthiness' of the food after the negative mood induction.

Strengths:

The topic is important and clinically relevant and methods are sound. The use of computational modeling to understand nuances in decision-making processes and how that might relate to eating disorder symptom severity is a strength of the study.

Weaknesses:

The sample size was relatively small and may have been underpowered to find differences in outcomes (i.e., food choice behaviors). Participants were all women with BN, which limits the generalizability of findings to the larger population of individuals who engage in binge eating. It is likely that the negative affect manipulation was weak and may not have been potent enough to change behavior. Moreover, it is unclear how long the negative affect persisted during the actual task. It is possible that any increases in negative affect would have dissipated by the time participants were engaged in the decision-making task.

Reviewer #3 (Public review):

Summary:

The study uses the food choice task, a well-established method in eating disorder research, particularly in anorexia nervosa. However, it introduces a novel analytical approach - the diffusion decision model - to deconstruct food choices and assess the influence of negative affect on how and when tastiness and healthiness are considered in decision-making among individuals with bulimia nervosa and healthy controls.

Strengths:

The introduction provides a comprehensive review of the literature, and the study design appears robust. It incorporates separate sessions for neutral and negative affect conditions and counterbalances tastiness and healthiness ratings. The statistical methods are rigorous, employing multiple testing corrections.

A key finding - that negative affect induction biases individuals with bulimia nervosa toward prioritizing tastiness over healthiness - offers an intriguing perspective on how negative affect may drive binge eating behaviors.

Weaknesses:

A notable limitation is the absence of a sample size calculation, which, combined with the relatively small sample, may have contributed to null findings. Additionally, while the affect induction method is validated, it is less effective than alternatives such as image or film-based stimuli (Dana et al., 2020), potentially influencing the results.

Another concern is the lack of clarity regarding which specific negative emotions were elicited. This is crucial, as research suggests that certain emotions, such as guilt, are more strongly linked to binge eating than others. Furthermore, recent studies indicate that negative affect can lead to both restriction and binge eating, depending on factors like negative urgency and craving (Leenaerts et al., 2023; Wonderlich et al., 2024). The study does not address this, though it could explain why, despite the observed bias toward tastiness, negative affect did not significantly impact food choices.

Reviewer #1 (Public review):

Summary:

Despite accumulating prior studies on the expressions of AVP and AVPR1a in the brain, a detailed, gender-specific mapping of AVP/AVPR1a neuronal nodes has been lacking. Using RNAscope, a cutting-edge technology that detects single RNA transcripts, the authors created a comprehensive neuroanatomical atlas of Avp and Avpr1a in male and female brains. The findings are important, given that: (1) a detailed, gender-specific mapping of AVP/AVPR1a neuronal nodes has been lacking, and (2) the study offers valuable new insights into Avpr1a expression across the mouse brain. The findings are solid, and with improved data presentation and analysis, this work could serve as an important resource for the neuroscience community.

Strengths:

This well-executed study provides valuable new insights into gender differences in the distribution of Avp and Avpr1a. The atlas is an important resource for the neuroscience community.

Weaknesses:

A few concerns remain to be addressed. The primary weakness of this manuscript lies in the robustness of its data presentation and analysis.

Reviewer #2 (Public review):

Summary:

The authors conducted a brain-wide survey of vasopressin and vasopressin receptor 1A gene expression in the mouse brain using a high-resolution in situ hybridization method called RNAscope. Overall, the findings are useful in identifying brain regions expressing Avpr1a transcript. The impact of findings is decreased by incomplete or inadequate data analysis due to limited description of Avpr1a mRNA distribution within brain regions and limited statistical inference. A comprehensive overview of Avpr1a expression in the mouse brain has the potential to be highly informative and impactful. The current manuscript used RNAscope (a proprietary method of in situ hybridization) to assess the transcript abundance of Avp (arginine vasopressin, a neuropeptide) and its receptor (Avpr1a). The style of graphs, limited use of photomicrographs, and low number of subjects all combine to limit the impact of the dataset. The finding of Avp-expressing cells outside of the hypothalamus and extended amygdala is poorly documented but would be novel. The Avpr1a data suggest expression in numerous brain regions. However, the data presented are difficult to interpret, with every value being an extremely small density value for a large swath of the brain. How many cells are impacted? Are puncta spread across many cells or only present in a few cells? Is density evenly distributed through a brain region or compacted into a subfield? For a descriptive study, there is minimal statistical inference and relatively little description. The authors make a case for the novel nature of the work but do not seem, at times, to recognize a robust literature developed over the last 50 years. In conclusion, the experimental data are important and informative; however, the low number of subjects, lack of statistical power, limited description of individual brain regions, and poor quality and design of data figures reduce the overall impact.

Strengths:

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

Weaknesses:

(1) The style and type of data presentation, focusing on the density of individual mRNA transcript across a whole brain region, seemed incomplete in so far as the data presentation did not provide a clear visualization of the distribution of Avpr1a-expressing cells or transcript itself. However, knowing which brain regions do express transcript is itself informative.

(2) The manuscript strongly emphases on the possibility of sex differences in Avp and Avpr1a expression. However, the low number of animals used does not provide adequate statistical power to make strong inferences regarding sex differences in the data.

(3) The manuscript's methods are minimal but adequate to understand data acquisition. The description of how quantitative analyses were conducted is inadequate and would be impossible to replicate beyond identifying the program used.

Reviewer #1 (Public review):

Summary:

The authors had previously found that brief social isolation could increase the activity of these neurons, and that manipulation of these neurons could alter social behavior in a social rank-dependent fashion. This manuscript explored which of the outputs were responsible for this, identifying the central nucleus of the amygdala as the key output region. The authors identified some discrete behavior changes associated with these outputs, and found that during photostimulation of these outputs, neuronal activity appeared altered in 'social response' neurons.

Strengths:

Rigorous analysis of the anatomy. Careful examination of the heterogenous effects on cell activity due to stimulation, linking the physiology with the behavior via photostimulation during recording in vivo.

Weaknesses:

(1) There are some clear imbalances in the sample size across the different regions parsed. The CeA has a larger sample size, likely in part to the previous work suggesting differential effects depending on social rank/dominance. Given the potential variance, it may be hard to draw conclusions about the impact of stimulation across different social ranks for other groups.

(2) It is somewhat unclear why only the 'social object ratio' was used to assess the effects versus more direct measurements of social behavior.

(3) Somewhat related, while it is statistically significant, it is unclear if the change seen in face investigation of biologically significant, on average, it looks like a few-seconds difference and that was not modulated by social rank.

(4) There are several papers studying these neurons that have explored behaviors examined here, as well as the physiological connectivity that are not cited that would provide important context for this work. In particular, multiple groups have found a dopamine-mediated IPSP in the BNST, in contrast to this work. There are technical differences that may drive these differences, but not addressing them is a major weakness.

(5) The inclusion of some markers for receptors for some of these outputs is interesting, and the authors suggest that this may be important, but this is somewhat disconnected from the rest of the work performed.

Reviewer #2 (Public review):

Summary:

The authors perform a series of studies to follow up on their previous work, which established a role for dorsal raphe dopamine neurons (DRN) in the regulation of social-isolation-induced rebound in mice. In the present study, Lee et. al, use a combination of modern circuit tools to investigate putatively distinct roles of DRN dopamine transporting containing (DAT) projections to the bed nucleus of the stria terminalis (BNST), central amygdala (CeA), and posterior basolateral amygdala (BLP). Notably, they reveal that optogenetic stimulation of distinct pathways confers specific behavioral states, with DRNDAT-BLP driving aversion, DRNDAT-BNST regulating non-social exploratory behavior, and DRNDAT-CeA promoting social ability. A combination of electrophysiological studies and in situ hybridization studies reveal heterogenous dopamine and neuropeptide expression and different firing properties, providing further evidence of pathway-specific neural properties. Lastly, the authors combine optogenetics and calcium imaging to resolve social encoding properties in the DRNDAT-CeA pathway, which correlates observed social behavior to socially engaged neural ensembles.

Collectively, these studies provide an interesting way of dissecting out separable features of a complex multifaceted social-emotional state that accompanies social isolation and the perception of 'loneliness.' The main conclusions of the paper provide an important and interesting set of findings that increase our understanding of these distinct DRN projections and their role in a range of social (e.g., prosocial, dominance), non-social, and emotional behaviors. However, as noted below, the examination of these circuits within a homeostatic framework is limited given that a number of the datasets did not include an isolated condition. The DRNDAT-CeA pathway was investigated with respect to social homeostatic states in the present study for some of the datasets.

Strengths:

(1) The authors perform a comprehensive and elegant dissection of the anatomical, behavioral, molecular, and physiological properties of distinct DRN projections relevant to social, non-social, and emotional behavior, to address multifaceted and complex features of social state.

(2) This work builds on prior findings of isolation-induced changes in DRN neurons and provides a working framework for broader circuit elements that can be addressed across the social homeostatic state.

(3) This work characterizes a broader circuit implicated in social isolation and provides a number of downstream targets to explore, setting a nice foundation for future investigation.

(4) The studies account for social rank and anxiety-like behavior in several of the datasets, which are an important consideration to the interpretation of social motivation states, especially in male mice with respect to dominance behavior.

Weaknesses:

(1) The conceptual framework of the study is based on the premise of social isolation and perceived 'loneliness' under the framework of social homeostasis, analogous to hunger. In this framework, social isolation should provoke an aversive state and compensatory social contact behavior. In the authors' prior work, they demonstrate synaptic changes in DRN neurons and social rebound following acute social isolation. Thus, the prediction would be that downstream projections also would show state-dependent changes as a function of social housing conditions (e.g., grouped vs. isolated). In the current paper, a social isolation condition was not included for the majority of the studies conducted (e.g., Figures 1-6 do not include an isolated condition, Figures 7-8 do include an isolated condition). Thus, while Figure 1-6 adds a very interesting and compelling set of data that is of high value to the social behavior field with respect to social and emotional processing and general circuit characterization, these studies do not directly investigate the impacts of dynamic social homeostatic state. The main claim of the paper, including the title (e.g., separable DRN projections mediate facets of loneliness-like state), abstract, intro, and discussion presents the claim of this work under the framework of dynamic social homeostatic states, which should be interpreted with caution, as the majority of the work in the paper did not include a social isolation comparison.

(2) In Figure 1, the authors confirm co-laterals in the BNST and CeA via anatomical tracing studies. The goal of the optogenetic studies is to dissociate the functional/behavioral roles of distinct projections. However, one limitation of optogenetic projection targeting is the possibility of back-propagating action potentials (stimulation of terminals in one region may back-propagate to activate cell bodies, and then afferent projections to other regions), and/or stimulation of fibers of passage. Therefore, one limitation in the dataset for the optogenetic stimulation studies is the possibility of non-specific unintended activation of projections other than those intended (e.g., DRNDAT-CeA). This can be dealt with by administering lidocaine to prevent back-propagating action potentials.

(3) It is unclear from the test, but in the subjects' section of the methods, it appears that only male animals were included in the study, with no mention of female subjects. It should be clear to the reader that this was conducted in males only if that is the case, with consideration or discussion, about female subjects and sex as a biological variable.

(4) Averaged data are generally reported throughout the study in the form of bar graphs, across most figures. Individual data points would increase the transparency of the data.

Reviewer #3 (Public review):

Summary:

The authors investigated the role of dopaminergic neurons (dopamine transporter expressing, DAT) in the dorsal raphe nucleus (DRN) in regulating social and affective behavior through projections to the central nucleus of the amygdala (CeA), bed nucleus of the stria terminalis (BNST), and the posterior subdivision of the basolateral amygdala. The largest effect observed was in the DRN-DAT projections to the CeA. Augmenting previously published results from this group (Matthews et al., 2016), the comprehensive behavioral analysis relative to social dominance, gene expression analysis, electrophysiological profiling, and in vivo imaging provides novel insights into how DRN-DAT projections to the CeA influence the engagement of social behavior in the contexts of group-housed and socially isolated mice.

Strengths:

Correlational analysis with social dominance is a nice addition to the study. The overall computational analyses performed are well-designed and rigorous.

Weaknesses:

(1) Analysis of dopamine receptor expression did not include Drd3, Drd4, or Drd5 which may provide more insights into how dopamine modulates downstream targets. This is particularly relevant to the BNST projection in which the densest innervation did not robustly co-localize with the expression of either Drd1 or Drd2. It is also possible that dopamine release from DRN-DAT neurons in any or all of these structures modulates neurotransmitter release from inputs to these regions that contain D2 receptors on their terminals.

(2) Although not the focus of this study, without pharmacological blockade of dopamine receptors, it is not possible to assess what the contribution of dopamine is to the behavioral outcomes. Given the co-release of glutamate and GABA from these neurons, it is possible that dopamine plays only a marginal role in the functional connectivity of DRN-DAT neurons. (

(3) Photostimulation parameters used during the behavioral studies (8 pulses of light delivered at 30 Hz for several minutes) could lead to confounding results limiting data interpretation. As shown in Figure 6J, 8 pulses of light delivered at 30 Hz result in a significant attenuation of the EPSC amplitude in the BLP and CeA projection. Thus, prolonged stimulation could lead to significant synaptic rundown resulting in an overall suppression of connectivity in the later stages of the behavioral analyses.

Reviewer #1 (Public review):

The authors investigated tactile spatial perception on the breast through discrimination, categorization, and direct localization tasks. They reach three main conclusions:

(1) The breast has poor tactile spatial resolution.<br /> This conclusion is based on comparing just noticeable differences, a marker of tactile spatial resolution, across four body regions, two on the breast. The data compellingly support the conclusion; the study outshines other studies on tactile spatial resolution that tend to use problematic measures of tactile resolution such as two-point-discrimination thresholds. The result will interest researchers in the field and possibly in other fields due to the intriguing tension between the finding and the sexually arousing function of touching the breast.

(2) Larger breasts are associated with lower tactile spatial resolution<br /> This conclusion is based on a strong correlation between participants' JNDs and the size of their breasts. The correlation convincingly supports the conclusion. It is of interest to the field, as it aligns with the hypothesis that nerve fibers are more sparsely distributed across larger body parts.

(3) The nipple is a landmark: perceptually a unit and an attractor for tactile percepts<br /> The data do not support these conclusions. The conclusion that the nipple is perceived as a unit is based on poor performance in tactile categorization for touches on the nipple. This categorization performance may simply mirror the breast's low tactile spatial resolution with JNDs about the size of a nipple.

The conclusion that tactile percepts are drawn towards the nipple is based on tactile localization biases towards the nipple for tactile stimuli on the breast compared to localization biases for tactile stimuli on the back. Currently, the statistical analysis of the data does not match the field, psychophysics, standards. Moreover, any bias towards the nipple could simply be another instance of regression to the mean of the stimulus distribution, given that the tested locations were centered on the nipple. This confound can only be experimentally solved by shifting the distribution of the tested locations. Finally, given that participants indicated the locations on a 3D model of the body part, further experimentation would be required to determine whether there is a perceptual bias towards the nipple or whether the authors merely find a response bias.

Further comments:

- Given that later analyses require regression models, the authors might consider using them throughout.

- The stability of the JND differences between body parts across subjects is already captured in the analysis of the JNDs; the ANOVA and the post-hoc testing would not be significant if the order were not relatively stable across participants. Thus, it is unclear why this is being evaluated again with reduced power due to improper statistics.

- The null hypothesis of an ANOVA is that at least one of the mean values is different from the others; adding participants as a factor does not provide evidence for similarity.

- The pairwise correlations between body parts seem to be exploratory in nature. Like all exploratory analyses, the question arises of how much potential extra insights outweigh the risk of false positives. It would be hard to generate data with significant differences between several conditions and not find any correlations between pairs of conditions. Thus, the a priori chance of finding a significant correlation is much higher than what a correction accounts for.

- If the JND at mid breast (measured with locations centered at the nipple) is roughly the same size as the nipple, it is not surprising that participants have difficulty with the categorical localization task on the nipple but perform better than chance on the significantly larger areola.

- To justify the conclusion that the nipple is a unit, additional data would be required. 1) One could compare psychometric curves with the nipple as the center and psychometric curves with a nearby point on the areola as the center. 2) Performance in the quadrant task could be compared for the nipple and an equally sized portion of the areola. Otherwise, the task "only" provides confirmatory evidence for a low tactile resolution in the midbreast area.

- A localization bias toward the nipple in this context does not show that the nipple is the anchor of the breast's tactile coordinate system. The result might simply be an instance of regression to the mean of the stimulus distribution (also known as experimental prior). To convincingly show localization biases towards the nipple, the tested locations should be centered at another location on the breast.

- Another problem is the visual salience of the nipple, even though Blender models were uniformly grey. With this type of direct localization, it is very difficult to distinguish perceptual from response biases even if the regression to the mean problem is solved. There are two solutions to this problem: 1) Varying the uncertainty of the tactile spatial information, for example, by using a pen that exerts lighter pressure. A perceptual bias should be stronger for more uncertain sensory information; a response bias should be the same across conditions. 2) Measure bias with a 2IFC procedure by taking advantage of the fact that sensory information is noisier if the test is presented before the standard.

- Neither signed nor absolute localization error can be compared to the results of the previous experiments. The JND should be roughly proportional to the variance of the errors.

- The statistically adequate way of testing the biases is a hierarchical regression model (LMM) with a distance of the physical location from the nipple as a predictor, and a distance of the reported location from the nipple as a dependent variable. Either variable can be unsigned or signed for greater power, for example, coding the lateral breast as negative and the medial breast as positive. The bias will show in regression coefficients smaller than 1.

- It does not matter whether distances are calculated based on skin or 3D coordinates, as Euclidean distances or based on polar coordinates. However, there should only be one consistent distance in the text across both independent and dependent variables. Calculating various versions of these measures can create issues in Frequentist Statistics. For transparency, it is good practice to report the results of other methods for calculating the distance in the supplement.

- The body part could be added as a predictor to the LMM, with differences in bias between the body parts showing a significant interaction between the two predictors. The figures suggest such an effect. However, the interpretation should take into account that 1) response biases are more likely to arise at the breast and 2) it might be harder to learn the range of locations on the back given that stimulation is not restricted to an anatomically defined region as it is the case for the breast.

Reviewer #2 (Public review):

The authors tested tactile acuity on the breast of females using several tasks and reported overall low acuity compared to the back, which is typically considered to have the worst acuity of all body parts. Moreover, there was evidence that acuity is worse the larger the breast; this finding mirrors similar findings for the hand and therefore suggests that the number of tactile sensors is fixed and must be distributed across a larger extent of skin when a body part is larger, thus resulting in comparably lower tactile acuity.

Strengths:

I find this an interesting paper with results that are relevant to the tactile community. The authors apply several tasks allowing them to link the paper with previous results. The methodology and psychophysical analysis are sound.

Weaknesses:

The analysis of localization error direction, with the result that the nipple area may be a landmark for tactile localization, is interesting and aligns the paper with some other recent papers that have suggested that such landmarks should exist. However, there are major issues with methodology and statistics, so that currently the conclusions are not supported.

In the following, line numbers refer to the re-formatted manuscript provided by the authors upon request and are mentioned for them to find the relevant passages faster.

(1) Comments on analysis of tactile acuity:

- I had a hard time understanding some parts of the report. What is meant by "broadly no relationship" in line 137?

- It is suggested that spatial expansion (which is correlated with body part size) is related between medial breast and hand - is this to say that women with large hands have large medial breast size? Nipple size was measured, but hand size was not measured, is this correct?

- It is furthermore unclear how the authors differentiate medial breast and NAC. The sentence in lines 140-141 seems to imply the two terms are considered the same, as a conclusion about NAC is drawn from a result about the medial breast. This requires clarification.

- Finally, given that the authors suspect that overall localization ability (or attention) may be overshadowed by a size effect, would not an analysis be adequate that integrates both, e.g. a regression with multiple predictors?

(2) Comments on analysis of "The nipple is a unit":

- Statistics in this section are not adequately described and may be partly false.

- In the paragraph about testing quadrants of the nipple, it is stated that only 3 of 10 participants barely outperformed chance with a p < 0.01. It is unclear how a significant t-test is an indication of "barely above chance".

- The final part of the paragraph on nipple quadrants (starting line 176) explains that there was a trend (4 of 10 participants) for lower tactile acuity being related to the inability to differentiate quadrants. It seems to me that such a result would not be expected: The stated hypothesis is that all participants have the same number of tactile sensors in their nipple and areola, independent of NAC size. In this section, participants determine the quadrant of a single touch. Theoretically, all participants should be equally able to perform this task, because they all have the same number of receptors in each quadrant of nipple and areola. Thus, the result in Figure 2C is curious.

(3) Comments on analysis of "Absolute localization on the breast is anchored to the nipple"

- Again, there are things that are unclear with the statistics and description of the analysis.

- This section reports an Anova (line 193/194) with a factor "participant". This doesn't appear sensible. Please clarify. The factor distance is also unclear; is this a categorical or a continuous variable? Line 400 implies a 6-level factor, but Anovas and their factors, respectively, are not described in methods (nor are any of the other statistical approaches).

- The analysis on imprecision using mean pairwise error (line 199) is unclear: does pairwise refer to x/y or to touch vs. center of the nipple?

- p8, upper text, what is meant by "relative over-representation of the depth axis"? Does this refer to the breast having depth but the equivalent area on the back not having depth? What are the horizontal planes (probably meant to be singular?) - do you simply mean that depth was ignored for the calculation of errors? This seems to be implied in Figure 3AB.

- Lines 232-241, I cannot follow the conclusions drawn here. First, it is not clear to a reader what the aim of the presented analyses is: what are you looking for when you analyze the vectors? Second, "vector strength" should be briefly explained in the main text. Third, it is not clear how the final conclusion is drawn. If there is a bias of all locations towards the nipple, then a point closer to the nipple cannot exhibit a large bias, because the nipple is close-by. Therefore, one would expect that points close to the nipple exhibit smaller errors, but this would not imply higher acuity - just less space for localizing anything. The higher acuity conclusion is at odds with the remaining results, isn't it: acuity is low on the outer breast, but even lower at the NAC, so why would it be high in between the two?

(4) Comments on the Discussion:

The discussion makes some concrete suggestions for sensors in implants (line 283). It is not clear how the stated numbers were computed. Also, why should 4 sensors nipple quadrants receive individual sensors if the result here was that participants cannot distinguish these quadrants?

Additional comments:

I would find it interesting to know whether participants with small breast measurement delta had breast acuity comparable to the back. Alternatively, it would be interesting to know whether breast and back acuity are comparable in men. Such a result would imply that the torso has uniform acuity overall, but any spatial extension of the breast is unaccounted for. The lowest single participant data points in Figure 1B appear similar, which might support this idea.

Reviewer #1 (Public review):

Summary:

The study explores the use of Transport-based morphometry (TBM) to predict hematoma expansion and growth 24 hours post-event, leveraging Non-Contrast Computed Tomography (NCCT) scans combined with clinical and location-based information. The research holds significant clinical potential, as it could enable early intervention for patients at high risk of hematoma expansion, thereby improving outcomes. The study is well-structured, with detailed methodological descriptions and a clear presentation of results. However, the practical utility of the predictive tool requires further validation, as the current findings are based on retrospective data. Additionally, the impact of this tool on clinical decision-making and patient outcomes needs to be further investigated.

Strengths

(1) Clinical Relevance: The study addresses a critical need in clinical practice by providing a tool that could enhance diagnostic accuracy and guide early interventions, potentially improving patient outcomes.

(2) Feature Visualization: The visualization and interpretation of features associated with hematoma expansion risk are highly valuable for clinicians, aiding in the understanding of model-derived insights and facilitating clinical application.

(3) Methodological Rigor: The study provides a thorough description of methods, results, and discussions, ensuring transparency and reproducibility.

Weaknesses:

(1) The limited sample size in this study raises concerns about potential model overfitting. While the reported AUCROC of 0.71 may be acceptable for clinical use, the robustness of the model could be further enhanced by employing techniques such as k-fold cross-validation. This approach, which aggregates predictive results across multiple folds, mimics the consensus of diagnoses from multiple clinicians and could improve the model's reliability for clinical application. Additionally, in clinical practice, the utility of the model may depend on specific conditions, such as achieving high specificity to identify patients at risk of hematoma expansion, thereby enabling timely interventions. Consequently, while AUC is a commonly used metric, it may not fully capture the model's clinical applicability. The authors should consider discussing alternative performance metrics, such as specificity and sensitivity, which are more aligned with clinical needs. Furthermore, evaluating the model's performance in real-world clinical scenarios would provide valuable insights into its practical utility and potential impact on patient outcomes.

(2) The authors compared the performance of TBM with clinical and location-based information, as well as other machine learning methods. While this comparison highlights the relative strengths of TBM, the study would benefit from providing concrete evidence on how this tool could enhance clinicians' ability to assess hematoma expansion in practice. For instance, it remains unclear whether integrating the model's output with a clinician's own assessment would lead to improved diagnostic accuracy or decision-making. Investigating this aspect-such as through studies evaluating the combined performance of clinician judgment and model predictions-could significantly enhance the tool's practical value.

Reviewer #2 (Public review):

Summary:

The author presents a transport-based morphometry (TBM) approach for the discovery of non-contrast computed tomography (NCCT) markers of hematoma expansion risk in spontaneous intracerebral hemorrhage (ICH) patients. The findings demonstrate that TBM can quantify hematoma morphological features and outperforms existing clinical scoring systems in predicting 24-hour hematoma expansion. In addition, the inversion model can visualize features, which makes it interpretable. In conclusion, this research has clinical potential for ICH risk stratification, improving the precision of early interventions.

Strengths:

TBM quantifies hematoma morphological changes using the Wasserstein distance, which has a well-defined physical meaning. It identifies features that are difficult to detect through conventional visual inspection (such as peripheral density distribution and density heterogeneity), which provides evidence supporting the "avalanche effect" hypothesis in hematoma expansion pathophysiology.

Weaknesses:

(1) As a methodology-focused study, the description of the methods section somewhat lacks depth and focus, which may make it challenging for readers to fully grasp the overall structure and workflow of the approach. For instance, the manuscript lacks a systematic overview of the entire process, from NCCT image input to the final prediction output. A potential improvement would be to include a workflow figure at the beginning of the manuscript, summarizing the proposed method and subsequent analytical procedures. This would help readers better understand the mechanism of the model.

(2) The description of the comparison algorithms could be more detailed. Since TBM directly utilizes NCCT images as input for prediction, while SVM and K-means are not inherently designed to process raw imaging data, it would be beneficial to clarify which specific features or input data were used for these comparison models. This would better highlight the effectiveness and advantages of the TBM method.

(3) The relatively small training and testing dataset may limit the model's performance and generalizability. Notably, while the study mentions that 1,066 patients from the ERICH dataset met the inclusion criteria, only 170 were randomly selected for the test set. Leveraging the full 1,066 ERICH cases for model training and internal validation might potentially enhance the model's robustness and performance.

(4) Some minor textual issues need to be checked and corrected, such as line 16 in the abstract "Incorporating these traits into a v achieved an AUROC of 0.71 ...".

(5) Some figures need to be reformatted (e.g., the x-axis in Figure 2 a is blocked).

Reviewer #1 (Public review):

Summary:

Govindan and Conrad use a genome-wide CRISPR screen to identify genes regulating retention of intron 4 in OGT, leveraging an intron retention reporter system previously described (PMID: 35895270). Their OGT intron 4 reporter reliably responds to O-GlcNAc levels, mirroring the endogenous splicing event. Through a genome-wide CRISPR knockout library, they uncover a range of splicing-related genes, including multiple core spliceosome components, acting as negative regulators of OGT intron 4 retention. They choose to follow up on SFSWAP, a largely understudied splicing regulator shown to undergo rapid phosphorylation in response to O-GlcNAc level changes (PMID: 32329777). RNA-sequencing reveals that SFSWAP depletion not only promotes OGT intron 4 splicing but also broadly induces exon inclusion and intron splicing, affecting decoy exon usage. While this study offers interesting insights into intron retention regulation and O-GlcNAc signaling, the RNA-Sequencing experiments lack essential controls needed to provide full confidence to the authors' conclusions.

Strengths:

(1) This study presents an elegant genetic screening approach to identify regulators of intron retention, uncovering core spliceosome genes as unexpected positive regulators of intron retention.<br /> (2) The work proposes a novel functional role for SFSWAP in splicing regulation, suggesting that it acts as a negative regulator of splicing and cassette exon inclusion, which contrasts with expected SR-related protein functions.<br /> (3) The authors suggest an intriguing model where SFSWAP, along with other spliceosome proteins, promotes intron retention by associating with decoy exons.

Weaknesses:

(1) The conclusions regarding SFSWAP's impact on alternative splicing rely on cells treated with a single pool of two siRNAs for five days. The absence of independent siRNA treatments raises concerns about potential off-target effects, which may reduce confidence in the observed SFSWAP-dependent splicing changes. Rescue experiments or using additional independent siRNA treatments would strengthen the conclusions.<br /> (2) The mechanistic role of SFSWAP in splicing would benefit from further exploration, though this may be more appropriate for future studies.

Comments on revisions:

The authors have addressed all my previous recommendations.

Reviewer #2 (Public review):

Summary:

The paper describes an effort to identify the factors responsible for intron retention and alternate exon splicing in a complex system known to be regulated by the O-GlcNAc cycling system. The CRISPR/Cas9 system was used to identify potential factors. The bioinformatic analysis is sophisticated and compelling. The conclusions are of general interest and advance the field significantly.

Strengths:

- Exhaustive analysis of potential splicing factors in an unbiased screen.<br /> - Extensive genome wide bioinformatic analysis.<br /> - Thoughtful discussion and literature survey

Weaknesses:

- No firm evidence linking SFSWA to an O-GlcNAc specific mechanism.<br /> - Resulting model leaves many unanswered questions.

Comments on revisions:

I think the authors have adequately dealt with the overall reviewer's comments.

Reviewer #3 (Public review):

Summary:

The major novel finding in this study is that SFSWAP, a splicing factor containing an RS domain but no canonical RNA binding domain, functions as a negative regulator of splicing. More specifically, it promotes retention of specific introns in a wide variety of transcripts including transcripts from the OGT gene previously studied by the Conrad lab. The balance between OGT intron retention and OGT complete splicing is an important regulator of O-GlcNAc expression levels in cells.

Strengths:

An elegant CRISPR knockout screen employed a GFP reporter, in which GFP is efficiently expressed only when the OGT retained intron is removed (so that the transcript will be exported from the nucleus to allow for translation of GFP). Factors whose CRISPR knockdown cause decreased intron retention therefore increase GFP, and these can be identified by sequencing RNA of GFP-sorted cells. SFSWAP was thus convincingly identified as a negative regulator of OGT retained intron splicing. More focused studies of OGT intron retention indicate that it may function by regulating a decoy exon previously identified in the intron, and that this may extend to other transcripts with decoy exons.

Weaknesses:<br /> The mechanism by which SFSWAP represses retained introns is unclear, although some data suggests it can operate (in OGT) at the level of a recently reported decoy exon within that intron. Interesting / appropriate speculation about possible mechanism are provided and will likely be the subject of future studies.

Overall the study is well done and carefully described.

Reviewer #1 (Public review):

Summary:

This study has preliminarily revealed the role of ACVR2A in trophoblast cell function, including its effects on migration, invasion, proliferation, and clonal formation, as well as its downstream signaling pathways.

Strengths:

The use of multiple experimental techniques, such as CRISPR/Cas9-mediated gene knockout, RNA-seq, and functional assays (e.g., Transwell, colony formation, and scratch assays), is commendable and demonstrates the authors' effort to elucidate the molecular mechanisms underlying ACVR2A's regulation of trophoblast function. The RNA-seq analysis and subsequent GSEA findings offer valuable insights into the pathways affected by ACVR2A knockout, particularly the Wnt and TCF7/c-JUN signaling pathways.

Weaknesses:

The current findings provide valuable insights into the role of ACVR2A in trophoblast cell function and its involvement in the regulation of migration, invasion, and proliferation, further validation in both in vitro and in vivo models would strengthen the conclusions. Additional techniques, such as animal models and more advanced clinical sample analyses, would help strengthen the conclusions and provide a more comprehensive understanding of the molecular pathways involved.

Reviewer #2 (Public review):

Summary:

ACVR2A is one of a handful of genes for which significant correlations between associated SNPs and the incidences of preeclampsia have been found in multiple populations. It is one of the TGFB family receptors, and multiple ligands of ACVR2A, as well as its coreceptors and related inhibitors, have been implicated in placental development, trophoblast invasion, and embryo implantation. This useful study builds on this knowledge by showing that ACVR2A knockout in trophoblast-related cell lines reduces trophoblast invasion, which could tie together many of these observations. The implication of cross-talk between the WNT and ACRV2A/SMAD2 pathways is an important contribution to the understanding of the regulation of trophoblast function.

Strengths:

(1) ACVR2A is one of very few genes implicated in preeclampsia in multiple human populations, yet its role in pathogenesis is not very well studied and this study begins to address that hole in our knowledge.

(2) ACVR2A is also indirectly implicated in trophoblast invasion and trophoblast development via its connections to many ligands, inhibitors, and coreceptors, suggesting its potential importance.

(3) The authors have used multiple cell lines to verify their most important observations.

Editors' note: Following the first round of peer review, the original reviewers were not available to review the revised manuscript. As several specific weakness detailed by the reviewers were largely addressed in the revised manuscript, they are not included here.

Reviewer #1 (Public review):

Lu et. al. proposed here a direct role of LPS in inducing hepatic fat accumulation and that metabolism of LPS therefore can mitigate fatty liver injury. With an Acyloxyacyl hydrolase whole-body KO mice, they demonstrated that Acyloxyacyl hydrolase deletion resulted in higher hepatic fat accumulation over 7 months of high glucose/high fructose diet. Previous literature has found that hepatocyte TLR4 (which is a main receptor for binding LPS) KO reduced fatty liver in MAFLD model, and this paper complement this by showing that degradation/metabolism of LPS can also reduce fatty liver. Using clodronate-liposomes to deplete KC, the authors went on to show that AOAH level decreased significantly with increased SREBP1 level, suggesting that KCs were the major source of AOAH in the liver. To explain the mechanism of LPS induced lipogenesis, the authors demostrated in vitro that LPS alone without KC can induce SREBP1 level in primary hepatocytes via mTOR activation. This result proposed a very interesting mechanism, and the translational implications of utilizing Acyloxyacyl hydrolase to decrease LPS exposure is intriguing.

The strengths of the present study include that they raised a very simplistic mechanism with LPS that is of interest in many diseases. The phenotype shown in the study is strong. The mechanism proposed by the findings are generally well supported. Manuscript significantly improved with revision. Overall, this work adds to the current understanding of the gut-liver axis and development of MAFLD, and will be of interest to many readers.

Reviewer #2 (Public review):

The authors of this article investigated the impact of the host enzyme AOAH on the progression of MASLD in mice. To achieve this, they utilized whole-body Aoah-/- mice. The authors demonstrated that AOAH reduced LPS-induced lipid accumulation in the liver, probably by decreasing the expression and activation of SREBP1. In addition, AOAH reduced hepatic inflammation and minimized tissue damage.

The authors have effectively addressed some key questions I raised. However, I still have some lingering concerns regarding the mechanisms underlying AOAH's effects.

(1) AOAH is expressed in the intestine, where it may inactivate LPS before it enters systemic circulation. In Fig. 3F, fecal LPS is significantly higher in Aoah⁻/⁻ mice compared to Aoah⁺/⁺ mice, indicating that AOAH in the intestine reduces bioactive LPS levels at the source. This implies that differences in hepatic LPS levels are already influenced by the gut environment, raising doubts about how much Kupffer cells contribute to inactivating LPS in the liver.

(2) The reliance on Kupffer cell depletion with clodronate-liposomes may overestimate the role of Kupffer cells because clodronate does not exclusively target hepatic Kupffer cells. Clodronate liposomes are taken up by macrophages systemically, potentially depleting macrophages in other organs, including the intestine and circulation. This means observed effects could also be due to loss of AOAH activity in non-hepatic macrophages.

Reviewer #3 (Public review):

Summary:

Chen et al. present a thorough statistical analysis of social interactions, more precisely, co-occupying the same chamber in the Eco-HAB measurement system. They also test the effect of manipulating the prelimbic cortex by using TIMP-1 that inhibits the MMP-9 matrix metalloproteinase. They conclude that altering neural plasticity in the prelimbic cortex does not eliminate social interactions, but it strongly impacts social information transmission.

Strengths:

The quantitative approach to analyzing social interactions is laudable and the study is interesting. It demonstrates that the Eco-HAB can be used for high throughput, standardized and automated tests of the effects of brain manipulations on social structure in large groups of mice.

Weaknesses:

A demonstration of TIMP-1 impairing neural plasticity specifically in the prelimbic cortex of the treated animals would greatly strengthen the biological conclusions. The Eco-HAB provides coarser spatial information compared to some other approaches, which may influence the conclusions.

Reviewer #1 (Public review):

Summary:

In this report, the authors made use of a murine cell line derived from a MYC-driven liver cancer to investigate the gene expression changes that accompany the switch from normoxic to hypoxia conditions during 2D growth and the switch from 2D monolayer to 3D organoid growth under normoxic conditions. They find a significant (ca. 40-50%) overlap among the genes that are dysregulated in response to hypoxia in 2D cultures and in response to spheroid formation. Unsurprisingly, hypoxia-related genes were among the most prominently deregulated under both sets of conditions. Many other pathways pertaining to metabolism, splicing, mitochondrial electron transport chain structure and function, DNA damage recognition/repair and lipid biosynthesis were also identified.

Comments on the revised manuscript:

In my original review of this manuscript, I raised 11 points that I thought needed to be addressed and/or clarified by the authors. In response, they have provided an adequate answer to only one of these (point 6), which is little more than a more thorough description of how spheroids were generated. The remaining points that I raised, which would have provided more mechanistic insight into their study were addressed by the authors with the following such comments:

- It is not the focus of this study (Points 1 and 4)

- It is worthy of further validation (Point 2)

- We apologize for not being able to validate everything (Point 3)

- This reviewer has raised an interesting question. We are investigating this hypothesis and hopefully we can give a clear answer in the future (Point 5)

- This is an excellent idea that we certainly will do it in our future experiments (Point 7)

As to responses that the authors made to the other two reviewers' comments: Most pertained to cosmetic alterations involving clarification of methods, inclusion of a new figure or rearrangement of old figures. These were generally answered. However, in response to the last point raised by Rev. 3 to compare "sgRNA abundances at the earliest harvesting time with the distribution in the library...to see whether and to what extent selection has already taken place before the three culture conditions were established", the authors responded with the comment: "This is great point. Unfortunately, we did not perform such an analysis."

I understand that it is often impossible to address all points raised by the reviewers. This can be for a variety of reasons and many times the omissions can be overlooked and accepted if the reviewer can be convinced that a good faith attempt has otherwise been made to address the other deficiencies. However, no such effort has been made here and the study remains deficient and largely descriptive as I pointed out in my original review.

Reviewer #1 (Public review):

Summary:

The authors address the role of the centromere histone core in force transduction by the kinetochore

Strengths:

They use a hybrid DNA sequence that combines CDEII and CDEIII as well as Widom 601 so they can make stable histones for biophysical studies (provided by the Widom sequence) and maintain features of the centromere (CDE II and III).

Weaknesses:

The main results are shown in one figure (Fig 2). Indeed the Centromere core of Widom and CDE II and III contribute to strengthening the binding force for the OA-beads. The data are very nicely done and convincingly demonstrate the point. The weakness is that this is the entire paper. It is certainly of interest to investigators in kinetochore biology, but beyond that the impact is fairly limited in scope.

Comments on revisions:

The additional information provided by the authors will help the reader understand and interpret the manuscript.

Reviewer #2 (Public review):

Summary:

This paper provides a valuable addendum to the findings described in Hamilton et al. 2020 (https://doi.org/10.7554/eLife.56582). In the earlier paper, the authors reconstituted the budding yeast centromeric nucleosome together with parts of the budding yeast kinetochore and tested which elements are required and sufficient for force transmission from microtubules to the nucleosome. Although budding yeast centromeres are defined by specific DNA sequences, this earlier paper did not use centromeric DNA but instead the generic Widom 601 DNA. The reason is that it has so far been impossible to stably reconstitute a budding yeast centromeric nucleosome using centromeric DNA.

In this new study, the authors now report that they were able to replace part of the Widom 601 DNA with centromeric DNA from chromosome 3. This makes the assay more closely resemble the in vivo situation. Interestingly, the presence of the centromeric DNA fragment makes one type of minimal kinetochore assembly, but not the other, withstand stronger forces.

Which kinetochore assembly turned out to be affected was somewhat unexpected, and can currently not be reconciled with structural knowledge of the budding yeast centromere/kinetochore. This highlights that, despite recent advances (e.g. Guan et al., 2021; Dendooven et al., 2023), aspects of budding yeast kinetochore architecture and function remain to be understood and that it will be important to dissect the contributions of the centromeric DNA sequence.

In the future, it will be interesting to pinpoint which interactions contribute to the enhanced force resistance in the presence of centromeric DNA.

Strength:

- The paper demonstrates that centromeric DNA can increase the attachment strength between budding yeast microtubules and centromeric nucleosomes.

Weakness:

- How centromeric DNA exerts this effect remains unclear.

Comments on revisions:

I appreciate the authors' detailed response and their decision to list all the tested in chimeras in Table 3.

All my prior comments have been addressed.

Reviewer #1 (Public review):

The authors set out to analyse the roles of the teichoic acids of Streptococcus pneumoniae in supporting the maintenance of the periplasmic region. Previous work has proposed the periplasm to be present in Gram positive bacteria and here advanced electron microscopy approach was used. This also showed a likely role for both wall and lipo-teichoic acids in maintaining the periplasm. Next, the authors use a metabolic labelling approach to analyse the teichoic acids. This is a clear strength as this method cannot be used for most other well studied organisms. The labelling was coupled with super-resolution microscopy to be able to map the teichoic acids at the subcellular level and a series of gel separation experiments to unravel the nature of the teichoic acids and the contribution of genes previously proposed to be required for their display. The manuscript could be an important addition to the field but there are a number of technical issues which somewhat undermine the conclusions drawn at the moment. These are shown below and should be addressed. More minor points are covered in the private

Recommendations for Authors.

Weaknesses to be addressed:

(1) l. 144 Was there really only one sample that gave this resolution? Biological repeats of all experiments are required.

(2) Fig. 4A. Is the pellet recovered at "low" speeds not just some of the membrane that would sediment at this speed with or without LTA? Can a control be done using an integral membrane protein and Western Blot? Using the tacL mutant would show the behaviour of membranes alone.

(3) Fig. 4A. Using enzymatic digestion of the cell wall and then sedimentation will allow cell wall associated proteins (and other material) to become bound to the membranes and potentially effect sedimentation properties. This is what is in fact suggested by the authors (l. 1000, Fig. S6). In order to determine if the sedimentation properties observed are due to an artefact of the lysis conditions a physical breakage of the cells, using a French Press, should be carried out and then membranes purified by differential centrifugation. This is a standard, and well-established method (low-speed to remove debris and high-speed to sediment membranes) that has been used for S. pneumoniae over many years but would seem counter to the results in the current manuscript (for instance Hakenbeck, R. and Kohiyama, M. (1982), Purification of Penicillin-Binding Protein 3 from Streptococcus pneumoniae. European Journal of Biochemistry, 127: 231-236).

(4) l. 303-305. The authors suggest that the observed LTA-like bands disappear in a pulse chase experiment (Fig. 6B). What is the difference between this and Fig. 5B, where the bands do not disappear? Fig. 5C is the WT and was only pulse labelled for 5 min and so would one not expect the LTA-like bands to disappear as in 6B?

(5) Fig. 6B, l. 243-269 and l. 398-410. If, as stated, most of the LTA-like bands are actually precursor then how can the quantification of LTA stand as stated in the text? The "Titration of Cellular TA" section should be re-evaluated or removed? If you compare Fig. 6C WT extract incubated at RT and 110oC it seems like a large decrease in amount of material at the higher temperature. Thus, the WT has a lot of precursors in the membrane? This needs to be quantified.

(6) L. 339-351, Fig. 6A. A single lane on a gel is not very convincing as to the role of LytR. Here, and throughout the manuscript, wherever statements concerning levels of material are made, quantification needs to be done over appropriate numbers of repeats and with densitometry data shown in SI.

(7) 14. l. 385-391. Contrary to the statement in the text, the zwitterionic TA will have associated counterions that results in net neutrality. It will just have both -ve and +ve counterions in equal amounts (dependent on their valency), which doesn't matter if it is doing the job of balancing osmolarity (rather than charge).

Comments on revisions:

The resubmitted manuscript now contains new data and changes to the text.

The authors have largely covered my previous points in both sets of reviews (Public/Recommendations).

Public Review Points:

1 & 6: I still do not see a reproducibility statement as such, with details of the number of biological repeats etc.

2 & 3. Fig S7 seems to be quite telling. As predicted after physical breakage the membrane proteins sediment at high speed (rather than low speed). This presumably also means that the LTA comes down at high and not low speed. LTA was not measured due to cost of reagents. The Microfluidizer breaks the cells using a shear force and thus is unlikely to create very small membrane fragments. Thus, the sedimentation properties of membranes containing LTA are likely dependent on the way in which the cells are lysed. It is therefore worthwhile qualifying the statements on l. 35-36, 46-47 and 212 (as Ref 8 used mechanical breakage). This will give better direction to those in the field following up the findings.

It is also a little alarming that the mutanolysin is contaminated by protease and one hopes this does not affect any of the properties of the materials being analysed.

Reviewer #2 (Public review):

The Gram-positive cell wall contains for a large part of TAs, and is essential for most bacteria. However, TA biosynthesis and regulation is highly understudied because of the difficulties in working with these molecules. This study closes some of our important knowledge gaps related to this and provides new and improved methods to study TAs. It also shows an interesting role for TAs in maintaining a 'periplasmic space' in Gram positives. Overall, this is an important piece of work. Future work will need to address the possible causal link between TAs and periplasmic space, for instance using complemented mutants and CEMOVIS. It will be interesting to see what happens with the periplasmic space in other mutants besides TA or also in strains with capsules/without capsules and in PG mutants, or in lafB (essential for production of another glycolipid) mutants. Overall, I support the publication of this revised work as it pioneers some new methods that will definitively move the field forward.

Joint Public Review:

Summary:

The behavioral switch between foraging and mating is important for resource allocation in insects. This study characterizes the role of sulfakinin and the sulfakinin receptor 1 in changes in olfactory responses associated with foraging versus mating behavior in the oriental fruit fly (Bactrocera dorsalis), a significant agricultural pest. This pathway regulates food consumption and mating receptivity in other species; here the authors use genetic disruption of sulfakinin and sulfakinin receptor 1 to provide strong evidence that changes in sulfakinin signaling modulate antennal responses to food versus pheromonal cues and alter the expression of ORs that detect relevant stimuli.

Strengths:

The authors utilize multiple complementary approaches including CRISPR/Cas9 mutagenesis, behavioral characterization, electroantennograms, RNA sequencing and heterologous expression to convincingly demonstrate the involvement of the sulfakinin pathway in the switch between foraging and mating behaviors. The use of both sulfakinin peptide and receptor mutants is a strength of the study and implicates specific signaling actors.

Weaknesses:

The authors demonstrate that SKR is expressed in olfactory neurons, however there are additional potential sites of action that may contribute to these results.

Reviewer #1 (Public review):

Summary:

This research article by Nath et al. from the Lee Lab addresses how lipolysis under starvation is achieved by a transient receptor potential channel, TRPγ, in the neuroendocrine neurons to help animals survive prolonged starvation. Through a series of genetic analyses, the authors identify that trpγ mutations specifically lead to a failure in lipolytic processes under starvation, thereby reducing animals' starvation resistance. The conclusion was confirmed through total triacylglycerol levels in the animals and lipid droplet staining in the fat bodies. This study highlights the importance of transient receptor potential (TRP) channels in the fly brain to modulate energy homeostasis and combat metabolic stress. However, the co-expression of trpγ and Dh44-R2 in the gut is not convincing, especially in the picture of the arrows pointing at the autofluorescence signals in the gut (Figure 7P). Therefore, the authors should either confirm the co-expression or acknowledge that trpγ and Dh44-R2 are not co-expressed in the gut and modify their model in Figure 8 accordingly, although clarifying their co-expression may not change the main conclusions of this study. Overall, the revised version includes the required clarifications on their important results that strengthen the interpretations of the research as well as the visibility of this study.

Strengths:

This study identifies the biological meaning of TRPγ in promoting lipolysis during starvation, advancing our knowledge about the TRPγ channel and the neural mechanisms to combat metabolic stress. Furthermore, this study demonstrates the potential of the TRPγ channel as a target to develop new therapeutic strategies for human metabolic disorders by showing that metformin and AMPK pathways are involved in its function in lipid metabolisms during starvation in Drosophila.

Reviewer #2 (Public review):

Summary

In this paper, the function of trpγ in lipid metabolism was investigated. The authors found that lipid accumulation levels were increased in trpγ mutants and remained high during starvation; the increased TAG levels in trpγ mutants were restored by the expression of active AMPK in DH44 neurons and oral administration of the anti-diabetic drug metformin. Furthermore, oral administration of lipase, TAG and free fatty acids effectively restored survival of trpγ mutants under starvation conditions. These results indicate that TRPv plays an important role in the maintenance of systemic lipid levels through the proper expression of lipase. Furthermore, authors have shown that this function is mediated by DH44R2. This study provides an interesting finding in that the neuropeptide DH44 released from the brain regulates lipid metabolism through a brain-gut axis, acting on the receptor DH44R2 expressed in gut cells.

Strengths

Using Drosophila genetics, careful analysis of which cells express trpγ regulates lipid metabolism is performed in this study. The study supports its conclusions from various angles, including not only TAG levels, but also fat droplet staining and survival rate under starved conditions, and oral administration of substances involved in lipid metabolism.

Weaknesses

The function of lipases, as well as identification of cell types, in the DH44R2-expressing cells in the gut can be investigated.

Reviewer #3 (Public review):

In this manuscript, the authors demonstrated the significance of the TRPγ channel in regulating internal TAG levels. They found high TAG levels in TRPγ mutant, which was ascribed to a deficit in the lipolysis process due to the downregulation of brummer (bmm). It was notable that the expression of TRPγ in DH44+ PI neurons, but not dILP2+ neurons, in the brain restored the internal TAG levels and that the knockdown of TRPγ in DH44+ PI neurons resulted in an increase in TAG levels. These results suggested a non-cell autonomous effect of Dh44+PI neurons. Additionally, the expression of the TRPγ channel in Dh44 R2-expressing cells restored the internal TAG levels. The authors, however, did not provide an explanation of how TRPγ might function in both presynaptic and postsynaptic cells in the non-cell autonomous manner to regulate the TAG storage. The authors further determined the effect of TRPγ mutation on the size of lipid droplets (LD) and the lifespan and found that TRPγ mutation caused an increase in the size of LD and a decrease in the lifespan, which were reverted by feeding lipase and metformin. These were creative endeavors, I thought. The finding that DH44+ PI neurons have non-cell autonomous functions in regulating bodily metabolism (mainly sugar/lipid) in addition to directing sugar nutrient sensing and consumption is likely correct, but the paper has many loose ends.

Comments on revisions:

The authors have addressed nearly all of my concerns with additional experiments and explanations.

Reviewer #1 (Public review):

This manuscript presents SAVEMONEY, a computational tool designed to enhance the utilization of Oxford Nanopore Technologies (ONT) long-read sequencing for the design and analysis of plasmid sequencing experiments. In the past few years, with the improvement in both sequencing length and accuracy, ONT sequencing is being rapidly extended to almost all omics analyses which are dominated by short-read sequencing (e.g., Illumina). However, relatively higher sequencing errors of long-read sequencing techniques including PacBio and ONT is still a major obstacle for plasmid/clone-based sequencing service that aims to achieve single base/nucleotide accuracy. This work provides a guideline for sequencing multiple plasmids together using the same ONT run without molecular barcoding, followed by data deconvolution. The whole algorithm framework is well-designed, and some real data and simulation data are utilized to support the conclusions. The tool SAVEMONEY is proposed to target users who have their own ONT sequencers and perform library preparation and sequencing by themselves, rather than relying on commercial services. As we know and discussed by the authors, in the real world, to ensure accuracy, the researchers will routinely pick up multiple colonies in the same plasmid construction and submit for Sanger sequencing. However, SAVEMONEY is not able to support the simultaneous analysis of multiple colonies in the same run, as compared to the barcoding-based approaches. This is a major limitation in the significance of this work. Encouraging computational efforts in ONT data debarcoding for mixed-plasmid or even single-cell sequencing would be more valuable in the field.

Comments on revisions:

My previous concerns have been addressed, and the revised manuscript has been significantly approved.

Reviewer #2 (Public review):

The authors developed an algorithm that allows to deconvolute plasmid sequences from a mixture of plasmids that have been sequenced by nanopore long read technology. As library preparations and barcoding of individual samples increases sequencing costs, the algorithm bypasses this need and thus decreases time on sample prep and sequencing costs. In a first step, the tool assesses which of the plasmid constructions can be mixed in a single library preparation by calculating a distance matrix between the reference plasmid and the constructions producing sequence clusters. The user is given groups of plasmids, from different clusters, to be pooled together for sequencing. After sequencing, the algorithm deconvolutes the reads by classifying them based on alignments to the reference sequence. A Bayesian analysis approach is used to obtain a consensus sequence and quality scores.

Strengths

The authors exploit one of the main advantages of long read sequencing that is to accurately resolve regions of high complexity, as regularly found in plasmids, and developed a tool that can validate plasmid constructions by reducing sequencing costs. Multiple plasmids (up to six) can be analyzed simultaneously in a single library without the need of sample barcoding, also reducing sample preparation time. Although inserts must be different, just 2 bases difference would be enough for correct assignation. Maximizes cost-efficiency for projects that require large amounts of plasmid constructions and high-throughput validation. The algorithm also allows for linear DNA analysis offering extra flexibility.

Reviewer #2 (Public review):

Summary:

This study investigates cold induced states in C. elegans, using polysome profiling and RNA seq to identify genes that are differentially regulated and concluding that cold-specific gene regulation occurs at the transcriptional level. This study also includes analysis of one gene from the differentially regulated set, lips-11 (a lipase), and finds that it is regulated in response to a specific set of ER stress factors.

Strengths:

(1) Understanding how environmental conditions are linked to stress pathways is generally interesting.<br /> (2) The study used well-established genetic tools to analyze ER stress pathways.

Weaknesses:

(1) The conclusions regarding a general transcriptional response are based on a few genes, with much of the emphasis on lips-11, which does not affect survival in response to cold.

(2) Definitive conclusions regarding transcription vs translational effects would require the use of blockers such as alpha-amanitin or cyclohexamide. Although this may be beyond the scope of the study, it does affect the breadth of the conclusions that can be made.

(3) Conclusions regarding the role of lipids are based on supplementation with oleic acid or choline, yet there is no lipid analysis of the cold animals, or after lips-1 knockdown. Although choline is important for PC production, adding choline in normal PC could have many other metabolic impacts and doesn't necessarily implicate PC without lipidomic or genetic evidence. Although they note the caveats, their evidence falls short of proving a role in PC production.

Reviewer #3 (Public review):

Summary:

The authors sought to understand the molecular mechanisms that cells use to survive cold temperatures by studying gene expression regulation in response to cold in C. elegans. They determined whether gene expression changes during cold adaptation occur primarily at the transcriptional level and identified specific pathways, such as the unfolded protein response pathway, that are activated to possibly promote survival under cold conditions.

Strengths:

Effective use of bulk RNA sequencing (RNA-seq) to measure transcript abundance and ribosome profiling (ribo-seq) to assess translation rates, providing a comprehensive view of gene expression regulation during cold adaptation. This combined approach allows for correlation between mRNA levels and their translation, thereby offering evidence for the authors' conclusion that transcriptional regulation is the primary mechanism of cold-specific gene expression changes.

Weaknesses:

Many aspects of the weakness have been addressed by the revision. Still, the weak cold sensitivity phenotype observed in ire-1 mutants suggests the ER-UPR pathway's role is likely minor, modulatory or there is an unknown compensatory mechanism responsible for surviving cold.

Reviewer #1 (Public Review):

The mechanisms that regulate establishment of the germline stem cells and germline progenitors during zebrafish reproductive development are not understood. Prior single cell analysis characterized the cell types of the early zebrafish ovary during and at stages after sexual differentiation. In this work Hsu et al. took a single approach to analyze the cell types present in the early gonad during early sex determination. As expected, they identified germline stem cells (GSCs) that express canonical GSC markers and distinct populations of progenitors. Unexpectedly, they found multiple populations of transcriptionally distinct progenitor populations that the authors termed early (those lacking the differentiation marker foxl2l), committed (those expressing fox2l2 and S-phase genes) and late (those expressing fox2l2 and meiotic genes) progenitors. Comparisons of their dataset to the published zebrafish ovary datasets confirmed the presence of these distinct progenitor populations in the ovary. Further, they convincingly validated the presence of these progenitor subtypes using fluorescent in situ hybridization. To investigate the relationship between progenitor subsets and known regulators of ovary differentiation, the authors conducted single cell analysis of gonads lacking the transcription factor, Foxl2l. As previously reported, Foxl2l absence blocks ovary differentiation and all foxl2l mutants develop testes. The single cell analysis here indicates that foxl2l is inappropriately expressed in GSCs and early progenitors and that germ cell differentiation is blocked at the committed progenitor stage since few committed progenitors and no late progenitors or meiotic transcripts were detected in the single cell analysis of foxl2l mutants. Based on the coexpression of genes that are not typically expressed together in normally developing germ cells, specifically nanos2 and foxl2l, and dmrt1 and foxl2l, the authors conclude that Foxl2l is required for the committed progenitor program and that it prevents committed progenitors from returning to the GSC state.

Overall, the data provide new insights into the cell populations of the early differentiating gonad, define distinct progenitor states, pinpoint a requirement for the ovary differentiation factor Foxl2l at a specific stage of progenitor differentiation, and generate new hypotheses to be tested. Many but not all of the conclusions are supported by compelling data, and some findings and conclusions need to be clarified in the context of the published literature.

(1) The authors conclude that the committed progenitors revert to GSCs based on the coexpression of nanos2 and foxl2l nanos2 and based on expression of id1 in mutants but not in WT. Without functional data demonstrating that the progenitors revert to an earlier state, alternative interpretations should be considered. For example, it is possible that the cells initiate the committed progenitor program but continue to express the GSC program and that the coexpression of both programs blocks differentiation. Consistent with this possibility, some Fox family members, FoxL2 and FoxPs for example, are known to be both activators and repressors of transcription or act primarily as repressors. Potentially relevant to this work, repressive activity of FoxL2 has been previously reported in the mammalian ovary (Pisarska et al Endocrinology 2004, Pisarska Am J. Phys Endo. Metabolism 2010, Kuo Reproduction 2012, Kuo Endocrinology 2011, as well as more recent publications). In that context interfering with FoxL2 was proposed to cause upregulated expression of genes normally repressed by FoxL2, accelerated follicle recruitment, and premature ovarian failure.

(2) The authors conclude that the committed progenitor stage is "the gate toward female determination" and that the cells "stay at S-Phase temporarily before differentiation". This conclusion seems to be based solely on single cell RNAseq expression. In several species, including zebrafish, meiotic entry occurs earlier in females and has been correlated with ovary development. The possibility that the late progenitor stage, the stage when meiotic genes are detected in this study and a stage missing in foxl2l mutants, is actually the key stage for female determination cannot be excluded by the data provided.

(3) The authors discuss prior working showing that loss of germ cells leads to male development and that germ cells are required for female development and claim to extend that work by showing here that some progenitors are already sexually differentiated. First, the stages compared are completely different. The earlier work looks at the primordial germ cells and their loss in the first few days of development before a gonad forms. In contrast, this work examines stages well after the gonad has formed and during sex determination. The second concern is that the conclusion that the progenitors are differentiated is based solely on the expression of foxl2l, which is initially expressed in the juvenile ovary state that lab strains have been shown to develop through (Wilson et al Front Cell Dev Bio 2024). While it is fair to state that some cells express ovary markers at this stage, it is unclear that this is sufficient evidence that the cells are differentiated. For example, in the context of the foxl2l mutant, the authors observe that GSCs and early progenitors inappropriately express foxl2l, but the mutants develop as males. Thus, expression of foxl2l transcripts alone is insufficient evidence to claim that the cells are already differentiated as female.

(4) The comparison between medaka and zebrafish foxl2l mutants seems to suggest that Foxl2l is required for meiosis in medaka but has a different role in zebrafish. However, if foxl2l represses the earlier developmental programs of GSCs and early progenitors, it is possible that continued expression of these early programs interferes with activation of meiotic genes. This could account for the absence of the late progenitor stage in foxl2l mutants since the late progenitor stage is defined by and distinguished from the earlier stages by expression of foxl2l and meiotic genes. If so, foxl2l may be similarly required in both systems.

(5) The authors state that "Foxl2l may ensure female differentiation by preventing stemness and antagonizing male development." It is unclear why suppressing stemness would be necessary for female differentiation since female zebrafish have stem cells as do male zebrafish. It seems likely that turning off the GSC and early differentiation programs is important for allowing expression of meiosis and oocyte differentiation genes, and that a gene other than Foxl2l is required for differentiation from GSCs to spermatocytes.

(6) Based on its expression in mutant progenitors, p53 is proposed to assist with alternative differentiation of mutant germ cells. Although p53 transcripts are expressed, no evidence is provided that p53 is involved in differentiation of germ cells, and sex bias has not been associated with the published p53 mutants in zebrafish. Furthermore, while p53 has been shown to be important for ovary to testis transformation in mutant contexts in adults, it appears dispensable for testis development in mutants that disrupt ovary differentiation in earlier stages (Rodriguez-Mari et al PLoS Gen 2010, Shive PNAS 2010, Hartung et al Mol. Reprod. Dev 2014, Miao Development 2017, Kaufman et al PLoSGen 2018, Bertho et al Development 2021. It is possible that p53 eliminates foxl2l mutant germ cells that are simultaneously expressing multiple developmental programs, but this possibility would need to be tested.

Reviewer #2 (Public Review):

In this manuscript, Hsu et al. used scRNA-seq to profile germ cells isolated from zebrafish ovaries. They identified the transcriptional profile of germ cells representing the early stages of oogenesis, from germline stem cells to newly formed follicle stage oocytes. They identified foxl2l as a gene expressed in probable oocyte progenitor cells, one of the least understood germ cell stages in the ovary. To understand to role of Foxl2l in oogenesis, they produced loss-of-function mutations in foxl2l using CRISPR/Cas9. They found that all foxl2l mutants are males as adults, suggesting that Foxl2l is required for oogenesis. To gain more insights, they performed scRNA-seq on cells isolated from 28 dpf foxl2l mutant ovaries and found that in the absence of foxl2l, germ cells appear to arrest as early progenitors. These results argue that Foxl2l, like its medaka homolog Foxl3, is necessary for promoting oocyte vs. spermatocyte differentiation during the oocyte progenitor stage.

Reviewer #3 (Public Review):

This is the first report to show a transcriptional factor, foxl2l, is essential for the development of female germs. Without foxl2l, germ cells will be developed into sperms. The report also clearly defined the arrested stage of early germ cells in foxl2l mutants, or stages that is critical for foxl2l to play a role for the further development of female germ cells. Due to lack of cell lineage tracing, the claim of foxl2l suppression of dedifferentiate of progenitor cells to GSC based on the gene expression and cell number changes is weak. In addition, separation of early germ cell types in foxl2l mutant using marker genes from WT may not be optimal.

Reviewer #1 (Public review):

Summary:

Pradhan et al investigated the potential gustatory mechanisms that allow flies to detect cholesterol. They found that flies are indifferent to low cholesterol and avoid high cholesterol. They further showed that the ionotropic receptors Ir7g, Ir51b, and Ir56d are important for the cholesterol sensitivity in bitter neurons. The figures are clear and the behavior result is interesting. However, I have several major comments, especially on the discrepancy of the expression of these Irs with other lab published results, and the confusing finding that the same receptors (Ir7g, Ir51b) have been implicated in the detection of various seemingly unrelated compounds.

Strengths:

The results are very well presented, the figures are clear and well-made, text is easy to follow.

Weaknesses:

(1) Regarding the expression of Ir56d. The reported Ir56d expression pattern contradicts multiple previous studies (Brown et al., 2021 eLife, Figure 6a-c; Sanchez-Alcaniz et al., 2017 Nature Communications, Figure 4e-h; Koh et al., 2014 Neuron, Figure 3b). These studies, using three different driver lines, consistently showed Ir56d expression in sweet-sensing neurons and taste peg neurons. Importantly, Sanchez-Alcaniz et al. demonstrated that Ir56d is not expressed in Gr66a-expressing (bitter) neurons. This discrepancy is critical since Ir56d is identified as the key subunit for cholesterol detection in bitter neurons, and misexpression of Ir7g and Ir51b together is insufficient to confer cholesterol sensitivity (Fig.4b,d). Which Ir56d-GAL4 (and Gr66a-I-GFP) line was used in this study? Is there additional evidence (scRNA sequencing, in-situ hybridization, or immunostaining) supporting Ir56d expression in bitter neurons?

(2) Ir51b has previously been implicated in detecting nitrogenous waste (Dhakal 2021), lactic acid (Pradhan 2024), and amino acids (Aryal 2022), all by the same lab. Additionally, both Ir7g and Ir51b have been implicated in detecting cantharidin, an insect-secreted compound that flies may or may not encounter in the wild, by the same lab. Is Ir51b proposed to be a specific receptor for these chemically distinct compounds or a general multimodal receptor for aversive stimuli? Unlike other multimodal bitter receptors, the expression level of Ir51b is rather low and it's unclear which subset of GRNs express this receptor. The chemical diversity among nitrogenous waste, amino acids, lactic acid, cantharidin, and cholesterol raises questions about the specificity of these receptors and warrants further investigation and at a minimum discussion in this paper. Given the wide and seemingly unrelated sensitivity of Ir51b and Ir7g to these compounds I'm leaning towards the hypothesis that at least some of these is non-specific and ecologically irrelevant without further supporting evidence from the authors.

(3) The Benton lab Ir7g-GAL4 reporter shows no expression in adults. Additionally, two independent labellar RNA sequencing studies (Dweck, 2021 eLife; Bontonou et al., 2024 Nature Communications) failed to detect Ir7g expression in the labellum. This contradicts the authors' previous RT-PCR results (Pradhan 2024 Fig. S4, Journal of Hazardous Materials) showing Ir7g expression in the labellum. Additionally the Benton and Carlson lab Ir51b-GAL4 reporters show no expression in adults as well. Please address these inconsistencies.

(4) The premise that high cholesterol intake is harmful to flies, which makes sensory mechanisms for cholesterol avoidance necessary, is interesting but underdeveloped. Animal sensory systems typically evolve to detect ecologically relevant stimuli with dynamic ranges matching environmental conditions. Given that Drosophila primarily consume fruits and plant matter (which contain minimal cholesterol) rather than animal-derived foods (which contain higher cholesterol), the ecological relevance of cholesterol detection requires more thorough discussion. Furthermore, at high concentrations, chemicals often activate multiple receptors beyond those specifically evolved for their detection. If the cholesterol concentrations used in this study substantially exceed those encountered in the fly's natural diet, the observed responses may represent an epiphenomenon rather than an ecologically and ethologically relevant sensory mechanism. What is the cholesterol content in flies' diet and how does that compare to the concentrations used in this paper?

Reviewer #2 (Public review):

Summary:

In Cholesterol Taste Avoidance in Drosophila melanogaster, Pradhan et al. used behavioral and electrophysiological assays to demonstrate that flies can: (1) detect cholesterol through a subset of bitter-sensing gustatory receptor neurons (GRNs) and (2) avoid consuming food with high cholesterol levels. Mechanistically, they identified five members of the IR family as necessary for cholesterol detection in GRNs and for the corresponding avoidance behavior. Ectopic expression experiments further suggested that Ir7g + Ir56d or Ir51b + Ir56d may function as tuning receptors for cholesterol detection, together with the Ir25a and Ir76b co-receptors.

Strengths:

The experimental design of this study was logical and straightforward. Leveraging their expertise in the Drosophila taste system, the research team identified the molecular and cellular basis of a previously unrecognized taste category, expanding our understanding of gustation. A key strength of the study was its combination of electrophysiological recordings with behavioral genetic experiments.

Weaknesses:

My primary concern with this study is the lack of a systematic survey of the IRs of interest in the labellum GRNs. Consequently, there is no direct evidence linking the expression of putative cholesterol IRs to the B GRNs in the S6 and S7 sensilla.

Specifically, the authors need to demonstrate that the IR expression pattern explains cholesterol sensitivity in the B GRNs of S6 and S7 sensilla, but not in other sensilla. Instead of providing direct IR expression data for all candidate IRs (as shown for Ir56d in Figure 2-figure supplement 1F), the authors rely on citations from several studies (Lee, Poudel et al. 2018; Dhakal, Sang et al. 2021; Pradhan, Shrestha et al. 2024) to support their claim that Ir7g, Ir25a, Ir51b, and Ir76b are expressed in B GRNs (Lines 192-194). However, none of these studies provide GAL4 expression or in situ hybridization data to substantiate this claim.

Without a comprehensive IR expression profile for GRNs across all taste sensilla, it is difficult to interpret the ectopic expression results observed in the B GRN of the I9 sensillum or the A GRN of the L-sensillum (Figure 4). It remains equally plausible that other tuning IRs-beyond the co-receptor Ir25a and Ir76b-could interact with the ectopically expressed IRs to confer cholesterol sensitivity, rather than the proposed Ir7g + Ir56d or Ir51b + Ir56d combinations.

Reviewer #3 (Public review):

Summary:

Whether and how animals can taste cholesterol is not well understood. The study provides evidence that 1) cholesterol activates a subset of bitter-sensing gustatory receptor neurons (GRNs) in the fly labellum, but not other types of GRNs, 2) flies show aversion to high concentrations of cholesterol, and this is mediated by bitter GRNs, and 3) cholesterol avoidance depends on a specific set of ionotropic receptor (IR) subunits acting in bitter GRNs. The claims of the study are supported by electrophysiological recordings, genetic manipulations, and behavioral readouts.

Strengths:

Cholesterol taste has not been well studied, and the paper provides new insight into this question. The authors took a comprehensive and rigorous approach in several different parts of the paper, including screening the responses of all 31 labellar sensilla, screening a large panel of receptor mutants, and performing misexpression experiments with nearly every combination of the 5 IRs identified. The effects of the genetic manipulations are very clear and the results of electrophysiological and behavioral studies match nicely, for the most part. The appropriate controls are performed for all genetic manipulations.

Weaknesses:

The weaknesses of the study, described below, are relatively minor and do not detract from the main conclusions of the paper.

(1) The paper does not state what concentrations of cholesterol are present in Drosophila's natural food sources. Are the authors testing concentrations that are ethologically relevant?

(2) The paper does not state or show whether the expression of IR7g, IR51b, and IR56d is confined to bitter GRNs. Bitter-specific expression of at least some of these receptors would be necessary to explain why bitter GRNs but not sugar GRNs (or other GRN types) normally show cholesterol responses.

(3) The authors only investigated the responses of GRNs in the labellum, but GRN responses in the leg may also contribute to the avoidance of cholesterol feeding. Alternatively, leg GRNs might contribute to cholesterol attraction that is unmasked when bitter GRNs are silenced. In support of this possibility, Ahn et al. (2017) showed that Ir56d functions in sugar GRNs of the leg to promote appetitive responses to fatty acids.

(4) The authors might consider using proboscis extension as an additional readout of taste attraction or aversion, which would help them more directly link the labellar GRN responses to a behavioral readout. Using food ingestion as a readout can conflate the contribution of taste with post-ingestive effects, and the regulation of food ingestion also may involve contributions from GRNs on multiple organs, whereas organ-specific contributions can be dissociated using proboscis extension. For example, does presenting cholesterol on the proboscis lead to aversive responses in the proboscis extension assay (e.g., suppression of responses to sugar)? Does this aversion switch to attraction when bitter GRNs are silenced, as with the feeding assay?

(5) The authors claim that the cholesterol receptor is composed of IR25a, IR76b, IR56d, and either IR7g or IR51b. While the authors have shown that IR25a and IR76b are each required for cholesterol sensing, they did not show that both are required components of the same receptor complex. If the authors are relying on previous studies to make this assumption, they should state this more clearly. Otherwise, I think further misexpression experiments may be needed where only IR25a or IR76b, but not both, are expressed in GRNs.

Reviewer #1 (Public review):

The aim of this study is to test the overarching hypothesis that plasticity in BNST CRF neurons drives distinct behavioral responses to unpredictable threat in males and females. The manuscript provides solid evidence for a sex-specific role for CRF-expressing neurons in the BNST in unpredictable aversive conditioning and subsequent hypervigilance across sexes. As the authors note, this is an important question given the high prevalence of sex differences in stress-related disorders, like PTSD, and the role of hypervigilance and avoidance behaviors in these conditions. The study includes in vivo manipulation, bulk calcium imaging, and cellular resolution calcium imaging, which yield important insights into cell-type specific activity patterns. A major strength of this manuscript is the inclusion of both males and females and attention to possible behavioral and neurobiological differences between them throughout.

Reviewer #2 (Public review):

This study examined the role of CRF neurons in the BNST in both phasic and sustained fear in males and females. The authors first established a differential fear paradigm whereby shocks were consistently paired with tones (Full) or only paired with tones 50% of the time (Part), or controls who were exposed to only tones with no shocks. Recall tests established that both Full and Part conditioned male and female mice froze to the tones, with no difference between the paradigms. Additional studies using the NSF and startle test, established that neither fear paradigm produced behavioral changes in the NSF test, suggesting that these fear paradigms do not result in an increase in anxiety-like behavior. Part fear conditioning, but not Full, did enhance startle responses in males but not females, suggesting that this fear paradigm did produce sustained increases in hypervigilance in males exclusively. Photometry studies found that while undifferentiated BNST neurons all responded to shock itself, only Full conditioning in males lead to a progressive enhancement of the magnitude of this response. BNST neurons in males, but not females, were also responsive to tone onset in both fear paradigms, but only in Full fear did the magnitude of this response increase across training. Knockdown of CRF from the BNST had no effect on fear learning in males or females, nor any effect in males on fear recall in either paradigm, but in females enhanced both baseline and tone-induced freezing only in Part fear group. When looking at anxiety following fear training, it was found in males that CRF knockdown modulated anxiety in Part fear trained animals and amplified startle in Full trained males but had no effect in either test in females. Using 1P imaging, it was found that CRF neurons in the BNST generally decline in activity across both conditioning and recall trials, with some subtle sex differences emerging in the Part fear trained animals in that in females BNST CRF neurons were inhibited after both shock and omission trials but in males this only occurred after shock and not omission trials. In recall trials, CRF BNST neuron activity remained higher in Part conditioned mice relative to Full conditioned mice.

Overall, this is a very detailed and complex study that incorporates both differing fear training paradigms and males and females, as well as a suite of both state-of-the-art imaging techniques and gene knockdown approaches to isolate the role and contributions of CRF neurons in the BNST to these behavioral phenomena. The strengths of this study come from the thorough approach that the authors have taken, which in turn helped to elucidate nuanced and sex specific roles of these neurons in the BNST to differing aspects of phasic and sustained fear. More so, the methods employed provide a strong degree of cellular resolution for CRF neurons in the BNST. In general, the conclusions appropriately follow the data, although the authors do tend to minimize some of the inconsistencies across studies, although this has now been addressed to some degree. The discussion has also been improved to now address some of the inconsistencies in the data head on. Discussion of a few other points is below:

- Given the focus on CRF neurons in the BNST, it was unclear why the photometry studies were performed in undifferentiated BNST neurons as opposed to CRF neurons specifically, although the authors have now explained this in better depth making this clearer to the reader.

- The CRF KD studies are interesting, but it remains speculative as to whether these effects are mediated locally in the BNST or due to CRF signaling at downstream targets. As the literature on local pharmacological manipulation of CRF signaling within the BNST seems to be largely performed in males, the addition of pharmacological studies here would benefit this to help to resolve if these changes are indeed mediated by local impairments in CRF release within the BNST or not. While it is not essential to add these experiments, the authors have addressed this point in the discussion and highlighted studies like this as necessary in future work.

- The authors have addressed the difference between arousal and anxiety by expanding the discussion to include more focus on the behavioral measures. The CRF KD data are still somewhat confusing but better contextualized now. Overall, the manuscript has been improved by the revisions and edits the authors have made.

Reviewer #3 (Public review):

Hon et al. investigated the role of BNST CRF signaling in modulating phasic and sustained fear in male and female mice. They found that partial and full fear conditioning had similar effects in both sexes during conditioning and during recall. However, males in the partially reinforced fear conditioning group showed enhanced acoustic startle, compared to the fully reinforced fear conditioning group, an effect not seen in females. Using fiber photometry to record calcium activity in all BNST neurons, the authors show that the BNST was responsive to foot shock in both sexes and both conditioning groups. Shock response increased over the session in males in the fully conditioned fear group, an effect not observed in the partially conditioned fear group. This effect was not observed in females. Additionally, tone onset resulted in increased BNST activity in both male groups, with the tone response increasing over time in the fully conditioned fear group. This effect was less pronounced in females, with partially conditioned females exhibiting a larger BNST response. During recall in males, BNST activity was suppressed below baseline during tone presentations and was significantly greater in the partially conditioned fear group. Both female groups showed an enhanced BNST response to the tone that slowly decayed over time. Next, they knocked CRF in the BNST to examine its effect on fear conditioning, recall and anxiety-like behavior after fear. They found no effect of the knockdown in either sex or group during fear conditioning. During fear recall, BNST CRF knockdown lead to an increase in freezing in only the partially conditioned females. In the anxiety-like behavior tasks, BNST CRF knockdown lead to increased anxiolysis in the partially reinforced fear male, but not in females. Surprisingly, BNST CRF knockdown increased startle response in fully conditioned, but not partially conditioned males. An effect not observed in either female group. In a final set of experiments, the authors single photon calcium imaging to record BNST CRF cell activity during fear conditioning and recall. Approximately, 1/3 of BNST CRF cells were excited by shock in both sexes, with the rest inhibited and no differences were observed between sexes or group during fear conditioning. During recall, BNST CRF activity decreased in both sexes, an effect pronounced in male and female fully conditioned fear groups.

Overall, these data provide novel, intriguing evidence in how BNST CRF neurons may encode phasic and sustained fear differentially in males and females. The experiments were rigorous. My biggest concerns I have regard the interpretations and some conclusions from this data set, which I have stated below.

(1) It was surprising to see minimal and somewhat conflicting behavioral effects due to BNST CRF knockdown. The authors provide a representative image and address this in the conclusion. They mention the role of local vs projection CRF circuits as well as the role of GABA. I don't think those experiments are necessary for this manuscript. However, it may be worthwhile to see through in situ hybridization or IHC, to see BNST CRF levels after both full and partial conditioned fear paradigms. Additionally, it would help to see a quantification of the knockdown of the animals. The authors can add a figure showing deltaF/F changes from control.

(2) Related to the previous point, it was surprising to see an effect of the CRF deletion in the full fear group compared to the partial fear in the acoustic startle task. To strengthen the conclusion about differential recruitment of CRF during phasic and sustained fear, the experiment in my previous point could help elucidate that. Conversely, intra-BNST administration of a CRF antagonist into the BNST before the acoustic startle after both conditioning tasks could also help. Or patch from BNST CRF neurons after the conditioning tasks to measure intrinsic excitability. Not all these experiments are needed to support the conclusion, it's some examples.

(3) In Figure 5 F and K, the authors report data combined for both part and full fear conditioning. Were there any differences between the number of excited or inhibited neurons b/t the conditioning groups? Also, can the authors separate male and female traces in Fig 5 E and P?

(4) Also, regarding the calcium imaging data, what was the average length of a transient induced by shock? Were there any differences between the sexes?

Reviewer #1 (Public review):

In this study, Osiurak and colleagues investigate the neurocognitive basis of technical reasoning. They use multiple tasks from two neuroimaging studies to show that the area PF is central to technical reasoning and plays an essential role in tool-use and non-tool-use physical problem-solving, as well as both conditions of mentalizing tasks. They also demonstrate the specificity of technical reasoning, finding that area PF is not involved in the fluid-cognition task or the mentalizing network (INT+PHYS vs. PHYS-only). This work enhances our understanding of the neurocognitive basis of technical reasoning that supports advanced technologies.

Strengths:

- The topic this study focuses on is intriguing and can help us understand the neurocognitive processes involved in technical reasoning and advanced technologies.<br /> - The researchers collected fMRI data from multiple tasks. The data is rich and encompasses the mechanical problem-solving task, psychotechnical task, fluid-cognition task, and mentalizing tasks.<br /> - The article is well written.

The authors have addressed many of the reviewers' concerns in their response. They utilized both correlation analysis and coordinate analysis to tackle alternative hypotheses, namely the same-region-but-different-function interpretation and the adjacency interpretation. Additionally, ROI analysis was conducted to validate the negative results. These additional analyses have enhanced the reliability of the findings. This study offers valuable insights into the neurocognitive mechanisms underlying technical reasoning.

Weaknesses:

While the authors attempted to address the limitations of overlap analysis by correlating activation across different tasks within subjects, this issue could not be entirely resolved due to the constraints of the current experimental design. The mechanical problem-solving task was not included since the sample of subjects differed from that of other tasks. Furthermore, the fluid-cognition task was not scanned in the same run as the psychotechnical and mentalizing tasks, which may have contributed to a lack of correlation between them, thereby affecting result interpretation. Moreover, the core cognitive focus of this study, technical reasoning, may be influenced by assumptions about motion-related information. While this issue has been discussed in the discussion section, further evidence is needed to substantiate this interpretation.

Reviewer #2 (Public review):

Strengths:

The authors have done a nice job providing additional data in response to reviewer feedback. I appreciate that accuracy plots are now included, as well as a separate analysis where differences in parameter estimates are performed for participants whose accuracy data were above chance levels. I also appreciate the new figure with the sphere ROIs for each participant, as they help us appreciate anatomical variability in the peak response separately for each task.

I have four concerns related to the weaknesses of the study:

(1) Although the results still hold when removing participants whose accuracy was 50% or less, a major limitation of this study is that participants made a button press response only to the last trial in a block. This is problematic because a participant could get all trials in a block correct except for the last one, or a participant could get all trials in a block wrong, and performance would be considered equivalent-as a consequence, it is not possible for one to know if participants who are at chance are performing differently from participants who are not at chance, and it is not possible to control for variance in reaction time (a concern also raised by reviewer 3).

(2) My second concern relates to the way in which the data are interpreted based on thresholding. There is above-threshold activation in the left SMG for all tasks except the fluid cognition task. The z-scores associated with significant voxels in Figure 3 are very strong (minimum z is 6). If one were to relax the threshold of the group level maps to, e.g., p < .001, uncorrected, FDR q < .05, or FWER of .10, there will be overlapping voxels outside the SMG. The discussion of the left SMG in the manuscript is prominent and narrowly construed-the left SMG is discussed as if it were 'the' region: "This confirms that the technical-reasoning network depends upon the recruitment of the left area PF, even if additional cognitive processes involving other peripheral brain areas can be engaged depending on the task" (pp. 9). My intuition is there will be numerous other areas of overlap when using a threshold that is still highly significant (e.g., z = 3 or 4). So, for proponents of the technical reasoning hypothesis, is there a counterfactual or alternative brain area/network/system not in the left SMG?

(3) I like the new Figure 6 because it shows variability in the location of the peak coordinate at the level of single participants. And, indeed, there's considerable variability that is typical when localizing ROIs in single participants. My concern is the level at which hypothesis testing is performed. An independent SMG ROI is used to extract parameter estimates and correlate responses between tasks to show a pattern of correlation that comports with a technical reasoning model of left SMG function. This is a fine approach but it does not rule out the so-called 'same region different function' interpretation because it relies on correlation-one cannot reverse infer that the left SMG is carrying out the same function across different tasks because the response in that area is more strongly correlated between certain tasks. This finding points to that possibility and makes interesting predictions for future studies to pursue, but it cannot tell us whether common functions in the left SMG are involved in each task. E.g., one interesting prediction for future studies is to test if patients with lesions to this site are disproportionately more inaccurate in the experimental condition of the mechanical problem solving task, the psychotechnical task, the mentalizing task, but not the fluid cognition task.

(4) I appreciated the approach to testing the adjacency interpretation by showing the sphere and peak Y coordinate across the tasks. It is interesting that across the groups, there is no difference in the peak Y coordinate of the psychotechnical task and both conditions of the mentalizing task, whereas the peak Y coordinate in the fluid intelligence task is more anterior in the post-central gyrus across participants (why is that?). But why restrict the analysis to just the Y coordinate? A rigorous way to test the adjacency hypothesis is to compute Euclidean distance among X, Y, and Z coordinates between any two tasks collected in the same participant. One can then test if the Euclidean distance between, e.g., the psychotechnical task and one condition of the mentalizing task is smaller than the Euclidean distance between the psychotechnical task and the fluid cognition task. Similarly, one can test whether Euclidean distance between the INT and PHY conditions of the mentalizing task is smaller than the Euclidean distance between the INT and psychotechnical task or PHY and psychotechnical task. There is no justification to restrict this analysis to the anterior-posterior dimension only.

Reviewer #3 (Public review):

The authors have responded very thoughtfully to many of the points raised, and the revised manuscript will make a useful contribution to our understanding of some of the computations performed by area PF. In particular, the investigators' addition of analyses of peak activations, their additional clarifications that area PF is likely to be part of a larger network concerned with technical reasoning, and their responses to the reviewers' concerns about differential task difficulty have strengthened the conclusions that can be drawn from the study.

The authors' response does not completely mitigate the concern noted by all 3 reviewers that the control tasks were easier than their corresponding experimental tasks (for everything but the fluid cognition task). The specific trouble with this issue can be appreciated by looking at Figure 4A, for example, which shows that area PF was activated for many individuals in both the control task and the experimental mechanical problem-solving task, but more so for the latter. Since the experimental task was harder (and more trial time was likely spent on task trying to solve it), the concern remains that area PF was driven harder by the experimental task in part due to the more challenging nature of that task.

The revised manuscript counters that the fluid cognition task was also harder than its control condition, yet did not activate PF more than its control condition. But this response seems to sidestep the central point of the reviewers' concerns: the fundamental computations that underlie the technical reasoning tasks may also be present in the respective (non technical-reasoning-based) control tasks and drive area PF activations to greater or lesser degrees based on how much they tax those computations. The fact that the fluid cognition experimental task and control task are not differentially difficult does not mitigate this concern, it just suggests that neither of those tasks tap the same fundamental computations, whatever they may be. (As an added note, Figures 2 and 4 show that both the PHYS-only and INT+PHYS mentalizing tasks only weakly activated PF, and both of these tasks were easier than the other technical cognition tasks).

The new ROI analysis with removal of subjects who performed below 50% in the revised manuscript is somewhat helpful, but there are two remaining issues: 1) chance performance is defined by a binomial test in this case, so scores somewhat above 50% may still be at chance depending on the number of items, and thus there may have been subjects who were not removed who could not perform the tasks; 2) it would have been convincing to include accuracy as a covariate in the modeling of BOLD parameter estimates for the remaining above-chance subjects to ensure that all reported effects remain once differential task difficulty is taken into account. It also appears that the legend for Figure S2, which indicates that the figure includes just subjects who performed at or below 50%, may not be correct; does the figure instead show data from subjects who performed at or above 50%?

Despite these remaining concerns, there are many aspects of this revised study that render it a useful contribution that will likely spur further research in this very interesting area.

Reviewer #1 (Public review):

Hüppe and colleagues had already developed an apparatus and an analytical approach to capture swimming activity rhythms in krill. In a previous manuscript they explained the system, and here they employ it to show a circadian clock, supplemented by exogenous light, produces an activity pattern consistent with "twilight" diel vertical migration (DVM; a peak at sunset, a midnight sink, and a peak in the latter half of the night).

They used light:dark (LD) followed by dark:dark (DD) photoperiods at two times of the year to confirm the circadian clock, coupled with DD experiments at four times a year to show rhythmicity occurs throughout the year along with DVM in the wild population. The individual activity data show variability in the rhythmic response, which is expected. However, their results showed rhythmicity was sustained in DD throughout the year, although the amplitude decayed quickly. The interpretation of a weak clock is reasonable, and they provide a convincing justification for the adaptive nature of such a clock in a species that has a wide distributional range and experiences various photic environments. These data also show that exogenous light increases the activity response and can explain the morning activity bouts, with the circadian clock explaining the evening and late-night bouts. This acknowledgement that vertical migration can be driven by multiple proximate mechanisms is important.

The work is rigorously done, and the interpretations are sound. I see no major weaknesses in the manuscript. Because a considerable amount of processing is required to extract and interpret the rhythmic signals (see Methods and previous AMAZE paper), it is informative to have the individual activity plots of krill as a gut check on the group data.

The manuscript will be useful to the field as it provides an elegant example of looking for biological rhythms in a marine planktonic organism and disentangling the exogenous response from the endogenous one. Furthermore, as high-latitude environments change, understanding how important organisms like krill have the potential to respond will become increasingly important. This work provides a solid behavioral dataset to complement the earlier molecular data suggestive of a circadian clock in this species.

Reviewer #2 (Public review):

Summary:

This manuscript provides experimental evidence on circadian behavioural cycles in Antarctic krill. The krill were obtained directly from krill fishing vessels and the experiments were carried out on board using an advanced incubation device capable of recording activity levels over a number of days. A number of different experiments were carried out where krill were first exposed to simulated light:dark (L:D) regimes for some days followed by continuous darkness (DD). These were carried out on krill collected during late autumn and late summer. A further set of experiments was performed on krill across three different seasons (summer, autumn, winter), where incubations were all DD conditions. Activity was measured as the frequency by which an infrared beam close to the top of the incubation tube was broken over unit time. Results showed that patterns of increased and decreased activity that appeared synchronised to the LD cycle persisted during the DD period. This was interpreted as evidence of the operation of an internal (endogenous) clock. The amplitude of the behavioural cycles decreased with time in DD, which further suggests that this clock is relatively weak. The authors argued that the existence of a weak endogenous clock is an adaptation to life at high latitudes since allowing the clock to be modulated by external (exogenous) factors is an advantage when there is a high degree of seasonality. This hypothesis is further supported by seasonal DD experiments which showed that the periodicity of high and low activity levels differed between seasons.

Strengths:

Although there has been a lot of field observations of various circadian type behaviour in Antarctic krill, relatively few experimental studies have been published considering this behaviour in terms of circadian patterns of activity. Krill are not a model organism and obtaining them and incubating them in suitable conditions are both difficult undertakings. Furthermore, there is a need to consider what their natural circadian rhythms are without the overinfluence of laboratory-induced artefacts. For this reason alone, the setup of the present study is ideal to consider this aspect of krill biology. Furthermore, the equipment developed for measuring levels of activity is well-designed and likely to minimise artefacts.

Reviewer #1 (Public review):

Summary:

This manuscript by Kaya et al. studies the effect of food consumption on hippocampal sharp wave ripples (SWRs) in mice. The authors use multiple foods and forms of food delivery to show that the frequency and power of SWRs increase following food intake, and that this effect depends on the caloric content of food. The authors also studied the effects of administration of various food-intake-related hormones on SWRs during sleep, demonstrating that ghrelin negatively affects SWR rate and power, but not GLP-1, insulin, or leptin. Finally, the authors use fiber photometry to show that GABAergic neurons in the lateral hypothalamus, increase activity during a SWR event.

Strengths:

The experiments in this study seem to be well performed, and the data are well presented, visually. The data support the main conclusions of the manuscript that food intake enhances hippocampal SWRs. Taken together, this study is likely to be impactful to the study of the impact of feeding on sleep behavior, as well as the phenomena of hippocampal SWRs in metabolism.

Weaknesses:

None

Reviewer #2 (Public review):

Summary:

Kaya et al uncover an intriguing relationship between hippocampal sharp wave-ripple production and peripheral hormone exposure, food intake, and lateral hypothalamic function. These findings significantly expand our understanding of hippocampal function beyond mnemonic processes and point a direction for promising future research.

Strengths:

Some of the relationships observed in this paper are highly significant. In particular, the inverse relationship between GLP1/Leptin and Insulin/Ghrelin are particularly compelling as this aligns well with opposing hormone functions on satiety.

Reviewer #3 (Public review):

Summary:

The manuscript by Kaya et al. explores the effects of feeding on sharp wave-ripples (SWRs) in the hippocampus, which could reveal a better understanding of how metabolism is regulated by neural processes. Expanding on prior work that showed that SWRs trigger a decrease in peripheral glucose levels, the authors further tested the relationship between SWRs and meal consumption by recording LFPs from the dorsal CA1 region of the hippocampus before and after meal consumption. They found an increase in SWR magnitude during sleep after food intake, in both food-restricted and ad libitum fed conditions. Using fiber photometry to detect GABAergic neuron activity in the lateral hypothalamus, they found increased activity locked to the onset of SWRs. They conclude that the animal's satiety state modulates the amplitude and rate of SWRs, and that SWRs modulate downstream circuits involved in regulating feeding.

The authors have addressed prior requests for revision and clarification, and provide a convincing case for SWRs being modulated by satiety state. These experiments provide an important step forward in understanding how metabolism is regulated in the brain. The study will likely be of great interest in the field of learning and memory while carrying broader implications for understanding brain-body physiology.

Reviewer #2 (Public review):

This manuscript addresses an important question which has not yet been solved in the field, what is the contribution of different gamma oscillatory inputs to the development of "theta sequences" in the hippocampal CA1 region. Theta sequences have received much attention due to their proposed roles in encoding short-term behavioral predictions, mediating synaptic plasticity, and guiding flexible decision-making. Gamma oscillations in CA1 offer a readout of different inputs to this region and have been proposed to synchronize neuronal assemblies and modulate spike timing and temporal coding. However, the interactions between these two important phenomena have not been sufficiently investigated. The authors conducted place cell and local field potential (LFP) recordings in the CA1 region of rats running on a circular track. They then analyzed the phase locking of place cell spikes to slow and fast gamma rhythms, the evolution of theta sequences during behavior and the interaction between these two phenomena. They found that place cell with the strongest modulation by fast gamma oscillations were the most important contributors to the early development of theta sequences and that they also displayed a faster form of phase precession within slow gamma cycles nested with theta.

Comments on revisions:

Several important shortcomings were noted in the original manuscript. These have been addressed in this revised version with the addition of multiple new analysis, controls and clarifications. The revised manuscript has been significantly improved and its conclusions are adequately supported by the results presented.

Reviewer #1 (Public review):

Summary:

This very interesting manuscript proposes a general mechanism for how activating signaling proteins respond to species specific signals arising from a variety of stresses. In brief, the authors propose that the activating signal alters the structure by a universal allosteric mechanism.

Strengths:

The unitary mechanism proposed is appealing and testable. The propose that the allosteric module consists of crossed alpha-helical linkers with similar architecture and that their attached regulatory domains connect to phosphatases or other molecules through coiled-coli domains, such that the signal is transduced via rigidifying the alpha helices, permitting downstream enzymatic activity. The authors present genetic and structural prediction data in favor of the model for the system they are studying, and stronger structural data in other systems.

Weaknesses:

I thank the authors for making significant revisions that addressed almost all of my concerns. I hope that the authors will consider addressing my last concern, which is that the title is inappropriate. However, I do not believe that this should hold up the publication of the ms.

"A General Mechanism for Initiating the General Stress Response in Bacteria" is misleading because it suggests a broadly applicable, universal mechanism across all bacterial species, whereas the study primarily focuses on Bacillus subtilis and its RsbU phosphatase activation. While the authors propose that the mechanism may extend to other bacteria, the evidence is largely based on structural modeling rather than direct experimental validation across multiple phyla. Additionally, the phrase "General Stress Response" might imply that the paper broadly explains stress response regulation, but it specifically examines the activation of RsbU by RsbT, which is just one really small part of the broader GSR network. The redundancy in "A General Mechanism for the General Stress Response" could also create an impression of an oversimplified, universal model when stress responses are often species- and context-specific. Furthermore, the study builds upon existing knowledge of partner-switching mechanisms rather than introducing an entirely new concept, making the claim of a general mechanism overstated and misleading for the field.

Title options could be "A Conserved Activation Mechanism for the General Stress Response Phosphatase in Bacteria", "Coiled-Coil Linker-Mediated Activation of a General Stress Response Phosphatase", all of which more accurately reflect the study's scope and findings.

Reviewer #2 (Public review):

Summary:

While bacteria have the ability to induce genes in response to specific stresses, they also use the General Stress Response (GSR) to deal with growth conditions that presumably include a larger range of stresses (for instance, stationary phase growth). The activation of GSR-specific sigma factors is frequently at the heart of the induction of a GSR. Given the range of stresses that can lead to GSR induction, the regulatory inputs are frequently complex. In B. subtilis, the stressosome, a multi-protein complex, contains a set of proteins that, upon appropriate stresses, initiate partner switching cascades that free the sigma B sigma factor from an anti-sigma. The focus here is on the mode of activation of RsbU, a serine/threonine phosphatase of the PPM family, leading to sigB activation. RbsT, a component of the degradosome interacts with RsbU upon stress, activating the phosphatase activity. Once active, RsbU dephosphorylates its target (RsbV, an anti-antisigma), which in turn binds the anti-sigma. The conclusion is that flexible linker domains upstream of the phosphatase domain are the target for activation, resulting in a crossed-linker dimeric structure. The authors then use the information on RsbU to suggest that parallel approaches may be used to activate PPM phosphatases for the GSR response in other bacteria.

Strengths and Weaknesses:

(1) A strength of the work is the combination of modeling, genetics and biochemical approaches to support the idea that the flexibility of the linker of the RsbU phosphatase is critical to signalling and that this changes as a result of interactions of the signaling protein RsbT.

(2) The impact of the work, beyond better understanding of this particular signalling system, lies in the suggested parallels with other GSR system regulators in a range of bacteria. The work here provides fairly clear indications of what mutational changes would be most likely to test the model.

(3) Assuming that these predictions are shown to be correct in future work, that will leave as an intriguing question why this particular geometry has been conserved in GSR - whether they emerge from a common ancestor (found where?) and/or there is some characteristic (flexibility of modulating the response?) that is particularly important for GSR signal input. Coupled with this will be further understanding of how the linker and/or interacting proteins change in different systems.

Reviewer #3 (Public review):

Summary:

The authors present a study building on their previous work on activation of the general stress response phosphatase, RsbU, from Bacillus subtilis. Using computed structural models of the RsbU dimer the authors map previously identified activating mutations onto the structure and suggest further protein variants to test the role of the predicted linker helix and the interaction with RsbT on the activation of the phosphatase activity.

Using in vivo and in vitro activity assays, the authors demonstrate that linker variants can constitutively activate RsbU and increase the affinity of the protein for RsbT, thus showing a link between the structure of the linker region and RsbT binding.

Small angle X-ray scattering experiments on RsbU variants alone, and in complex with RsbT show structural changes consistent with a decreased flexibility of the RsbU protein, which are hypothesised to indicate an disorder-order transition in the linker when RsbT binds. This interpretation of the data is consistent with the biochemical data presented by the authors.

Further computed structure models are presented for other protein phosphates from different bacterial species and the authors propose a model for phosphatase activation by partner binding. They compare this to the activation mechanisms proposed for histidine kinase two-component systems and GGDEF proteins and suggest the individual domains could be swapped to give a toolkit of modular parts for bacterial signalling.

Strengths:

The key mutagenesis data is presented with two lines of evidence to demonstrate RsbU activation - in vivo sigma-b activation assays utilising a beta-galactosidase reporter and in vitro activity assays against the RsbV protein, which is the downstream target of RsbU. These data support the hypothesis for RsbT binding to the RsbU linker region as well as the dimerisation domain to activate the RsbU activity.

Weaknesses:

Small angle scattering curves are difficult to unambiguously interpret, but the authors present good interpretations that fit with the biochemical data presented. These interpretations should be considered as models for future testing with other methods - hydrogen/deuterium exchange mass spectrometry, would be a good additional method to use, as exchange rates in the linker region would be affected significantly by the disorder/order transition on RsbT binding.

The interpretation of the computed structure models is provided with a few caveats related to the bias in the models returned by AlphaFold2. For the full-length models of RsbU and other phosphatase proteins, the relationship of the domains to each other is likely to be the least reliable part of the models - this is apparent from the PAE plots shown in supplementary figure 8.

Comments on revisions:

The authors have addressed the review comments satisfactorily for this manuscript to stand as a version of record.

Reviewer #1 (Public review):

Summary:

Kimura et al performed a saturation mutagenesis study of CDKN2A to assess functionality of all possible missense variants and compare them to previously identified pathogenic variants. They also compared their assay result with those from in silico predictors.

Strengths:

CDKN2A is an important gene that modulate cell cycle and apoptosis, therefore it is critical to accurately assess functionality of missense variants. Overall, the paper reads well and touches upon major discoveries in a logical manner.

Weaknesses:

The paper lacks proper details for experiments and basic data, leaving the results less convincing. Analyses are superficial and does not provide variant-level resolution.

Comments on revisions

The manuscript was improved during the revision process.

Reviewer #3 (Public review):

Summary:

The authors investigate the effect of high concentrations of the lipid aldehyde trans-2-hexadecenal (t-2-hex) in a yeast deletion strain lacking the detoxification enzyme. Transcriptomic analyses as global read out reveals that a large range of cellular functions across all compartments are affected (transcriptomic changes affect 1/3 of all genes). The authors provide additional analyses, which indicate that mitochondrial protein import is affected.

Strengths:

Global analyses (transcriptomic and functional genomics approach) to obtain an overview of changes upon yeast treatment with high doses of t-2-hex.

Weaknesses:

The use of high concentrations of t-2-hex in combination with a deletion of the detoxifying enzyme Hfd1 limits the possibility to identify physiological relevant changes. For the follow-up analysis, the authors focus on mitochondrial proteins and describe an impairment of mitochondrial protein biogenesis, but the underlying molecular modification resulting in the observed impairment is not yet known.

Reviewer #1 (Public review):

Summary:

The authors have developed self-amplifying RNAs (saRNAs) encoding additional genes to suppress dsRNA-related inflammatory responses and cytokine release. Their results demonstrate that saRNA constructs encoding anti-inflammatory genes effectively reduce cytotoxicity and cytokine production, enhancing the potential of saRNAs. This work is significant for advancing saRNA therapeutics by mitigating unintended immune activation.

Strengths:

This study successfully demonstrates the concept of enhancing saRNA applications by encoding immune-suppressive genes. A key challenge for saRNA-based therapeutics, particularly for non-vaccine applications, is the innate immune response triggered by dsRNA recognition. By leveraging viral protein properties to suppress immunity, the authors provide a novel strategy to overcome this limitation. The study presents a well-designed approach with potential implications for improving saRNA stability and minimizing inflammatory side effects.

Weaknesses:

(1) Impact on Cellular Translation:

The authors demonstrate that modified saRNAs with additional components enhance transgene expression by inhibiting dsRNA-sensing pathways. However, it is unclear whether these modifications influence global cellular translation beyond the expression of GFP and mScarlet-3 (which are encoded by the saRNA itself). Conducting a polysome profiling analysis or a puromycin labeling assay would clarify whether the modified saRNAs alter overall translation efficiency. This additional data would strengthen the conclusions regarding the specificity of dsRNA-sensing inhibition.

(2) Stability and Replication Efficiency of Long saRNA Constructs:

The saRNA constructs used in this study exceed 16 kb, making them more fragile and challenging to handle. Assessing their mRNA integrity and quality would be crucial to ensure their robustness.<br /> Furthermore, the replicative capacity of the designed saRNAs should be confirmed. Since Figure 4 shows lower inflammatory cytokine production when encoding srIkBα and srIkBα-Smad7-SOCS1, it is important to determine whether this effect is due to reduced immune activation or impaired replication. Providing data on replication efficiency and expression levels of the encoded anti-inflammatory proteins would help rule out the possibility that reduced cytokine production is a consequence of lower replication.

(3) Comparative Data with Native saRNA:

Including native saRNA controls in Figures 5-7 would allow for a clearer assessment of the impact of additional genes on cytokine production. This comparison would help distinguish the effect of the encoded suppressor proteins from other potential factors.

(4) In vivo Validation and Safety Considerations:

Have the authors considered evaluating the in vivo potential of these saRNA constructs? Conducting animal studies would provide stronger evidence for their therapeutic applicability. If in vivo experiments have not been performed, discussing potential challenges - such as saRNA persistence, biodistribution, and possible secondary effects-would be valuable.

(5) Immune Response to Viral Proteins:

Since the inhibitors of dsRNA-sensing proteins (E3, NSs, and L*) are viral proteins, they would be expected to induce an immune response. Analyzing these effects in vivo would add insight into the applicability of this approach.

(6) Streamlining the Discussion Section:

The discussion is quite lengthy. To improve readability, some content - such as the rationale for gene selection-could be moved to the Results section. Additionally, the descriptions of Figure 3 should be consolidated into a single section under a broader heading for improved coherence.

Reviewer #2 (Public review):

Summary:

Lim et al. have developed a self-amplifying RNA (saRNA) design that incorporates immunomodulatory viral proteins, and show that the novel design results in enhanced protein expression in vitro in mouse primary fibroblast-like synoviocytes. They test constructs including saRNA with the vaccinia virus E3 protein and another with E3, Toscana virus NS protein and Theiler's virus L protein (E3 + NS + L), and another with srIκBα-Smad7-SOCS1. They have also tested whether ML336, an antiviral, enables control of transgene expression.

Strengths:

The experiments are generally well-designed and offer mechanistic insight into the RNA-sensing pathways that confer enhanced saRNA expression. The experiments are carried out over a long timescale, which shows the enhance effect of the saRNA E3 design compared to the control. Furthermore, the inhibitors are shown to maintain the cell number, and reduce basal activation factor-⍺ levels.

Weaknesses:

One limitation of this manuscript is that the RNA is not well characterized; some of the constructs are quite long and the RNA integrity has not been analyzed. Furthermore, for constructs with multiple proteins, it's imperative to confirm the expression of each protein to confirm that any therapeutic effect is from the effector protein (e.g. E3, NS, L). The ML336 was only tested at one concentration; it is standard in the field to do a dose-response curve. These experiments were all done in vitro in mouse cells, thus limiting the conclusion we can make about mechanisms in a human system.

Reviewer #1 (Public review):

Summary:

The authors present a novel usage of fluorescence lifetime imaging microscopy (FLIM) to measure NAD(P)H autofluorescence in the Drosophila brain, as a proxy for cellular metabolic/redox states. This new method relies on the fact that both NADH and NADPH are autofluorescent, with a different excitation lifetime depending on whether they are free (indicating glycolysis) or protein-bound (indicating oxidative phosphorylation). The authors successfully use this method in Drosophila to measure changes in metabolic activity across different areas of the fly brain, with a particular focus on the main center for associative memory: the mushroom body.

Strengths:

The authors have made a commendable effort to explain the technical aspects of the method in accessible language. This clarity will benefit both non-experts seeking to understand the methodology and researchers interested in applying FLIM to Drosophila in other contexts.

Weaknesses:

(1) Despite being statistically significant, the learning-induced change in f-free in α/β Kenyon cells is minimal (a decrease from 0.76 to 0.73, with a high variability). The authors should provide justification for why they believe this small effect represents a meaningful shift in neuronal metabolic state.

(2) The lack of experiments examining the effects of long-term memory (after spaced or massed conditioning) seems like a missed opportunity. Such experiments could likely reveal more drastic changes in the metabolic profiles of KCs, as a consequence of memory consolidation processes.

(3) The discussion is mostly just a summary of the findings. It would be useful if the authors could discuss potential future applications of their method and new research questions that it could help address.

Reviewer #2 (Public review):

This manuscript presents a compelling application of NAD(P)H fluorescence lifetime imaging (FLIM) to study metabolic activity in the Drosophila brain. The authors reveal regional differences in oxidative and glycolytic metabolism, with a particular focus on the mushroom body, a key structure involved in associative learning and memory. In particular, they identify metabolic shifts in α/β Kenyon cells following classical conditioning, consistent with their established role in energy-demanding middle- and long-term memories.

These results highlight the potential of label-free FLIM for in-vivo neural circuit studies, providing a powerful complement to genetically encoded sensors. This study is well-conducted and employs rigorous analysis, including careful curve fitting and well-designed controls, to ensure the robustness of its findings. It should serve as a valuable technical reference for researchers interested in using FLIM to study neural metabolism in vivo. Overall, this work represents an important step in the application of FLIM to study the interactions between metabolic processes, neural activity, and cognitive function.

Reviewer #3 (Public review):

This study investigates the characteristics of the autofluorescence signal excited by 740 nm 2-photon excitation, in the range of 420-500 nm, across the Drosophila brain. The fluorescence lifetime (FL) appears bi-exponential, with a short 0.4 ns time constant followed by a longer decay. The lifetime decay and the resulting parameter fits vary across the brain. The resulting maps reveal anatomical landmarks, which simultaneous imaging of genetically encoded fluorescent proteins helps to identify. Past work has shown that the autofluorescence decay time course reflects the balance of the redox enzyme NAD(P)H vs. its protein-bound form. The ratio of free-to-bound NADPH is thought to indicate relative glycolysis vs. oxidative phosphorylation, and thus shifts in the free-to-bound ratio may indicate shifts in metabolic pathways. The basics of this measure have been demonstrated in other organisms, and this study is the first to use the FLIM module of the STELLARIS 8 FALCON microscope from Leica to measure autofluorescence lifetime in the brain of the fly. Methods include registering the brains of different flies to a common template and masking out anatomical regions of interest using fluorescence proteins.

The analysis relies on fitting an FL decay model with two free parameters, f_free and t_bound. F_free is the fraction of the normalized curve contributed by a decaying exponential with a time constant of 0.4 ns, thought to represent the FL of free NADPH or NADH, which apparently cannot be distinguished. T_bound is the time constant of the second exponential, with scalar amplitude = (1-f_free). The T_bound fit is thought to represent the decay time constant of protein-bound NADPH but can differ depending on the protein. The study shows that across the brain, T_bound can range from 0 to >5 ns, whereas f_free can range from 0.5 to 0.9 (Figure 1a). These methods appear to be solid, the full range of fits are reported, including maximum likelihood quality parameters, and can be benchmarks for future studies.

The authors measure the properties of NADPH-related autofluorescence of Kenyon Cells (KCs) of the fly mushroom body. The results from the three main figures are:

(1) Somata and calyx of mushroom bodies have a longer average tau_bound than other regions (Figure 1e);

(2) The f_free fit is higher for the calyx (input synapses) region than for KC somata (Figure 2b);

(3) The average across flies of average f_free fits in alpha/beta KC somata decreases from 0.734 to 0.718. Based on the first two findings, an accurate title would be "Autofluorecense lifetime imaging reveals regional differences in NADPH state in Drosophila mushroom bodies."

The third finding is the basis for the title of the paper and the support for this claim is unconvincing. First, the difference in alpha/beta f_free (p-value of 4.98E-2) is small compared to the measured difference in f_free between somas and calyces. It's smaller even than the difference in average soma f_free across datasets (Figure 2b vs c). The metric is also quite derived; first, the model is fit to each (binned) voxel, then the distribution across voxels is averaged and then averaged across flies. If the voxel distributions of f_free are similar to those shown in Supplementary Figure 2, then the actual f_free fits could range between 0.6-0.8. A more convincing statistical test might be to compare the distributions across voxels between alpha/beta vs alpha'/beta' vs. gamma KCs, perhaps with bootstrapping and including appropriate controls for multiple comparisons.

I recommend the authors address two concerns. First, what degree of fluctuation in autofluorescence decay can we expect over time, e.g. over circadian cycles? That would be helpful in evaluating the magnitude of changes following conditioning. And second, if the authors think that metabolism shifts to OXPHOS over glycolosis, are there further genetic manipulations they could make? They test LDH knockdown in gamma KCs, why not knock it down in alpha/beta neurons? The prediction might be that if it prevents the shift to OXPHOS, the shift in f_free distribution in alpha/beta KCs would be attenuated. The extensive library of genetic reagents is an advantage of working with flies, but it comes with a higher standard for corroborating claims.

FLIM as a method is not yet widely prevalent in fly neuroscience, but recent demonstrations of its potential are likely to increase its use. Future efforts will benefit from the description of the properties of the autofluorescence signal to evaluate how autofluorescence may impact measures of FL of genetically engineered indicators.

Joint Public Review:

The manuscript describes the role of mmp21, a metallopeptidase, in left-right patterning. MMP21 has been implicated in genetic studies of patients with heterotaxy and the authors add an additional case. However, a molecular mechanism for Htx/LR patterning defects is not clear although one previous study implicated Notch signaling. The authors find that mmp21 does indeed cause LR patterning defects in Xenopus consistent with work in mice and zebrafish without affecting cilia motility. Importantly, the authors extend this work to place mmp21 in the LR pathway between dand5 (in the nodal cascade) and the cilia-driven sensation of flow. With RNA overexpression studies, the authors show MMP21 can induce Nodal signaling bilaterally suggesting it is an activator of the pathway, potentially through regulation of dand5 asymmetry. The authors also show that the role of MMP21 is upstream of another matrix metalloprotease CIROP which is tethered to the plasma membrane and possibly the cilium. They propose that mmp21, which is secreted, may represent a morphogen that is asymmetrically distributed along the LR axis due to cilia-driven flow and sensed by sensory cilia in the LRO.

The authors attempt to address a highly controversial subject in the LR patterning field, that is, the debate between Nodal Vesicular Particles (NVP, ie morphogens) being driven by cilia to activate signaling on the left and the Two Cilia model which posits that mechanosensation of fluid flow and not morphogens drive asymmetric organogenesis.

The model they propose is that mmp21 is secreted in the center of the LRO. LRO cilia generate leftward flow driving mmp21 to the left where sensory cilia at the LRO margin detect the mmp21 via cirop and suppress dand5, leading to activation of Nodal and Pitx2 expression.

First and foremost, the authors need to consider alternative models in the discussion and acknowledge the strengths and weaknesses of their work. All three reviewers felt that their conclusion that mmp21 is a morphogen is premature and that other models could also fit their data which needs to be discussed. The authors need to soften the conclusion that other models have been excluded.

Reviewer #1 (Public review):

Summary:

The authors demonstrate that two human preproprotein human mutations in the BMP4 gene cause a defect in proprotein cleavage and BMP4 mature ligand formation, leading to hypomorphic phenotypes in mouse knock-in alleles and in Xenopus embryo assays.

Strengths:

They provide compelling biochemical and in vivo analyses supporting their conclusions, showing the reduced processing of the proprotein and concomitant reduced mature BMP4 ligand protein from impressively mouse embryonic lysates. They perform excellent analysis of the embryo and post-natal phenotypes demonstrating the hypomorphic nature of these alleles. Interesting phenotypic differences between the S91C and E93G mutants are shown with excellent hypotheses for the differences. Their results support that BMP4 heterodimers act predominantly throughout embryogenesis whereas BMP4 homodimers play essential roles at later developmental stages.

Weaknesses:

In the revision the authors have appropriately addressed the previous minor weaknesses.

Reviewer #2 (Public review):

Summary:

The revised paper by Kim et al. reports two disease mutations in proBMP4, S91C and E93G, disrupt the FAM20C phosphorylation site at Ser91, blocking the activation of proBMP4 homodimers, while still allowing BMP4/7 heterodimers to function. Analysis of DMZ explants from Xenopus embryos expressing the proBMP4 S91C or E93G mutants showed reduced expression of pSmad1 and tbxt1. The expert amphibian tissue transplant studies were expanded to in vivo studies in Bmp4S91C/+ and Bmp4E93G/+ mice, highlighting the impact of these mutations on embryonic development, particularly in female mice, consistent with patient studies. Additionally, studies in mouse embryonic fibroblasts (MEFs) demonstrated that the mutations did not affect proBMP4 glycosylation or ER-to-Golgi transport but appeared to inhibit the furin-dependent cleavage of proBMP4 to BMP4. Based on these findings and AI modeling using AlphaFold of proBMP4, the authors speculate that pSer91 influences access of furin to its cleavage site at Arg289AlaLysArg292 in a new "Ideas and Speculation" section. Overall, the authors addressed the reviewers' comments, improving the presentation.

Strengths:

The strengths of this work continue to lie in the elegant Xenopus and mouse studies that elucidate the impact of the S91C and E93G disease mutations on BMP signaling and embryonic development. Including an "Ideas and Speculation" subsection for mechanistic ideas reduces some shortcomings regarding the analysis of the underlying mechanisms.

Weaknesses:

(Minor) In Figure S1 and lines 165-174 and 179-180, the authors should consider that, unlike the wild-type protein (Ser), which can be reversibly phosphorylated or dephosphorylated, phosphomimic mutations are locked into mimicking either the phosphorylated state (Asp) or the non-phosphorylated state (Ala). Consequently, if the S91D mutant exhibits lower activity than WT, it could imply that S91D interferes with other regulatory constraints, as the authors suggest. However, it may also be inhibiting activation. Therefore, caution is warranted when comparing S91D with S91C to conclude that Ser91 phosphorylation increases BMP4 activity. While additional experiments are not necessary, further consideration is essential.

In Figure 4, panels A, E, and I, the proBMP bands in the mouse embryonic lysates and MEFs expressing the mutations show a clear size shift. Are these shifts a cause or a consequence of the lack of cleavage? Regardless, the size shifts should be explicitly noted.

(Minor) In line 314, the authors should consider modifying the wording to: "is required for modulating proprotein convertase..."

(Minor) In lines 394-399, the authors cleverly speculate that pS91 interacts with Arg289-the essential P4 arginine for furin processing. If so, this interaction could hinder the cleavage of proBMP4, as indicated by the results in Figure S1. The discussion would benefit from considering that, contrary to their favored model, dephosphorylation at Ser91 might actually facilitate cleavage.

Reviewer #3 (Public review):

Summary:

The authors describe important new biochemical elements in the synthesis of a class of critical developmental signaling molecules, BMP4. They also present a highly detailed description of developmental anomalies in mice bearing known human mutations at these specific elements.

Strengths:

This paper presents exceptionally detailed descriptions of pathologies occurring in BMP4 mutant mice. Novel findings are shown regarding the interaction of propeptide phosphorylation and convertase cleavage, both of which will move the field forward. Lastly, a provocative hypothesis regarding furin access to cleavage sites is presented, supported by Alphafold predictions.

Reviewer #2 (Public review):

Summary:

In this paper, the authors first examined lens phenotypes in mice with Le-Cre-mediated knockdown (KD) of all the four FGFR (FGFR1-4), and found that pERK signals, Jag1 and foxe3 expression are absent or drastically reduced, indicating that FGF signaling is essential for lens induction. Next, the authors examined lens phenotypes of FGFR1/2-KD mice and found that lens fiber differentiation is compromised, and that proliferative activity and cell survival are also compromised in lens epithelium. Interestingly, Kras activation rescues defects in lens growth and lens fiber differentiation in FGFR1/2-KD mice, indicating that Ras activation is a key step for lens development, downstream of FGF signaling. Next, the authors examined the role of Frs2, Shp2 and Grb2 in FGF signaling for lens development. They confirmed that lens fiber differentiation is compromised in FGFR1/3-KD mice combined with Frs2-dysfunctional FGFR2 mutants, which is similar to lens phenotypes of Grb2-KD mice. However, lens defects are milder in mice with Shp2YF/YF and Shp2CS mutant alleles, indicating that involvement of Shp2 is limited for the Grb2 recruitment for lens fiber differentiation. Lastly, the authors showed new evidence on the possibility that another adapter protein, Shc1, promotes Grb2 recruitment independent of Frs2/Shp2-mediated Grb2 recruitment.

Strengths:

Overall, the manuscript provides valuable data on how FGFR activation leads to Ras activation through the adapter platform of Frs2/Shp2/Grb2, which advances our understanding on complex modification of FGF signaling pathway. The authors applied a genetic approach using mice, whose methods and results are valid to support the conclusion. The discussion also well summarizes the significance of their findings.

Weaknesses:

The authors found that the new adaptor protein Shc1 is involved in Grb2 recruitment in response to FGF receptor activation. However, the main data on Shc1 are only histological sections and statistical evaluation of lens size. Cellular-level evidence on Shc1 makes the authors' conclusion more convincing.

Comments on latest version:

In the 2nd revised version of the manuscript, the authors responded to my recommendation to show the number of biological replicates for Prox1 and αA-crystallin (Fig. 1F) and conductedstatistical analysis for pmTOR, and pS6 (Supplementary figure 1B).

The authors also explained why the animals are no longer available for the additional experiments that I requested. I may understand the situation, but hope that the authors will investigate the cellular-level evidence on Shc1 in more detail and report it maybe as another paper in future.

Reviewer #1 (Public review):

Summary:

Chang and colleagues use tetrode recordings in behaving rats to study how learning an audiovisual discrimination task shapes multisensory interactions in auditory cortex. They find that a significant fraction of neurons in auditory cortex responded to visual (crossmodal) and audiovisual stimuli. Both auditory-responsive and visually-responsive neurons preferentially responded to the cue signaling the contralateral choice in the two-alternative forced choice task. Importantly, multisensory interactions were similarly specific for the congruent audiovisual pairing for the contralateral side.

Strengths:

The experiments are conducted in a rigorous manner. Particularly thorough are the comparisons across cohorts of rats trained in a control task, in a unisensory auditory discrimination task and the multisensory task, while also varying the recording hemisphere and behavioral state (engaged vs. anesthesia). The resulting contrasts strengthen the authors' findings and rule out important alternative explanations regarding the effect of experience. Through the comparisons, they show that the enhancements of activity in multisensory trials in auditory cortex are specific to the paired audiovisual stimulus and specific to contralateral choices in correct trials and thus dependent on learned associations in a task engaged state.

Weaknesses:

The main result that multisensory interactions are specific for contralateral paired audiovisual stimuli is consistent across experiments and interpretable as a learned task-dependent effect. However, the alternative interpretation of behavioral signals is crucial to rule out, which would also be specific to contralateral, correct trials in trained animals. Although the authors focus on the first 150 ms after cue onset, some of the temporal profiles of activity suggest that choice-related activity could confound some of the results.

The main concern (noted by all reviewers) is the interpretation of the evoked activity in visual trials. In the revised manuscript, the authors have not provided much data to disentangle movement related activity from sensory related activity. The only new data is on the visual response dynamics in supplementary figure 2, which is unconvincing both in terms of visual response latency and response dynamics. Therefore, the response of the authors has been insufficient to prove the visual nature of the evoked responses.

In this supplemental figure 2 the same example neuron as in the original manuscript is shown again as well as the average z-scored visual response. First, the visual response latency is inconsistent with literature. The first evoked activity in mouse V1 (!) is routinely reported around 50 ms (for example, 45 ms in Niell Stryker 2008, 52 ms, Schnabel et al. 2018, 54 ms in Oude Lohuis et al. 2024). According to the authors the potential route of crossmodal modulation of AC can occur through either corticocortical connections (which will impose further polysynaptic delays - monosynaptic projection from dLGN or V1 incredibly sparse), or through pulvinar (but pulvinar visual responses are much later (they find 170 vs 80 ms in dLGN, Roth et al. 2019) as expected from a higher order thalamic nucleus). One can also critique the estimation of the response latency which depends on the signal strength (visual response is smaller) and thus choice of threshold. With a different arbitrary threshold one would come to different conclusions.

Second, the temporal response dynamics to visual input are the same as the auditory response. It can be observed that if the data were normalized by the max response the dynamics are very similar, with the response back to near baseline levels at 100 ms post stimulus. I am not aware of publications that have observed response dynamics that are similar between A and V stimuli, nor such short-lasting visual response. In the visual system, mean activity typically drops again around 150-200ms.<br /> With the nature of the observed activity unclear, careful interpretation is warranted about audiovisual interactions in auditory cortex.

Reviewer #2 (Public review):

In this revision the authors have made a solid effort to address each of the points raised by all three reviewers. Due to the fact that animals in this study were freely moving, and there has not been any high-speed video recordings to measure whisker movements or other possible stimulus-induced motor effects it is still not possible to rule out motor effects completely. However, the fact that the multisensory enhancements are stimulus specific, much stronger in the multisensory case than the visual only condition, and short in latency it does seem the most parsimonious explanation is likely that these responses are visual in nature.

The delayed auditory stimulus offers some explanation for the very small latency difference between audio and visual stimulus elements. Studies using LED flashes in rat V2 report latencies around ~50 ms (e.g. 2017 paper from Brian Allman's group). The response latencies for visual stimuli in this manuscript are of this order of magnitude, albeit still shorter than that (which presumably means they don't originate from V2).

There are still parts of the manuscript that are inappropriately causal - e.g. line 283 "this suggests that strong multisensory integration is critical for behavior" - it could just as well be the case that high attention / motivation / arousal leads to both strong integration and good behavior.

Reviewer #3 (Public review):

Summary:

The manuscript by Chang et al. aims to investigate how the behavioral relevance of auditory and visual stimuli influences the way in which the primary auditory cortex encodes auditory, visual and audiovisual information. The main results is that behavioral training induces an increase in the encoding of auditory and visual information and in multisensory enhancement that is mainly related to the choice located contralaterally with respect to the recorded hemisphere.

Strengths:

The manuscript reports the results of an elegant and well planned experiment meant to investigate if auditory cortex encodes visual information and how learning shapes visual responsiveness in auditory cortex. Analyses are typically well done and properly address the questions raised

Weaknesses:

The authors have addressed most of my comments satisfactorily. However, I am still not convinced by the authors' claim that the use of LED should lead to visually-evoked responses with faster dynamics compared to the use of normal screens. In fact, previous studies using screen-emitted flashed did not report such faster dynamics. Visually-evoked responses in V1 (which are expected to occur earlier than A1) typically do not show onset latencies faster than 40 ms, and have a peak latency of about 100-120 ms. The dynamics shown in the new supplementary Fig. 2 are still faster than this, and thus should be explained. The authors' claim is in fact not supported by cited literature. The authors should at least provide evidence that a similar effect has been observed previously, or otherwise collect evidence themselves. In the absence of such evidence, I remain dubious about the visual nature of the observed activity, especially since, in contrast with what the authors say elsewhere in the rebuttal, involuntary motor reaction to (at least auditory) stimuli can be extremely fast (<40 ms; Clayton et al. 2024) and might thus potentially, at least partially, explain the observed "visual" response.

Reviewer #2 (Public review):

Summary:

In this work, the authors manage to optimize a simple and rapid protocol using SEC followed by DGCU to isolate sEVs with adequate purity and yield from small volumes of plasma. Isolated fractions containing sEVs using SEC, DGCU, SEC-DGCU and DGCU-SEC are compared in terms of their yield, purity surface protein profile and RNA content. Although the combined use of these methodologies has already been evaluated in previous works, the authors manage to adapt them for the use of small volumes of plasma, which allows working in 1.5 mL tubes and reducing the centrifugation time to 2 hours.<br /> The authors finally find that although both the SEC-DGCU and DGCU-SEC combinations achieve isolates with high purity, the SEC-DGCU combination results in higher yields.<br /> This work provides an interesting tool for the rapid obtention of sEVs with sufficient yield and purity for detailed characterization which could be very useful in research and clinical therapy.

Strengths:

The work is well written and organized.<br /> The authors clearly state the problem they want to address, that is, optimizing a method that allows sEV to be isolated from small volumes of plasma.<br /> Although these methodologies have been tested in previous works, the authors manage to isolate sEVs of high purity and good performance through a simple and fast methodology.<br /> The characteristics of all isolated fractions are exhaustively analyzed through various state-of-the-art methodologies.<br /> They present a good interpretation of the results obtained through the methodologies used.

Weaknesses:

Although this work focuses on comparing different techniques and their combinations to find an optimal option, the authors could strengthen their analysis by using statistical methods that reliably show the differences between the explored techniques.

Comments on revisions:

Although superiority of the proposed method was demonstrated by other techniques, it is always advisable to calculate the differences between different methodologies through different statistical methods, whenever possible, to strengthen the obtained results.

Reviewer #1 (Public review):

Summary:

In this manuscript entitled "Molecular dynamics of the matrisome across sea anemone life history", Bergheim and colleagues report the prediction, using an established sequence analysis pipeline, of the "matrisome" - that is, the compendium of genes encoding constituents of the extracellular matrix - of the starlet sea anemone Nematostella vectensis. Re-analysis of an existing scRNA-Seq dataset allowed the authors to identify the cell types expressing matrisome components and different developmental stages. Last, the authors apply time-resolved proteomics to provide experimental evidence of the presence of the extracellular matrix proteins at three different stages of the life cycle of the sea anemone (larva, primary polyp, adult) and show that different subsets of matrisome components are present in the ECM at different life stages with, for example, basement membrane components accompanying the transition from larva to primary polyp and elastic fiber components and matricellular proteins accompanying the transition from primary polyp to the adult stage.

Strengths:

The ECM is a structure that has evolved to support the emergence of multicellularity and different transitions that have accompanied the complexification of multicellular organisms. Understanding the molecular makeup of structures that are conserved throughout evolution is thus of paramount importance.

The in-silico predicted matrisome of the sea anemone has the potential to become an essential resource for the scientific community to support big data annotation efforts and understand better the evolution of the matrisome and of ECM proteins, an important endeavor to better understand structure/function relationships. This study is also an excellent example of how integrating datasets generated using different -omic modalities can shed light on various aspects of ECM metabolism, from identifying the cell types of origins of matrisome components using scRNA-Seq to studying ECM dynamics using proteomics.

Weaknesses:

My concerns pertain to the three following areas of the manuscript:

(1) In-silico definition of the anemone matrisome using sequence analysis:

a) While a similar computational pipeline has been applied to predict the matrisome of several model organisms, the authors fail to provide a comprehensive definition of the anemone matrisome: In the text, the authors state the anemone matrisome is composed of "551 proteins, constituting approximately 3% of its proteome (see page 6, line 14), but Figure 1 lists 829 entries as part of the "curated" matrisome, Supplementary Table S1 lists the same 829 entries and the authors state that "Here, we identified 829 ECM proteins that comprise the matrisome of the sea anemone Nematostella vectensis" (see page 17, line 10). Is the sea anemone matrisome composed of 551 or 829 genes? If we refer to the text, the additional 278 entries should not be considered as part of the matrisome, but what is confusing is that some are listed as glycoproteins and the "new_manual_annotation" proposed by the authors and that refer to the protein domains found in these additional proteins suggest that in fact, some could or should be classified as matrisome proteins. For example, shouldn't the two lectins encoded by NV2.3951 and NV2.3157 be classified as matrisome-affiliated proteins? Based on what has been done for other model organisms, receptors have typically been excluded from the "matrisome" but included as part of the "adhesome" for consistency with previously published matrisome; the reviewer is left wondering whether the components classified as "Other" / "Receptor" should not be excluded from the matrisome and moved to a separate "adhesome" list.

In addition to receptors, the authors identify nearly 70 glycoproteins classified as "Other". Here, does other mean "non-matrisome" or "another matrisome division" that is not core or associated? If the latter, could the authors try to propose a unifying term for these proteins? Unfortunately, since the authors do not provide the reasons for excluding these entries from the bona fide matrisome (list of excluding domains present, localization data), the reader is left wondering how to treat these entries.

Overall, the study would gain in strength if the authors could be more definitive and, if needed, even propose novel additional matrisome annotations to include the components for now listed as "Other" (as was done, for example, for the Drosophila or C. elegans matrisomes).

b) It is surprising that the authors are not providing the full currently accepted protein names to the entries listed in Supplementary Table S1 and have used instead "new_manual_annotation" that resembles formal protein names. This liberty is misleading. In fact, the "new_manual_annotation" seems biased toward describing the reason the proteins were positively screened for through sequence analysis, but many are misleading because there is, in fact, more known about them, including evidence that they are not ECM proteins. The authors should at least provide the current protein names in addition to their "new_manual_annotations".

c) To truly serve as a resource, the Table should provide links to each gene entry in the Stowers Institute for Medical Research genome database used and some sort of versioning (this could be added to columns A, B, or D). Such enhancements would facilitate the assessment of the rigor of the list beyond the manual QC of just a few entries.

d) Since UniProt is the reference protein knowledge database, providing the UniProt IDs associated with the predicted matrisome entries would also be helpful, giving easy access to information on protein domains, protein structures, orthology information, etc.

e) In conclusion, at present, the study only provides a preliminary draft that should be more rigorously curated and enriched with more comprehensive and authoritative annotations if the authors aspire the list to become the reference anemone matrisome and serve the community.

(2) Proteomic analysis of the composition of the mesoglea during the sea anemone life cycle:

a) The product of 287 of the 829 genes proposed to encode matrisome components was detected by proteomics. What about the other ~550 matrisome genes? When and where are they expressed? The wording employed by the authors (see line 11, page 13) implies that only these 287 components are "validated" matrisome components. Is that to say that the other ~550 predicted genes do not encode components of the ECM? This should be discussed.

b) Can the authors comment on how they have treated zero TMT values or proteins for which a TMT ratio could not be calculated because unique to one life stage, for example?

c) Could the authors provide a plot showing the distribution of protein abundances for each matrisome category in the main figure 4? In mammals, the bulk of the ECM is composed of collagens, followed by fibrillar ECM glycoproteins, the other matrisome components being more minor. Is a similar distribution observed in the sea anemone mesoglea?

d) Prior proteomic studies on the ECM of vertebrate organisms have shown the importance of allowing certain post-translational modifications during database search to ensure maximizing peptide-to-spectrum matching. Such PTMs include the hydroxylation of lysines and prolines that are collagen-specific PTMs. Multiple reports have shown that omitting these PTMs while analyzing LC-MS/MS data would lead to underestimating the abundance of collagens and the misidentification of certain collagens. The authors may want to re-analyze their dataset and include these PTMs as part of their search criteria to ensure capturing all collagen-derived peptides.

e) The authors should ensure that reviewers are provided with access to the private PRIDE repository so the data deposited can also be evaluated. They should also ensure that sufficient meta-data is provided using the SRDF format to allow the re-use of their LC-MS/MS datasets.

(3) Supplementary tables:

The supplementary tables are very difficult to navigate. They would become more accessible to readers and non-specialists if they were accompanied by brief legends or "README" tabs and if the headers were more detailed (see, for example, Table S2, what does "ctrl.ratio_Larvae_rep2" exactly refer to? Or Table S6 whose column headers using extensive abbreviations are quite obscure). Similarly, what do columns K to BX in Supplementary Table S1 correspond to? Without more substantial explanations, readers have no way of assessing these data points.

Reviewer #2 (Public review):

This work set out to identify all extracellular matrix proteins and associated factors present within the starlet sea anemone Nematostella vectensis at different life stages. Combining existing genomic and transcriptomic datasets, alongside new mass spectometry data, the authors provide a comprehensive description of the Nematostella matrisome. In addition, immunohistochemistry and electron microscopy were used to image whole mount and de-cellularized mesoglea from all life stages. This served to validate the de-cellularization methods used for proteomic analyses, but also resulted in a very nice description of mesoglea structure at different life stages. A previously published developmental cell type atlas was used to identify the cell type specificity of the matrisome, indicating that the core matrisome is predominantly expressed in the gastrodermis, as well as cnidocytes. The analyses performed were rigorous and the results were clear, supporting the conclusions made by the authors.

Reviewer #3 (Public review):

Summary:

This manuscript by Bergheim et al investigates the molecular and developmental dynamics of the matrisome, a set of gene products that comprise the extra cellular matrix, in the sea anemone Nematostella vectensis using transcriptomic and proteomic approaches. Previous work has examined the matrisome of the hydra, a medusozoan, but this is the first study to characterize the matrisome in an anthozoan. The major finding of this work is a description of the components of the matrisome in Nematostella, which turns out to be more complex than that previously observed in hydra. The authors also describe remodeling of the extra cellular matrix that occurs in the transition from larva to primary polyp, and from primary polyp to adult. The authors interpret these data to support previously proposed (Steinmetz et al. 2017) homology between the cnidarian endoderm with the bilaterian mesoderm.

Strengths:

The data described in this work are comprehensive (but see important considerations of reviewer #1) combining both transcriptome and proteomic interrogation of key stages in the life history of Nematostella and are of value to the community.

Weaknesses:

The authors offer numerous evolutionary interpretations of their results that I believe are unfounded. The main problem with extending these results, together with previous results from hydra, into an evolutionary synthesis that aims to reconstruct the matrisome of the ancestral cnidarian is that we are considering data from only two species. I agree with the authors' depiction of hydra as "derived" relative to other medusozoans and see it as potentially misleading to consider the hydra matrisome as an exemplar for the medusozoan matrisome. Given the organismal and morphological diversity of the phylum, a more thorough comparative study that compares matrisome components across a selection of anthozoan and medusozoan species using formal comparative methods to examine hypotheses is required.<br /> Specifically, I question the author's interpretation of the evolutionary events depicted in this statement:

"The observation that in Hydra both germ layers contribute to the synthesis of core matrisome proteins (Epp et al. 1986; Zhang et al. 2007) might be related to a secondary loss of the anthozoan-specific mesenteries, which represent extensions of the mesoglea into the body cavity sandwiched by two endodermal layers."<br /> Anthozoans and medusozoans are evolutionary sisters. Therefore, secondary loss of "anthozoan-like mesenteries" in hydrozoans is at least as likely as the gain of this character state in anthozoans. By extension, there is no reason to prefer the hypothesis that the state observed in Nematostella, where gastroderm is responsible for the synthesis of the core matrisome components, is the ancestral state of the phylum.<br /> Moreover, the fossil evidence provided in support of this hypotheses (Ou et al. 2022)is not relevant here because the material described in that work is of a crown group anthozoan, which diversified well after the origin of Anthozoa. The phylogenetic structure of Cnidaria has been extensively studied using phylogenomic approaches and is generally well supported(Kayal et al. 2018; DeBiasse et al. 2024). Based on these analyses, anthozoans are not on a "basal" branch, as the authors suggest. The structure of cnidarian phylogeny bifurcates with Anthozoa forming one clade and Medusozoa forming the other. From the data reported by Bergheim and co-workers, it is not possible to infer the evolutionary events that gave rise to the different matrisome states observed in Nematostella (an anthozoan) and hydra (a medusozoan).<br /> Furthermore, I take the observation in Fig 5 that anthozoan matrisomes generally exhibit a higher complexity than other cnidarian species to be more supportive of a lineage specific expansion of matrisome components in the Anthozoa, rather than those components being representative of an ancestral state for Cnidaria. Whatever the implication, I take strong issue with the statement that "the acquisition of complex life cycles in medusozoa, that are distinguished by the pelagic medusa stage, led to a secondary reduction in the matrisome repertoire." There is no causal link in any of the data or analyses reported by Bergheim and co-workers to support this statement and, as stated above, while we are dealing with limited data, insufficient to address this question, it seems more likely to me that the matrisome expanded in anthozoans, contrasting with the authors conclusions. While the discussion raises many interesting evolutionary hypotheses related to the origin of the cnidarian matrisome, which is of vital interest if we are to understand the origin of the bilaterian matrisome, a more thorough comparative analysis, inclusive of a much greater cnidarian species diversity, is required if we are to evaluate these hypotheses.

DeBiasse MB, Buckenmeyer A, Macrander J, Babonis LS, Bentlage B, Cartwright P, Prada C, Reitzel AM, Stampar SN, Collins A, et al. 2024. A Cnidarian Phylogenomic Tree Fitted With Hundreds of 18S Leaves. Bulletin of the Society of Systematic Biologists [Internet] 3. Available from: https://ssbbulletin.org/index.php/bssb/article/view/9267

Epp L, Smid I, Tardent P. 1986. Synthesis of the mesoglea by ectoderm and endoderm in reassembled hydra. J Morphol [Internet] 189:271-279. Available from: https://pubmed.ncbi.nlm.nih.gov/29954165/

Kayal E, Bentlage B, Sabrina Pankey M, Ohdera AH, Medina M, Plachetzki DC, Collins AG, Ryan JF. 2018. Phylogenomics provides a robust topology of the major cnidarian lineages and insights on the origins of key organismal traits. BMC Evol Biol [Internet] 18:1-18. Available from: https://bmcecolevol.biomedcentral.com/articles/10.1186/s12862-018-1142-0

Ou Q, Shu D, Zhang Z, Han J, Van Iten H, Cheng M, Sun J, Yao X, Wang R, Mayer G. 2022. Dawn of complex animal food webs: A new predatory anthozoan (Cnidaria) from Cambrian. The Innovation 3:100195.

Steinmetz PRH, Aman A, Kraus JEM, Technau U. 2017. Gut-like ectodermal tissue in a sea anemone challenges germ layer homology. Nature Ecology & Evolution 2017 1:10 [Internet] 1:1535-1542. Available from: https://www.nature.com/articles/s41559-017- 0285-5

Zhang X, Boot-Handford RP, Huxley-Jones J, Forse LN, Mould AP, Robertson DL, Li L, Athiyal M, Sarras MP. 2007. The collagens of hydra provide insight into the evolution of metazoan extracellular matrices. J Biol Chem [Internet] 282:6792-6802. Available from: https://pubmed.ncbi.nlm.nih.gov/17204477/

Reviewer #1 (Public review):

Summary:

The authors aimed to assess the variability in the expression of surface protein multigene families between amastigote and trypomastigote Trypanosoma cruzi, as well as between individuals within each population. The analysis presented shows higher expression of multigene family transcripts in trypomastigotes compared to amastigotes and that there is variation in which copies are expressed between individual parasites. Notably, they find no clear subpopulations expressing previously characterised trans-sialidase groups. The mapping accuracy to these multicopy genes requires demonstration to confirm this, and the analysis could be extended further to probe the features of the top expressed genes and the other multigene families also identified as variable.

Strengths:

The authors successfully process methanol-fixed parasites with the 10x Genomics platform. This approach is valuable for other studies where using live parasites for these methods is logistically challenging.

Weaknesses:

The authors describe a single experiment, which lacks controls or complementation with other approaches and the investigation is limited to the trans-sialidase transcripts.

It would be more convincing to show either bioinformatically or by carrying out a controlled experiment, that the sequencing generated has been mapped accurately to different members of multigene families to distinguish their expression. If mapping to the multigene families is inaccurate, this will impact the transcript counts and downstream analysis.

Reviewer #2 (Public review):

Summary:

This manuscript presents a valuable single-cell RNA-seq study on Trypanosoma cruzi, an important human parasite. It investigates the expression heterogeneity of surface proteins, particularly those from the trans-sialidase-like (TcS) superfamily, within amastigote and trypomastigote populations. The findings suggest a previously underappreciated level of diversity in TcS expression, which could have implications for understanding parasite-host interactions and immune evasion strategies. The use of single-cell approaches to delve into population heterogeneity is strong. However, the study does have some limitations that need to be addressed.

The focus on single-cell transcriptional heterogeneity in surface proteins, especially the TcS family, in T. cruzi is novel. Given the important role of these proteins in parasite biology and host interaction, the findings have potential significance.

Strengths:

The key finding of heterogeneous TcS expression in trypomastigotes is well-supported. The analysis comparing multigene families, single-copy genes, and ribosomal proteins highlights the unusual nature of the variation in surface protein-coding genes.

Weaknesses:

While the manuscript identifies TcS heterogeneity, the functional implications of the different expression profiles remain speculative. The authors state it may reflect differences in infectivity, but no direct experimental evidence supports this.

The manuscript lacks any functional validation of the single-cell findings. For instance, do the trypomastigote subpopulations identified based on TcS expression exhibit differences in infectivity, host cell tropism, or immune evasion? Such experiments would greatly strengthen the study.

The authors identify a subpopulation of TcS genes that are highly expressed in many cells. However, it is unclear if these correspond to previously characterized TcS members with specific functions.<br /> The authors hypothesize that observed heterogeneity may relate to chromatin regulation. However, the study does not directly address these mechanisms. There are interesting connections to be made with what they identify as the colocalization of genes within chromatin folding domains, but the authors do not fully explore this. It would be insightful to address these mechanisms in future work.

The merging of technical replicates needs further justification and explanation as they were not processed through separate experimental conditions. While barcodes were retained, it would be informative to know how well each technical replicate corresponds with the other. If both datasets were sequenced on the same lane, the inclusion of technical replicates adds noise to the analysis.<br /> While the number of cells sequenced (3192) seems reasonable, it's not clear how much the conclusions are affected by the depth of sequencing. A more detailed description of the sequencing depth and its impact on gene detection would be valuable.

While most of the methods are clear, the way in which the subsampled gene lists were generated could be more thoroughly described, as some details are not clear for the subsampling of single-copy genes.

Some of the figures are difficult to interpret. For example, the color scaling in the heatmap of Supplementary Figure 3B is not self-explanatory and it is hard to extract meaningful conclusions from the graph.

Reviewer #3 (Public review):

The study aimed to address a fundamental question in T. cruzi and Chagas disease biology - how much variation is there in gene expression between individual parasites? This is particularly important with respect to the surface protein-encoding genes, which are mainly from massive repetitive gene families with 100s to 1000s of variant sequences in the genome. There is very little direct evidence for how the expression of these genes is controlled. The authors conducted a single-cell RNAseq experiment of in vitro cultured parasites with a mixture of amastigotes and trypomastigotes. Most of the analysis focused on the heterogeneity of gene expression patterns amongst trypomastigotes. They show that heterogeneity was very high for all gene classes, but surface-protein encoding genes were the most variable. In the case of the trans-sialidase gene family, many sequence variants were only detected in a small minority of parasites. The biology of the parasite (e.g. extensive post-transcriptional regulation) and potential technical caveats (e.g. high dropout rates across the genome) make it difficult to infer what this might mean for actual protein expression on the parasite surface.

(1) Limit of detection and gene dropouts

An average of ~1100 genes are detected per parasite which indicates a dropout rate of over 90%. It appears that RNA for the "average" single copy 'core' gene is only detected in around 3% of the parasites sampled (Figure 2c: ~100 / 3192). This may be comparable with some other trypanosome scRNAseq studies, but this still seems to be a major caveat to the interpretation that high cell-to-cell variability in gene expression is explained by biological rather than technical factors. The argument would be more convincing if the dropout rates and expression heterogeneity were minimal for well-known highly expressed genes e.g. tubulin, GAPDH, and ribosomal RNAs. Admittedly, in their Final Remarks, the authors are very cautious in their interpretation, but it would be good to see a more thorough discussion of technical factors that might explain the low detection rates and how these could be tested or overcome in future work.

(2) Heterogeneity across the board

The authors focus on the relative heterogeneity in RNA abundance for surface proteins from the multicopy gene families vs core genes. While multicopy gene sequences do show more cell-to-cell variability, the differences (Figure 2D) are roughly average Gini values of 0.99 vs 0.97 (single copy) or 0.95 (ribosomal). Other studies that have applied similar approaches in other systems describe Gini values of < 0.2-0.25 for evenly expressed "housekeeping" genes (PMIDs 29428416, 31784565). Values observed here of >0.9 indicate that the distribution for all gene classes is extremely skewed and so the biological relevance of the comparison is uncertain.

Nevertheless, this study does provide some tantalising evidence that the expression of surface genes may vary substantially between individual parasites in a single clonal population. The study is also amongst the very first to apply scRNAseq to T. cruzi, so the broader data set will be an important resource for researchers in the field.

Reviewer #1 (Public review):

Liu et al., present glmSMA, a network-regularized linear model that integrates single-cell RNA-seq data with spatial transcriptomics, enabling high-resolution mapping of cellular locations across diverse datasets. Its dual regularization framework (L1 for sparsity and generalized L2 via a graph Laplacian for spatial smoothness) demonstrates robust performance of their model and offers novel tools for spatial biology, despite some gaps in fully addressing spatial communication.

Overall, the manuscript is commendable for its comprehensive benchmarking across different spatial omics platforms and its novel application of regularized linear models for cell mapping. I think this manuscript can be improved by addressing method assumptions, expanding the discussion on feature dependence and cell type-specific biases, and clarifying the mechanism of spatial communication.

The conclusions of this paper are mostly well supported by data, but some aspects of model development and performance evaluation need to be clarified and extended.

(1) What were the assumptions made behind the model? One of them could be the linear relationship between cellular gene expression and spatial location. In complex biological tissues, non-linear relationships could be present, and this would also vary across organ systems and species. Similarly, with regularization parameters, they can be tuned to balance sparsity and smoothness adequately but may not hold uniformly across different tissue types or data quality levels. The model also seems to assume independent errors with normal distribution and linear additive effects - a simplification that may overlook overdispersion or heteroscedasticity commonly observed in RNA-seq data.

(2) The performance of glmSMA is likely sensitive to the number and quality of features used. With too few features, the model may struggle to anchor cells correctly due to insufficient discriminatory power, whereas too many features could lead to overfitting unless appropriately regularized. The manuscript briefly acknowledges this issue, but further systematic evaluation of how varying feature numbers affect mapping accuracy would strengthen the claims, particularly in settings where marker gene availability is limited. A simple way to show some of this would be testing on multiple spatial omics (imaging-based) platforms with varying panel sizes and organ systems. Related to this, based on the figures, it also seems like the performance varies by cell type. What are the factors that contribute to this? Variability in expression levels, RNA quantity/quality? Biases in the panel? Personally, I am also curious how this model can be used similarly/differently if we have a FISH-based, high-plex reference atlas. Additional explanation around these points would be helpful for the readers.

(3) Application 3 (spatial communication) in the graphical abstract appears relatively underdeveloped. While it is clear that the model infers spatial proximities, further explanation of how these mappings translate into insights into cell-cell communication networks would enhance the biological relevance of the findings.

(4) What is the final resolution of the model outputs? I am assuming this is dictated by the granularity of the reference atlas and the imposed sparsity via the L1 norm, but if there are clear examples that would be good. In figures (or maybe in practice too), cells seem to be assigned to small, contiguous patches rather than pinpoint single-cell locations, which is a pragmatic compromise given the inherent limitations of current spatial transcriptomics technologies. Clarification on the precise spatial scale (e.g., pixel or micrometer resolution) and any post-mapping refinement steps would be beneficial for the users to make informed decisions on the right bioinformatic tools to use.

Reviewer #2 (Public review):

Summary:

The author proposes a novel method for mapping single-cell data to specific locations with higher resolution than several existing tools.

Strengths:

The spatial mapping tests were conducted on various tissues, including the mouse cortex, human PDAC, and intestinal villus.

Weaknesses:

(1) Although the researchers claim that glmSMA seamlessly accommodates both sequencing-based and image-based spatial transcriptomics (ST) data, their testing primarily focused on sequencing-based ST data, such as Visium and Slide-seq. To demonstrate its versatility for spatial analysis, the authors should extend their evaluation to imaging-based spatial data.

(2) The definition of "ground truth" for spatial distribution is unclear. A more detailed explanation is needed on how the "ground truth" was established for each spatial dataset and how it was utilized for comparison with the predicted distribution generated by various spatial mapping tools.

(3) In the analysis of spatial mapping results using intestinal villus tissue, only Figure 3d supports their findings. The researchers should consider adding supplemental figures illustrating the spatial distribution of single cells in comparison to the ground truth distribution to enhance the clarity and robustness of their investigation.

(4) The spatial mapping tests were conducted on various tissues, including the mouse cortex, human PDAC, and intestinal villus. However, the original anatomical regions are not displayed, making it difficult to directly compare them with the predicted mapping results. Providing ground truth distributions for each tested tissue would enhance clarity and facilitate interpretation. For instance, in Figure 2a and Supplementary Figures 1 and 2, only the predicted mapping results are shown without the corresponding original spatial distribution of regions in the mouse cortex. Additionally, in Figure 3c, four anatomical regions are displayed, but it is unclear whether the figure represents the original spatial regions or those predicted by glmSMA. The authors are encouraged to clarify this by incorporating ground truth distributions for each tissue.

(5) The cell assignment results from the mouse hippocampus (Supplementary Figure 6) lack a corresponding ground truth distribution for comparison. DG and CA cells were evaluated solely based on the gene expression of specific marker genes. Additional analyses are needed to further validate the robustness of glmSMA's mapping performance on Slide-seq data from the mouse hippocampus.

(6) The tested spatial datasets primarily consist of highly structured tissues with well-defined anatomical regions, such as the brain and intestinal villus. It remains unclear whether glmSMA can be effectively applied to tissue types where anatomical regions are not distinctly separated, such as liver tissue. Further evaluation of such tissues would help determine the method's broader applicability.

Reviewer #3 (Public review):

Summary:

The authors aim to develop glmSMA, a network-regularized linear model that accurately infers spatial gene expression patterns by integrating single-cell RNA sequencing data with spatial transcriptomics reference atlases. Their goal is to reconstruct the spatial organization of individual cells within tissues, overcoming the limitations of existing methods that either lack spatial resolution or sensitivity.

Strengths:

(1) Comprehensive Benchmarking:

Compared against CellTrek and Novosparc, glmSMA consistently achieved lower Kullback-Leibler divergence (KL divergence) scores, indicating better cell assignment accuracy.

Outperformed CellTrek in mouse cortex mapping (90% accuracy vs. CellTrek's 60%) and provided more spatially coherent distributions.

(2) Experimental Validation with Multiple Real-World Datasets:

The study used multiple biological systems (mouse brain, Drosophila embryo, human PDAC, intestinal villus) to demonstrate generalizability.

Validation through correlation analyses, Pearson's coefficient, and KL divergence support the accuracy of glmSMA's predictions.

Weaknesses:

(1) The accuracy of glmSMA depends on the selection of marker genes, which might be limited by current FISH-based reference atlases.

(2) glmSMA operates under the assumption that cells with similar gene expression profiles are likely to be physically close to each other in space which not be true under various heterogeneous environments.

Reviewer #1 (Public review):

Summary:

Kwon et al present a very well-conducted and well-written sieve analysis of rotavirus infections in a passive surveillance network in the US, considering how relative vaccine efficacy changes with genetic distance from the vaccine strains including the whole genome. The results are compelling, supported by a number of sensitivity analyses, and the manuscript is generally easy to follow.

Strengths:

(1) The underlying study base, a surveillance network across multiple sites in the US.

(2) The use of a test-negative design, which is well established for rotavirus, to estimate vaccine efficacy.

(3) The use of genetic distance to measure differences between infecting and vaccine strains, and the innovative use of k-means clustering to make results more interpretable.

(4) The secondary and sensitivity analyses that provide additional context and support for the primary findings.

Weaknesses:

(1) As identified by the authors, there is a limited sample size for the analysis of RV1 (monovalent rotavirus vaccine).

(2) Sieve analyses were originally designed for randomized trials, in which setting their key assumptions are more likely to be met. There is little discussion in this paper of how those assumptions might be violated and what effect that might have on the results. The authors have access to some important confounders, but I believe some more discussion on potential biases in this observational study is warranted.

Reviewer #2 (Public review):

Summary:

This study introduces a new metric for assessing the efficacy of rotavirus vaccines through the genetic distance clustering of strains. The authors analyzed variations in vaccine protection using whole genome sequencing.

Strengths:

Evaluating vaccine efficacy using whole genome sequencing can enhance our understanding of how pathogen evolution influences disease transmission and control.

Weaknesses:

While the study proposed a new method for evaluating vaccine efficacy using genetic information, its weaknesses arise from the insufficient evidence that analyses based on whole genome sequencing are more reliable than those that rely solely on VP7 and VP4 genotypes.

Though most cases received the RV5 vaccine (n=119 compared to n=30 for RV1), Figure 2 and the primary focus of the paper concentrate on RV1, as the authors identified a stronger association with genetic distance.

Additionally, it is unclear whether the difference between the two groups (j=0 versus j=1) is statistically significant for the analysis based on genetic distance to the RV1 strain, as well as for that based on minimum genetic distance to any of the RV5 vaccine strains. In both cases, the confidence intervals show substantial overlap.

The authors do not seem to have used a criterion for model selection based on the number of clusters; therefore, k=2 may not represent the optimal number of clusters, particularly in relation to the genetic distance associated with the RV5 vaccine (Figure 1B), which does not appear to show a bimodal distribution.

Finally, outcomes for RV1 are highly associated with both homotypic and heterotypic antibody responses (Supplemental Figure 10), which have already been shown to impact vaccine effectiveness (The Pediatric Infectious Disease Journal 40(12):p 1135-1143, 2021, doi:10.1097/INF.0000000000003286). Given this strong association, the benefit of using genetic distance is unclear, as the GxPx genotype serves as a good proxy for genetic similarity.

Reviewer #3 (Public review):

Overall, this is an outstanding paper. It presents a novel approach to estimating rotavirus vaccine efficacy; is clearly written and presented; and has implications for this vaccine specifically as well as type-specific vaccine evaluation more generally. The analytical framework is a creative and there is rigorous use of data and statistical approaches. It has long been argued that rotavirus immunity/vaccine performance operates beyond the scale of G/P genotyping. This paper is the first to demonstrate that convincingly, using data on all 11 viral genes and whole genome sequence analysis. I have only minor comments that I recommend should be addressed.

Reviewer #1 (Public review):

Summary:

This study presents findings on dual TCR regulatory T cells (Tregs) using previously published single-cell RNA and TCR sequencing datasets. The authors aimed to quantify dual TCR Tregs in different tissues and analyze their characteristics. Rather than perform the difficult experiments needed to ascertain the functional role of dual receptors, this study relies entirely on scRNA-VDJ-seq data published by two other groups. The findings primarily confirm prior work rather than provide new insights, and the methodology has significant weaknesses that limit the study's impact. We have concerns about the scientific integrity of this work.

Strengths:

(1) The use of single-cell RNA and TCR sequencing is appropriate for addressing potential relationships between gene expression and dual TCR.

(2) The data confirm the presence of dual TCR Tregs in various tissues, with proportions ranging from 10.1% to 21.4%, aligning with earlier observations in αβ T cells.

(3) Tissue-specific patterns of TCR gene usage are reported, which could be of interest to researchers studying T cell adaptation, although these were more rigorously analyzed in the original works.

Weaknesses

(1) Lack of Novelty: The primary findings do not substantially advance our understanding of dual TCR expression, as similar results have been reported previously in other contexts.

(2) Incomplete Evidence: The claims about tissue-specific differences lack sufficient controls (e.g., comparison with conventional T cells) and functional validation (e.g., cell surface expression of dual TCRs).

(3) Methodological Weaknesses: The diversity analysis does not account for sample size differences, and the clonal analysis conflates counts and clonotypes, leading to potential misinterpretation.

(4) Insufficient Transparency: The sequence analysis pipeline is inadequately described, and the study lacks reproducibility features such as shared code and data.

(5) Weak Gene Expression Analysis: No statistical validation is provided for differential gene expression, and the UMAP plots fail to reveal meaningful clustering patterns.

(6) A quick online search reveals that the same authors have repeated their approach of reanalysing other scientists' publicly available scRNA-VDJ-seq data in six other publications:

(1) Peng, Q., Xu, Y. & Yao, X. scRNA+ TCR-seq revealed dual TCR T cells antitumor response in the TME of NSCLC. J Immunother Cancer 12 (2024). https://doi.org:10.1136/jitc-2024-009376

(2) Wang, H., Li, J., Xu, Y. & Yao, X. scRNA + BCR-seq identifies proportions and characteristics of dual BCR B cells in the peritoneal cavity of mice and peripheral blood of healthy human donors across different ages. Immun Ageing 21, 90 (2024). https://doi.org:10.1186/s12979-024-00493-6

(3) Xu, Y. et al. scRNA+TCR-seq reveals the pivotal role of dual receptor T lymphocytes in the pathogenesis of Kawasaki disease and during IVIG treatment. Front Immunol 15, 1457687 (2024). https://doi.org:10.3389/fimmu.2024.1457687

(4) Yuanyuanxu, Qipeng, Qingqingma & Yao, X. scRNA + TCR-seq revealed the dual TCR pTh17 and Treg T cells involvement in autoimmune response in ankylosing spondylitis. Int Immunopharmacol 135, 112279 (2024). https://doi.org:10.1016/j.intimp.2024.112279

(5) Zhu, L. et al. scRNA-seq revealed the special TCR beta & alpha V(D)J allelic inclusion rearrangement and the high proportion dual (or more) TCR-expressing cells. Cell Death Dis 14, 487 (2023). https://doi.org:10.1038/s41419-023-06004-7

(6) Zhu, L., Peng, Q., Wu, Y. & Yao, X. scBCR-seq revealed a special and novel IG H&L V(D)J allelic inclusion rearrangement and the high proportion dual BCR expressing B cells. Cell Mol Life Sci 80, 319 (2023). https://doi.org:10.1007/s00018-023-04973-8

In other words, the approach used here seems to be focused on quick re-analyses of publicly available data without further validation and/or exploration

Appraisal of the Study's Aims and Conclusions:

The authors set out to analyze dual TCR Tregs across tissues, but the lack of robust controls, incomplete analyses, and insufficient novelty limit the study's ability to achieve its aims. The results confirm prior findings but do not provide compelling evidence to support the broader claims about the characteristics or significance of dual TCR Tregs.

Impact and Utility:

While the study provides a descriptive analysis of dual TCR Tregs, its limited novelty and methodological weaknesses reduce its likely impact on the field. The methods and data could have utility for researchers interested in tissue-specific TCR gene usage, but additional rigor is required to make the findings broadly applicable.

Reviewer #2 (Public review):

Summary:

The manuscript, "scRNA+TCR-seq Reveals the Proportion and Characteristics of Dual TCR Treg Cells in Mouse Lymphoid and Non-lymphoid Tissues" by Xu and Peng, et al. investigates whether co-expression of 2 T cell receptor (TCR) clonotypes can be detected in FoxP3+ regulatory CD4+ T cells (Tregs) and if it is associated with identifiable phenotypic effects. This paper presents data reanalyzing publicly available single-cell TCR sequencing and transcriptional analysis, convincingly demonstrating that dual TCR co-expression can be detected in Tregs, both in peripheral circulation as well as among Tregs in tissues. They then compare metrics of TCR diversity between single-TCR and dual TCR Tregs, as well as between Tregs in different anatomic compartments, finding the TCR repertoires to be generally similar though with dual TCR Tregs exhibiting a less diverse repertoire and some moderate differences in clonal expansion in different anatomic compartments. Finally, they examine the transcriptional profile of dual TCR Tregs in these datasets, finding some potential differences in the expression of key Treg genes such as Foxp3, CTLA4, Foxo3, Foxo1, CD27, IL2RA, and Ikzf2 associated with dual TCR-expressing Tregs, which the authors postulate implies a potential functional benefit for dual TCR expression in Tregs.

Strengths:

This report examines an interesting and potentially biologically significant question, given recent demonstrations that dual TCR co-expression is a much more common phenomenon than previously appreciated (approximately 15-20% of T cells) and that dual TCR co-expression has been associated with significant effects on the thymic development and antigenic reactivity of T cells. This investigation leverages large existing datasets of single-cell TCRseq/RNAseq to address dual TCR expression in Tregs. The identification and characterization of dual TCR Tregs is rigorously demonstrated and presented, providing convincing new evidence of their existence.

Weaknesses:

The existence of dual TCR expression by Tregs has previously been demonstrated in mice and humans (Reference #18 and Tuovinen. 2006. Blood. 108:4063; Schuldt. 2017. J Immunol. 199:33, both omitted from references). The presented results should be considered in the context of these prior important findings.

This demonstration of dual TCR Tregs is notable, though the authors do not compare the frequency of dual TCR co-expression by Tregs with non-Tregs. This limits interpreting the findings in the context of what is known about dual TCR co-expression in T cells.

Comparison of gene expression by single- and dual TCR Tregs is of interest, but as presented is difficult to interpret. Statistical analyses need to be performed to provide statistical confidence that the observed differences are true.

The interpretations of the gene expression analyses are somewhat simplistic, focusing on the single-gene expression of some genes known to have a function in Tregs. However, the investigators miss an opportunity to examine larger patterns of coordinated gene expression associated with developmental pathways and differential function in Tregs (Yang. 2015. Science. 348:589; Li. 2016. Nat Rev Immunol. Wyss. 2016. 16:220; Nat Immunol. 17:1093; Zenmour. 2018. Nat Immunol. 19:291).

Reviewer #3 (Public review):

Summary:

This study addressed the TCR pairing types and CDR3 characteristics of Treg cells. By analyzing scRNA and TCR-seq data, it claims that 10-20% of dual TCR Treg cells exist in mouse lymphoid and non-lymphoid tissues and suggests that dual TCR Treg cells in different tissues may play complex biological functions.

Strengths:

The study addresses an interesting question of how dual-TCR-expressing Treg cells play roles in tissues.

Weaknesses:

This study is inadequate, particularly regarding data interpretation, statistical rigor, and the discussion of the functional significance of Dual TCR Tregs.

Major Comments:

(1) Definition of Dual TCR and Validity of Doublet Removal<br /> This study analyzes Treg cells with Dual TCR, but it is not clearly stated how the possibility of doublet cells was eliminated. The authors mention using DoubletFinder for detecting doublets in scRNA-seq data, but is this method alone sufficient?<br /> We strongly recommend reporting the details of doublet removal and data quality assessment in the Supplementary Data.

(2) Inconsistency in the Proportion of Dual TCR T Cells in the Skin Across Figures<br /> In Figure 3D, the proportion of Dual TCR T cells (A1+A2+B1+B2) in the skin is reported to be very high compared to other tissues. However, in Figure 4C, the proportion appears lower than in other tissues, which may be due to contamination by non-Tregs. The authors should clarify why it was necessary to include non-Tregs as a target for analysis in this study. Additionally, the sensitivity of scRNA-seq and TCR-seq may vary between tissues and may also be affected by RNA quality and sequencing depth in skin samples, so the impact of measurement bias should be assessed.

(3) Issue of Cell Contamination<br /> In Figure 2A, the data suggest a high overlap between blood, kidney, and liver samples, likely due to contamination. Can the authors effectively remove this effect? If the dataset allows, distinguishing between blood-derived and tissue-resident Tregs would significantly enhance the reliability of the findings. Otherwise, it would be difficult to separate biological signals from contamination noise, making interpretation challenging.

(4) Inconsistency Between CDR3 Overlap and TCR Diversity<br /> The manuscript states that Single TCR Tregs have a higher CDR3 overlap, but this contradicts the reported data that Dual TCR Tregs exhibit lower TCR diversity (higher 1/DS score). Typically, when TCR diversity is low (i.e., specific clones are concentrated), CDR3 overlap is expected to increase. The authors should carefully address this discrepancy and discuss possible explanations.

(5) Functional Evaluation of Dual TCR Tregs<br /> This study indicates gene expression differences among tissue-resident Dual TCR T cells, but there is no experimental validation of their functional significance. Including functional assays, such as suppression assays or cytokine secretion analysis, would greatly enhance the study's impact.

(6) Appropriateness of Statistical Analysis<br /> When discussing increases or decreases in gene expression and cell proportions (e.g., Figure 2D), the statistical methods used (e.g., t-test, Wilcoxon, FDR correction) should be explicitly described. They should provide detailed information on the statistical tests applied to each analysis.

Reviewer #1 (Public review):

Summary:

The authors report four cryoEM structures (2.99 to 3.65 Å resolution) of the 180 kDa, full-length, glycosylated, soluble Angiotensin-I converting enzyme (sACE) dimer, with two homologous catalytic domains at the N- and C-terminal ends (ACE-N and ACE-C). ACE is a protease capable of effectively degrading Aβ. The four structures are C2 pseudo-symmetric homodimers and provide insight into sACE dimerization. These structures were obtained using discrete classification in cryoSPARC and show different combinations of open, intermediate, and closed states of the catalytic domains, resulting in varying degrees of solvent accessibility to the active sites.

To deepen the understanding of the gradient of heterogeneity (from closed to open states) observed with discrete classification, the authors performed all-atom MD simulations and continuous conformational analysis of cryo-EM data using cryoSPARC 3DVA, cryoDRGN, and RECOVAR. cryoDRGN and cryoSPARC 3DVA revealed coordinated open-closed transitions across four catalytic domains, whereas RECOVAR revealed independent motion of two ACE-N domains, also observed with cryoSPARC-focused classification. The authors suggest that the discrepancy in the results of the different methods for continuous conformational analysis in cryo-EM could result from different approaches used for dimensionality reduction and trajectory generation in these methods.

Strengths:

This is an important study that shows, for the first time, the structure and the snapshots of the dynamics of the full-length sACE dimer. Moreover, the study highlights the importance of combining insights from different cryo-EM methods that address questions difficult or impossible to tackle experimentally while lacking ground truth for validation.

Weaknesses:

The open, closed, and intermediate states of ACE-N and ACE-C in the four cryo-EM structures from discrete classification were designated quantitatively (based on measured atomic distances on the models fitted into cryo-EM maps, Figure 2D). Unfortunately, atomic models were not fitted into cryo-EM maps obtained with cryoSPARC 3DVA, cryoDRGN, and RECOVAR, and the open/closed states in these cases were designated based on qualitative analysis. As the authors clearly pointed out, there are many other methods for continuous conformational heterogeneity analysis in cryo-EM. Among these methods, some allow analyzing particle images in terms of atomic models, like MDSPACE (Vuillemot et al., J. Mol. Biol. 2023, 435:167951), which result in one atomic model per particle image and can help in analyzing cooperativity of domain motions through measuring atomic distances or angular differences between different domains (Valimehr et al., Int. J. Mol. Sci. 2024, 25: 3371). This could be discussed in the article.

Reviewer #2 (Public review):

Summary:

The manuscript presents a valuable contribution to the field of ACE structural biology and dynamics by providing the first complete full-length dimeric ACE structure in four distinct states. The study integrates cryo-EM and molecular dynamics simulations to offer important insights into ACE dynamics. The depth of analysis is commendable, and the combination of structural and computational approaches enhances our understanding of the protein's conformational landscape. However, the strength of evidence supporting the conclusions needs refinement, particularly in defining key terms, improving structural validation, and ensuring consistency in data analysis. Addressing these points through major revisions will significantly improve the clarity, rigor, and accessibility of the study to a broader audience, allowing it to make a stronger impact in the field.

Strengths:

The integration of cryo-EM and MD simulations provides valuable insights into ACE dynamics, showcasing the authors' commitment to exploring complex aspects of protein structure and function. This is a commendable effort, and the depth of analysis is appreciated.

Weaknesses:

Several aspects of the manuscript require further refinement to improve clarity and scientific rigor as detailed in my recommendations for the authors.

Reviewer #3 (Public review):

Summary:

Mancl et al. report four Cryo-EM structures of glycosylated and soluble Angiotensin-I converting enzyme (sACE) dimer. This moves forward the structural understanding of ACE, as previous analysis yielded partially denatured or individual ACE domains. By performing a heterogeneity analysis, the authors identify three structural conformations (open, intermediate open, and closed) that define the openness of the catalytic chamber and structural features governing the dimerization interface. They show that the dimer interface of soluble ACE consists of an N-terminal glycan and protein-protein interaction region, as well as C-terminal protein-protein interactions. Further heterogeneity mining and all-atom molecular dynamic simulations show structural rearrangements that lead to the opening and closing of the catalytic pocket, which could explain how ACE binds its substrate. These studies could contribute to future drug design targeting the active site or dimerization interface of ACE.

Strengths:

The authors make significant efforts to address ACE denaturation on cryo-EM grids, testing various buffers and grid preparation techniques. These strategies successfully reduce denaturation and greatly enhance the quality of the structural analysis. The integration of cryoDRGN, 3DVA, RECOVAR, and all-atom simulations for heterogeneity analysis proves to be a powerful approach, further strengthening the overall experimental methodology.

Weaknesses:

In general, the findings are supported by experimental data, but some experimental details and approaches could be improved. For example, CryoDRGN analysis is limited to the top 5 PCA components for ease of comparison with cryoSPARC 3DVA, but wouldn't an expansion to more components with CryoDRGN potentially identify further conformational states? The authors also say that they performed heterogeneity analysis on both datasets but only show data for one. The results for the first dataset should be shown and can be included in supplementary figures. In addition, the authors mention that they were not successful in performing cryoSPARC 3DFLex analysis, but they do not show their data or describe the conditions they used in the methods section. These data should be added and clearly described in the experimental section.

Some cryo-EM data processing details are missing. Please add local resolution maps, box sizes, and Euler angle distributions and reference the initial PDB model used for model building.

Reviewer #1 (Public review):

Summary:

In their manuscript, Andriani et al. show intracellular zinc is exported from sperm during capacitation and suppresses the alkalinization-induced hyperpolarization in sperm. Intracellular zinc inhibits Slo3 current, which is enhanced by the co-expression of gamma subunit Lrrc52. Computational studies reveal that the Zn binding site on mSlo3 is located near E169 and E205, which are involved in the sustained zinc inhibition of mSlo3 current. The authors propose that intracellular zinc plays a key role in sperm capacitation by inhibiting the Slo3 channel.

Strengths:

Overall, the work appears well-designed (e.g., oocyte patch-clamp experiments), and clearly presented. Three-dimensional structural modeling and flooding simulations are executed.

Weaknesses:

The simple mutagenesis analysis of E169 and E205 showed partial abolishment, but the molecular mechanism by which zinc inhibits Slo3 current is not yet fully shown. The authors should consider performing more extensive experiments, such as creating double mutants or combination mutants involving other residues. Additionally, could other mechanisms explain the role of zinc in regulating the Slo3 current?

While elucidating the mechanism of Slo3 is interesting, there is substantial literature indicating how zinc regulates channel functions at a molecular level. Given this, the manuscript should provide a deeper understanding by clearly elucidating the molecular mechanism of the regulation of Slo3 current by zinc.<br /> The manuscript includes no experimental data on the mechanism of intracellular zinc export during sperm capacitation, despite being crucial for the regulation of sperm function.

Reviewer #2 (Public review):

Summary:

In this paper, Andriani and colleagues are examining the potential role of Zn flux in sperm and its effect on Slo3 channels. This is an interesting question that is likely critical to how sperm function properly and Slo3 channels are a possible candidate for a downstream molecule that is impacted by Zn. In this paper, the authors use Zn imaging, sperm motility assays, and electrophysiology to show that Zn flux impacts sperm function. They then go on to look at the impact Zn has on Slo3 current and propose a binding site based on MD simulations. While the ideas are interesting, the experiments are not well described in many places making understanding the results very difficult. In addition, critical controls are missing throughout the paper.

Strengths:

The question of how Zn flux impacts membrane potential and sperm motility is an important one. Moreover, Slo3 presents an interesting candidate or the target of Zn regulation. The combination of methods used here also has the potential to uncover mechanisms of Zn regulation of Slo3.

Weaknesses:

Much of the paper lacks experimental description which makes interpretation quite difficult, or a detailed discussion is missing. Examples include:

(1) Figure 1, particularly the Zn imaging, is not sufficiently described. How is the fluorescence intensity measured? A representative ROI? The whole tail and head? Are the sperm immobile? If not, there is evidence that motion artifacts can significantly distort these sorts of measures from Calcium measurements in Cilia. Were there controls done? Is the small amount of Zn seen in the tail above the background?

(2) The second half of Figure 1 is also not well described. What is the extracellular solution in the recordings? When you apply the Zn ionophore, do you expect influx or efflux? I assume efflux is based on the conclusions but this should be discussed explicitly.

(3) Figure 2H labels the Y axis, "normalized current". Normalized to what? Why do neither of the curves end at 1? A better description of what this figure represents is needed.

(4) The alpha fold simulations are not well described. How many Zn binding sites were found? Are all of the histidine mutations in Figure 4 Supplement 1 the ones that were found?

(5) There is no discussion of physiological intracellular Zn concentration. How much Zn is inside the sperm? How much if likely Free vs buffered? Is 100uM a reasonable physiological concentration?

There are a number of areas where the interpretation is not well supported by the data including:

(6) You say in the Figure 4 supplement, that "we did not observe any significant decrease in the percentage of current inhibition." But that is a pretty misleading statement. There are large changes (increases) in the amount of zinc inhibition. These might be allosteric changes but I don't think you can safely eliminate these as relevant Zn binding sites. Also, some of these mutations appear to allow at least some unbinding of Zn.

(7) Following up on the above point, it seems unfair to conclude that the D162S, E169A, and E205 mutants are part of the inhibitory binding site for Zn when the mutation has no effect on inhibition and only an effect on the washout. The mutations on the intracellular side also had an impact on the washout so it seems equally likely that they are the critical residues based on your data.

(8) Nowhere in the paper do you make the specific link between Zn flux and membrane hyperpolariation via Slo3. You show that Zn flux changes the ability of the sperm to hyperpolarize and you show that Slo3 is inhibited by Zn but the connection between the two is not demonstrated. There appears to be a specific Slo3 blocker. If you use this in sperm, do you no longer see the Zn effect?

(9) In the second half of Figure 1, the authors suggest that there is "no hyperpolization in 100uM Zn. That is not really true. It is reduced but not absent.

(10) The claim that Lrcc52 with Slo3 shows a higher current inhibition at pH 7.5 than pH 8 is not well supported because there are only 3 replicates in the 7.5 case. In addition, the claim is made in the test that 100uM ZnCl2 "already inhibited mSlo3+Lrcc52 at pH7.5", contrasted with mSlo3 alone, is not tested statistically.

In a number of places, better controls are needed.

(11) How specific is this effect for Zn? Mg2+, for instance, is also a divalent cation that is in the hundreds of uM range inside the cell. Does it exert the same effect? Each ion certainly has unique preferred coordination geometries, does your predicted binding with MD show what you might expect for tetrahedral coordination with Zn? Did you test other divalent cations functionally or in silicon?

(12) For the VCF experiments, a significantly higher concentration of Zn was used (10mM). What is the reason for this? There is no discussion of how much a "puff" is. Assuming you are using the RNA injector it is probably on the order of 50nL or less. Assuming the volume of an oocyte is 1uL that would argue that the final concentration is 500uM or higher. But this is also complicated by potential local effects of high Zn at the injection site, artifacts of injecting that much metal, and the fact that a great deal of the Zn will likely be bound to other things inside the cell. Better controls are needed for this experiment.

Reviewer #3 (Public review):

Summary:

The study titled "Zinc is a Key Regulator of the Sperm-Specific K+ Channel (Slo3) Function" aims to investigate the role of intracellular zinc in sperm capacitation and its regulation of the sperm-specific Slo3 potassium channel. Capacitation is a crucial physiological process that enables sperm to fertilize an egg, and membrane hyperpolarization through Slo3 activation is a well-established event in this process. The authors propose that intracellular zinc dynamically decreases during capacitation and inhibits Slo3-mediated K⁺ currents, thereby playing a regulatory role in sperm function.

Strengths:

(1) Novel Contribution to Sperm Physiology.

The study provides new insights into how zinc dynamics contribute to sperm capacitation, specifically through its direct inhibition of Slo3 activity.<br /> Previous research has focused primarily on extracellular zinc's effect on sperm function; this work expands the discussion to intracellular zinc regulation, an area with limited prior investigation.

(2) Strong Electrophysiological Evidence.

The study employs inside-out patch-clamp recordings in Xenopus oocytes to demonstrate zinc's direct inhibition of Slo3 currents.<br /> The observed slow dissociation of zinc from Slo3 suggests a long-lasting regulatory effect, adding to the understanding of ion channel modulation in sperm cells.

(3) Molecular Mechanistic Insights

Using Molecular Dynamics (MD) simulations and mutagenesis, the authors identify potential zinc-binding sites within Slo3's voltage-sensing domain (VSD), particularly E169 and E205.

These computational predictions are supported by electrophysiological recordings, strengthening the argument that zinc directly binds and inhibits Slo3.

(4) Physiological Relevance and Functional Implications

The study suggests that zinc inhibition of Slo3 could contribute to sperm motility regulation during capacitation.

The authors provide sperm motility assays as supporting evidence, showing that zinc chelation affects motility only after capacitation has begun, suggesting a dynamic role of intracellular zinc in the capacitation process.

Weaknesses:

While the study presents compelling electrophysiological data and molecular insights, there are several critical gaps that must be addressed before fully supporting the physiological relevance of the findings.

(1) The authors should measure the effects in sperm cells using the patch-clamp technique to directly record Slo3 currents. By normalizing Slo3 currents to cell capacitance at different intracellular zinc concentrations, the authors can quantitatively assess the extent of Slo3 inhibition by zinc and strengthen the physiological relevance of their findings.

(2) Lack of Controls in Non-Capacitated Sperm

The claim that zinc is exported from sperm during capacitation needs stronger experimental validation.

The authors did not include a control group of non-capacitated sperm in key fluorescence imaging experiments, making it difficult to confirm that the observed zinc decrease is capacitation-specific rather than a general zinc redistribution process.

To strengthen this conclusion, experiments should be performed in non-capacitating conditions to determine whether intracellular zinc levels remain unchanged.

(3) Unclear Role of Zinc in Physiological Capacitation

The study clearly demonstrates zinc inhibition of Slo3 but does not sufficiently establish how this affects capacitation at a functional level.

Additional motility and capacitation markers should be analyzed to confirm that zinc influences sperm behavior beyond Slo3 inhibition.

(4) Insufficient Data on Zinc-Slo3 Specificity

The authors should consider using quinidine, a known washable Slo3 inhibitor, to confirm that zinc acts specifically on Slo3 channels rather than other endogenous ion channels.

The study would benefit from including washout controls in the inside-out patch-clamp recordings, as seen in Figure 3-Supplement 1, to confirm that zinc inhibition is reversible or long-lasting.

(5) Missing Discussion of Zinc's Role in CatSper Regulation

The study focuses solely on Slo3 but does not mention CatSper, the principal Ca²⁺ channel essential for sperm capacitation.

Zinc has been reported to inhibit CatSper activity, which could significantly impact sperm function.

The discussion should address whether zinc's effect on Slo3 represents a broader regulatory mechanism influencing multiple ion channels during capacitation.

Final Assessment

This work presents important findings on zinc regulation of Slo3 channels, supported by strong electrophysiological and molecular analyses. However, the physiological relevance of these findings remains unclear due to missing controls, and needs additional functional assays. Addressing these issues would significantly enhance the manuscript's scientific rigor and impact.

Reviewer #1 (Public review):

Summary:

The manuscript "Lifestyles shape genome size and gene content in fungal pathogens" by Fijarczyk et al. presents a comprehensive analysis of a large dataset of fungal genomes to investigate what genomic features correlate with pathogenicity and insect associations. The authors focus on a single class of fungi, due to the diversity of lifestyles and availability of genomes. They analyze a set of 12 genomic features for correlations with either pathogenicity or insect association and find that, contrary to previous assertions, repeat content does not associate with pathogenicity. They discover that the number of protein-coding genes, including the total size of non-repetitive DNA does correlate with pathogenicity. However, unique features are associated with insect associations. This work represents an important contribution to the attempts to understand what features of genomic architecture impact the evolution of pathogenicity in fungi.

Strengths:

The statistical methods appear to be properly employed and analyses thoroughly conducted. The manuscript is well written and the information, while dense, is generally presented in a clear manner.

Weaknesses:

My main concerns all involve the genomic data, how they were annotated, and the biases this could impart to the downstream analyses. The three main features I'm concerned with are sequencing technology, gene annotation, and repeat annotation.

The collection of genomes is diverse and includes assemblies generated from multiple sequencing technologies including both short- and long-read technologies. Not only has the impact of the sequencing method not been evaluated, but the technology is not even listed in Table S1. From the number of scaffolds it is clear that the quality of the assemblies varies dramatically. This is going to impact many of the values important for this study, including genome size, repeat content, and gene number. Additionally, since some filtering was employed for small contigs, this could also bias the results.

I have considerable worries that the gene annotation methods could impart biases that significantly affect the main conclusions. Only 5 reference training sets were used for the Sordariomycetes and these are unequally distributed across the phylogeny. Augusts obviously performed less than ideally, as the authors reported that it under-annotated the genomes by 10%. I suspect it will have performed worse with increasing phylogenetic distance from the reference genomes. None of the species used for training were insect-associated, except for those generated by the authors for this study. As this feature was used to split the data it could impact the results. Some major results rely explicitly on having good gene annotations, like exon length, adding to these concerns. Looking manually at Table S1 at Ophiostoma, it does seem to be a general trend that the genomes annotated with Magnaporthe grisea have shorter exons than those annotated with H294. I also wonder if many of the trends evident in Figure 5 are also the result of these biases. Clades H1 and G each contain a species used in the training and have an increase in genes for example.

Unfortunately, the genomes available from NCBI will vary greatly in the quality of their repeat masking. While some will have been masked using custom libraries generated with software like Repeatmodeler, others will probably have been masked with public databases like repbase. As public databases are again biased towards certain species (Fusarium is well represented in repbase for example), this could have significant impacts on estimating repeat content. Additionally, even custom libraries can be problematic as some software (like RepeatModeler) will include multicopy host genes leading to bona fide genes being masked if proper filtering is not employed. A more consistent repeat masking pipeline would add to the robustness of the conclusions.

To a lesser degree, I wonder what impact the use of representative genomes for a species has on the analyses. Some species vary greatly in genome size, repeat content, and architecture among strains. I understand that it is difficult to address in this type of analysis, but it could be discussed.

Reviewer #2 (Public review):

Summary:

In this paper, the authors report on the genomic correlates of the transition to the pathogenic lifestyle in Sordariomycetes. The pathogenic lifestyle was found to be better explained by the number of genes, and in particular effectors and tRNAs, but this was modulated by the type of interacting host (insect or not insect) and the ability to be vectored by insects.

Strengths:

The main strength of this study lies in the size of the dataset, and the potentially high number of lifestyle transitions in Sordariomycetes.

Weaknesses:

The main strength of the study is not the clarity of the conclusions.

(1) This is due firstly to the presentation of the hypotheses. The introduction is poorly structured and contradictory in some places. It is also incomplete since, for example, fungus-insect associations are not mentioned in the introduction even though they are explicitly considered in the analyses.

(2) The lack of clarity also stems from certain biases that are challenging to control in microbial comparative genomics. Indeed, defining lifestyles is complicated because many fungi exhibit different lifestyles throughout their life cycles (for instance, symbiotic phases interspersed with saprotrophic phases). In numerous fungi, the lifestyle referenced in the literature is merely the sampling substrate (such as wood or dung), which doesn't mean that this substrate is a crucial aspect of the life cycle. This issue is discussed by the authors, but they do not eliminate the underlying uncertainties.

Reviewer #3 (Public review):

Summary:

This important study combines comparative genomics with other validation methods to identify the factors that mediate genome size evolution in Sordariomycetes fungi and their relationship with lifestyle. The study provides insights into genome architecture traits in this Ascomycete group, finding that, rather than transposons, the size of their genomes is often influenced by gene gain and loss. With an excellent dataset and robust statistical support, this work contributes valuable insights into genome size evolution in Sordariomycetes, a topic of interest to both the biological and bioinformatics communities.

Strengths:

This study is complete and well-structured.

Bioinformatics analysis is always backed by good sampling and statistical methods. Also, the graphic part is intuitive and complementary to the text.

Weaknesses:

The work is great in general, I just had issues with the Figure 1B interpretation.

I struggled a bit to find the correspondence between this sentence: "Most genomic features were correlated with genome size and with each other, with the strongest positive correlation observed between the size of the assembly excluding repeats and the number of genes (Figure 1B)." and the Figure 1B. Perhaps highlighting the key p values in the figure could help.

Reviewer #1 (Public review):

IBEX Knowledge Database

Here, Anidi and colleagues present the IBEX knowledge base. A community tool developed to centralize knowledge and help its adoption by more users. The authors have done a fantastic job, and there is careful consideration of the many aspects of data management and FAIR principles. The manuscript needs no further work, as it is very well written and has detailed descriptions for data contribution as well as describing the KB itself. Overall, it is a great initiative, especially the aim to inform about negative data and non-recommended reagents, which will positively affect the user community and scientific reproducibility.

As such amount of work has been put into developing this community tool, it would be worth thinking about how it could serve other multiplex-immunofluorescence methods (such as immunoSABER, 4i, etc). Adding an extra tab where the particular method that uses those reagents is mentioned. This would also help as IBEX itself and related methods evolve in the future.

It has a rather minimal description of the software. In particular, there is software that has not been developed for IBEX specifically but that could be used for IBEX datasets (ASHLAR, WSIReg, VALIS, WARPY, and QuPath, etc). It would be nice if there was mention of those.

There is a concern about how the negative data information will be added, as no publication or peer-review process can back it up. Perhaps the particular conditions of the experiment should be very well described to allow future users to assess the validity. The proposed scheme where a reagent can be validated or recommended against by up to 4 different labs should be good. It may be good to make sure that researchers who validate belong to different labs and are not only different ORCID that belong to the same group. Similar to making a case of recommendations against a reagent.

It is very interesting to keep track of the protocol versions used. Perhaps users should be able to validate independent versions and it will be important to know how information is kept.

The final point I would make is that the need to form a GitHub repository may deter some people from submitting data. For sporadic contributions, authors could think that users could either reach out to main developers and/or provide a submission form that can help less experienced users of command-line and GitHub programming, but still promote the contribution from the community.

I am keen to see how the KB evolves and how it helps disseminate the use of this and other great techniques.

Reviewer #2 (Public review):

Summary:

The paper introduces the IBEX Knowledge-Base (KB), a shared online resource designed to help scientists working with immunofluorescence imaging. It acts as a central hub where researchers can find and share information about reagents, protocols, and imaging methods. The KB is not static like traditional publications; instead, it evolves as researchers contribute new findings and refinements. A key highlight is that it includes results of both successful and unsuccessful experiments, helping scientists avoid repeating failed experiments and saving time and resources. The platform is built on open-access tools ensuring that the information remains available to everyone. Overall, the KB aims to collaboratively accelerate research, improve reproducibility, and reduce wasted effort in imaging experiments.

Strengths:

(1) The IBEX KB is built entirely on open-source tools, ensuring accessibility and long-term sustainability. This approach aligns with FAIR data principles and ensures that the KB remains adaptable to future advancements.

(2) The KB also follows strict data organization standards, ensuring that all information about reagents and protocols is clearly documented and easy to find with little ambiguity.

(3) The KB allows scientists to report both positive and negative results, reducing duplication of effort and speeding up the research process.

(4) The KB is helpful for all researchers, but even more so for scientists in resource-limited settings. It provides guidance on finding affordable alternatives to expensive or discontinued reagents, making it easier for researchers with fewer resources to perform high-quality experiments.

(5) The KB includes a community discussion forum where scientists can ask for advice, share troubleshooting tips, and collaborate with others facing similar challenges.

Weaknesses:

(1) The potential impact of IBEX KB is very clear. However, the paper would benefit by also discussing more on KB maintenance and outreach, and how higher participation could be incentivized.

(2) Use of resources like GitHub may limit engagement from non-coding members of the scientific community. Will there be alternative options like a user-friendly web interface to contribute more easily?

Reviewer #3 (Public review):

Summary:

The authors have developed an interactive knowledge-base that uses crowdsourcing information on antibodies and reagents for immunofluorescence imaging.

Strengths:

The authors provide an extremely relevant and needed interphase for a community-based IF reagent and protocol knowledgebase, and a well-built interface. All the links on their website work, the information provided, reagents, datasets, videos, and protocols are very informative. The instructions for the community researchers to contribute are clear and they provide detailed instructions on how to technically proceed.

Weaknesses:

Reporting of the validation of antibodies could be improved. To increase public participation they suggest reducing the amount of details that one needs to submit to claim that something does not work. However, in our experience, this information is critical to be shared with the community.

Reviewer #1 (Public review):

Summary:

In this study, Le et al.. aimed to explore whether AAV-mediated overexpression of Oct4 could induce neurogenic competence in adult murine Müller glia, a cell type that, unlike its counterparts in cold-blooded vertebrates, lacks regenerative potential in mammals. The primary goal was to determine whether Oct4 alone, or in combination with Notch signaling inhibition, could drive Müller glia to transdifferentiate into bipolar neurons, offering a potential strategy for retinal regeneration.

The authors demonstrated that Oct4 overexpression alone resulted in the conversion of 5.1% of Müller glia into Otx2+ bipolar-like neurons by five weeks post-injury, compared to 1.1% at two weeks. To further enhance the efficiency of this conversion, they investigated the synergistic effect of Notch signaling inhibition by genetically disrupting Rbpj, a key Notch effector. Under these conditions, the percentage of Müller glia-derived bipolar cells increased significantly to 24.3%, compared to 4.5% in Rbpj-deficient controls without Oct4 overexpression. Similarly, in Notch1/2 double-knockout Müller glia, Oct4 overexpression increased the proportion of GFP+ bipolar cells from 6.6% to 15.8%.

To elucidate the molecular mechanisms driving this reprogramming, the authors performed single-cell RNA sequencing (scRNA-seq) and ATAC-seq, revealing that Oct4 overexpression significantly altered gene regulatory networks. They identified Rfx4, Sox2, and Klf4 as potential mediators of Oct4-induced neurogenic competence, suggesting that Oct4 cooperates with endogenously expressed neurogenic factors to reshape Müller glia identity.

Overall, this study aimed to establish Oct4 overexpression as a novel and efficient strategy to reprogram mammalian Müller glia into retinal neurons, demonstrating both its independent and synergistic effects with Notch pathway inhibition. The findings have important implications for regenerative therapies as they suggest that manipulating pluripotency factors in vivo could unlock the neurogenic potential of Müller glia for treating retinal degenerative diseases.

Strengths:

(1) Novelty: The study provides compelling evidence that Oct4 overexpression alone can induce Müller glia-to-bipolar neuron conversion, challenging the conventional view that mammalian Müller glia lacks neurogenic potential.

(2) Technological Advances: The combination of Muller glia-specific labeling and modifying mouse line, AAV-GFAP promoter-mediated gene expression, single-cell RNA-seq, and ATAC-seq provides a comprehensive mechanistic dissection of glial reprogramming.

(3) Synergistic Effects: The finding that Oct4 overexpression enhances neurogenesis in the absence of Notch signaling introduces a new avenue for retinal repair strategies.

Weaknesses:

(1) In this study, the authors did not perform a comprehensive functional assessment of the bipolar cells derived from Müller glia to confirm their neuronal identity and functionality.

(2) Demonstrating visual recovery in a bipolar cell-deficiency disease model would significantly enhance the translational impact of this work and further validate its therapeutic potential.

Reviewer #2 (Public review):

Summary:

The authors harness single-cell RNAseq data from zebrafish and mice to identify Oct4 as a candidate driver of neurogenesis. They then use adeno-associated virus vectors to show that while Oct4 overexpression alone converts rare adult Müller glia (MG) to bipolar cells, it synergizes with Notch pathway inhibition to cause this neurogenesis (achieved by Cre-mediated knockout of Rbpj floxed allele). Importantly, they genetically lineage-mark adult MG using a GLAST-CreER transgene and a Sun-GFP reporter, so that any non-MG cells that convert can be identified unambiguously. This is crucial because several high-profile papers made erroneous claims using short promoters in the viral delivery vector itself to mark MG, but those promoters are leaky and mark other non-MG cell types, making it impossible to definitively state whether manipulations studied were actually causing neurogenesis, or were merely the result of expression in pre-existing neurons. Once the authors establish Oct4 + RbpjKO synergy they use snRNAseq/ATACseq to identify known and novel transcription factors that could play a role in driving neurogenesis.

Strengths:

The system to mark MG is stringent, so the authors are studying transdifferentiation, not artifactual effects due to leaky viral promoters. The synergy between Oct4 and Notch pathway blockade is notable. The single-cell results add the potential involvement of new players such as Rfx4 in adult-MG-neurogenesis.

Weaknesses:

The existing version is difficult to read due to an unusually high number of text errors (e.g. references to the wrong figure panels etc.). A fuller explanation for the fraction of non-MG cells seen in control scRNAseq assays is required, particularly because the neurogenic trajectory which is enhanced in the Oct4/Rbpj-KO context is also evident in the control retina. Claims regarding the involvement of transcription factors in adult neurogenesis (such as Rfx4) need to be toned down unless they are backed up with functional data. It is possible that such factors are important, but equally, they may have no role or a redundant role, and without functional tests, it's impossible to say one way or the other.

Overall, the authors achieved what they set out to do, and have made new insights into how neurogenesis can be stimulated in MG. Ultimately, a major long-term goal in the field is to replace lost photoreceptors as this is most relevant to many human visual disorders, and while this paper (like all others before it) does not generate rods or cones, it opens new strategies to coax MG to form a related neuronal cell type. Their approach underscores the benefits of using a gold-standard approach for lineage tracing.

Reviewer #1 (Public review):

The paper by Fournier et al. investigates the sensitivity of neural circuits to changes in intrinsic and synaptic conductances. The authors use models of the stomatogastric ganglion (STG) to compare how perturbations to intrinsic and synaptic parameters impact network robustness. Their main finding is that changes to intrinsic conductances tend to have a larger impact on network function than changes to synaptic conductances, suggesting that intrinsic parameters are more critical for maintaining circuit function.

The paper is well-written, and the results are compelling. The authors addressed most of the minor comments I had and improved the manuscript.

However, it remains unclear how general the results are and what the underlying mechanism is. Regarding generality, the authors changed the title and added a sentence in the discussion. At this point, they do not claim generality beyond the specific function they explore in the STG circuit. While this is acceptable, I still believe the paper would be much more insightful if it provided a more general statement and investigated the mechanism behind why, in their hands, synaptic parameters appear more resilient to changes than intrinsic parameters.

Reviewer #1 (Public review):

Summary:

This study takes a detailed approach to understand the effect of menopausal hormone therapy (MHT) in brain aging of females. Neuroimaging data from the UK Biobank is used to explore brain aging and shows an unexpected effect of current MHT use and poorer brain health outcomes relative to never users. There is considerable debate about the benefits of MHT and estrogens in particular for brain health, and this analysis illustrates thta the effects are certainly not straight forward and require greater considerations.

Strengths:

(1) The detailed approach to obtain important information about MHT use from primary care records. Prior studies have suggested that factors such as estrogen/progestin type, route of administration, duration, and timing of use relative to menopause onset can contribute to whether MHT benefits brain health.<br /> (2) Consideration of type of menopause (spontaneous, or surgical) in the analysis, as well as sensitivity diagnoses to rule out the effect being driven by those with clinical conditions<br /> (3) The incorporation of the brain age estimate along with hippocampal volume to address brain health<br /> (4) The complex data are also well explained and interpretations are reasonable.<br /> (5) Limitations of the UKbiobank data are acknowledged

Weaknesses:

These have since been addressed by the authors in the revision.

Reviewer #2 (Public review):

Summary:

In this observational study, Barth et al. investigated the association between menopausal hormone therapy and brain health in middle- to older-aged women from the UK Biobank. The study evaluated detailed MHT data (never, current, or past user), duration of mHT use (age first/last used), history of hysterectomy with or without bilateral oophorectomy, APOEE4 genotype, and brain characteristics in a large, population-based sample. The researchers found that current mHT use (compared to never-users), but not past use, was associated with a modest increase in gray and white matter brain age gap (GM and WM BAG) and decrease in hippocampal volumes. No significant association was found between the age of mHT initiation and brain measures among mHT users. Longer duration of use and older age at last MHT use post-menopause were associated with higher GM and WM BAG, larger WMH volumes, and smaller hippocampal volumes. In a sub-sample, after adjusting for multiple comparisons, no significant associations were found between detailed mHT variables (formulations, route of administration, dosage) and brain measures. The association between mHT variables and brain measures was not influenced by APOEE4 allele carrier status. Women with a history of hysterectomy with or without bilateral oophorectomy had lower GM BAG compared to those without such history. Overall, these observational data suggest that the association between mHT use and brain health in women may vary depending on the duration of use and surgical history.

Strengths:

The study has several strengths, including a large, population-based sample of women in the UK, and comprehensive details of demographic variables such as menopausal status, history of oophorectomy/hysterectomy, genetic risk factors for Alzheimer's disease (APOE ε4 status), age at mHT initiation, age at last use, duration of mHT, and brain imaging data (hippocampus and WMH volume).

In a sub-sample, the study accessed detailed mHT prescription data (formulations, route of administration, dosage, duration), allowing the researchers to study how these variables were associated with brain health outcomes. This level of detail is generally missing in observational studies investigating the association of mHT use with brain health.

Weaknesses:

While the study has many strengths, it also has some weaknesses. These weaknesses were properly discussed throughout the article. The manuscript has indicated that the need of mHT use which might be associated with these symptoms may be indicators of preexisting neurological changes, potentially reflecting worse brain health scores, including higher BAG and lower hippocampal volume and/or higher WMH. The authors noted that the UK Biobank lacks detailed information on menopausal symptoms and perimenopausal staging, limiting the study's ability to understand how these variables influence outcomes. The authors also highlighted that these results don't reflect causal relationships. The authors caution that these findings should not guide individual-level decisions regarding the benefits versus risks of mHT use. However, the study raises new questions that should be addressed by randomized clinical trials to investigate the varying effects of MHT on brain health and dementia risk.

Reviewer #1 (Public review):

Summary:

The author studied metabolic networks for central metabolism, focusing on how system trajectories returned to their steady state. To quantify the response, systematic perturbation was performed in simulation and the maximal destabilization away from steady state (compared with initial perturbation distance) was characterized. The author analyzed the perturbation response and found that sparse network and networks with more cofactors are more "stable", in the sense that the perturbed trajectories have smaller deviation along the path back to the steady state.

Strengths and major contributions:

The author compared three metabolic models and performed systematic perturbation analysis in simulation. This is the first work characterized how perturbed trajectories deviate from equilibrium in large biochemical systems and illustrated interesting findings about the difference between sparse biological systems and randomly simulated reaction networks.

Discussion and impact for the field:

Metabolic perturbation is an important topic in cell biology and has important clinical implication in pharmacodynamics. The computational analysis in this study provides an initiative for future quantitative analysis on metabolism and homeostasis.

Comments on latest version:

In the latest version of this work, the author included NADH, NADPH into the analysis, and perform some comparison about sensitivity analysis. I think this paper is ready to be finalized, and many open questions inspired from this work can be studied in future.

Reviewer #2 (Public review):

The authors have conducted a valuable comparative analysis of perturbation responses in three nonlinear kinetic models of E. coli central carbon metabolism found in the literature. They aimed to uncover commonalities and emergent properties in the perturbation responses of bacterial metabolism. They discovered that perturbations in the initial concentrations of specific metabolites, such as adenylate cofactors and pyruvate, significantly affect the maximal deviation of the responses from steady-state values. Furthermore, they explored whether the network connectivity (sparse versus dense connections) influences these perturbation responses. The manuscript is reasonably well written.

Comments on latest version:

The authors have adequately addressed my concerns.

Reviewer #1 (Public review):

Summary:

The authors examine the role of the medial prefrontal cortex (mPFC) in cognitive control, i.e. the ability to use task-relevant information and ignore irrelevant information, in the rat. According to the central-computation hypothesis, cognitive control in the brain is centralized in the mPFC and according to the local hypothesis, cognitive control is performed in task-related local neural circuits. Using the place avoidance task which involves cognitive control, it is predicted that if mPFC lesions affect learning, this would support the central computation hypothesis whereas no effect of lesions would rather support the local hypothesis. The authors thus examine the effect of mPFC lesions in learning and retention of the place avoidance task. They also look at functional interconnectivity within a large network of areas that could be activated during the task by using cytochrome oxydase, a metabolic marker. In addition, electrophysiological unit recordings of CA1 hippocampal cells are made in a subset of (mPFC-lesioned or intact) animals to evaluate overdispersion, a firing property that reflects cognitive control in the hippocampus. The results indicate that mPFC lesions disrupted correlations of activity between functionally-related regions. Behaviorally, lesions did not impair place avoidance learning and retention (though flexibility was altered during conflict training). In addition, hippocampal place cell overdispersion was decreased in lesioned rats only in the absence of cognitive control challenge (pretraining). Cognitive control seen in hippocampal place cell activity (alternation of frame-specific firing) was not affected by the lesion. Overall, the absence of effects of mPFC lesions on cognitive control in the task or in hippocampal place cells firing support the local hypothesis.

Strengths:

Straightforward hypothesis: clarification of the involvement of the mPFC in the brain is expected and achieved. Appropriate use of fully mastered methods (active place avoidance task, electrophysiological unit recordings, measure of metabolic marker cytochrome oxidase) and rigorous analysis of the data. The conclusion is strongly supported by the data.

Weaknesses:

No notable weaknesses in the conception, making of the study and data analysis.

Comments on revisions:

The authors have satisfactorily addressed all my comments in the revised version.

Reviewer #2 (Public review):

Park et al. set out to test two competing hypotheses about the role of the medial prefrontal cortex (PFC) in cognitive control, the ability to use task-relevant cues and ignore task-irrelevant cues to guide behavior. The "central computation" hypothesis assumes that cognitive control relies on computations performed by the PFC, which then interacts with other brain regions to accomplish the task. Alternatively, the "local computation" hypothesis suggests that computations necessary for cognitive control are carried out by other brain regions that have been shown to be essential for cognitive control tasks, such as the dorsal hippocampus and the thalamus. If the central computation hypothesis is correct, PFC lesions should disrupt cognitive control. Alternatively, if the local computation hypothesis is correct, cognitive control would be spared after PFC lesions. The task used to assess cognitive control is the active place avoidance task in which rats must avoid a sector of a rotating arena using the stationary room cues and ignoring the local olfactory cues on the rotating platform. Performance on this task has previously been shown to be disrupted by hippocampal lesions and hippocampal ensembles dynamically represent the room and arena depending on the animal's proximity to the shock zone. They found no group (lesion vs. sham) differences in the three behavioral parameters tested: distance traveled, latency to enter the shock zone, and number of shock zone entries for both the standard task and the "conflict" task in which the shock zone was rotated by 180 degrees. The only significant difference was the savings index; the lesion group entered the new shock zone more often than the sham group during the first 5 minutes of the second conflict session. This deficit was interpreted as a cognitive flexibility deficit rather than a cognitive control failure. Next, the authors compared cytochrome oxidase activity between sham and lesion groups in 14 brain regions and found that only the amygdala shows significant elevation in the lesion vs. sham group. Pairwise correlation analysis revealed a striking difference between groups, with many correlations between regions lost in the lesion group (between reuniens and hippocampus, reuniens and amygdala and a correlation between dorsal CA1 and central amygdala that appeared in the lesion group and were absent in the sham group. Finally, the authors assessed dorsal hippocampal representations of the spatial frame (arena vs. room) and found no differences between lesion and sham groups. The only difference in hippocampal activity was reduced overdispersion in the lesion group compared to the sham group on the pretraining session only and this difference disappeared after the task began. Collectively, the authors interpret their findings as supporting the local computation hypothesis; computations necessary for cognitive control occur in brain regions other than the PFC.

Strengths:

The data were collected in a rigorous way with experimental blinding and appropriate statistical analyses.<br /> Multiple approaches were used to assess differences between lesion and sham groups, including behavior, metabolic activity in multiple brain regions, and hippocampal single unit recording.

Weaknesses:

Only male rats were used with no justification provided for excluding females from the sample.

The conceptual framework used to interpret the findings was to present two competing hypotheses with mutually exclusive predictions about the impact of PFC lesions on cognitive control. The authors then use mainly null findings as evidence in support of the local computation hypothesis. They acknowledge that some people may question the notion that the active place avoidance task indeed requires cognitive control, but then call the argument "circular" because PFC has to be involved in cognitive control. This assertion does not address the possibility that the active place avoidance task simply does not require cognitive control.

The authors did not link the CO activity with the behavioral parameters even though the CO imaging was done on a subset of the animals that ran the behavioral task nor do they make any attempt to interpret these findings in light of the two competing hypotheses posed in the introduction. Moreover, the discussion is lacking any mechanistic interpretations of the findings. For example, there are no attempts to explain why amygdala activity and its correlation with dCA1 activity might be higher in the PFC lesioned group.

Publishing null results is important to avoid wasting animals, time, and money. This study's results will have a significant impact on how the field views the role of the PFC in cognitive control. Whether or not some people reject the notion that the active place avoidance task measures cognitive control, the findings are solid and can serve as a starting point for generating hypotheses about how brain networks change when deprived of PFC input.

Reviewer #3 (Public review):

Summary:

This study by Park and colleagues investigated how the medial prefrontal cortex (mPFC) influences behavior and hippocampal place cell activity during a two-frame active place avoidance task in rats. Rats learned to avoid the location of mild shock within a rotating arena, with the shock zone being defined relative to distal cues in the room. Permanent chemical lesions of the mPFC did not impair the ability to avoid the shock zone by using the distal cues and ignoring proximal cues in the arena. In parallel, hippocampal place cells alternated between two spatial tuning patterns, one anchored to the distal cues and the other to the proximal cues, and this alteration was not affected by the mPFC lesion. Based on these findings, the authors argue that the mPFC is not essential for differentiating between task-relevant and irrelevant information.

Strengths:

This study was built on substantial work by the Fenton lab that validated their two-frame active place avoidance task and provided sound theoretical and analytical foundations. Additionally, the effectiveness of mPFC lesions was validated by several measures, enabling the authors to base their argument on the lack of lesion effects on behavior and place cell dynamics.

Weaknesses:

The authors define cognitive control as "the ability to judiciously use task-relevant information while ignoring salient concurrent information that is currently irrelevant for the task." (Lines 77-78). This definition is much simpler than the one by Miller and Cohen: "the ability to orchestrate thought and action in accordance with internal goals (Ref. 1)" and by Robbins: "processes necessary for optimal scheduling of complex sequence of behaviour." (Dalley et al., 2004, PMID: 15555683). Differentiating between task-relevant and irrelevant information is required in various behavioral tasks, such as differential learning, reversal learning, and set-shifting tasks. Previous rodent behavioral studies have shown that the integrity of the mPFC is necessary for set-shifting but not for differential or reversal learning (e.g., Enomoto et al., 2011, PMID: 21146155; Cho et al., 2015, PMID: 25754826). In the present task design, the initial training is a form of differential learning between proximal and distal cues, and the conflict training is akin to reversal learning. Therefore, the lack of lesion effects is somewhat expected. It would be interesting to test whether mPFC lesions impair set-shifting in their paradigm (e.g., the shock zone initially defined by distal cues and later by proximal cues). If the mPFC lesions do not impair this ability and associated hippocampal place dynamics, it will provide strong support for the authors' local-computation hypothesis.

Comments on revisions:

The authors fully addressed my comments. I do not have any additional suggestions.

Reviewer #1 (Public review):

Summary:

In this manuscript by Obray et al., the authors show that adolescent ethanol exposure increases mechanical allodynia in adulthood. Additionally, the show that BLA mediated inhibition of prelimbic cortex is reduced, resulting in increased excitability in neurons that then project to vlPAG. This effect was mediated by BLA inputs onto PV interneurons. The primary finding of the manuscript is that these AIE induced changes further impact acute pain processing in the BLA-PrL-vlPAG circuit, albeit behavioral readouts after inducing acute pain were not different between AIE rats and controls. These results provide novel insights into how AIE can have long lasting effects on pain-related behaviors and neurophysiology.In this manuscript by Obray et al., the authors show that adolescent ethanol exposure increases mechanical allodynia in adulthood. Additionally, the show that BLA mediated inhibition of prelimbic cortex is reduced, resulting in increased excitability in neurons that then project to vlPAG. This effect was mediated by BLA inputs onto PV interneurons. The primary finding of the manuscript is that these AIE induced changes further impact acute pain processing in the BLA-PrL-vlPAG circuit, albeit behavioral readouts after inducing acute pain were not different between AIE rats and controls. These results provide novel insights into how AIE can have long lasting effects on pain-related behaviors and neurophysiology.

The manuscript was very well written and the experiments were rigorously conducted. The inclusion of both behavioral and neurophysiological circuit recordings was appropriate and compelling. The authors analyzed their data extensively, and consider how many different factors may influence physiological activity and downstream behavior. The attention to SABV and appropriate controls was well thought out. The Discussion provided novel ideas for how to think about AIE and chronic pain, and proposed several interesting mechanisms. This was a very well executed set of experiments.

Comments on revisions:

The authors have addressed the concerns raised by the reviewers. Excellent work!

Reviewer #2 (Public review):

Summary:

The study by Obray et al. entitled "Adolescent alcohol exposure promotes mechanical allodynia and alters synaptic function at inputs from the basolateral amygdala to the prelimbic cortex" investigated how adolescent intermittent ethanol exposure (AIE) affects the BLA -> PL circuit, with an emphasis on PAG projecting PL neurons, and how AIE changes mechanical and thermal nociception. The authors found that AIE increased mechanical, but not thermal nociception, and an injection of an inflammatory agent did not produce changes in an ethanol-dependent manner. Physiologically, a variety of AIE-specific effects were found in PL neuron firing at BLA synapses, suggestive of AIE-induced alterations in neurotransmission at BLA-PVIN synapses.

Strengths:

This was a comprehensive examination of the effects of AIE on this neural circuit, with an in-depth dissection of the various neuronal connections within the PL.

Sex was included as a biological variable, yet, there were little to no sex differences in AIE's effects, suggestive of similar adaptations in males and females.

Comments on revisions:

The authors addressed the reviews from the first submission which has substantially strengthened the conclusions of the study, including acknowledgement of unanswered questions for future studies to address.

Reviewer #3 (Public review):

Summary:

Obray et al. investigate the long-lasting effects of adolescent intermittent ethanol (AIE) in rats, a model of alcohol dependence, on a neural circuit within prefrontal cortex. The studies are focused on inputs from the basolateral amygdala (BLA) onto parvalbumin (PV) interneurons and pyramidal cells that project to the periaqueductal gray (PAG). The authors found that AIE increased BLA excitatory drive onto parvalbumin interneurons and increased BLA feedforward inhibition onto PAG-projecting neurons.

Strengths:

Fully powered cohorts of male and female rodents are used, and the design incorporates both AIE and an acute pain model. The authors used several electrophysiological techniques to assess synaptic strength and excitability from a few complimentary angles. The design and statistical analysis are sound, and the evidence supporting synaptic changes following AIE results is convincing. The authors have also revised the Discussion to assimilate the findings within prior work out of their lab and others.

Weaknesses:

(1) There is incomplete evidence supporting some of the conclusions drawn in this manuscript. The authors claim the changes in feedforward inhibition onto pyramidal cells are due to the changes in parvalbumin interneurons; however, the authors did not determine that PV cells mediate the feedforward BLA op-IPSCs and changes following AIE (this would require a manipulation to reduce/block PV-IN activity). This limitation in results and interpretation is important because prior work shows BLA-PFC feedforward IPSCs can be driven by somatostatin cells. Cholecystokinin cells are also abundant basket cells in PFC and have been recently shown to mediate feedforward inhibition from thalamus and ventral hippocampus, so it's also possible that CCK cells are involved in the effects observed here

(2) The authors conclude that the changes in this circuit likely mediate long-lasting hyperalgesia, but this is not addressed experimentally. In some ways, the focused nature of the study is a benefit in this regard, as there is extensive prior literature linking this circuit with pain behaviors in alternative models (e.g., SNI), but it should be noted that these studies have not assessed hyperalgesia stemming from prior alcohol exposure. While the current studies do not include a causative behavioral manipulation, the strength of the association between BLA-PL-PAG function and hyperalgesia could be bolstered by with current data if there were relationships detected between electrophysiological properties and hyperalgesia.

(3) It should be noted that asEPSC frequency can also reflect changes in number of functional/detectable synapses. This measurement is also fairly susceptible to differences in inter-animal differences in ChR2 expression. There are other techniques for assessing presynaptic release probability (e.g., PPR, MK-801 sensitivity) that would improve the interpretation of these studies if that is intended to be a point of emphasis.

Reviewer #1 (Public review):

Summary:

This is a convincing description of approximately ten years of funding from the NIH BRAIN initiative. It is of particular value at this moment in history, given the cataclysmic changes in the US government structure and function occurring in early 2025.

Strengths:

The paper contains a fair bit of documentation so that the curious reader can actually parse what this BRAIN program funded.

Weaknesses:

There are too many acronyms, and the manuscript reads as if it were an internal NIH document, where the audience knows all of the NIH nomenclature and program details. It is not particularly friendly to the outside, lay reader.

Reviewer #2 (Public review):

Summary:

The authors provide an important summary of ten years of Brain Initiative funding including a description of the historical development of the initiative, the specific funding mechanisms utilized, and examples of grants funded and work produced. The authors also conduct analyses of the impact on overall funding in Systems and Computational Neuroscience, the raw and field normalized bibliographic impact of the work, the social media impact of the funded work, and the popularity of some tools developed.

Strengths:

This is a useful perspective on an important funding initiative over a ten-year period. It is clearly written and the illustrations and analyses are mostly useful for understanding the impact of the initiative.

Weaknesses:

The major limitation is that the bibliographic analysis does not provide a comparison group of funded grants. Because work that successfully competes for funding is likely to be more impactful than all work in a given area, the normalization of citations to field medians may reflect this "grant review" effect, rather than anything special about the Brain Initiative. Hopefully, this speculation is incorrect (I would guess that it is), but it would be helpful to try to demonstrate this more directly by including a funded comparison group.

There are also minor inconsistencies in the numbering of the figures that need to be cleared up.

Reviewer #1 (Public review):

Summary:

In this useful narrative, the authors attempt to capture their experience of the success of team projects for the scientific community.

Strengths:

The authors are able to draw on a wealth of real-life experience reviewing, funding, and administering large team projects, and assessing how well they achieve their goals.

Weaknesses:

The utility of the RCR as a measure is questionable. I am not sure if this really makes the case for the success of these projects. The conclusions do not depend on Figure 1.

Reviewer #2 (Public review):

Summary:

The authors review the history of the team projects within the Brain initiative and analyze their success in progression to additional rounds of funding and their bibliographic impact.

Strengths:

The history of the team projects and the fact that many had renewed funding and produced impactful papers is well documented.

Weaknesses:

The core bibliographic and funding impact results have largely been reported in the companion manuscript and so represent "double dipping" I presume the slight disagreement in the number of grants (by one) represents a single grant that was not deemed to address systems/computational neuroscience. The single figure is relatively uninformative. The domains of study are sufficiently large and overlapping that there seems to be little information gained from the graphic and the Sankey plot could be simply summarized by rates of competing success.

Reviewer #1 (Public review):

This computational study builds on a previous study (Liu et al) from the Marder lab from 1998, where a model was proposed that demonstrated activity-dependent homeostatic recovery of activity in individual bursting neurons, based on three "sensors" of intrinsic calcium concentration. The original model modified levels of ion channel conductances. The current model builds on that and adds activity-dependent modifications of the voltage-dependence of these ionic currents, implemented to happen concurrently with maximum conductance levels, but at a different timescale. The faster timescale change in voltage dependence is justified by the assumption that such changes can occur by neuromodulatory chemicals or similar second messenger-based mechanisms that presumably act at a faster rate than the regulation of channel densities. The main finding is that the difference in timescales between the two homeostatic mechanisms (channel density vs. voltage dependence) could result in distinct subsets of parameters, depending on how fast the second messenger mechanisms operate.

This study is an interesting and noteworthy extension of the theoretical ideas proposed by the classic study of Liu et al, 1998. It addresses a very important question: How do two known mechanisms of modifications of neuronal activity that occur at different timescales interact within an activity-dependent homeostatic framework? However, the study and its presentation have some major shortcomings that should be addressed to strengthen the claim.

Major comments:

(1) The main issue that I have with this study is the lack of exploration of "why" the model produces the results it does. Considering this is a model, it should be possible to find out why the three timescales of half-act/inact parameter modifications lead to different sets of results. Without this, it is simply an exploratory exercise. (The model does this, but we do not know the mechanism.) Perhaps this is enough as an interesting finding, but it remains unconvincing and (clearly) does not have the impact of describing a potential mechanism that could be potentially explored experimentally.

(2) A related issue is the use of bootstrapping to do statistics for a family of models, especially when the question is in fact the width of the distribution of output attributes. I don't buy this. One can run enough models to find say N number of models within a tight range (say 2% cycle period) and the same N number within a loose range (say 20%) and compare the statistics within the two groups with the same N.

(3) The third issue is that many of the results that are presented (but not the main one) are completely expected. If one starts with gmax values that would never work (say all of them 0), then it doesn't matter how much one moves the act/inact curves one probably won't get the desired activity. Alternately, if one starts with gmax values that are known to work and randomizes the act/inact midpoints, then the expectation would be that it converges to something that works. This is Figure 1 B and C, no surprise. But it should work the other way around too. If one starts with random act/inact curves that would never work and fixes those, then why would one expect any set of gmax values would produce the desired response? I can easily imagine setting the half-act/inact values to values that never produce any activity with any gmax.

(4) A potential response to my previous criticism would be that you put reasonable constraints on gmax's or half-act/inact values or tie the half-act to half-inact. But that is simply arbitrary ad hoc decisions made to make the model work, much like the L8-norm used to amplify some errors. There is absolutely no reason to believe this is tied to the biology of the system.

(5) The discussion of this manuscript is at once too long and not adequate. It goes into excruciating detail about things that are simply not explored in this study, such as phosphorylation mechanisms, justification of model assumptions of how these alterations occur, or even the biological relevance. (The whole model is an oversimplification - lack of anatomical structure, three calcium sensors, arbitrary assumptions, and how parameter bounds are implemented.) Lengthy justifications for why channel density & half-act/inact of all currents are obeying the same time constant are answering a question that no one asked. It is a simplified model to make an important point. The authors should make these parts concise and to the point. More importantly, the authors should discuss the mechanism through which these differences may arise. Even if it is not clear, they should speculate.

(6) There should be some justification or discussion of the arbitrary assumptions made in the model/methods. I understand some of this is to resolve issues that had come up in previous iterations of this approach and in fact the Alonso et al, 2023 paper was mainly to deal with these issues. However, some level of explanation is needed, especially when assumptions are made simply because of the intuition of the modeler rather than the existence of a biological constraint or any other objective measure.

Reviewer #2 (Public review):

Summary:

In this study, Mondal and co-authors present the development of a computational model of homeostatic plasticity incorporating activity-dependent regulation of gating properties (activation, inactivation) of ion channels. The authors show that, similar to what has been observed for activity-dependent regulation of ion channel conductances, implementing activity-dependent regulation of voltage sensitivity participates in the achievement of a target phenotype (bursting or spiking). The results however suggest that activity-dependent regulation of voltage sensitivity is not sufficient to allow this and needs to be associated with the regulation of ion channel conductances in order to reliably reach the target phenotype. Although the implementation of this biologically relevant phenomenon is undeniably relevant, the main conclusions of the paper and the insights brought by this computational work are difficult to grasp.

Strengths:

(1) Implementing activity-dependent regulation of gating properties of ion channels is biologically relevant.

(2) The modeling work appears to be well performed and provides results that are consistent with previous work performed by the same group.

Weaknesses:

(1) The writing is rather confusing, and the state of the art explaining the need for the study is unclear.

(2) The main outcomes and conclusions of the study are difficult to grasp. What is predicted or explained by this new version of homeostatic regulation of neuronal activity?

Reviewer #3 (Public review):

Mondal et al. use computational modeling to investigate how activity-dependent shifts in voltage-dependent (in)activation curves can complement activity-dependent changes in ion channel conductance to support homeostatic plasticity. While changes in the voltage-dependent properties of ion channels are known to modulate neuronal excitability, their role as a homeostatic plasticity mechanism interacting with channel conductance has been largely unexplored. The results presented here demonstrate that activity-dependent regulation of voltage-dependent properties can interact with plasticity in channel conductance to allow neurons to attain and maintain target activity patterns, in this case, intrinsic bursting. These results also show that the rate of channel voltage-dependent shifts can influence steady-state parameters reached as the model stabilizes into a stable intrinsic bursting state. That is, the rate of these modifications shapes the range of channel conductances and half-(in)activation parameters as well as activity characteristics such as burst period and duration. A major conclusion of the study is that altering the timescale of channel voltage dependence can seamlessly shift a neuron's activity characteristics, a mechanism that the authors argue may be employed by neurons to adapt to perturbations. While the study's conclusions are mostly well-supported, additional analyses, and simulations are needed.

(1) A main conclusion of this study is that the speed at which (in)activation dynamics change determines the range of possible electrical patterns. The authors propose that neurons may dynamically regulate the timescale of these changes (a) to achieve alterations in electrical activity patterns, for example, to preserve the relative phase of neuronal firing in a rhythmic network, and (b) to adapt to perturbations. The results presented in Figure 4 clearly demonstrate that the timescale of (in)activation modifications impacts the range of activity patterns generated by the model as it transitions from an initial state of no activity to a final steady-state intrinsic burster. This may have important implications for neuronal development, as discussed by the authors.

However, the authors also argue that the model neuron's dynamics - such as period, and burst duration, etc - could be dynamically modified by altering the timescale of (in)activation changes (Figure 6 and related text). The simulations presented here, however, do not test whether modifications in this timescale can shift the model's activity features once it reaches steady state. In fact, it is unlikely that this would be the case since, at steady-state, calcium targets are already satisfied. It is likely, however, as the authors suggest, that the rate at which (in)activation dynamics change may be important for neuronal adaptation to perturbations, such as changes in temperature or extracellular potassium. Yet, the results presented here do not examine how modifying this timescale influences the model's response to perturbations. Adding simulations to characterize how alterations in the rate of (in)activation dynamics affect the model's response to perturbations-such as transiently elevated extracellular potassium (Figure 5) - would strengthen this conclusion.

(2) Another key argument in this study is that small, coordinated changes in channel (in)activation contribute to shaping neuronal activity patterns, but that, these subtle effects may be obscured when averaging across a population of neurons. This may be the case; however, the results presented don't clearly demonstrate this point. This point would be strengthened by identifying correlations, if they exist, between (in)activation curves, conductance, and the resulting bursting patterns of the models for the simulations presented in Figure 2 and Figure 4, for example. Alternatively, or additionally, relationships between (in)activation curves could be probed by perturbing individual (in)activation curves and quantifying how the other model parameters compensate, which could clearly illustrate this point.

Reviewer #1 (Public review):

Summary:

Inhibitory hM4Di and excitatory hM3Dq DREADDs are currently the most commonly utilized chemogenetic tools in the field of nonhuman primate research, but there is a lack of available information regarding the temporal aspects of virally-mediated DREADD expression and function. Nagai et al. investigated the longitudinal expression and efficacy of DREADDs to modulate neuronal activity in the macaque model. The authors demonstrate that both hM4Di and hM3Dq DREADDs reach peak expression levels after approximately 60 days and are stably expressed for a period of at least 1.5 years in the macaque brain. During this period, DREADDs effectively modulated neuronal activity, as evidenced by a variety of measures, including behavioural testing, functional imaging, and/or electrophysiological recording. Notably, some of the data suggest that DREADD expression may decline after two years. This is a novel finding and has important implications for the utilization of this technology for long-term studies, as well as its potential therapeutic applications. Lastly, the authors highlight that peak DREADD expression may be significantly influenced by the choice of viral titer and the expressed protein tag, emphasizing the importance of careful design and selection of viral constructs for neuroscientific research. This study represents a critical step in the field of chemogenetics, setting the scene for future development and optimization of this technology.

Strengths:

The longitudinal approach of this study provides important preliminary insights into the long-term utility of chemogenetics, which has not yet been thoroughly explored.

The data presented are novel and inclusive, relying on well-established in vivo imaging methods, as well as behavioral and immunohistochemical techniques. The conclusions made by the authors are generally supported by a combination of these techniques. In particular, the utilization of in vivo imaging as a non-invasive method is translationally relevant and likely to make an impact in the field of chemogenetics, such that other researchers may adopt this method of longitudinal assessment in their own experiments. Rigorous standards have been applied to the datasets, and the appropriate controls have been included where possible.

The number of macaque subjects (20) from which data was available is also notable. Behavioral testing was performed in 11 subjects, FDG-PET in 5, electrophysiology in 1, and [11C]DCZ-PET in 15. This is an impressive accumulation of work that will surely be appreciated by the growing community of researchers using chemogenetics in nonhuman primates.

The implication that chemogenetic effects can be maintained for up to 1.5-2 years, followed by a gradual decline beyond this period, is an important development in knowledge. The limited duration of DREADD expression may present an obstacle in the translation of chemogenetic technology as a potential therapeutic tool, and it will be of interest for researchers to explore whether this limitation can be overcome. This study therefore represents a key starting point upon which future research can build.

Weaknesses:

Overall, the conclusions of the paper are mostly supported by the data but may be overstated in some cases, and some details are also missing or not easily recognizable within the figures. The provision of additional information and analyses would be valuable to the reader and may even benefit the authors' interpretation of the data.

The conclusion that DREADD expression gradually decreases after 1.5-2 years is only based on a select few of the subjects assessed; in Figure 2, it appears that only 3 hM4Di cases and 2 hM3Dq cases are assessed after the 2-year timepoint. The observed decline appears consistent within the hM4Di cases, but not for the hM3Dq cases (see Figure 2C: the AAV2.1-hSyn-hM3Dq-IRES-AcGFP line is increasing after 2 years.)

Given that individual differences may affect expression levels, it would be helpful to see additional labels on the graphs (or in the legends) indicating which subject and which region are being represented for each line and/or data point in Figure 1C, 2B, 2C, 5A, and 5B. Alternatively, for Figures 5A and B, an accompanying table listing this information would be sufficient.

While the authors comment on several factors that may influence peak expression levels, including serotype, promoter, titer, tag, and DREADD type, they do not comment on the volume of injection. The range in volume used per region in this study is between 2 and 54 microliters, with larger volumes typically (but not always) being used for cortical regions like the OFC and dlPFC, and smaller volumes for subcortical regions like the amygdala and putamen. This may weaken the claim that there is no significant relationship between peak expression level and brain region, as volume may be considered a confounding variable. Additionally, because of the possibility that larger volumes of viral vectors may be more likely to induce an immune response, which the authors suggest as a potential influence on transgene expression, not including volume as a factor of interest seems to be an oversight.

The authors conclude that vectors encoding co-expressed protein tags (such as HA) led to reduced peak expression levels, relative to vectors with an IRES-GFP sequence or with no such element at all. While interesting, this finding does not necessarily seem relevant for the efficacy of long-term expression and function, given that the authors show in Figures 1 and 2 that peak expression (as indicated by a change in binding potential relative to non-displaced radioligand, or ΔBPND) appears to taper off in all or most of the constructs assessed. The authors should take care to point out that the decline in peak expression should not be confused with the decline in longitudinal expression, as this is not clear in the discussion; i.e. the subheading, "Factors influencing DREADD expression," might be better written as, "Factors influencing peak DREADD expression," and subsequent wording in this section should specify that these particular data concern peak expression only.

Reviewer #2 (Public review):

Summary

This paper reports histological, PET imaging, functional, and behavioural data evaluating the longevity of AAV2 infection in multiple brain areas of macaques in the context of DREADD experiments. The central aim is to provide unprecedented information about how long the expression of HM4di or HM3dq receptors is expressed and efficient in modulating brain functions after vector injections. The data show peak expression after 40 to 60 days of vector injection, and stable expressions for up to 1.5 years for hM4di, and that hM3dq remained mostly at 75% of peak after a year, declining to 50% after 2 years. DREADDs effectively modulated neuronal activity and behaviour for approximately two years, evaluated with behavioral testings, neural recordings, or FDG-PET. A statistical evaluation revealed that vector titers, DREADD type, and tags contribute to the measured peak level of DREADD expression.

The article presents a thorough discussion of the limitations and specificities of chemogenetic approaches in monkeys.

Strength

These are unique data, in non-human primates (NHP), an animal model that not only features physiological and immunological characteristics similar to humans but also contribute to neurobiological functional studies on a long timescale with experiments spanning months or years. This evaluation of the long-term efficacy of DREADDs will be very important for all laboratories using this approach in NHP but also for future use of such approach in experimental therapies. The longevity estimates are based on multiple approaches including behavioural and neurophysiological ones, thus providing information on the functional efficacy of DREADD expression.

Performing such evaluation requires specific tools like PET imaging that very few monkey labs have access to in the world. This study was done by the laboratory that has developed the radiotracer c11-DCZ used here, a radiotracer binding selectively to DREADDs and providing, using PET, quantitative in vivo measures of DREADD expression. This study and its data should thus be a reference in the field, providing estimates to plan future chemogenetic experiments.

Publishing databases of experimental outcomes in NHP DREADD experiments is crucial for the community because such experiments are rare, expensive, and long. It contributes to refining experiments and reducing the number of animals overall used in the domain.

Weaknesses

This study is a meta-analysis of several experiments performed in one lab. The good side is that it combined a large amount of data that might not have been published individually; the downside is that all things were not planned and equated, creating a lot of unexplained variances in the data. This was yet judiciously used by the authors, but one might think that planned and organized multicentric experiments would provide more information and help test more parameters, including some related to inter-individual variability, and particular genetic constructs.

Reviewer #3 (Public review):

Summary

This manuscript, from the developers of the novel DREADD-selective agonist DCZ (Nagai et al., 2020), utilizes a unique dataset where multiple PET scans in a large number of monkeys, including baseline scans before AAV injection, 30-120 days post-injection, and then periodically over the course of the prolonged experiments, were performed to access short- and long-term dynamics of DREADD expression in vivo, and to associate DREADD expression with the efficacy of manipulating the neuronal activity or behavior. The goal was to provide critical insights into the practicality and design of multi-year studies using chemogenetics and to elucidate factors affecting expression stability.

Strengths are systematic quantitative assessment of the effects of both excitatory and inhibitory DREADDs, quantification of both the short-term and longer-term dynamics, a wide range of functional assessment approaches (behavior, electrophysiology, imaging), and assessment of factors affecting DREADD expression levels, such as serotype, promoter, titer (concentration), tag, and DREADD type.

Minor weaknesses are related to a few instances of suboptimal phrasing, and some room for improvement in time course visualization and quantification. These would be easily addressed in a revision.

These findings will undoubtedly have a very significant impact on the rapidly growing but still highly challenging field of primate chemogenetic manipulations. As such, the work represents an invaluable resource for the community.

Reviewer #1 (Public review):

Summary:

The manuscript from Kaletsky et al is a response to a paper recently published by Craig Hunter's group (Gainey et al 2024). The Murphy lab has previously shown that learned avoidance of C. elegans to PA14 can be transmitted through four generations. In a series of detailed studies, they defined the mechanism of this transgenerational epigenetic inheritance (TEI), identifying both PA14 and C. elegans factors required for this effect (Moore et al., 2019, Kaletsky et al., 2020; Moore et al., 2021). PA14 produces a small RNA, P11, that is necessary and sufficient for transgenerational epigenetic inheritance of avoidance behaviour in C. elegans. In the worm, P11 decreases maco-1 expression, which in turn regulates daf-7.

In the study by Gainey et al (eLife 2024), the authors report their attempt at replicating the original findings of the Murphy lab using a modified experimental setup. The Gainey study observed avoidance of PA14 and upregulation of daf-7::GFP in the F1 progeny of trained parents, but not in subsequent generations. Importantly, although they examined a number of different deviations of the protocol, they did not repeat the original experiment using the exact protocol outlined in the Moore or Kaletsky papers. Nevertheless, the authors concluded that "this example of TEI is insufficiently robust for experimental investigations".

The manuscript by Kaletsky et al. attempts to provide an explanation as to why Gainey et al., were unable to observe transgenerational avoidance of PA14. They identify two discrepancies in the methodology used between the two studies and examine the possible impacts of these.

One of the primary differences in protocols between the two papers is how avoidance is measured. The Murphy group uses the traditional method of adding azide to bacterial spots on the choice plates to trap worms once they have come close to the food spot. The animals are on the plate for 1 hour but most have likely been immobilized before this time point. Gainey et al. omit the azide and instead shift animals to 4C after 30-60 minutes of exposure to immobilize the worms for counting. Kaletsky et al show that the choice of assay has a significant impact on measuring attraction and avoidance.

While Gainey et al., assert that the addition of azide had no discernable effect on the choice assay results, these data are not shown in their paper. Kaletsky et al. test these conditions head-to-head with the same 1 hour exposure time, showing that with azide, the initial response to PA14 in untrained worms is attraction. By contrast, in the absence of azide, when cold temperature is used to immobilize the worms , the response recorded is aversion to PA14. The choice assay generated by Kaletsky et al without azide is consistent with the choice assays in untrained worms shown in the Gainey paper, demonstrating that this is likely one factor that contributed to the different outcomes reported in the Gainey paper.

Kaletsky et al. propose that learned aversion to PA14 may be occurring within the 1-hour exposure time when worms are not trapped in their initial decision with the use of azide. This is consistent with previous findings from another group (Ooi and Prahlad 2017), showing that 45 minutes of exposure is sufficient to overcome the attraction to PA14 and shift to avoidance of PA14. Importantly, the Gainey paper notes exposure times between 30 and 60 minutes before shifting worms to 4C to count, this window may have generated additional variability between assays.

The second possibility explored by Kaletsky et al. is that the expression of P11 differed between the studies. Because P11 is required for TEI, differences in P11 expression is a reasonable explanation for different observations between studies. Unfortunately, in the Gainey study, P11 levels were not measured; it is therefore not possible to know whether low or absent levels of P11 explain the inability to observe TEI. Nevertheless, Kaletsky et al. test the potential for changes in one growth condition, temperature, to influence the production P11. Indeed, the expression of P11 differs in PA14 grown at different growth temperatures, providing an additional explanation for the discrepancies.

While it is possible that temperature is the culprit, it may be another culture condition or media component suppressing P11 expression. Nevertheless, the fact that expression of P11 can so easily be modified demonstrates that P11 expression is not immune to differences in culture conditions. Given its role in nitrogen fixation, I would be surprised if it was not regulated by environmental conditions. Differences in iron content between media batches are notorious for altering bacteria phenotypes. Although outside the scope of this study, with the connection to biofilm formation, I would be curious if iron levels had an impact on P11 expression. All in all, the data highlight the fact that P11 levels should be measured if TEI is not seen.

Strengths:

Overall, this is an excellent study that has provided additional understanding of the difference between naïve preference and TEI and provides guidance for investigators in replicating TEI experiments. The manuscript is very well written and provides additional understanding regarding the replication of TEI in response to P. aeruginosa.

The manuscript provides an important discussion about differences in methodology and how they might reflect specific biology. Many examples of experimental deviations that have large impacts have simple biological explanations. I believe the authors have done an excellent job making this point.

Weaknesses:

None noted.

Reviewer #2 (Public review):

In addition to the study by Kaletsky et al. (2025), I read the bioRxiv and eLife versions, as well as the eLife reviewer comments, for Gainey et al. (2024), to which Kaletsky et al. respond.

Kaletsky et al. provide detailed, rigorous, and reproducible protocols and results. The authors point out the critical methods that the Hunter group failed to follow/confirm (e.g. azide to paralyze animals during pathogenic learning/memory assays; the expression of the P11 small RNA that is both necessary and sufficient for TEI of avoidance behavior; a single condition for training - PA14 grown on plates at 25°C and training at 20°C for 24 hr - that the Hunter lab did not follow and could not reproduce). The Kaletsky et al. response is evidence-based, fair, level-headed and unbiased, which is in contrast to the Gainey et al. paper.

Reading the eLife review of Gainey et al., I note that the reviewers repeatedly pointed out that authors did not follow published protocols by the Murphy lab.

Public response by Gainey et al. to Reviewer 2: "It remains possible that we misunderstood the published Murphy lab protocols, but we were highly motivated to replicate the results so we could use these assays to investigate the reported RNAi-pathway dependent steps, thus we read every published version with extreme care."

Public response by Gainey et al. to Reviewer 3: "We agree that our study was not exhaustive in our exploration of variables that might be interfering with our ability to detect F2 avoidance."

Gainey et al. provide reasons/excuses for why they did not follow published methods - notably their subjective decision to exclude the paralyzing agent sodium azide from their choice assays, but their abstract reads "We conclude that this example of transgenerational inheritance lacks robustness." I strongly disagree with this conclusion.

Reviewer #3 (Public review):

A recent bioRxiv paper from Craig Hunter's lab (Gainey et al. 2024) puts into question several manuscripts that report that pathogen avoidance by the nematode C. elegans to the pathogenic bacteria, Pseudomonas aeruginosa, for several generations after initial exposure is not robust nor repeatable. From the Hunter lab publication, the authors tried to eliminate genetic drift of the pathogenic bacterial strains and C. elegans, as well as several experimental conditions, including assay temperature conditions and the effect of light.

The papers (Moore et al. 2019, Kaletsky et al. 2020, Moore et al. 2021 and Sengupta et al. 2024) that the Gainey et al. manuscript brings into question discovered that Pseudomonas aeruginosa can produce a small RNA (sRNA), P11, that is necessary and sufficient for pathogen avoidance of the future generation of C. elegans (up to F4 generation). The Gainey et al. manuscript does not assess the status of P11 production in their work.

Here, the Murphy group has made several new discoveries that highlight the differences with the work performed in the Hunter lab. One, the assay used to test attraction and avoidance of C. elegans for pathogenic bacteria differs amongst the two groups. In the Murphy lab papers, and many others in this field, the assay is established whereby worms can decide between spots of non-pathogenic bacteria (E. coli) or pathogenic (P. aeruginosa) on a single plate separated by a few centimeters. Also included in each spot is an aliquot of NaN3 to freeze the animals upon entry into their first bacterial choice. C. elegans will initially choose the pathogenic bacteria as its first choice and then learn to avoid the pathogenic spot thereafter. Therefore, establishing this first baseline attraction point is essential for determining future avoidance events. The Hunter lab did not use NaN3 and instead relied upon moving plates to 4°C to slow the worm's movements to count the population. Furthermore, the Hunter lab allowed the "choice" to proceed for an hour before moving to 4°C, making capture of the initial attraction phase of the choice assay difficult to discern since the worms could move freely from their initial choice due to the lack of the paralyzing NaN3.

The second major advance that the Murphy group has found is that the growth of P. aeruginosa prior to being used for the choice assay is critical. Growth on plates at 25°C, but not 20°C on plates or in liquid at 37°C, can produce the transgenerational inheritance of pathogen avoidance. Interestingly, P11 is only produced by P. aeruginosa at 25°C grown on plates. The Hunter group grew the Pseudomonas bacteria at 37°C in liquid with gentle shaking and then spotted onto assay plates followed by growth for 2 days at 25°C and then equilibrated to room temperature before the choice assay. The Hunter lab did not check the status of P11 production in any of their experiments.

The results from the Murphy group are solid and they go on to find genetic requirements in C. elegans required for the transgenerational response to P. aeruginosa and P11. Furthermore, they repeat their results with additional members of the Pseudomonas clade and find the same transgenerational avoidance response and new sRNAs responsible for the avoidance response to the newly tested Pseudomonas members.

Overall, the discrepancies between the Hunter work and the numerous papers for the Murphy group would tend to complicate this area of research. However, this eLife paper plainly illustrates the straightforward nature of the experimental setup and reconfirms the necessary and sufficient nature of P11 in orchestrating the multigenerational response to pathogenic Pseudomonas. It appears that ensuring the production of P11 from the Pseudomonas culture and ensuring that the assay captures the initial bacterial choice are essential to observe the transgenerational inheritance of the avoidance phenotype.

Reviewer #1 (Public review):

Summary:

This study presents a system for delivering precisely controlled cutaneous stimuli to freely moving mice by coupling markerless real-time tracking to transdermal optogenetic stimulation, using the tracking signal to direct a laser via galvanometer mirrors. The principal claims are that the system achieves sub-mm targeting accuracy with a latency of <100 ms. The nature of mouse gait enables accurate targeting of forepaws even when mice are moving.

Strengths:

The study is of high quality and the evidence for the claims is convincing. There is increasing focus in neurobiology in studying neural function in freely moving animals, engaged in natural behaviour. However, a substantial challenge is how to deliver controlled stimuli to sense organs under such conditions. The system presented here constitutes notable progress towards such experiments in the somatosensory system and is, in my view, a highly significant development that will be of interest to a broad readership.

Weaknesses:

(1) "laser spot size was set to 2.00 } 0.08 mm2 diameter (coefficient of variation = 3.85)" is unclear. Is the 0.08 SD or SEM? (not stated). Also, is this systematic variation across the arena (or something else)? Readers will want to know how much the spot size varies across the arena - ie SD. CV=4 implies that SD~7 mm. ie non-trivial variation in spot size, implying substantial differences in power delivery (and hence stimulus intensity) when the mouse is in different locations. If I misunderstood, perhaps this helps the authors to clarify. Similarly, it would be informative to have mean & SD (or mean & CV) for power and power density. In future refinements of the system, would it be possible/useful to vary laser power according to arena location?

(2) "The video resolution (1920 x 1200) required a processing time higher than the frame interval (33.33 ms), resulting in real-time pose estimation on a sub-sample of all frames recorded". Given this, how was it possible to achieve 84 ms latency? An important issue for closed-loop research will relate to such delays. Therefore please explain in more depth and (in Discussion) comment on how the latency of the current system might be improved/generalised. For example, although the current system works well for paws it would seem to be less suited to body parts such as the snout that do not naturally have a stationary period during the gait cycle.

Reviewer #2 (Public review):

Parkes et al. combined real-time keypoint tracking with transdermal activation of sensory neurons to examine the effects of recruitment of sensory neurons in freely moving mice. This builds on the authors' previous investigations involving transdermal stimulation of sensory neurons in stationary mice. They illustrate multiple scenarios in which their engineering improvements enable more sophisticated behavioral assessments, including (1) stimulation of animals in multiple states in large arenas, (2) multi-animal nociceptive behavior screening through thermal and optogenetic activation, and (3) stimulation of animals running through maze corridors. Overall, the experiments and the methodology, in particular, are written clearly. However, there are multiple concerns and opportunities to fully describe their newfound capabilities that, if addressed, would make it more likely for the community to adopt this methodology:

The characterization of laser spot size and power density is reported as a coefficient of variation, in which a value of ~3 is interpreted as uniform. My interpretation would differ - data spread so that the standard deviation is three times larger than the mean indicates there is substantial variability in the data. The 2D polynomial fit is shown in Figure 2 - Figure Supplement 1A and, if the fit is good, this does support the uniformity claim (range of spot size is 1.97 to 2.08 mm2 and range of power densities is 66.60 to 73.80 mW). The inclusion of the raw data for these measurements and an estimate of the goodness of fit to the polynomials would better help the reader evaluate whether these parameters are uniform across space and how stable the power density is across repeated stimulations of the same location. Even more helpful would be an estimate of whether the variation in the power density is expected to meaningfully affect the responses of ChR2-expressing sensory neurons.

While the error between the keypoint and laser spot error was reported as ~0.7 to 0.8 mm MAE in Figure 2L, in the methods, the authors report that there is an additional error between predicted keypoints and ground-truth labeling of 1.36 mm MAE during real-time tracking. This suggests that the overall error is not submillimeter, as claimed by the authors, but rather on the order of 1.5 - 2.5 mm, which is considerable given the width of a hind paw is ~5-6 mm and fore paws are even smaller. In my opinion, the claim for submillimeter precision should be softened and the authors should consider that the area of the paw stimulated may differ from trial to trial if, for example, the error is substantial enough that the spot overlaps with the edge of the paw.

As the major advance of this paper is the ability to stimulate animals during ongoing movement, it seems that the Figure 3 experiment misses an opportunity to evaluate state-dependent whole-body reactions to nociceptor activation. How does the behavioral response relate to the animal's activity just prior to stimulation?

Given the characterization of full-body responses to activation of TrpV1 sensory neurons in Figure 4 and in the authors' previous work, stimulation of TrpV1 sensory neurons has surprisingly subtle effects as the mice run through the alternating T maze. The authors indicate that the mice are moving quickly and thus that precise targeting is required, but no evidence is shared about the precision of targeting in this context beyond images of four trials. From the characterization in Figure 2, at max speed (reported at 241 +/- 53 mm/s, which is faster than the high speeds in Figure 2), successful targeting occurs less than 50% of the time. Is the initial characterization consistent with the accuracy in this context? To what extent does inaccuracy in targeting contribute to the subtlety of affecting trajectory coherence and speed? Is there a relationship between animal speed and disruption of the trajectory?

Reviewer #3 (Public review):

Summary:

To explore the diverse nature of somatosensation, Parkes et al. established and characterized a system for precise cutaneous stimulation of mice as they walk and run in naturalistic settings. This paper provides a framework for real-time body part tracking and targeted optical stimuli with high precision, ensuring reliable and consistent cutaneous stimulation. It can be adapted in somatosensation labs as a general technique to explore somatosensory stimulation and its impact on behavior, enabling rigorous investigation of behaviors that were previously difficult or impossible to study.

Strengths:

The authors characterized the closed-loop system to ensure that it is optically precise and can precisely target moving mice. The integration of accurate and consistent optogenetic stimulation of the cutaneous afferents allows systematic investigation of somatosensory subtypes during a variety of naturalistic behaviors. Although this study focused on nociceptors innervating the skin (Trpv1::ChR2 animals), this setup can be extended to other cutaneous sensory neuron subtypes, such as low-threshold mechanoreceptors and pruriceptors. This system can also be adapted for studying more complex behaviors, such as the maze assay and goal-directed movements.

Weaknesses:

Although the paper has strengths, its weakness is that some behavioral outputs could be analyzed in more detail to reveal different types of responses to painful cutaneous stimuli. For example, paw withdrawals were detected after optogenetically stimulating the paw (Figures 3E and 3F). Animals exhibit different types of responses to painful stimuli on the hind paw in standard pain assays, such as paw lifting, biting, and flicking, each indicating a different level of pain. Improving the behavioral readouts from body part tracking would greatly strengthen this system by providing deeper insights into the role of somatosensation in naturalistic behaviors. Additionally, if the laser spot size could be reduced to a diameter of 2 mm², it would allow the activation of a smaller number of cutaneous afferents, or even a single one, across different skin types in the paw, such as glabrous or hairy skin.

Reviewer #1 (Public review):

Summary:

Fluorescence imaging has become an increasingly popular technique for monitoring neuronal activity and neurotransmitter concentrations in the living brain. However, factors such as brain motion and changes in blood flow and oxygenation can introduce significant artifacts, particularly when activity-dependent signals are small. Yogesh et al. quantified these effects using GFP, an activity-independent marker, under two-photon and wide-field imaging conditions in awake behaving mice. They report significant GFP responses across various brain regions, layers, and behavioral contexts, with magnitudes comparable to those of commonly used activity sensors. These data highlight the need for robust control strategies and careful interpretation of fluorescence functional imaging data.

Strengths:

The effect of hemodynamic occlusion in two-photon imaging has been previously demonstrated in sparsely labeled neurons in V1 of anesthetized animals (see Shen and Kara et al., Nature Methods, 2012). The present study builds on these findings by imaging a substantially larger population of neurons in awake, behaving mice across multiple cortical regions, layers, and stimulus conditions. The experiments are extensive, the statistical analyses are rigorous, and the results convincingly demonstrate significant GFP responses that must be accounted for in functional imaging experiments.

In the revised version, the authors have provided further methodological details that were lacking in the previous version, expanded discussions regarding alternative explanations of these GFP responses as well as potential mitigation strategies. They also added a quantification of brain motion (Fig. S5) and the fraction of responsive neurons when conducting the same experiment using GCaMP6f (Fig. 3D-3F), among other additional information.

Weaknesses:

(1) The authors have now included a detailed methodology for blood vessel area quantification, where they detect blood vessels as dark holes in GFP images and measure vessel area by counting pixels below a given intensity threshold (line 437-443). However, this approach has a critical caveat: any unspecific decrease in image fluorescence will increase the number of pixels below the threshold, leading to an apparent increase in blood vessel area, even when the actual vessel size remains unchanged. As a result, this method inherently introduces a positive correlation between fluorescence decrease and vessel dilation, regardless of whether such a relationship truly exists.

To address this issue, I recommend labelling blood vessels with an independent marker, such as a red fluorescence dye injected into the bloodstream. This approach would allow vessel dilation to be assessed independently of GFP fluorescence -- dilation would cause opposite fluorescence changes in the green and red channels (i.e., a decrease in green due to hemodynamic occlusion and an increase in red due to the expanding vessel area). In my opinion, only when such ani-correlation is observed can one reliably infer a relationship between GFP signal changes and blood vessel dynamics.

Because this relationship is central to the author's conclusion regarding the nature of the observed GFP signals, including this experiment would greatly strengthen the paper's conclusion.

(2) Regarding mitigation strategy, the authors advocate repeating key functional imaging experiments using GFP, and state that their aim here is to provide a control for their 2012 study (Keller et al., Neuron). Given this goal, I find it important to discuss how these new findings impact the interpretation of their 2012 results, particularly given the large GFP responses observed.

For example, Keller et al. (2012) concluded that visuomotor mismatch strongly drives V1 activity (Fig. 3A in that study). However, in the present study, mismatch fails to produce any hemodynamic/GFP response (Fig. 3A, 3B, rightmost bar), and the corresponding calcium response is also the weakest among the three tested conditions (Fig. 3D). How do these findings affect their 2012 conclusions?

Similarly, the present study shows that GFP reveals twice as many responsive neurons as GCaMP during locomotion (Fig. 3A vs. Fig. 3D, "running"). Does this mean that their 2012 conclusions regarding locomotion-induced calcium activity need reconsideration? Given that more neurons responded with GFP than with GCaMP, the authors should clarify whether they still consider GCaMP a reliable tool for measuring brain activity during locomotion.

(3) More generally, the author should discuss how functional imaging data should be interpreted going forward, given the large GFP responses reported here. Even when key experiments are repeated using GFP, it is not entirely clear how one could reliably estimate underlying neuronal activity from the observed GFP and GCaMP responses.

For example, consider the results in Fig. 3A vs. 3D: how should one assess the relative strength of neuronal activity elicited by running, grating, or visuomotor mismatch? Does mismatch produce the strongest neuronal activity, since it is least affected by the hemodynamic/GFP confounds (Fig. 3A)? Or does mismatch actually produce the weakest neuronal activity, given that both its hemodynamic and calcium responses are the smallest?

In my opinion, such uncertainty makes it difficult to robustly interpret functional imaging results. Simply repeating experiments with GFP does not fully resolve this issue, as it does not provide a clear framework for quantifying the underlying neuronal activity. Does this suggest a need for a better mitigation strategy? What could these strategies be?

In my opinion, addressing these questions is critical not only for the authors' own work but also for the broader field to ensure a robust and reliable interpretation of functional imaging data.

(4) The authors now discuss various alternative sources of the observed GFP signals. However, I feel that they often appear to dismiss these possibilities too quickly, rather than appreciating their true potential impacts (see below).

For example, the authors argue that brain movement cannot explain their data, as movement should only result in a decrease in observed fluorescence. However, while this might hold for x-y motion, movement in the axial (z) direction can easily lead to both fluorescence increase and decrease. Neurons are not always precisely located at the focal plane -- some are slightly above or below. Axial movement in a given direction will bring some cells into focus while moving others out of focus, leading to fluorescence changes in both directions, exactly as observed in the data (see Fig. S2).

Furthermore, the authors state that they discard data with 'visible' z-motion. However, subtle axial movements that escape visual detection could still cause fluorescence fluctuations on the order of a few percent, comparable to the reported signal amplitudes.

Finally, the authors state that "brain movement kinematics are different in shape than the GFP responses we observe". However, this appears to contradict what they show in Fig. 2A. Specifically, the first example neuron exhibits fast GFP transients locked to running onset, with rapid kinematics closely matching the movement speed signals in Fig. S5A. These fast transients are incompatible with slower blood vessel area signals (Fig. 4), suggesting that alternative sources could contribute significantly.

In sum, the possibility that alternative signal sources could significantly contribute should be taken seriously and more thoroughly discussed.

(5) The authors added a quantification of brain movement (Fig. S5) and claim that they "only find detectable brain motion during locomotion onsets and not the other stimuli." However, Fig. S5 presents brain 'velocity' rather than 'displacement'. A constant (non-zero) velocity in Fig. S5 B-D indicates that the brain continues to move over time, potentially leading to significant displacement from its initial position across all conditions. While displacement in the x-y plane are corrected, similar displacement in the z direction likely occurs concurrently and cannot be easily accounted for. To assess this possibility, the authors should present absolute displacement relative to pre-stimulus frames, as displacement -- not velocity -- determines the size of movement-related fluorescence changes.

(6) In line 132-133, the authors draw an analogy between the effect of hemodynamic occlusion and liquid crystal display (LCD) function. However, there are fundamental differences between the two. LCDs modulate light transmission by rotating the polarization of light, which then passes through a crossed polarizer. In contrast, hemodynamic occlusion alters light transmission by changing the number and absorbance properties of hemoglobin. Additionally, LCDs do not involve 'emission' light - back-illumination travels through the liquid crystal layer only once, whereas hemodynamic occlusion affects both incoming excitation light and the emitted fluorescence. Given these fundamental differences, the LCD analogy may not be entirely appropriate.

Reviewer #2 (Public review):

- Approach

In this study, Yogesh et al. aimed at characterizing hemodynamic occlusion in two photon imaging, where its effects on signal fluctuations are underappreciated compared to that in wide field imaging and fiber photometry. The authors used activity-independent GFP fluorescence, GCaMP and GRAB sensors for various neuromodulators in two-photon and widefield imaging during a visuomotor context to evaluate the extent of hemodynamic occlusion in V1 and ACC. They found that the GFP responses were comparable in amplitude to smaller GCaMP responses, though exhibiting context-, cortical region-, and depth-specific effects. After quantifying blood vessel diameter change and surrounding GFP responses, they argued that GFP responses were highly correlated with changes in local blood vessel size. Furthermore, when imaging with GRAB sensors for different neuromodulators, they found that sensors with lower dynamic ranges such as GRAB-DA1m, GRAB-5HT1.0, and GRAB-NE1m exhibited responses most likely masked by the hemodynamic occlusion, while a sensor with larger SNR, GRAB-ACh3.0, showed much more distinguishable responses from blood vessel change. They thoroughly investigate other factors that could contribute to these signals and demonstrate hemodynamic occlusion is the primary cause.

- Impact of revision

This is an important update to the initial submission, adding much supplemental imaging and population data that provide greater detail to the analyses and increase the confidence in the authors conclusions.

Specifically, inclusion of the supplemental figures 1 and 2 showing GFP expression across multiple regions and the fluorescence changes of thousands of individual neurons provides a clearer picture of how these effects are distributed across the population. Characterization of brain motion across stimulation conditions in supplemental figure 5 provides strong evidence that the fluorescence changes observed in many of the conditions are unlikely to be primarily due to brain motion associated imaging artifacts. The role of vascular area on fluorescence is further supported by addition of new analyses on vasoconstriction leading to increased fluorescence in Figures 4C1-4, complementing the prior analyses of vasodilation.

The expansion of the discussion on other factors that could lead to these changes is thorough and welcome. The arguments against pH playing a factor in fluorescence changes of GFP, due to insensitivity to changes in the expected pH range are reasonable, as are the other discussed potential factors.

With respect to the author's responses to prior critique, we agree that activity dependent hemodynamic occlusion is best investigated under awake conditions. Measurement of these dynamics under anesthesia could lead to an underestimation of their effects. Isoflurane anesthesia causes significant vasodilation and a large reduction in fluorescence intensity in non-functional mutant GRABs. This could saturate or occlude activity dependent effects.

- Strengths

This work is of broad interest to two photon imaging users and GRAB developers and users. It thoroughly quantifies the hemodynamic driven GFP response and compares it to previously published GCaMP data in a similar context, and illustrates the contribution of hemodynamic occlusion to GFP and GRAB responses by characterizing the local blood vessel diameter and fluorescence change. These findings provide important considerations for the imaging community and a sobering look at the utility of these sensors for cortical imaging.

Importantly, they draw clear distinctions between the temporal dynamics and amplitude of hemodynamic artifacts across cortical regions and layers. Moreover, they show context dependent (Dark versus during visual stimuli) effects on locomotion and optogenetic light-triggered hemodynamic signals.

The authors suggest that signal to noise ratio of an indicator likely affects the ability to separate hemodynamic response from the underlying fluorescence signal. With a new analysis (Supplemental Figure 4) They show that the relative degree of background fluorescence does not affect the size of the artifact.

Most of the first generation neuromodulator GRAB sensors showed relatively small responses, comparable to blood vessel changes in two photon imaging, which emphasizes a need for improved the dynamic range and response magnitude for future sensors and encourages the sensor users to consider removing hemodynamic artifacts when analyzing GRAB imaging data.

- Weaknesses

The largest weakness of the paper remains that, while they convincingly quantify hemodynamic artifacts across a range of conditions, they provide limited means of correcting for them. However they now discuss the relative utility of some hemodynamic correction methods (e.g. from Ocana-Santero et al., 2024).

The paper attributes the source of 'hemodynamic occlusion' primarily to blood vessel dilation, but leaves unanswered how much may be due to shifts in blood oxygenation. Figure 4 directly addresses the question of how much of the signal can be attributed to occlusion by measuring the blood vessel dilation, and has been improved by now showing positive fluorescence effects with vasoconstriction. They now also discuss the potential impact of oxygenation.

Along these lines, the authors carefully quantified the correlation between local blood vessel diameter and GFP response (or neuropil fluorescence vs blood vessel fluorescence with GRAB sensors). We are left to wonder to what extent does this effect depend on proximity to the vessels? Do GFP/ GRAB responses decorrelate from blood vessel activity in neurons further from vessels (refer to Figure 5A and B in Neyhart et al., Cell Reports 2024)? The authors argue that the primary impact of occlusion is from blood vessels above the plane of imaging, but without a vascular reconstruction, their evidence for this is anecdotal.

The choice of ACC as the frontal region provides a substantial contrast in location, brain movement, and vascular architecture as compared to V1. As the authors note, ACC is close to the superior sagittal sinus and thus is the region where the largest vascular effects are likely to occur. A less medial portion of M2 may have been a more appropriate comparison. The authors now include example imaging fields for ACC and interesting out-of-plane vascular examples in the supplementary figures that help assess these impacts.

-Overall Assessment

This paper is an important contribution to our understanding of how hemodynamic artifacts may corrupt GRAB and calcium imaging, even in two-photon imaging modes. While it would be wonderful if the authors were able to demonstrate a reliable way to correct for hemodynamic occlusion which did not rely on doing the experiments over with a non-functional sensor or fluorescent protein, the careful measurement and reporting of the effects here is, by itself, a substantial contribution to the field of neural activity imaging. It's results are of importance to anyone conducting two-photon or widefield imaging with calcium and GRAB sensors and deserves the attention of the broader neuroscience and in-vivo imaging community.

Reviewer #3 (Public review):

Summary:

In this study, the authors aimed to investigate if hemodynamic occlusion contributes to fluorescent signals measured with two-photon microscopy. For this, they image the activity-independent fluorophore GFP in 2 different cortical areas, at different cortical depths and in different behavioral conditions. They compare the evoked fluorescent signals with those obtained with calcium sensors and neuromodulator sensors and evaluate their relationship to vessel diameter as a readout of blood flow.<br /> They find that GFP fluorescence transients are comparable to GCaMP6f stimuli-evoked signals in amplitude, although they are generally smaller. Yet, they are significant even at the single neuronal level. They show that GFP fluorescence transients resemble those measured with the dopamine sensor GRAB-DA1m and the serotonin sensor GRAB-5HT1.0 in amplitude an nature, suggesting that signals with these sensors are dominated by hemodynamic occlusion. 
Moreover, the authors perform similar experiments with wide-field microscopy which reveals the similarity between the two methods in generating the hemodynamic signals. Together the evidence presented calls for the development and use of high dynamic range sensors to avoid measuring signals that have another origin from the one intended to measure. In the meantime, the evidence highlights the need to control for those artifacts such as with the parallel use of activity independent fluorophores.

Strengths:

- Comprehensive study comparing different cortical regions in diverse behavioral settings in controlled conditions.<br /> - Comparison to the state-of-the-art, i.e. what has been demonstrated with wide-field microscopy.<br /> - Comparison to diverse activity-dependent sensors, including the widely used GCaMP.

Comments on revisions:

The authors have addressed my concerns well. I have no further comments.

Reviewer #1 (Public review):

Summary:

The authors performed experimental evolution of MreB mutants that have a slow growing round phenotype and studied the subsequent evolutionary trajectory using analysis tool from molecular biology. It was remarkable and interesting that they found that the original phenotype was not restored (most common in these studies) but that the round phenotype was maintained.

Strengths:

The finding that the round phenotype was maintained during evolution rather than that the original phenotype, rod shape cells, was recovered is interesting. The paper extensively investigates what happens during adaptation with various different techniques. Also the extensive discussion of the findings at the end of the paper is well thought through and insightful.

Reviewer #3 (Public review):

This paper addresses a long-standing problem in microbiology: the evolution of bacterial cell shape. Bacterial cells can take a range of forms, among the most common being rods and spheres. The consensus view is that rods are the ancestral form and spheres the derived form. The molecular machinery governing these different shapes is fairly well understood but the evolutionary drivers responsible for the transition between rods and spheres is not. Enter Yulo et al.'s work. The authors start by noting that deletion of a highly conserved gene called MreB in the Gram-negative bacterium Pseudomonas fluorescens reduces fitness but does not kill the cell (as happens in other species like E. coli and B. subtilis) and causes cells to become spherical rather than their normal rod shape. They then ask whether evolution for 1000 generations restores the rod shape of these cells when propagated in a rich, benign medium.

The answer is no. The evolved lineages recovered fitness by the end of the experiment, growing just as well as the unevolved rod-shaped ancestor, but remained spherical. The authors provide an impressively detailed investigation of the genetic and molecular changes that evolved. Their leading results are:

(1) The loss of fitness associated with MreB deletion causes high variation in cell volume among sibling cells after cell division;<br /> (2) Fitness recovery is largely driven by a single, loss-of-function point mutation that evolves within the first ~250 generations that reduces the variability in cell volume among siblings;<br /> (3) The main route to restoring fitness and reducing variability involves loss of function mutations causing a reduction of TPase and peptidoglycan cross-linking, leading to a disorganized cell wall architecture characteristic of spherical cells.

The inferences made in this paper are on the whole well supported by the data. The authors provide a uniquely comprehensive account of how a key genetic change leads to gains in fitness and the spectrum of phenotypes that are impacted and provide insight into the molecular mechanisms underlying models of cell shape.

Reviewer #1 (Public review):

Summary:

Evading predation is of utmost importance for most animals and camouflage is one of the predominant mechanisms. Wu et al. set out to test the hypothesis of a unique camouflage system in leafhoppers. These animals coat themselves with brochosomes, which are spherical nanostructures that are produced in the Malpighian tubules and are distributed on the cuticle after eclosion. Based on previous findings on reflectivity properties of brochosomes, the authors provide convincing evidence that these nanostructures indeed reduce reflectivity of the animals thereby reducing predation by jumping spiders. Further, they identify four proteins, which are essential for proper development and function of brochosomes: In RNAi experiments, the regular brochosome structure is lost, the reflectivity reduced and the respective animals are prone to increased predation. Finally, the authors provide phylogenetic sequence analyses and speculate about the evolution of these genes.

Strengths:

The study is very comprehensive including careful optical measurements, EM and TM analysis of the nanoparticles and their production line in the malphigian tubules, in vivo predation tests and knock-down experiments to identify essential proteins. Indeed, the results are very convincingly in line with the starting hypothesis such that the study robustly assigns a new biological function to the brochosome coating system.

A key strength of the study is that the biological relevance of the brochosome coating is convincingly shown by an in vivo predation test using a known predator from the same habitat.

Another major step forward is an RNAi screen, which identified four proteins, which are essential for the brochosome structure (BSMs). After respective RNAi knock-downs, the brochosomes show curious malformations that are interesting in terms of the self-assembly of these nanostructures. The optical and in vivo predation tests provide excellent support for the model that the RNAi knock-down leads to a change of brochosomes structure, which reduces reflectivity, which in turn leads to a decrease of the antipredatory effect.

Conclusion:

The authors successfully tested their hypothesis in a multidisciplinary approach and convincingly assigned a new biological function to the brochosomes system. The results fully support their claims on the involvement of the four BSM genes in brochosome structure, the relevance of brochosomes for predation avoidance and they provide evidence for the evolution of these genes.

The work is a very interesting study case of the evolutionary emergence of a new system to evade predators. Based on this study, the function of the BSM genes could now be studied in other species to provide insights into putative ancestral functions. Further, studying the self-assembly of such highly regular complex nano-structures will be strongly fostered by the identification of the four key structural genes.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigate the optical properties of brochosomes produced by leafhoppers. They hypothesize that brochosomes reduce light reflection on the leafhopper's body surface, aiding in predator avoidance. Their hypothesis is supported by experiments involving jumping spiders. Additionally, the authors employ a variety of techniques including micro-UV-Vis spectroscopy, electron microscopy, transcriptome and proteome analysis, and bioassays. This study is highly interesting, and the experimental data is well-organized and logically presented.

Strengths:

The use of brochosomes as a camouflage coating has been hypothesized since 1936 (R.B. Swain, Entomol. News 47, 264-266, 1936) with evidence demonstrated by similar synthetic brochosome systems in a number of recent studies (S. Yang, et al. Nat. Commun. 8:1285, 2017; L. Wang, et al., PNAS. 121: e2312700121, 2024). However, direct biological evidence or relevant field studies have been lacking to directly support the hypothesis that brochosomes are used for camouflage. This work provides the first biological evidence demonstrating that natural brochosomes can be used as a camouflage coating to reduce the leafhoppers' observability to their predators. The design of the experiments is novel.

Weaknesses:

(1) The observation that brochosome coatings become sparse after 25 days in both male and female leafhoppers, resulting in increased predation by jumping spiders, is intriguing. However, since leafhoppers consistently secrete and groom brochosomes, it would be beneficial to explore why brochosomes become significantly less dense after 25 days.

(2) The authors demonstrate that brochosome coatings reduce UV (specular) reflection compared to surfaces without brochosomes, which can be attributed to the rough geometry of brochosomes as discussed in the literature. However, it would be valuable to investigate whether the proteins forming the brochosomes are also UV absorbing.

(3) The experiments with jumping spiders show that brochosomes help leafhoppers avoid predators to some extent. It would be beneficial for the authors to elaborate on the exact mechanism behind this camouflage effect. Specifically, why does reduced UV reflection aid in predator avoidance? If predators are sensitive to UV light, how does the reduced UV reflectance specifically contribute to evasion?

(4) An important reference regarding the moth-eye effect is missing. Please consider including the following paper: Clapham, P. B., and M. C. Hutley. "Reduction of lens reflection by the 'Moth Eye' principle." Nature 244: 281-282 (1973).

(5) The introduction should be revised to accurately reflect the related contributions in literature. Specifically, the novelty of this work lies in the demonstration of the camouflage effect of brochosomes using jumping spiders, which is verified for the first time in leafhoppers. However, the proposed use of brochosome powder for camouflage was first described by R.B. Swain (R.B. Swain, Notes on the oviposition and life history of the leafhopper Oncometopta undata Fabr. (Homoptera: Cicadellidae), Entomol. News. 47: 264-266 (1936)). Recently, the antireflective and potential camouflage functions of brochosomes were further studied by Yang et al. based on synthetic brochosomes and simulated vision techniques (S. Yang, et al. "Ultra-antireflective synthetic brochosomes." Nature Communications 8: 1285 (2017)). Later, Lei et al. demonstrated the antireflective properties of natural brochosomes in 2020 (C.-W. Lei, et al., "Leafhopper wing-inspired broadband omnidirectional antireflective embroidered ball-like structure arrays using a nonlithography-based methodology." Langmuir 36: 5296-5302 (2020)). Very recently, Wang et al. successfully fabricated synthetic brochosomes with precise geometry akin to those natural ones, and further elucidated the antireflective mechanisms based on the brochosome geometry and their role in reducing the observability of leafhoppers to their predators (L. Wang et al. "Geometric design of antireflective leafhopper brochosomes." Proceedings of the National Academy of Sciences 121: e2312700121 (2024)).

Comments on revisions:

In this revision, the authors have addressed some of the key concerns I raised in our previous comments. However, a few issues remain unaddressed. Additionally, the new experimental data introduced in the manuscript require further clarification, which I outline below.

(1) As I pointed out in my previous review comments, "The use of brochosomes as a camouflage coating has been hypothesized since 1936 (R.B. Swain, Entomol. News 47, 264-266, 1936) with evidence demonstrated by similar synthetic brochosome systems in a number of recent studies (S. Yang, et al. Nat. Commun. 8:1285, 2017; L. Wang, et al., PNAS. 121: e2312700121, 2024). However, direct biological evidence or relevant field studies have been lacking to directly support the hypothesis that brochosomes are used for camouflage." While the authors did cite the original hypothesis proposed by R.B. Swain (1936), they have omitted important references that provide evidence on the use of antireflective properties of brochosomes for camouflage in a synthetic setting (see for example, Fig. 5a of S. Yang, et al. Nat. Commun. 8:1285, 2017). The authors are recommended to revise the Abstract and Introduction accordingly to ensure a fair and accurate representation of the existing literature.

(2) The antireflection mechanisms of brochosome structures have been discussed in detail, specifically, how their geometries (i.e., brochosome diameter and pore size) contribute to reducing UV reflectance (L. Wang, et al., PNAS. 121: e2312700121, 2024 and P. Banergee, et al., Advanced Photonics Research 4:2200343, 2023). The authors should incorporate these recent findings into their discussion (line 381 - line 383 of the manuscript).

(3) The authors presented new data brochosomes deposited on a quartz slide and measured their reflectance across UV, visible light, and infrared wavelengths. Since reflectance is highly sensitive to the uniformity of brochosome coverage on the substrate, it is crucial to quantify this coverage across the measurement area for comparison. While the authors include SEM images to illustrate the packing of brochosomes on both the leafhopper wing and the quartz substrate (Fig. S7) at a microscopic scale (~10 um view), it would be beneficial to also provide SEM images at a larger scale (e.g., 100 um - 1 mm) and quantify the density of brochosomes per unit area for comparison.

(4) For the negative control using acetone to remove the brochosomes the leafhopper wing, have the authors confirmed the absence of brochosomes after treatment? If so, the authors should explicitly indicate this for clarity.

Reviewer #1 (Public review):

The article provides a timely and well-written examination of how group identification influences collective behaviors and performance using fNIRs and behavioral data.

Comments on revisions:

Most Reviewer concerns have been addressed in the revised manuscript, but some limitations persist with respect to core aspects of study design (e.g., long block durations and lack of counter-balancing) and analysis (i.e., the potential circularity of some analyses, the insufficiency of a mediation model to demonstrate causality, and a lack of clarity concerning the model us to map task activation).

Editor's note: Although the Reviewers found the reviews generally responsive, some fundamental concerns remain which will not be changed by further revision.

Reviewer #1 (Public review):

The goal of this study was to identify the phenotype of olfactory ensheathing cells (OECs) that have been associated with neural tissue repair, and investigate the properties of these cells that can be used to identify them. OECs modify inhibitory glial scar formation, enabling axon regeneration past the scar border and into the lesion center. Single-cell RNA sequencing revealed diverse subtypes of OECs expressing novel marker genes associated with progenitor, axonal regeneration, repair, and microglia-like functions, suggesting their potential roles in wound healing, injury repair, and axonal regeneration. Additionally, the study identified secreted molecules such as Reelin and Connective tissue growth factor, which are important for neural repair and axonal outgrowth, further supporting the multifunctional nature of OECs in facilitating spinal cord injury recovery. This is an extremely well written and impactful series of experiments from a renowned leader in the field. The experimental questions are timely, with similar therapeutic approaches being prepared for clinical trial. The results address a gap that has persisted in the field for several decades, and one that has asked by many scientists long before technology existed to find answers. This highlights the importance of these experiments and the results reported here. The authors have also included a thoughtful discussion that highlights the importance of their data in the context of prior research. They have carefully interpreted their results and also indicate where additional studies in future work will continue to expand our knowledge of these important cells and their potential use for neural repair.

Reviewer #2 (Public review):

Summary

This manuscript explores the transcriptomic identities of olfactory ensheathing cells (OECs), glial cells that support life-long axonal growth in olfactory neurons, as they relate to spinal cord injury repair. The authors show that transplantation of cultured, immunopurified rodent OECs at a spinal cord injury site can promote injury-bridging axonal regrowth. They then characterize these OECs using single-cell RNA sequencing, identifying five subtypes and proposing functional roles that include regeneration, wound healing, and cell-cell communication. They identify one progenitor OEC subpopulation and also report several other functionally relevant findings, notably, that OEC marker genes contain mixtures of other glial cell type markers (such as for Schwann cells and astrocytes), and that these cultured OECs produce and secrete Reelin, a regrowth-promoting protein that has been disputed as a gene product of OECs.

Strengths

This manuscript offers an extensive, cell-level characterization of OECs, supporting their potential therapeutic value for spinal cord injury and suggesting potential underlying repair mechanisms. The authors use various approaches to validate their findings, providing interesting images that show the overlap between sprouting axons and transplanted OECs, and showing that OEC marker genes identified using single-cell RNA sequencing are present in vivo, in both olfactory bulb tissue and spinal cord after OEC transplantation.

Concerns about quantification raised during the review were suitably addressed by the authors.

Reviewer #1 (Public review):

Summary:

This study provides new insights on the phenomenon of pre-saccadic foveal prediction previously reported by the same authors. In particular, this study examines to what extent this phenomenon varies based on the visibility of the saccade target. Visibility is defined as the contrast level of the target with respect to the noise background, and it is related to the signal-to-noise ratio of the target. A more visible target facilitates the oculomotor behavior planning and execution, however, as speculated by the authors, it can also benefit foveal prediction even if the foveal stimulus visibility is maintained constant. Remarkably, the authors show that presenting a highly visible saccade target is beneficial for foveal vision as detection of stimuli with an orientation similar to that of the saccade target is improved, the lower is the saccade target visibility, the less prominent is this effect. The results are convincing and the research methodology is technically sound.

Comments on revisions:

The authors addressed all the concerns raised in the previous rounds of reviews.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors ran a dual task. Subjects monitored a peripheral location for a target onset (to generate a saccade to), and they also monitored a foveal location for a foveal probe. The foveal probe could be congruent or incongruent with the orientation of the peripheral target. In this study, the authors manipulated the conspicuity of the peripheral target, and they saw changes in performance in the foveal task.

Comments on revisions:

The authors have addressed all comments. Thanks.

Reviewer #1 (Public review):

Summary:

The manuscript by Velichko et al. argues that the ability of nucleolar protein Treacles to form phase-separated condensates is necessary for its function in nucleolar organization, rRNA transcription, and rDNA repair. These findings may be of interest to the communities studying biomolecular condensates, nucleolar organization, and ribosome biogenesis. The authors propose that Treacle's ability to undergo liquid-liquid phase separation is the key to its role as a scaffold for the FC of the nucleolus. The experiments in this study were designed and performed well, particularly the overexpression studies, done in the absence of endogenous protein and accounted for the protein expression levels.

Comments on revisions:

I am satisfied with the authors' revisions; my earlier concerns have been addressed thoroughly, and the manuscript is considerably improved. This study is important for our understanding of the role of Treacle in nucleolar organization and function, as well as general principles of cellular compartmentalization that involve biomolecular condensates.

Reviewer #2 (Public review):

Summary:

Velichko, et al. investigate the role played by the long intrinsically disordered protein Trecle in nucleolar morphology and function, with an interest in its potential ability to undergo condensation. The authors explore Treacle's role in core functions of the nucleolus (rRNA biogenesis and DNA repair), which has been a subject of continual investigation since it was identified that truncation of Treacle is the primary genetic cause of Treacher-Collins syndrome. They show that knock out of Treacle leads to de-mixing of canonical markers of the FC (UBF, RPA194) and DFC (FBL) phases of the nucleolus. They also show that replacing Treacle with mutants that either remove the central region of Treacle (∆83-1121) or reduce the segregation of charged residues by scrambling them (CS- Charge Scrambled) results in different FRAP behavior of the condensates that result from Treacle over-expression. These data give new insight into the role played by the charge-segregated central region of Treacle in terms of having the potential to undergo condensation.

Strengths:

The characterizations of changes to nuclear morphology upon Treacle knockout is the strength of this study. The authors characterized effects on the canonical markers of the FC and DFC phases support the idea that Treacle has a scaffolding function. While the effect of Treacle perturbations has been studied before, this has often been investigated in the context of organismal development or rRNA biogenesis and less often at the sub-cellular level, as the authors have carried out.

Another strength of this study is its characterization of the effects of the charge scramble mutant. The authors find that replacing endogenous Treacle with this mutant reduces the bulk dynamics of Treacle as assessed by FRAP, de-mixes FBL from the DFC, lowers pre-rRNA synthesis, and abolishes the recruitment of the DNA-damage response factor TOPBP1.

Weaknesses:

The conclusion that Treacle is a core scaffold of the FC is weakly supported. Recombinant Treacle has intrinsic potential to condense, and its condensation is disrupted by the expected solution conditions (i.e., condensates fail to form at high salt but do form in the presence of an aliphatic alcohol). It should be kept in mind that all proteins will condense at sufficiently high concentrations and under crowding. The authors observed condensation at 100uM protein and 5% PEG8000.

Reviewer #3 (Public review):

Summary:

This study provides evidence that the protein Treacle plays an essential role in the structure and function of the fibrillar center (FC) of the nucleolus, which is surrounded by the dense fibrillar component (DFC) and the granular component (GC). The authors provide new evidence that, like the DFC and GC, the functional FC compartment involves a biomolecular condensate that contains Treacle as a key component. Treacle is essential to transcription of the rDNA as well as proper rRNA processing that the authors tie to a role in maintaining separation of FC components from the DFC. In vitro and in vivo experiments highlight that Treacle is itself capable of undergoing condensation in a manner that depends on concentration and charge-charge interactions, but is not affected by 1,6 hexanediol, which disrupts weak hydrophobic interactions. Attempting to generate separation-of-function mutants, the authors provide further evidence of complex interactions that drive proper condensation in the FC mediated by both the central repeat (low-complexity, likely driving the condensation) and C-terminal domain (which appears to target the specificity of the condensation to the proper location). Using mutant forms of Treacle defective in condensation, the authors provide evidence that these same protein forms are also disrupted in supporting Treacle's functions in rDNA transcription and rRNA processing. Last, the authors suggest that cells lacking Treacle are defective in the DNA damage response at the rDNA in response to VP16.

Strengths:

In general, the data are of high quality, the experiments are well-designed and the findings are carefully interpreted. The findings of the work complement prior high-impact studies of the DFC and GC that have identified constituent proteins as the lynchpins of the biomolecular condensates that organize the nucleolus into its canonical three concentric compartment structure and are therefore likely to be of broad interest. The attempts to generate separation-of-function mutants to dissect the contribution of condensation to Treacle function are ambitious and critical to demonstrating the relevance of this property to the biology of the FC. The complementarity of the methods applied to investigate Treacle function are appropriate and the findings integrate well towards a compelling narrative.

Weaknesses:

While the separation of function mutants of Treacle are a major strength of the work, further studies will be required to fully explore the relevance of Treacle condensation to the stability of the rDNA repeats.

Reviewer #1 (Public review):

Summary:

In this meticulously conducted study, the authors show that Drosophila epidermal cells can modulate escape responses to noxious mechanical stimuli. First, they show that activation of epidermal cells evokes many types of behaviors including escape responses. Subsequently, they demonstrate that most somatosensory neurons are activated by activation of epidermal cells, and that this activation has a prolonged effect on escape behavior. In vivo analyses indicate that epidermal cells are mechanosensitive and require stored-operated calcium channel Orai. Altogether, the authors conclude that epidermal cells are essential for nociceptive sensitivity and sensitization, serving as primary sensory noxious stimuli.

Strengths:

The manuscript is clearly written. The experiments are logical and complementary. They support the authors' main claim that epidermal cells are mechanosensitive and that epidermal mechanically evoked calcium responses require the stored-operated calcium channel Orai. Epidermal cells activate nociceptive sensory neurons as well as other somatosensory neurons in Drosophila larvae, and thereby prolong escape rolling evoked by mechanical noxious stimulation.

Weaknesses:

In several places the text is unclear. For example, core details are missing in the protocols, including the level of LED intensity used, which are necessary for other researchers to reproduce the experiments. Secondly, the rationales are missing for some experiments (for experiments X, Y, and Z). It would be helpful to clarify for your readers why the experiments (for example Figure 3S2) were performed. Finally, for most experiments, the epidermal cells are activated for 60 s, which is long when considering that nocifensive rolling occurs on a timescale of milliseconds. It would be informative to know the shortest duration of epidermal cell activation that is sufficient for observing the behavioral phenotype (prolongation of escape behavior) and activation of sensory neurons.

Reviewer #2 (Public review):

Summary:

The authors provide compelling evidence that stimulation of epidermal cells in Drosophila larvae results in the stimulation of sensory neurons that evoke a variety of behavioral responses. Further, the authors demonstrate that epidermal cells are inherently mechanoresponsive and implicate a role for store-operated calcium entry (mediated by Stim and Orai) in the communication to sensory neurons.

Strengths:

The study represents a significant advance in our understanding of mechanosensation. Multiple strengths are noted. First, the genetic analyses presented in the paper are thorough with appropriate consideration to potential confounds. Second, behavioral studies are complemented by sophisticated optogenetics and imaging studies. Third, identification of roles for store-operated calcium entry is intriguing. Lastly, conservation of these pathways in vertebrates raise the possibility that the described axis is also functional in vertebrates.

Weaknesses:

The study has a few conceptual weaknesses that are arguably minor. The involvement of store-operated calcium entry implicates ER calcium store release. Whether mechanical stimulation evokes ER calcium release in epidermal cells and how this might come about (e.g., which ER calcium channels, roles for calcium-induced calcium release etc.) remains unaddressed. On a related note, the kinetics of store-operated calcium entry is very distinct from that required for SV release. The link between SOC and epidermal cells-neuron transmission is not reconciled. Finally, it is not clear how optogenetic stimulation of epidermal cells results in the activation of SOC.

Revised manuscript:

The authors have adequately addressed my original concerns.

Reviewer #1 (Public review):

Summary:

The authors show certain memory deficits in a mouse knock-in model of Alzheimer's Disease (AD). They show that the observed memory deficits can be explained by a computational model, the latent cause model of associative memory. The memory tasks used include the fear memory task (CFC) and the 'reverse' Barnes maze. Research on AD is important given its known huge societal burden. Likewise, better characterization of the behavioral phenotypes of genetic mouse models of AD is also imperative to advance our understanding of the disease using these models. In this light, I applaud the authors' efforts.

Strengths:

(1) Combining computational modelling with animal behavior in genetic knock-in mouse lines is a promising approach, which will be beneficial to the field and potentially explain any discrepancies in results across studies as well as provide new predictions for future work.

(2) The authors' usage of multiple tasks and multiple ages is also important to ensure generalization across memory tasks and 'modelling' of the progression of the disease.

Weaknesses:

(1) I have some concerns regarding the interpretation of the behavioral results. Since the computational model then rests on the authors' interpretation of the behavioral results, it, in turn, makes judging the model's explanatory power difficult as well. For the CFC data, why do knock-in mice have stronger memory in test 1 (Figure 2C)? Does this mean the knock-in mice have better memory at this time point? Is this explained by the latent cause model? Are there some compensatory changes in these mice leading to better memory? The authors use a discrimination index across tests to infer a deficit in re-instatement, but this indicates a relative deficit in re-instatement from memory strength in test 1. The interpretation of these differential DIs is not straightforward. This is evident when test 1 is compared with test 2, i.e., the time point after extinction, which also shows a significant difference across groups, Figure 2F, in the same direction as the re-instatement. A clarification of all these points will help strengthen the authors' case

(2) I have some concerns regarding the interpretation of the Barnes maze data as well, where there already seems to be a deficit in the memory at probe test 1 (Figure 6C). Given that there is already a deficit in memory, would not a more parsimonious explanation of the data be that general memory function in this task is impacted in these mice, rather than the authors' preferred interpretation? How does this memory weakening fit with the CFC data showing stronger memories at test 1? While I applaud the authors for using multiple memory tasks, I am left wondering if the authors tried fitting the latent cause model to the Barnes maze data as well.

(3) Since the authors use the behavioral data for each animal to fit the model, it is important to validate that the fits for the control vs. experimental groups are similar to the model (i.e., no significant differences in residuals). If that is the case, one can compare the differences in model results across groups (Figures 4 and 5). Some further estimates of the performance of the model across groups would help.

(4) Is there an alternative model the authors considered, which was outweighed in terms of prediction by this model? One concern here is also parameter overfitting. Did the authors try leaving out some data (trials/mice) and predicting their responses based on the fit derived from the training data?

Reviewer #2 (Public review):

Summary:

This manuscript proposes that the use of a latent cause model for the assessment of memory-based tasks may provide improved early detection of Alzheimer's Disease as well as more differentiated mapping of behavior to underlying causes. To test the validity of this model, the authors use a previously described knock-in mouse model of AD and subject the mice to several behaviors to determine whether the latent cause model may provide informative predictions regarding changes in the observed behaviors. They include a well-established fear learning paradigm in which distinct memories are believed to compete for control of behavior. More specifically, it's been observed that animals undergoing fear learning and subsequent fear extinction develop two separate memories for the acquisition phase and the extinction phase, such that the extinction does not simply 'erase' the previously acquired memory. Many models of learning require the addition of a separate context or state to be added during the extinction phase and are typically modeled by assuming the existence of a new state at the time of extinction. The Niv research group, Gershman et al. 2017, have shown that the use of a latent cause model applied to this behavior can elegantly predict the formation of latent states based on a Bayesian approach, and that these latent states can facilitate the persistence of the acquisition and extinction memory independently. The authors of this manuscript leverage this approach to test whether deficits in the production of the internal states, or the inference and learning of those states, may be disrupted in knock-in mice that show both a build-up of amyloid-beta plaques and a deterioration in memory as the mice age.

Strengths:

I think the authors' proposal to leverage the latent cause model and test whether it can lead to improved assessments in an animal model of AD is a promising approach for bridging the gap between clinical and basic research. The authors use a promising mouse model and apply this to a paradigm in which the behavior and neurobiology are relatively well understood - an ideal situation for assessing how a disease state may impact both the neurobiology and behavior. The latent cause model has the potential to better connect observed behavior to underlying causes and may pave a road for improved mapping of changes in behavior to neurobiological mechanisms in diseases such as AD.

Weaknesses:

I have several substantial concerns which I've detailed below. These include important details on how the behavior was analyzed, how the model was used to assess the behavior, and the interpretations that have been made based on the model.

(1) There is substantial data to suggest that during fear learning in mice separate memories develop for the acquisition and extinction phases, with the acquisition memory becoming more strongly retrieved during spontaneous recovery and reinstatement. The Gershman paper, cited by the authors, shows how the latent causal model can predict this shift in latent states by allowing for the priors to decay over time, thereby increasing the posterior of the acquisition memory at the time of spontaneous recovery. In this manuscript, the authors suggest a similar mechanism of action for reinstatement, yet the model does not appear to return to the acquisition memory state after reinstatement, at least based on the examples shown in Figures 1 and 3. Rather, the model appears to mainly modify the weights in the most recent state, putatively the 'extinction state', during reinstatement. Of course, the authors must rely on how the model fits the data, but this seems problematic based on prior research indicating that reinstatement is most likely due to the reactivation of the acquisition memory. This may call into question whether the model is successfully modeling the underlying processes or states that lead to behavior and whether this is a valid approach for AD.

(2) As stated by the authors in the introduction, the advantage of the fear learning approach is that the memory is modified across the acquisition-extinction-reinstatement phases. Although perhaps not explicitly stated by the authors, the post-reinstatement test (test 3) is the crucial test for whether there is reactivation of a previously stored memory, with the general argument being that the reinvigorated response to the CS can't simply be explained by relearning the CS-US pairing, because re-exposure the US alone leads to increase response to the CS at test. Of course there are several explanations for why this may occur, particularly when also considering the context as a stimulus. This is what I understood to be the justification for the use of a model, such as the latent cause model, that may better capture and compare these possibilities within a single framework. As such, it is critical to look at the level of responding to both the context alone and to the CS. It appears that the authors only look at the percent freezing during the CS, and it is not clear whether this is due to the contextual US learning during the US re-exposure or to increased response to the CS - presumably caused by reactivation of the acquisition memory. For example, the instance of the model shown in Figure 1 indicates that the 'extinction state', or state z6, develops a strong weight for the context during the reinstatement phase of presenting the shock alone. This state then leads to increased freezing during the final CS probe test as shown in the figure. By not comparing the difference in the evoked freezing CR at the test (ITI vs CS period), the purpose of the reinstatement test is lost in the sense of whether a previous memory was reactivated - was the response to the CS restored above and beyond the freezing to the context? I think the authors must somehow incorporate these different phases (CS vs ITI) into their model, particularly since this type of memory retrieval that depends on assessing latent states is specifically why the authors justified using the latent causal model.

(3) This is related to the second point above. If the question is about the memory processes underlying memory retrieval at the test following reinstatement, then I would argue that the model parameters that are not involved in testing this hypothesis be fixed prior to the test. Unlike the Gershman paper that the authors cited, the authors fit all parameters for each animal. Perhaps the authors should fit certain parameters on the acquisition and extinction phase, and then leave those parameters fixed for the reinstatement phase. To give a more concrete example, if the hypothesis is that AD mice have deficits in differentiating or retrieving latent states during reinstatement which results in the low response to the CS following reinstatement, then perhaps parameters such as the learning rate should be fixed at this point. The authors state that the 12-month-old AD mice have substantially lower learning rate measures (almost a 20-fold reduction!), which can be clearly seen in the very low weights attributed to the AD mouse in Figure 3D. Based on the example in Figure 3D, it seems that the reduced learning rate in these mice is most likely caused by the failure to respond at test. This is based on comparing the behavior in Figures 3C to 3D. The acquisition and extinction curves appear extremely similar across the two groups. It seems that this lower learning rate may indirectly be causing most of the other effects that the authors highlight, such as the low σx, and the changes to the parameters for the CR. It may even explain the extremely high K. Because the weights are so low, this would presumably lead to extremely low likelihoods in the posterior estimation, which I guess would lead to more latent states being considered as the posterior would be more influenced by the prior.

(4) Why didn't the authors use the latent causal model on the Barnes maze task? The authors mention in the discussion that different cognitive processes may be at play across the two tasks, yet reversal tasks have been suggested to be solved using latent states to be able to flip between the two different task states. In this way, it seems very fitting to use the latent cause model. Indeed, it may even be a better way to assess changes in σx as there are presumably 12 observable stimuli/locations.

Reviewer #3 (Public review):

Summary:

This paper seeks to identify underlying mechanisms contributing to memory deficits observed in Alzheimer's disease (AD) mouse models. By understanding these mechanisms, they hope to uncover insights into subtle cognitive changes early in AD to inform interventions for early-stage decline.

Strengths:

The paper provides a comprehensive exploration of memory deficits in an AD mouse model, covering the early and late stages of the disease. The experimental design was robust, confirming age-dependent increases in Aβ plaque accumulation in the AD model mice and using multiple behavior tasks that collectively highlighted difficulties in maintaining multiple competing memory cues, with deficits most pronounced in older mice.

In the fear acquisition, extinction, and reinstatement task, AD model mice exhibited a significantly higher fear response after acquisition compared to controls, as well as a greater drop in fear response during reinstatement. These findings suggest that AD mice struggle to retain the fear memory associated with the conditioned stimulus, with the group differences being more pronounced in the older mice.

In the reversal Barnes maze task, the AD model mice displayed a tendency to explore the maze perimeter rather than the two potential target holes, indicating a failure to integrate multiple memory cues into their strategy. This contrasted with the control mice, which used the more confirmatory strategy of focusing on the two target holes. Despite this, the AD mice were quicker to reach the target hole, suggesting that their impairments were specific to memory retrieval rather than basic task performance.

The authors strengthened their findings by analyzing their data with a leading computational model, which describes how animals balance competing memories. They found that AD mice showed somewhat of a contradiction: a tendency to both treat trials as more alike than they are (lower α) and similar stimuli as more distinct than they are (lower σx) compared to controls.

Weaknesses:

While conceptually solid, the model struggles to fit the data and to support the key hypothesis about AD mice's ability to retain competing memories. These issues are evident in Figure 3:

(1) The model misses key trends in the data, including the gradual learning of fear in all groups during acquisition, the absence of a fear response at the start of the experiment, the increase in fear at the start of day 2 of extinction (especially in controls), and the more rapid reinstatement of fear observed in older controls compared to acquisition.

(2) The model attributes the higher fear response in controls during reinstatement to a stronger association with the context from the unsignaled shock phase, rather than to any memory of the conditioned stimulus from acquisition.

These issues lead to potential overinterpretation of the model parameters. The differences in α and σx are being used to make claims about cognitive processes (e.g., overgeneralization vs. overdifferentiation), but the model itself does not appear to capture these processes accurately.

The authors could benefit from a model that better matches the data and that can capture the retention and recollection of a fear memory across phases.

Conclusion:

Overall, the data support the authors' hypothesis that AD model mice struggle to retain competing memories, with the effect becoming more pronounced with age. While I believe the right computational model could highlight these differences, the current model falls short in doing so.

Reviewer #1 (Public review):

Summary:

In the current study, Huang et al. examined ACC response during a novel discrimination-avoid task. The authors concluded that ACC neurons primarily encode post-action variables over extended periods, reflecting the animal's preceding actions rather than the outcomes or values of those actions. Specifically, they identified two subgroups of ACC neurons that responded to different aspects of the actions. This work represents admirable efforts to investigate the role of ACC in task-performing mice. However, in my opinion, alternative explanations of the data were not sufficiently explored, and some key findings were not well supported.

Strengths:

The development of the new discrimination-avoid task is applauded. Single-unit electrophysiology in task-performing animals represents admirable efforts and the datasets are valuable. The identification of different groups of encoding neurons in ACC can be potentially important.

Weaknesses:

One major conclusion is that ACC primarily encodes the so-called post-action variables (specifically shuttle crossing). However, only a single example session was included in Figure 2, while in Supplementary Figure 2 a considerable fraction of ACC neurons appears to respond to either the onset of movement or ramp up their activity prior to movement onset. How did the authors reach the conclusion that ACC preferentially respond to shuttle crossing?

In Figure 4, it was concluded that ACC neurons respond to action independent of outcome. Since these neurons are active on both correct and incorrect shuttle but not stay trials, they seem to primarily respond to overt movement. If so, the rationale for linking ACC activity and adaptive behavior/associative learning is not very clear to me. Further analyses are needed to test whether their firing rates correlated with locomotion speed or acceleration/deceleration. On a similar note, to what extent are the action state neurons actually responding to locomotion-related signals? And can ACC activity actually differentiate correct vs. incorrect stays?

Given that a considerable amount of ACC neurons encode 'action content', it is not surprising that by including all neurons the model is able to make accurate predictions in Figure 6. How would the model performance change by removing the content neurons?

Moving on to Figure 7. Since Figure 4 showed that ACC neurons respond to movement regardless of outcome, it is somewhat puzzling how ACC activity can be linked to future performance.

Two mice contributed about 50% of all the recorded cells. How robust are the results when analyzing mouse by mouse?

Lastly, the development of the new discrimination-avoid task is applauded. However, a major missing piece here is to show the importance of ACC in this task and what aspects of this behavior require ACC.

Reviewer #2 (Public review):

Summary:

The current dataset utilized a 2x2 factorial shuttle-escape task in combination with extracellular single-unit recording in the anterior cingulate cortex (ACC) of mice to determine ACC action coding. The contributions of neocortical signaling to action-outcome learning as assessed by behavioral tasks outside of the prototypical reward versus non-reward or punished vs non-punished is an important and relevant research topic, given that ACC plays a clear role in several human neurological and psychiatric conditions. The authors present useful findings regarding the role of ACC in action monitoring and learning. The core methods themselves - electrophysiology and behavior - are adequate; however, the analyses are incomplete since ruling out alternative explanations for neural activity, such as movement itself, requires substantial control analyses, and details on statistical methods are not clear.

Strengths:

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

(2) The figures are mostly well-presented, labeled, and easy to read.

(3) 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.

(4) 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.

(5) 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:

(1) The behavioral data could use slightly more characterization, such as separating stay versus shuttle trials.

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

(3) Many of the neural analyses seem to utilize long time windows, not leveraging the very real strength of recording spike times. Specifics on the exact neural activity binning/averaging, tests, classifier validation, and methods for quantification are difficult to find.

(4) The neural analyses seem to suggest that ACC neurons encode one variable or the other, but are there any that multiplex? Given the overwhelming evidence of multiplexing in the ACC a bit more discussion of its presence or absence is warranted.

Reviewer #3 (Public review):

Summary:

The authors record from the ACC during a task in which animals must switch contexts to avoid shock as instructed by a cue. As expected, they find neurons that encode context, with some encoding of actions prior to the context, and encoding of neurons post-action. The primary novelty of the task seems to be dynamically encoding action-outcome in a discrimination-avoidance domain, while this is traditionally done using operant methods. While I'm not sure that this task is all that novel, I can't recall this being applied to the frontal cortex before, and this extends the well-known action/context/post-context encoding of ACC to the discrimination-avoidance domain.

While the analysis is well done, there are several points that I believe should be elaborated upon. First, I had questions about several details (see point 3 below). Second, I wonder why the authors downplayed the clear action coding of ACC ensembles. Third, I wonder if the purported 'novelty' of the task (which I'm not sure of) and pseudo-debate on ACC's role undermines the real novelty - action/context/outcome encoding of ACC in discrimination-avoidance and early learning.

Strengths:

Recording frontal cortical ensembles during this task is particularly novel, and the analyses are sophisticated. The task has the potential to generate elegant comparisons of action and outcome, and the analyses are sophisticated.

Weaknesses:

I had some questions that might help me understand this work better.

(1) I wonder if the field would agree that there is a true 'debate' and 'controversy' about the ACC and conflict monitoring, or if this is a pseudodebate (Line 34). They cite 2 very old papers to support this point. I might reframe this in terms of the frontal cortex studying action-outcome associations in discrimination-avoidance, as the bulk of evidence in rodents comes from overtrained operant behavior, and in humans comes from high-level tasks, and humans are unlikely to get aversive stimuli such as shocks.

(2) Does the purported novelty of the task undermine the argument? While I don't have an exhaustive knowledge of this behavior, the novelty involves applying this ACC. There are many paradigms where a shock triggers some action that could be antecedents to this task.

(3) The lack of details was confusing to me:

a) How many total mice? Are the same mice in all analyses? Are the same neurons? Which training day? Is it 4 mice in Figure 3? Five mice in line 382? An accounting of mice should be in the methods. All data points and figures should have the number of neurons and mice clearly indicated, along with a table. Without these details, it is challenging to interpret the findings.

b) How many neurons are from which stage of training? In some figures, I see 325, in some ~350, and in S5/S2B, 370. The number of neurons should be clearly indicated in each figure, and perhaps a table.

c) Were the tetrodes driven deeper each day? The depth should be used as a regressor in all analyses?

d) Was is really ACC (Figure 2A)? Some shanks are in M2? All electrodes from all mice need to be plotted as a main figure with the drive length indicated.

e) It's not clear which sessions and how many go into which analysis

f) How many correct and incorrect trials (<7?) are there per session?

g) Why 'up to 10 shocks' on line 358? What amplitudes were tried? What does scrambled mean?

(4) Why do the authors downplay pre-action encoding? It is clearly evident in the PETHs, and the classifiers are above chance. It's not surprising that post-shuttle classification is so high because the behavior has occurred. This is most evident in Figure S2B, which likely should be a main figure.

(5) The statistics seem inappropriate. A linear mixed effects model accounting for between-mouse variance seems most appropriate. Statistical power or effect size is needed to interpret these results. This is important in analyses like Figure 7C or 6B.

(6) Better behavioral details might help readers understand the task. These can be pulled from Figures S2 and S5. This is particularly important in a 'novel' task.

(7) Can the authors put post-action encoding on the same classification accuracy axes as Figure 6B? It'd be useful to compare.

(8) What limitations are there? I can think of several - number of animals, lack of causal manipulations, ACC in rodents and humans.

Minor:

(1) Each PCA analysis needs a scree plot to understand the variance explained.

(2) Figure 4C - y and x-axes have the same label?

(3) What bin size do the authors use for machine learning (Not clear from line 416)?

(4) Why not just use PCA instead of 'dimension reduction' (of which there are many?)

(5) Would a video enhance understanding of the behavior?

Reviewer #1 (Public review):

Summary:

The authors tackled the public concern about E-cigarettes among young adults by examining the lung immune environment in mice using single-cell RNA sequencing, discovering a subset of Ly6G- neutrophils with reduced IL-1 activity and increased CD8 T cells following exposure to tobacco-flavored e-cigarettes. Preliminary serum cotinine (nicotine metabolite) measurements validated the effective exposure to fruit, menthol, and tobacco-flavored e-cigarettes with air and PG:VG serving as control groups. They also highlighted the significance of metal leaching, which fluctuated over different exposure durations to flavored e-cigarettes, underscoring the inherent risks posed by these products. The scRNAseq analysis of e-cig exposure to flavors and tobacco demonstrated the most notable differences in the myeloid and lymphoid immune cell populations. Differentially expressed genes (DEGs) were identified for each group and compared against the air control. Further sub-clustering revealed a flavor-specific rise in Ly6G- neutrophils and heightened activation of cytotoxic T cells in response to tobacco-flavored e-cigarettes. These effects varied by sex, indicating that immune changes linked to e-cig use are dependent on gender. By analyzing the expression of various genes and employing gene ontology and gene enrichment analysis, they identified key pathways involved in this immune dysregulation resulting from flavor exposure. Overall, this study affirmed that e-cigarette exposure can suppress the neutrophil-mediated immune response, subsequently enhancing T cell toxicity in the lung tissue of mice.

Strengths:

This study used single-cell RNA sequencing to comprehensively analyze the impact of e-cigarettes on the lung. The study pinpointed alterations in immune cell populations and identified differentially expressed genes and pathways that are disrupted following e-cigarette exposure. The manuscript is well written, the hypothesis is clear, the experiments are logically designed with proper control groups, and the data is thoroughly analyzed and presented in an easily interpretable manner. Overall, this study suggested novel mechanisms by which e-cigs impact lung immunity and created a dataset that could benefit the lung immunity field.

Weaknesses:

(1) The authors included a valuable control group - the PG:VG group, since PG:VG is the foundation of the e-liquid formulation. However, most of the comparative analyses use the air group as the control. Further analysis comparing the air group to the PG:VG group, and the PG:VG group to the individual flavored e-cig groups will provide more clear insights into the true source of irritation. This is done for a few analyses but not consistently throughout the paper. Flavor-specific effects should be discussed in greater detail. For example, Figure 1E shows that the Fruit flavor group exhibits more severe histological pathology but similar effects were not corroborated by the single-cell data.

(2) The characterization of Ly6g+ vs Ly6g- neutrophils is interesting and potentially very impactful. Key results like this from scRNAseq analyses should be validated by qPCR and flow cytometry.

Also, a recent study by Ruscitti et al reported Ly6g+ macrophages in the lung which can potentially confound the cell type analysis. A more detailed marker gene and sub-population analysis of the myeloid clusters could rule out this potential confounding factor.

Reviewer #2 (Public review):

This study provides some interesting observations on how different flavors of e-cigarettes can affect lung immunology, however there are numerous flaws including a low number of replicates and a lack of effective validation methods which reduces the robustness and rigor of the findings.

Strengths:

The strength of the study is the successful scRNA-seq experiment which gives good preliminary data that can be used to create new hypotheses in this area.

Weaknesses:

The major weakness is the low number of replicates and the limited analysis methods. Two biological n per group is not acceptable to base any solid conclusions. Any validatory data was too little (only cell % data) and did not always support the findings (e.g. Figure 4D does not match 4C). Often n seems to be combined and only one data point is shown, it is not at all clear how the groups were analysed and how many cells in each group were compared.

Other specific weaknesses were identified in addition to the ones above:

(1) Only 71,725 cells means only 7,172 per group, which is 3,586 per animal - how many of these were neutrophils, T-cells, and macrophages? This was not shown and could be too low.

(2) The dynamic range of RNA measurement using scRNAseq is known to be limited - how do we know whether genes are not expressed or just didn't hit detection? This links into the Ly6G negative neutrophil comment, but in general, the lack of gene expression in this kind of data should be viewed with caution, especially with a low n number and few cells.

(3) There is no rigorous quantification of Ly6G+ and Ly6G- cells int he flow cytometry data.

(4) Eosinophils are heavily involved in lung biology but are missing from the analysis.

(5) The figures had no titles so were difficult to navigate.

(6) PGVG is not defined and not introduced early enough.

(7) Neutrophils are not well known to proliferate, so any claims about proliferation need to be accompanied by validation such as BrdU or other proliferation assays.

(8) It was not clear how statistics were chosen and why Table S2 had a good comparison (two-way ANOVA with gender as a variable) but this was not used for other data particularly when looking at more functional RNA markers (Table S2 also lacks the interaction statistic which is most useful here).

(9) Many statistics are only vs air control, but it would be more useful as a flavour comparison to see these vs PGVG. In some cases, the carrier PGVG looks worse than some of the flavours (which have nicotine).

(10) The n number is a large issue, but in Figures such as 4, 6, and 7 it could be a bigger factor. The number of significant genes identified has been determined by chance rather than any real difference, e.g. Is Il1b not identified in Fruit flavour vs air because there wasn't enough n, while in Air vs Tobacco, it randomly hit the significance mark. This is but an example of the problems with the analysis and conclusions

(11) The data in Figure 7A is confusing, if this is a comparison to air, then why does air vs air not equal 1? Even if this was the comparison to the average of air between males and females, then this doesn't explain why CCL12 is >1 in both. Is this z-score instead? Regardless the data is difficult to interpret in this format.

(12) Individual n was not shown for almost all experiments - e.g. Figure 1D - what is this representative of? Figure 2D - is this bulk-grouped data for all cells and all mice? The heatmaps are also pooled from 2n and don't show the variability.

Reviewer #3 (Public review):

This work aims to establish cell-type specific changes in gene expression upon exposure to different flavors of commercial e-cigarette aerosols compared to control or vehicle. Kaur et al. conclude that immune cells are most affected, with the greatest dysregulation found in myeloid cells exposed to tobacco-flavored e-cigs and lymphoid cells exposed to fruit-flavored e-cigs. The up-and-down-regulated genes are heavily associated with innate immune response. The authors suggest that a Ly6G-deficient subset of neutrophils is found to be increased in abundance for the treatment groups, while gene expression remains consistent, which could indicate impaired function. Increased expression of CD4+ and CD8+ T cells along with their associated markers for proliferation and cytotoxicity is thought to be a result of activation following this decline in neutrophil-mediated immune response.

Strengths:

(1) Single-cell sequencing data can be very valuable in identifying potential health risks and clinical pathologies of lung conditions associated with e-cigarettes considering they are still relatively new.

(2) Not many studies have been performed on cell-type specific differential gene expression following exposure to e-cig aerosols.

(3) The assays performed address several factors of e-cig exposure such as metal concentration in the liquid and condensate, coil composition, cotinine/nicotine levels in serum and the product itself, cell types affected, which genes are up- or down-regulated and what pathways they control.

(4) Considerations were made to ensure clinical relevance such as selecting mice whose ages corresponded with human adolescents so that the data collected was relevant.

Weaknesses:

(1) The exposure period of 1 hour a day for 5 days is not representative of chronic use and this time point may be too short to see a full response in all cell types. The experimental design is not well-supported based on the literature available for similar mouse models.

(2) Several claims lack supporting evidence or use data that is not statistically significant. In particular, there were no statistical analyses to compare results across sex, so conclusions stating there is a sex bias for things like Ly6G+ neutrophil percentage by condition are observational.

(3) Statistical analyses lack rigor and are not always displayed with the most appropriate graphical representation.

(4) Overall, the paper and its discussion are relatively limited and do not delve into the significance of the findings or how they fit into the bigger picture of the field.

(5) The manuscript lacks validation of findings in tissue by other methods such as staining.

(6) This paper provides a foundation for follow-up experiments that take a closer look at the effects of e-cig exposure on innate immunity. There is still room to elaborate on the differential gene expression within and between various cell types.

Reviewer #1 (Public review):

Summary:

Praegel et al. explore the differences in learning an auditory discrimination task between adolescent and adult mice. Using freely moving (Educage) and head-fixed paradigms, they compare behavioral performance and neuronal responses over the course of learning. The mice were initially trained for seven days on an easy pure frequency tone Go/No-go task (frequency difference of one octave), followed by seven days of a harder version (frequency difference of 0.25 octave). While adolescents and adults showed similar performances on the easy task, adults performed significantly better on the harder task. Quantifying the lick bias of both groups, the authors then argue that the difference in performance is not due to a difference in perception, but rather to a difference in cognitive control. The authors then used neuropixel recordings across 4 auditory cortical regions to quantify the neuronal activity related to the behavior. At the single-cell level, the data shows earlier stimulus-related discrimination for adults compared to adolescents in both the easy and hard tasks. At the neuronal population level, adults displayed a higher decoding accuracy and lower onset latency in the hard task as compared to adolescents. Such differences were not only due to learning, but also to age as concluded from recordings in novice mice. After learning, neuronal tuning properties had changed in adults but not in adolescents. Overall, the differences between adolescent and adult neuronal data correlate with the behavior results in showing that learning a difficult task is more challenging for younger mice.

Strengths:

(1) The behavioral task is well designed, with the comparison of easy and difficult tasks allowing for a refined conclusion regarding learning across ages. The experiments with optogenetics and novice mice complete the research question in a convincing way.

(2) The analysis, including the systematic comparison of task performance across the two age groups, is most interesting and reveals differences in learning (or learning strategies?) that are compelling.

(3) Neuronal recording during both behavioral training and passive sound exposure is particularly powerful and allows interesting conclusions.

Weaknesses:

(1) The presentation of the paper must be strengthened. Inconsistencies, mislabeling, duplicated text, typos, and inappropriate color code should be changed.

(2) Some claims are not supported by the data. For example, the sentence that says that "adolescent mice showed lower discrimination performance than adults (l.22) should be rewritten, as the data does not show that for the easy task (Figure 1F and Figure 1H).

(3) The recording electrodes cover regions in the primary and secondary cortices. It is well known that these two regions process sounds quite differently (for example, one has tonotopy, the other does not), and separating recordings from both regions is important to conclude anything about sound representations. The authors show that the conclusions are the same across regions for Figure 4, but is it also the case for the subsequent analysis? In Figure 7 for example, are the quantified properties not distinct across primary and secondary areas? If this is not the case, how is it compatible with the published literature?

(4) Some analysis interpretations should be more cautious. For example, I do not understand how the lick bias, defined -according to the method- as the inverse normal distribution of the z-score (hit rate) +z-scored (false alarm rate; Figure 1j?, l.749-750), should reflect a cognitive difficulty (l. 161-162, l.171). A lower lick rate in general could reflect a weaker ability to withhold licking- as indicated on l.164, but also so many other things, like a lower frustration threshold, lower satiation, more energy, etc).

Reviewer #2 (Public review):

Summary:

The authors aimed to find out how - and how well - adult and adolescent mice discriminate tones of different frequencies and whether there are differences in processing at the level of the auditory cortex that might explain differences in behavior between the two groups. Adolescent mice were found to be worse at sound frequency discrimination than adult mice. The performance difference between the groups was most pronounced when the sounds were close in frequency and thus difficult to distinguish, and could, at least in part, be attributed to the younger mice's inability to withhold licking in no-go trials. By recording the activity of individual neurons in the auditory cortex when mice performed the task or were passively listening as well as in untrained mice the authors identified differences in the way that the adult and adolescent brains encode sounds and the animals' choice that could potentially contribute to the differences in behavior.

Strengths:

The study combines behavioural testing in freely-moving and head-fixed mice, optogenetic manipulation, and high-density electrophysiological recordings in behaving mice to address important open questions about age differences in sound-guided behavior and sound representation in the auditory cortex.

Weaknesses:

For some of the analyses that the authors conducted it is unclear what the rationale behind them is and, consequently, what conclusion we can draw from them. The results of the optogenetic manipulation, while very interesting, warrant a more in-depth discussion.

Reviewer #3 (Public review):

Summary:

In this study, Benedikt et al. sought to understand how adolescents and adult mice differ in auditory cortical processing, performance on a go/nogo sound-guided task, and learning. They report that behavioral performance is superior in adults. They also report that neuronal representations of both the acoustic stimulus and behavioral choice are weaker and sluggish in adolescents compared to adults and that these differences were larger in expert mice than in novices. The neural basis of adolescent auditory cognition is an important topic (both clinically and from a basic science perspective) and vastly understudied. However, many aspects of the study fell short, thereby undermining the primary conclusions drawn by the authors. My major concerns are as follows:

(1) The authors report that "adolescent mice showed lower auditory discrimination performance compared to adults" and that this performance deficit was due to (among other things) "weaker cognitive control". I'm not fully convinced of this interpretation, for a few reasons. First, the adolescents may simply have been thirstier, and therefore more willing to lick indiscriminately. The high false alarm rates in that case would not reflect a "weaker cognitive control" but rather, an elevated homeostatic drive to obtain water. Second, even the adult animals had relatively high (~40%) false alarm rates on the freely moving version of the task, suggesting that their behavior was not particularly well controlled either. One fact that could help shed light on this would be to know how often the animals licked the spout in between trials. Finally, for the head-fixed version of the task, only d' values are reported. Without the corresponding hit and false alarm rates (and frequency of licking in the intertrial interval), it's hard to know what exactly the animals were doing.

(2) There are some instances where the citations provided do not support the preceding claim. For example, in lines 64-66, the authors highlight the fact that the critical period for pure tone processing in the auditory cortex closes relatively early (by ~P15). However, one of the references cited (ref 14) used FM sweeps, not pure tones, and even provided evidence that the critical period for this more complex stimulus occurred later in development (P31-38). Similarly, on lines 72-74, the authors state that "ACx neurons in adolescents exhibit high neuronal variability and lower tone sensitivity as compared to adults." The reference cited here (ref 4) used AM noise with a broadband carrier, not tones.

(3) Given that the authors report that neuronal firing properties differ across auditory cortical subregions (as many others have previously reported), why did the authors choose to pool neurons indiscriminately across so many different brain regions? And why did they focus on layers 5/6? (Is there some reason to think that age-related differences would be more pronounced in the output layers of the auditory cortex than in other layers?)

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors demonstrate for the first time that opioid signaling has opposing effects on the same target neuron depending on the source of the input. Further, the authors provide evidence to support the role of potassium channels in regulating a brake on glutamatergic and cholinergic signaling, with the latter finding being developmentally regulated and responsive to opioid treatment. This evidence solves a conundrum regarding cholinergic signaling in the interpeduncular nucleus that evaded elucidation for many years.

Strengths:

This manuscript provides 3 novel and important findings that significantly advance our understanding of the medial habenula-interpeduncular circuitry:

(1) Mu opioid receptor activation (mOR) reduces postsynaptic glutamatergic currents elicited from substance P neurons while simultaneously enhancing postsynaptic glutamatergic currents from cholinergic neurons, with the latter being developmentally regulated.

(2) Substance P neurons from the Mhb provide functional input to the rostral nucleus of the IPN, in addition to the previously characterized lateral nuclei.

(3) Potassium channels (Kv1.2) provide a break in neurotransmission in the IPN.

Weaknesses:

Overall I find the data presented compelling, but I feel that the number of observations is quite low (typically n=3-7 neurons, typically one per animal). While I understand that only a few slices can be obtained for the IPN from each animal, the strength of the novel findings would be more convincing with more frequent observations (larger n, more than one per animal). The findings here suggest that the authors have identified a novel mechanism for the normal function of neurotransmission in the IPN, so it would be expected to be observable in almost any animal. Thus it is not clear to me why the authors investigated so few neurons per slice and chose to combine different treatments into one group (e.g. Figure 2f), even if the treatments have the same expected effect.

There are also significant sex differences in nAChR expression in the IPN that might not be functionally apparent using the low n presented here. It would be helpful to know which of the recorded neurons came from each sex, rather than presenting only the pooled data.

There are also some particularly novel observations that are presented but not followed up on, and this creates a somewhat disjointed story. For example, in Figure 2, the authors identify neurons in which no response is elicited by light stimulation of ChAT-neurons, but the application of DAMGO (mOR agonist) un-silences these neurons. Are there baseline differences in the electrophysiological or morphological properties of these "silent" neurons compared to the responsive neurons?

Reviewer #2 (Public review):

Summary:

In this paper, Chittajallu and colleagues present compelling evidence that mu opioid receptor (MOR) activation can potentiate synaptic neurotransmission in a medial habenula to interpeduncular nucleus (mHb-IPN) subcircuit. While, projections from mHb tachykinin 1 (Tac1) neurons onto lateral IPN neurons show a canonical opioid-induced synaptic depression in glutamate release, excitatory neurotransmission in mHb choline acetyltransferase (ChAT) projections to the rostral IPN is potentiated by opioids. This process may require the inhibition of voltage-gated potassium channels (Kv1.2) and results in an augmented co-release of glutamate and acetylcholine. This function emerges around age P27 in mice, when MOR expression in the IPN peaks.

Strengths:

Carefully executed electrophysiological experiments with appropriate controls. Interesting description of a neurodevelopmental change in the effects of opioids on mHb-IPN signaling.

Weaknesses:

The genetic strategy used to target the mHb-IPN pathway (constitutive expression in all ChAT+ and Tac1+ neurons) is not specific to this projection. In addition, a braking mechanism involving Kv1.2 has not been identified.

Reviewer #3 (Public review):

Summary:

Here the authors describe the role of mORs in synaptic glutamate release from substance P and cholinergic neurons in the medial habenula to the interpeduncular nucleus (IPN) circuit in adult mice. They show that mOR activation reduces evoked glutamate release from substance P neurons yet increases evoked glutamate release and Ach release from cholinergic neurons. Unlike glutamate release, Ach release is only detected when potassium channels are blocked with 4-AP or dendrotoxin, implicating Kv1.2. The authors also report a previously unidentified glutamatergic input to IPR mediated from SP neurons and describe the developmental timing of mOR-facilitation in adolescent mice.

Strengths:

(1) The experiments provide new insight into the role of mORs in controlling evoked glutamate release in a circuit with high levels of mORs and established roles in relevant behaviors.

(2) The experimental design is generally rigorous, and the results are clear-cut. The conclusions are largely supported by the data.

(3) The findings will be of interest to those working in the field.

Weaknesses:

(1) The mechanistic underpinnings of the most interesting results are not pursued. For example, the experiments do not provide new insight into the differential effects of evoked and spontaneous glutamate/Ach release by Gi/o coupled mORs, nor the differential threshold for glutamate versus Ach release.

(2) The significance of the ratio of AMPA versus nACh EPSCs shown in Figure 6 is unclear since nAChR EPSCs measured in the K+ channel blockers are compared to AMPA EPSCs in control (presumably 4-AP would also increase AMPA EPSCs).

(3) The authors note that blocking Kv1 channels typically enhances transmitter release by slowing action potential repolarization. The idea that Kv1 channels serve as a brake for Ach release in this system would be strengthened by showing that these channels are the target of neuromodulators or that they contribute to activity-dependent regulation that allows the brake to be released.

Reviewer #1 (Public review):

Summary:

The authors were attempting to describe whether trained innate immunity would modulate antibody-dependent cellular phagocytosis (ADCP) and/or efferocytosis.

Strengths:

The use of primary murine macrophages, and not a cell line, is considered a strength.

The trained immunity-mediated changes to phagocytosis affected both melanoma and breast cancer cells. The broad effect is consistent with trained immunity.

Weaknesses:

The most significant weakness, also noted by the authors in the discussion, is the lack of in vivo data. Without these data, it is not possible to put the in vitro data in context. It is unknown if the described effects on efferocytosis will be relevant to the in vivo progression of cancer.

Reviewer #2 (Public review):

Summary:

The authors follow up their preclinical work on beta-glucan-induced trained immunity in murine tumor models that they published in Cell in 2020. In particular, they focus on the role of trained immunity and efferocytosis of cancer cells

Strengths:

While properly conducted, the work is underwhelming and fully depends on in vitro observations performed with co-cultures of bone marrow derived macrophages from beta-glucan-treated mice and tumor cell lines. From these in vitro studies, the authors conclude that trained immunity induction has no effect on antibody-dependent cellular phagocytosis, while it decreases efferocytosis.

Weaknesses:

It would be important to study these phenomena in tumor mouse models in vivo. The authors clearly have the expertise as they have shown in previous studies. Especially because the in vitro observation appears to conflict with the in vivo anti-tumor found in mice prophylactically treated with beta-glucan. Clearly, trained immunity is associated with diverse cellular responses and mechanisms, some of which may promote tumor growth, as the current manuscript suggests, but in the absence of in vivo studies, it is merely a mechanistic exercise of which the relevance is difficult to determine.

Reviewer #3 (Public review):

Summary:

Chatzis et al showed that β-glucan trained macrophages have decreased phagocytic activity of apoptotic tumor cells and that is accompanied by lower levels of secreted IL-1β using a mouse model.

Strengths:

This finding has a potential impact on designing new cancer immunotherapeutic approaches by targeting macrophage efferocytosis.

Weaknesses:

Whether this finding could be applied to other scenarios is underdetermined.

(1) Does the decrease of efferocytosis also occur in human monocytes/macrophages after training?

(2) Both β-glucan and BCG are well-trained innate immunity agents, the authors showed that β-glucan decreased efferocytosis via IL-1 β, so it is interesting to know whether BCG has a similar effect.

Reviewer #1 (Public review):

Summary:

Integrating large-field stimulation with a retinotopic atlas, this study introduces an fMRI-based method for measuring contrast sensitivity across the visual field. Retinotopy was assessed using pRF mapping and a calibrated Benson atlas. The authors validate their method by replicating known patterns of contrast sensitivity across eccentricities and visual field quadrants in healthy subjects and demonstrate its potential clinical utility through case studies of both simulated and real visual field loss.

Strengths:

The new method is promising, with potential clinical utility in assessing visual field loss.

Weaknesses:

The current claims should be better supported by more evidence.

In the first experiment, have the statistics undergone multiple comparison corrections (e.g., Line 441-442)? Given the small sample size, incorporating additional statistical tests (such as the Bayes Factor) could strengthen the analysis.

The authors claim that "structure-based atlases can replace the need for pRF mapping in cases where it might otherwise be difficult or impossible to collect pRF data." This claim needs further scrutiny. Currently, only one simulated condition of visual field loss was examined in one subject. Also, in Figure 7, contrast sensitivity in the periphery differs between pRF mapping and the Benson atlas. How do the authors explain this discrepancy?

Overall, the writing could be significantly improved.

Reviewer #2 (Public review):

Summary:

This study uses functional MRI to evaluate visual contrast sensitivity across the visual field at the level of the visual cortex, testing the method in a small group of normally sighted individuals and one with sight loss as proof of principle. The results suggest a promising technique to measure vision objectively across the visual field and overcomes the requirement for careful fixation which is often challenging in those with low vision or sight loss.

Strengths:

(1) Objective measure of central vision: The proposed method may provide a more comprehensive and objective assessment of residual visual function in individuals with sight loss. This may be particularly useful for those with central visual field loss without the requirement of stable fixation or subjective motor responses.

(2) More sensitive measure: The use of slope to calculate contrast sensitivity across a range of contrasts within the brain is clever and likely more sensitive than single threshold measurements or standard clinical measures of visual acuity using letter charts. Standard supra-threshold (high contrast) tests are not ideal for capturing residual vision or partial vision loss.

(3) Good agreement with standard atlas: The Benson atlas provides a good estimate of visual field maps within V1 based on anatomical landmarks, and the authors take steps to refine this informed by cortical magnification and V1 surface area (brain size) for each individual participant. This could allow the technique to be generalised without the need to collect lengthy individual mapping data from every participant.

(4) Within-subject reproducibility: The measurements appear to be sensitive and reproducible, particularly in those with normal vision, and are consistent with known features of visual sensitivity differences in different parts of the visual field.

(5) Potential tool to measure visual field sensitivity in controls: Even if the proposed methods are not ideal for widespread clinical translation, they do offer an exciting tool to test hypotheses about visual field differences in healthy controls. For example, there seems to be an increase in sensitivity on either side of the simulated ring scotoma (Figure 6 - perhaps due to the release of lateral inhibition?). Reliability measures suggest that individual differences are consistent in healthy controls (although not tested statistically, perhaps due to the small sample size?). Whether they reflect behaviourally meaningful differences in visual field sensitivity could be tested in individuals by comparing them to behavioural measures across the visual field.

(6) Potential tool to test novel treatments: The proposed techniques could be used to test within-subject changes in visual function in environments that are equipped to measure and analyse fMRI data, including clinical trials aimed at determining the success of novel treatments. Further testing should reveal whether the method is suitable for testing low-vision patients with unstable fixation (e.g., nystagmus) and whether this affects slope and contrast sensitivity estimates. In theory, it should not have a substantial effect, except perhaps in regions near the stimulus edges.

Weaknesses:

(1) Questionable sensitivity to differences in patients. The variability in heat maps across healthy control participants is somewhat surprising. Do differences between individuals represent actual visual sensitivity differences, or are they an artifact of the measurement technique, e.g., due to signal-to-noise differences introduced by local variations in brain anatomy? Will the substantial variance across controls allow for a sufficiently stable baseline to detect meaningful differences in individual patients? Also, as the authors rightly point out, Benson atlas does not model differences along meridians, so upper/lower field differences might not be detectable.

(2) Effects of unstable fixation/eye movements not explicitly tested: The methods state, 'In all tasks, participants were asked to report when the color of a central fixation dot changed', suggesting participants maintained fairly good fixation. Most of the results seem to pertain to measurements where central fixation is required. How does unstable fixation affect measurements?

(3) Potential for clinical translation. Although it is a sensitive measure, functional MRI is costly, is not available in all clinical settings, requires significant post-processing analyses, and may be contraindicated in some individuals due to safety (e.g., metallic implants) or other concerns (e.g., claustrophobia). These could present significant barriers to widespread clinical translation if this were the ultimate goal of the study.

(4) Limited range of spatial frequencies. The spatial frequencies tested were still quite low (0.3 and 3cpd) compared to measures such as visual acuity. Extending the measurements to higher spatial frequencies could allow better characterization of central vision, although necessarily for peripheral vision.