Reviewer #3 (Public review):

Summary:

The authors suggest a new biomarker of chronic back pain with an option to predict a result of treatment.

Strengths:

The results were reproduced in three studies.

Weaknesses:

The number of participants is still low, an explanation of microstructure changes was not given, and some technical drawbacks are presented.

Reviewer #1 (Public review):

Summary:

The authors intended to investigate the earliest mechanisms enabling self-prioritization, especially in the attention. Combining a temporal order judgement task with computational modelling based on the Theory of Visual Attention (TVA), the authors suggested that the shapes associated with the self can fundamentally alter the attentional selection of sensory information into awareness. This self-prioritization in attentional selection occurs automatically at early perceptual stages. Furthermore, the processing benefits obtained from attentional selection via self-relatedness and physical salience were separated from each other.

Strengths:

The manuscript is written in a way that is easy to follow. The methods of the paper are very clear and appropriate.

Weaknesses:

There are two main concerns:

(1) The authors had a too strong pre-hypothesis that self-prioritization was associated with attention. They used the prior entry to consciousness (awareness) as an index of attention, which is not appropriate. There may be other processing that makes the stimulus prior to entry to consciousness (e.g. high arousal, high sensitivity), but not attention. The self-related/associated stimulus may be involved in such processing but not attention to make the stimulus easily caught. Perhaps the authors could include other methods such as EEG or MEG to answer this question.

(2) The authors suggested that there are two independent attention processes. I suspect that the brain needs two attention systems. Is there a probability that the social and perceptual (physical properties of the stimulus) salience fired the same attention processing through different processing?

Reviewer #2 (Public review):

Summary:

The main aim of this research was to explore whether and how self-associations (as opposed to other associations) bias early attentional selection, and whether this can explain well-known self-prioritization phenomena, such as the self-advantage in perceptual matching tasks. The authors adopted the Visual Attention Theory (VAT) by estimating VAT parameters using a hierarchical Bayesian model from the field of attention and applied it to investigate the mechanisms underlying self-prioritization. They also discussed the constraints on the self-prioritization effect in attentional selection. The key conclusions reported were:

(1) Self-association enhances both attentional weights and processing capacity

(2) Self-prioritization in attentional selection occurs automatically but diminishes when active social decoding is required, and

(3) Social and perceptual salience capture attention through distinct mechanisms.

Strengths:

Transferring the Theory of Visual Attention parameters estimated by a hierarchical Bayesian model to investigate self-prioritization in attentional selection was a smart approach. This method provides a valuable tool for accessing the very early stages of self-processing, i.e., attention selection. The authors conclude that self-associations can bias visual attention by enhancing both attentional weights and processing capacity and that this process occurs automatically. These findings offer new insights into self-prioritization from the perspective of the early stage of attentional selection.

Weaknesses:

(1) The results are not convincing enough to definitively support their conclusions. This is due to inconsistent findings (e.g., the model selection suggested condition-specific c parameters, but the increase in processing capacity was only slight; the correlations between attentional selection bias and SPE were inconsistent across experiments), unexpected results (e.g., when examining the impact of social association on processing rates, the other-associated stimuli were processed faster after social association, while the self-associated stimuli were processed more slowly), and weak correlations between attentional bias and behavioral SPE, which were reported without any p-value corrections. Additionally, the reasons why the attentional bias of self-association occurs automatically but disappears during active social decoding remain difficult to explain. It is also possible that the self-association with shapes was not strong enough to demonstrate attention bias, rather than the automatic processes as the authors suggest. Although these inconsistencies and unexpected results were discussed, all were post hoc explanations. To convince readers, empirical evidence is needed to support these unexpected findings.

(2) The generalization of the findings needs further examination. The current results seem to rely heavily on the perceptual matching task. Whether this attentional selection mechanism of self-prioritization can be generalized to other stimuli, such as self-name, self-face, or other domains of self-association advantages, remains to be tested. In other words, more converging evidence is needed.

(3) The comparison between the "social" and "perceptual" tasks remains debatable, as it is challenging to equate the levels of social salience and perceptual salience. In addition, these two tasks differ not only in terms of social decoding processes but also in other aspects such as task difficulty. Whether the observed differences between the tasks can definitively suggest the specificity of social decoding, as the authors claim, needs further confirmation.

Reviewer #1 (Public review):

Summary:

The authiors show that SVZ derived astrocytes respond to a middle carotid artery occlusion (MCAO) hypoxia lesion by secreting and modulating hyaluronan at the edge of the lesion (penumbra) and that hyaluronin is a chemoattractant to SVZ astrocytes. They use lineage tracing of SVZ cells to determine their origin. They also find that SVZ derived astrocytes express Thbs-4 but astrocytes at the MCAO-induced scar do not. Also, they demonstrate that decreased HA in the SVZ is correlated with gliogenesis. While much of the paper is descriptive/correlative they do overexpress Hyaluronan synthase 2 via viral vectors and show this is sufficient to recruit astrocytes to the injury. Interestingly, astrocytes preferred to migrate to the MCAO than to the region of overexpressed HAS2.

Strengths:

The field has largely ignored the gliogenic response of the SVZ, especially with regards to astrocytic function. These cells and especially newborn cells may provide support for regeneration. Emigrated cells from the SVZ have been shown to be neuroprotective via creating pro-survival environments, but their expression and deposition of beneficial extracellular matrix molecules is poorly understood. Therefore, this study is timely and important. The paper is very well written and the flow of results logical.

Comments on revised version:

The authors have addressed my points and the paper is much improved. Here are the salient remaining issues that I suggest be addressed.

The authors have still not shown, using loss of function studies, that Hyaluronan is necessary for SVZ astrogenesis and or migration to MCAO lesions.

(1) The co-expression of EGFr with Thbs4 and the literature examination is useful.

(2) Too bad they cannot explain the lack of effect of the MCAO on type C cells. The comparison with kainate-induced epilepsy in the hippocampus may or may not be relevant.

(3) Thanks for including the orthogonal confocal views in Fig S6D.

(4) The statement that "BrdU+/Thbs4+ cells mostly in the dorsal area" and therefore they mostly focused on that region is strange. Figure 8 clearly shows Thbs4 staining all along the striatal SVZ. Do they mean the dorsal segment of the striatal SVZ or the subcallosal SVZ? Fig. 4b and Fig 4f clearly show the "subcallosal" area as the one analysed but other figures show the dorsal striatal region (Fig. 2a). This is important because of the well-known embryological and neurogenic differences between the regions.

(5) It is good to know that the harsh MCAO's had already been excluded.

(6) Sorry for the lack of clarity - in addition to Thbs4, I was referring to mouse versus rat Hyaluronan degradation genes (Hyal1, Hyal2 and Hyal3) and hyaluronan synthase genes (HAS1 and HAS2) in order to address the overall species differences in hyaluronan biology thus justifying the "shift" from mouse to rat. You examine these in the (weirdly positioned) Fig. 8h,i. Please add a few sentences on mouse vs rat Thbs4 and Hyaluronan relevant genes.

(7) Thank you for the better justification of using the naked mole rat HA synthase.

Reviewer #3 (Public review):

Summary:

The authors aimed to study the activation of gliogenesis and the role of newborn astrocytes in a post-ischemic scenario. Combining immunofluorescence, BrdU-tracing and genetic cellular labelling, they tracked the migration of newborn astrocytes (expressing Thbs4) and found that Thbs4-positive astrocytes modulate the extracellular matrix at the lesion border by synthesis but also degradation of hyaluronan. Their results point to a relevant function of SVZ newborn astrocytes in the modulation of the glial scar after brain ischemia. This work's major strength is the fact that it is tackling the function of SVZ newborn astrocytes, whose role is undisclosed so far.

Strengths:

The article is innovative, of good quality, and clearly written, with properly described Materials and Methods, data analysis and presentation. In general, the methods are designed properly to answer the main question of the authors, being a major strength. Interpretation of the data is also in general well done, with results supporting the main conclusions of this article.

In this revised version, the points raised/weaknesses were clarified and discussed in the article.

Reviewer #1 (Public review):

Summary:

Liu et al., present an immersion objective adapter design called RIM-Deep, which can be utilized for enhancing axial resolution and reducing spherical aberrations during inverted confocal microscopy of thick cleared tissue.

Strengths:

RI mismatches present a significant challenge to deep tissue imaging, and developing a robust immersion method is valuable in preventing losses in resolution. Liu et al., present data showing that RIM-Deep is suitable for tissue cleared with two different clearing techniques, demonstrating the adaptability and versatility of the approach.

Weaknesses:

Liu et al., claim to have developed a useful technique for deep tissue imaging, but in its current form, the paper does not provide sufficient evidence that their technique performs better than existing ones.

Reviewer #2 (Public review):

Summary:

Liu et al investigated the performance of a novel imaging technique called RIM-Deep to enhance the imaging depth for cleared samples. Usually, the imaging depth using the classical confocal microscopy sample chamber is limited due to optical aberrations, resulting in loss of resolution and image quality. To overcome this limitation and increase depth, they generated a special imaging chamber, that is affixed to the objective and filled with a solution matching the refractive indices to reduce aberrations. Importantly, the study was conducted using a standard confocal microscope, that has not been modified apart from exchanging the standard sample chamber with the RIM-Deep sample holder. Upon analysing the imaging depth, the authors claim that the RIM-Deep method increased the depth from 2 mm to 5 mm. In summary, RIM-Deep has the potential to significantly enhance imaging quality of thick samples on a low budget, making in-depth measurements possible for a wide range of researchers that have access to an inverted confocal microscope.

Strengths:

The authors used different clearing methods to demonstrate the suitability of RIM-Deep for various sample preparation protocols with clearing solutions of different refractive indices. They clearly demonstrate that the RIM-Deep chamber is compatible with all 3 methods. Brain samples are characterized by complex networks of cells and are often hard to visualize. Despite the dense, complex structure of brain tissue, the RIM-Deep method generated high quality images of all 3 samples given. As the authors already stated, increasing imaging depth often goes hand in hand with purchasing expensive new equipment, exchanging several microscopy parts or purchasing a new microscopy set-up. Innovations, such as the RIM-Deep chamber, hence, might pave the way for cost-effective imaging and expand the applicability of an inverted confocal microscope.

Weaknesses:

(1) However, since this study introduces a novel imaging technique, and therefore, aims to revolutionize the way of imaging large samples, additional control experiments would strengthen the data. From the 3 clearing protocol used (CUBIC, MACS and iDISCO), only the brain section from Macaca fascicularis cleared with iDISCO was imaged with the standard chamber and the RIM-Deep method. This comparison indeed shows that the imaging depth thereby increases more than 2-fold, which is a significant enhancement in terms of microscopy. However, it would have been important to evaluate and show the difference of the imaging depth also on the other two samples, since they were cleared with different protocols and, thus, treated with clearing solutions of different refractive indices compared to iDCISCO.

(2) The description of the figures and figure panels should be improved for a better understanding of the experiments performed and the thus resulting images/data.

(3) While the authors used a Nikon AX inverted laser scanning confocal microscope, the study would highly benefit from evaluating the performance of the RIM-Deep method using other inverted confocal microscopes or even wide-field microscopes.

Reviewer #1 (Public review):

The authors have successfully addressed most of the issues raised in the first review. Nevertheless, some of the mentioned problems require further attention, mostly regarding the formal derivation of the learning rules, as well as connections to previous research.

Regarding the derivations of learning rules: The authors have provided Goal functions for each of the plastic neural connections to give some insight into what these connections do. However, as I understand, this does not address the main concern raised in the previous review: Why do these rules lead to overall network dynamics that sample from the input distribution? Virtually all other work on neural sampling that I am aware of (e.g., from Maass Lab, Lengyel Lab, etc.) start from a single goal function for all connections that somehow quantifies the difference of network dynamics from the target distribution. In the presented work the authors specify different goal functions for the different weights, which does not make clear how the desired network dynamics are ultimately achieved.

This becomes especially evident looking at the two different recurrent connections (M and G). M minimizes the difference between network activity f and recurrent prediction DKL[f|phi(My)], but why is this alone not enough to ensure a good sampling? G minimizes the squared error [f-phi(Gy)]^2, but what does that mean? The problem is that the goal functions are self-consistent in the sense that both f and phi(Gy) depend on G, which makes an interpretation very difficult. Ultimately it's easier to interpret this by looking at the plasticity rule and see that it leads to a balance. For G the authors furthermore actually ignore the derived plasticity rule and switch to a rule similar to the one for M, meaning that the actual goal function for G is also something like DKL[f|phi(Gy)]. Overall, an overarching optimization goal for the entire network is missing, which makes the interpretation very difficult. I understand that this might be very difficult to provide at this stage, but the authors should at least point out this shortcoming as an open question for the proposed framework.

Regarding the relation to previous work the authors have provided a lot more detailed discussion, which very much clears up the contributions and novel ideas in their work. Still, there are some claims that are not consistent with the literature. Especially, in lines 767 ff. the authors state that Kappel et al "assumed plasticity only at recurrent synapses projecting onto the excitatory neurons. In addition, unlike our model, the cell assembly memberships need to be preconfigured in the [...] model." This is not correct, as Kappel et al learn both the feed-forward and recurrent connections, hence the main difference is that in Kappel et al sampling is sequential and not random. This is why I mentioned this work in the first review, as it speaks against the authors claims of novelty (719 ff.), which should be adjusted accordingly.

Reviewer #2 (Public review):

Summary:

The paper reconsiders the formation of Hebbian-type assemblies, with their spontaneous reactivation representing the statistics of the sensory inputs, in the light of predictive synaptic plasticity. It convincingly shows that not all plasticity rules can be predictive in the narrow sense. While plasticity for the excitatory synapses (the forward projecting and recurrent ones) are predictive, two types of plasticity in the recurrent inhibition is required: a homeostatic and competitive one.

Details:

Besides the excitatory forward and recurrent connections that are learned based on predictive synaptic plasticity, two types of inhibitory plasticity are considered. A first type of inhibition is homeostatic and roughly balances excitation within the cell assemblies. Plasticity in this type 1 inhibition is also predictive, analogous to the plasticity of the excitatory synapses. However, plasticity in type 2 inhibition is competitive and has a switched sign. Both types of inhibitory plasticity, the predictive (homeostatic) and the anti-predictive (competitive) one, work together with the predictive excitatory plasticity to form cell assemblies representing sensory stimuli. Only if the two types of homeostatic and competitive inhibitory plasticity are present, will the spontaneous replay of the assemblies reflect the statistics of the stimulus presentation.

Critical review:

The simulations include Dale's law, making them more biologically realistic. The paper emphasizes predictive plasticity and introduces type 1 inhibitory plasticity that, by construction, tries to fully explain away the excitatory input. In the absence of external inputs, however, due to the symmetry between the excitatory and inhibitory-type-1 plasticity rules, excitation and inhibition tend to fully cancel each other. Multiple options may solve the dilemma:

(1) As other predictive dendritic plasticity models assume, the presynaptic source for recurrent inhibition is typically less informative than the presynaptic source of excitation, so that inhibition is not able to fully explain away excitation.

(2) Beside the inhibitory predictive plasticity that mirrors the analogous excitatory predictive plasticity, and additional competitive plasticity can be introduced.

The paper chooses solution (2) and suggests and additional inhibitory recurrent pathway that is not predictive, but instead anti-predictive with a reversed sign. The combination of the two types of inhibitory plasticities lead to a stable formation of cell assemblies. The stable target activity of the plasticity rules in a memory recall is not anymore 0, as it would be with only type-1-inhibitory plasticity.<br /> Instead, the target activity of plasticity is now enhanced within a winning assembly, and also positive but reduced in the loosing assemblies.

Reviewer #3 (Public review):

Summary:

The work shows how learned assembly structure and its influence on replay during spontaneous activity can reflect the statistics of stimulus input. In particular, stimuli that are more frequent during training elicit stronger wiring and more frequent activation during replay. Past works (Litwin-Kumar and Doiron, 2014; Zenke et al., 2015) have not addressed this specific question, as classic homeostatic mechanisms forced activity to be similar across all assemblies. Here, the authors use a dynamic gain and threshold mechanism to circumnavigate this issue and link this mechanism to a cellular monitoring of membrane potential history.

Strengths:

(1) This is an interesting advance, and the authors link this to experimental work in sensory learning in environments with non-uniform stimulus probabilities.

(2) The authors consider their mechanism in a variety of models of increasing complexity (simple stimuli, complex stimuli; ignoring Dale's law, incorporating Dale's law).

(3) Links a cellular mechanism of internal gain control (their variable h) to assembly formation and the non-uniformity of spontaneous replay activity. Offers a promise of relating cellular and synaptic plasticity mechanisms under a common goal of assembly formation.

Weaknesses:

(1) However, while the manuscript does show that assembly wiring does follow stimulus likelihood, it is not clear how the assembly specific statistics of h reflect these likelihoods. I find this to be a key issue.

(2) The authors model does take advantage of the sigmoidal transfer function, and after learning an assembly is either fully active or near fully silent (Fig. 2a). This somewhat artificial saturation may be the reason that classic homeostasis is not required, since runaway activity is not as damaging to network activity.

(3) Classic mechanisms of homeostatic regulation (synaptic scaling, inhibitory plasticity) try to ensure that firing rates match a target rate (on average). If the target rate is the same for all neurons then having elevated firing rates for one assembly compared to others during spontaneous activity would be difficult. If these homeostatic mechanisms were incorporated, how would they permit the elevated firing rates for assemblies that represent more likely stimuli?

Reviewer #1 (Public review):

Summary:

The authors of this article have presented a timely and well-written study exploring the impact of group identification on collective behaviors and performance. The breadth of analyses is impressive and contributes significantly to our understanding of the collective performance. However, there are several areas where further clarification and revision would strengthen the study.

Strengths:

(1) Timeliness and Relevance:<br /> The topic is highly relevant, particularly in today's interconnected and team-oriented work environments. Triadic hyperscanning is important to understand group dynamics, but most previous work has been limited to dyadic work.

(2) Comprehensive Analysis:<br /> The authors have conducted extensive analyses, offering valuable insights into how group identification affects collective behaviors.

(3) Clear Writing:<br /> The manuscript is well-written and easy to follow, making complex concepts accessible.

Weaknesses (clarifications needed):

(1) Experimental Design:<br /> The study does not mention whether the authors examined sex differences or any measures of attractiveness or hierarchy among participants (e.g., students vs. teachers). Including these variables could provide a more nuanced understanding of group dynamics.

(2) fNIRS Data Acquisition:<br /> The authors' approach to addressing individual differences in anatomy is lacking in detail. Understanding how they identified the optimal channels for synchrony between participants would be beneficial. Was this done by averaging to find the location with the highest coherence?

(3) Behavioral Analysis:<br /> For group identification, the analysis currently uses a dichotomous approach. Introducing a regression model to capture the degree of identification could offer more granular insights into how varying levels of group identification affect collective behavior and performance.

(4) Single Brain Activation Analysis:<br /> The application of the General Linear Model (GLM) is unclear, particularly given the long block durations and absence of multiple trials. Further explanation is needed on how the GLM was implemented under these conditions.

(5) Within-group neural Synchrony (GNS) Calculation:<br /> The method for calculating GNS could be improved by using mutual information instead of pairwise summation, as suggested by Xie et al. (2020) in their study on fMRI triadic hyperscanning. Additionally, the explanation of GNS calculation is inconsistent. At one point, it is mentioned that GNS was averaged across time and channels, while elsewhere, it is stated that channels with the highest GNS were selected. Clarification on this point is essential.

(6) Placement of fNIRS Probes:<br /> The probes were only placed in the frontal regions, despite literature suggesting that the superior temporal sulcus (STS) and temporoparietal junction (TPJ) regions are crucial for triadic team performance. A justification for this choice or inclusion of these regions in future studies would be beneficial.

(7) Interpretation of fNIRS Data:<br /> Given that fNIRS signals are slow, similar to BOLD signals in fMRI, the interpretation of Figure 6 raises concerns. It suggests that it takes several minutes (on the order of 4-5 minutes) for people to collaborate, which seems implausible. More context or re-evaluation of this interpretation is needed.

Reviewer #2 (Public review):

Summary:

This study primarily aims to examine the relationship between collective performance and group identification. Additionally, the authors propose that inter-brain synchronization (IBS) underlies collective performance and that changes in intra-brain functional connectivity or single-brain activation may, in turn, underlie IBS. The topic addressed in this paper is of great importance in the field using hyperscanning. However, the details of the experiments and analysis described in the paper are unclear, and the hypothesis as to why IBS is thought to underlie collective performance is not clearly presented. In addition, some of the analysis seems to be inappropriate.

Strengths:

I find the model presented in Figure 7 to be intriguing. Understanding why inter-brain synchronization occurs and how it is supported by specific single-brain activations or intra-brain functional connectivity is indeed a critical area for researchers conducting hyperscanning studies to explore.

Understanding triadic-interaction is really important, while almost all hyperscanning neuroimaging focuses on the dyadic interaction. The exploring neural/behavioral/psychological basis behind triadic interaction is a promising method for understanding collective behavior and decision-making.

Weaknesses:

The authors need to clearly articulate their hypothesis regarding why neural synchronization occurs during social interaction. For example, in line 284, it is stated that "It is plausible that neural synchronization is closely associated with group identification and collective performance...", but this is far from self-evident. Neural synchronization can occur even when people are merely watching a movie (Hasson et al., 2004), and movie-watchers are not engaged in collective behavior. There is no direct link between the IBS and collective behavior. The authors should explain why they believe inter-brain synchronization occurs in interactive settings and why they think it is related to collective behavior/performance.

The authors state that "GNS in the OFC was a reliable neuromarker, indicating the influence of group identification on collective performance," but this claim is too strong. Please refer to Figure 4B. Do the authors really believe that collective performance can be predicted given the correlation with the large variance shown? There is a significant discrepancy between observing a correlation between two variables and asserting that one variable is a predictive biomarker for the other.

Why are the individual answers being analyzed as collective performance (See, L-184)? Although these are performances that emerge after the group discussion, they seem to be individual performances rather than collective ones. Typically, wouldn't the result of a consensus be considered a collective performance? The authors should clarify why the individual's answer is being treated as the measure of collective performance.

Performing SPM-based mapping followed by conducting a t-test on the channels within statistically significant regions constitutes double dipping, which is not an acceptable method (Kriegeskorte et al., 2011). This issue is evident in, for example, Figures 3A and 4A.

Please refer to the following source:<br /> https://www.nature.com/articles/nn.2303

In several key analyses within this study (e.g., single-brain activation in the paragraph starting from L398, neural synchronization in the paragraph starting from L393), the TPJ is mentioned alongside the DLPFC. However, in subsequent detailed analyses, the TPJ is entirely ignored.

The method for analyzing single-brain activation is unclear. Although it is mentioned that GLM (generalized linear model) was used, it is not specified what regressors were prepared, nor which regressor's β-values are reported as brain activity. Without this information, it is difficult to assess the validity of the reported results.

While the model illustrated in Figure 7 seems to be interesting, for me, it seems not to be based on the results of this study. This is because the study did not investigate the causal relationships among the three metrics. I guess, Figure 5D might be intended to explain this, but the details of the analysis are not provided, making it unclear what is being presented.

The details of the experiment are not described at all. While I can somewhat grasp what was done abstractly, the lack of specific information makes it impossible to replicate the study.

Reviewer #4 (Public review):

Summary:

This is an important study that underscores that reproduction-survival trade-offs are not manifested (contrary to what generally accepted theory predicts) across a range of studies on birds. This has been studied by a meta-analytical approach, gathering data from a set of 46 papers (30 bird species). The overall conclusion is that there are no trade-offs apparent unless experimental manipulations push the natural variability to extreme values. In the wild, the general pattern for within-species variation is that birds with (naturally) larger clutches survive better.

Strengths:

I agree this study highlights important issues and provides good evidence of what it claims, using appropriate methods.

Weaknesses:

I also think, however, that it would benefit from broadening its horizon beyond bird studies. The conclusions can be reinforced through insights from other taxa. General reasoning is that there is positive pleiotropy (i.e. individuals vary in quality and therefore some are more fit (perform better) than others. Of course, this is within their current environment (biotic, abiotic, social. ...), with consequences of maintaining genetic variation across generations - outlined in Maklakov et al. 2015 (https://doi.org/10.1002/bies.201500025). This explains the outcomes of this study very well and would come to less controversy and surprise for a more general audience.

I have two fish examples in my mind where this trade-off is also discounted. Of course, given that it is beyond brood-caring birds, the wording in those studies is slightly different, but the evolutionary insight is the same. First, within species but across populations, Reznick et al. (2004, DOI: 10.1038/nature02936) demonstrated a positive correlation between reproduction and parental survival in guppies. Second, an annual killifish study (2021, DOI: 10.1111/1365-2656.13382) showed, within a population, a positive association between reproduction and (reproductive) aging.

In fruit flies, there is also a strong experimental study demonstrating the absence of reproduction-lifespan trade-offs (DOI: 10.1016/j.cub.2013.09.049).

I suggest that incorporating insights from those studies would broaden the scope and reach of the current manuscript.

Likely impact:

I think this is an important contribution to a slow shift in how we perceive the importance of trade-offs in ecology and evolution in general. While the current view still is that one individual excelling in one measure of its life history (i.e. receiving benefits) must struggle (i.e. pay costs) in another part. However, a positive correlation between all aspects of life history traits is possible within an individual (such as due to developmental conditions or fitting to a particular environment). Simply, some individuals can perform generally better (be of good quality than others).

Reviewer #1 (Public review):

Summary

In this study, Nishi et al. claim that the ratio of long-term hematopoietic stem cell (LT-HSC) versus short-term HSC (ST-HSC) determines the lineage output of HSCs and reduced ratio of ST-HSC in aged mice causes myeloid-biased hematopoiesis. Authors used Hoxb5 reporter mice to isolated LT-HSC and ST-HSC and performed molecular analyses and transplantation assays to support their arguments. How hematopoietic system becomes myeloid-biased upon aging is an important question with many implications in disease context as well. However, this study needs more definitive data.

(1) Authors' experimental designs have some caveats to definitely support their claims. Authors claimed that aged LT-HSCs have no myeloid-biased clone expansion using transplantation assays. In these experiments, authors used 10 HSCs and young mice as recipients. Given the huge expansion of old HSC by number and known heterogeneity in immunophenotypically defined HSC populations, it is questionable how 10 out of so many old HSCs (an average of 300,000 up to 500,000 cells per mouse; Mitchell et al., Nature Cell Biology, 2023) can faithfully represent old HSC population. The Hoxb5+ old HSC primary and secondary recipient mice data (Fig. 2C and D) support this concern. In addition, they only used young recipients. Considering the importance of inflammatory aged niche in the myeloid-biased lineage output, transplanting young vs old LT-HSCs into aged mice will complete the whole picture.

(2) Authors' molecular data analyses need more rigor with unbiased approaches. They claimed that neither aged LT-HSCs nor aged ST-HSCs exhibited myeloid or lymphoid gene set enrichment but aged bulk HSCs, which are just a sum of LT-HSCs and ST-HSCs by their gating scheme (Fig. 4A), showed the "tendency" of enrichment of myeloid-related genes based on the selected gene set (Fig. 4D). Although the proportion of ST-HSCs is reduced in bulk HSCs upon aging, since ST-HSCs do not exhibit lymphoid gene set enrichment based on their data, it is hard to understand how aged bulk HSCs have more myeloid gene set enrichment compared to young bulk HSCs. This bulk HSC data rather suggest that there could be a trend toward certain lineage bias (although not significant) in aged LT-HSCs or ST-HSCs. Authors need to verify the molecular lineage priming of LT-HSCs and ST-HSCs using another comprehensive dataset.

(3) Although authors could not find any molecular evidence for myeloid-biased hematopoiesis from old HSCs (either LT or ST), they argued that the ratio between LT-HSC and ST-HSC causes myeloid-biased hematopoiesis upon aging based on young HSC experiments (Fig. 6). However, old ST-HSC functional data showed that they barely contribute to blood production unlike young Hoxb5- HSCs (ST-HSC) in the transplantation setting (Fig. 2). Is there any evidence that in unperturbed native old hematopoiesis, old Hoxb5- HSCs (ST-HSC) still contribute to blood production? If so, what are their lineage potential/output? Without this information, it is hard to argue that the different ratio causes myeloid-biased hematopoiesis in aging context.

Reviewer #2 (Public review):

Summary:

Nishi et al, investigate the well-known and previously described phenomenon of age-associated myeloid-biased hematopoiesis. Using a previously established HoxB5mCherry mouse model, they used HoxB5+ and HoxB5- HSCs to discriminate cells with long-term (LT-HSCs) and short-term (ST-HSCs) reconstitution potential and compared these populations to immunophenotypically defined 'bulk HSCs' that consists of a mixture of LT-HSC and ST-HSCs. They then isolated these HSC populations from young and aged mice to test their function and myeloid bias in non-competitive and competitive transplants into young and aged recipients. Based on quantification of hematopoietic cell frequencies in the bone marrow, peripheral blood, and in some experiments the spleen and thymus, the authors argue against the currently held belief that myeloid-biased HSCs expand with age.

While aspects of their work are fascinating and might have merit, several issues weaken the overall strength of the arguments and interpretation. Multiple experiments were done with a very low number of recipient mice, showed very large standard deviations, and had no statistically detectable difference between experimental groups. While the authors conclude that these experimental groups are not different, the displayed results seem too variable to conclude anything with certainty. The sensitivity of the performed experiments (e.g. Fig 3; Fig 6C, D) is too low to detect even reasonably strong differences between experimental groups and is thus inadequate to support the author's claims. This weakness of the study is not acknowledged in the text and is also not discussed. To support their conclusions the authors need to provide higher n-numbers and provide a detailed power analysis of the transplants in the methods section.

As the authors attempt to challenge the current model of the age-associated expansion of myeloid-biased HSCs (which has been observed and reproduced by many different groups), ideally additional strong evidence in the form of single-cell transplants is provided.

It is also unclear why the authors believe that the observed reduction of ST-HSCs relative to LT-HSCs explains the myeloid-biased phenotype observed in the peripheral blood. This point seems counterintuitive and requires further explanation.

Based on my understanding of the presented data, the authors argue that myeloid-biased HSCs do not exist, as<br /> a) they detect no difference between young/aged HSCs after transplant (mind low n-numbers and large std!!!); b) myeloid progenitors downstream of HSCs only show minor or no changes in frequency and c) aged LT-HSCs do not outperform young LT-HSC in myeloid output LT-HScs in competitive transplants (mind low n-numbers and large std!!!).<br /> However, given the low n-numbers and high variance of the results, the argument seems weak and the presented data does not support the claims sufficiently. That the number of downstream progenitors does not change could be explained by other mechanisms, for instance, the frequently reported differentiation short-cuts of HSCs and/or changes in the microenvironment.

Strengths:

The authors present an interesting observation and offer an alternative explanation of the origins of aged-associated myeloid-biased hematopoiesis. Their data regarding the role of the microenvironment in the spleen and thymus appears to be convincing.

Weaknesses:

"Then, we found that the myeloid lineage proportions from young and aged LT-HSCs were nearly comparable during the observation period after transplantation (Fig. 3, B and C)."<br /> [Comment to the authors]: Given the large standard deviation and low n-numbers, the power of the analysis to detect differences between experimental groups is very low. Experimental groups with too large standard deviations (as displayed here) are difficult to interpret and might be inconclusive. The absence of clearly detectable differences between young and aged transplanted HSCs could thus simply be a false-negative result. The shown experimental results hence do not provide strong evidence for the author's interpretation of the data. The authors should add additional transplants and include a detailed power analysis to be able to detect differences between experimental groups with reasonable sensitivity.

Line 293: "Based on these findings, we concluded that myeloid-biased hematopoiesis observed following transplantation of aged HSCs was caused by a relative decrease in ST-HSC in the bulk-HSC compartment in aged mice rather than the selective expansion of myeloid-biased HSC clones."<br /> Couldn't that also be explained by an increase in myeloid-biased HSCs, as repeatedly reported and seen in the expansion of CD150+ HSCs? It is not intuitively clear why a reduction of ST-HSCs clones would lead to a myeloid bias. The author should try to explain more clearly where they believe the increased number of myeloid cells comes from. What is the source of myeloid cells if the authors believe they are not derived from the expanded population of myeloid-biased HSCs?

Reviewer #3 (Public review):

In this manuscript, Nishi et al. propose a new model to explain the previously reported myeloid-biased hematopoiesis associated with aging. Traditionally, this phenotype has been explained by the expansion of myeloid-biased hematopoietic stem cell (HSC) clones during aging. Here, the authors question this idea and show how their Hoxb5 reporter model can discriminate long-term (LT) and short-term (ST) HSC and characterized their lineage output after transplant. From these analyses, the authors conclude that changes during aging in the LT/ST HSC proportion explain the myeloid bias observed.

Although the topic is appropriate and the new model provides a new way to think about lineage-biased output observed in multiple hematopoietic contexts, some of the experimental design choices, as well as some of the conclusions drawn from the results could be substantially improved. Also, they do not propose any potential mechanism to explain this process, which reduces the potential impact and novelty of the study.

The authors have satisfactorily replied to some of my comments. However, there are multiple key aspects that still remain unresolved.

Reviewer #1 (Public review):

Summary:

The study identifies two types of activation: one that is cue-triggered and non-specific to motion directions, and another that is specific to the exposed motion directions but occurs in a reversed manner. The finding that activity in the medial temporal lobe (MTL) preceded that in the visual cortex suggests that the visual cortex may serve as a platform for the manifestation of replay events, which potentially enhance visual sequence learning.

Strengths:

Identifying the two types of activation after exposure to a sequence of motion directions is very interesting. The experimental design, procedures, and analyses are solid. The findings are interesting and novel.

Weaknesses:

It was not immediately clear to me why the second type of activation was suggested to occur spontaneously. The procedural differences in the analyses that distinguished between the two types of activation need to be a little better clarified.

Reviewer #2 (Public review):

This paper shows and analyzes an interesting phenomenon. It shows that when people are exposed to sequences of moving dots (that is moving dots in one direction, followed by another direction, etc.), showing either the starting movement direction or ending movement direction causes a coarse-grained brain response that is similar to that elicited by the complete sequence of 4 directions. However, they show by decoding the sensor responses that this brain activity actually does not carry information about the actual sequence and the motion directions, at least not on the time scale of the initial sequence. They also show a reverse reply on a highly compressed time scale, which is elicited during the period of elevated activity, and activated by the first and last elements of the sequence, but not others. Additionally, these replays seem to occur during periods of cortical ripples, similar to what is found in animal studies.

These results are intriguing. They are based on MEG recordings in humans, and finding such replays in humans is novel. Also, this is based on what seems to be sophisticated statistical analysis. However, this is the main problem with this paper. The statistical analysis is not explained well at all, and therefore its validity is hard to evaluate. I am not at all saying it is incorrect; what I am saying is that given how it is explained, it cannot be evaluated.

Reviewer #1 (Public review):

These experiments are some of the first to assess the role of dopamine release and the activity of D1 and D2 MSNs in pair bond formation in Mandarin voles. This is a novel and comprehensive study that presents exciting data about how the dopamine system is involved in pair bonding. The authors provide very detailed methods and clearly presented results. Here they show dopamine release in the NAc shell is enhanced when male voles encounter their pair bonded partner 7 days after co-habitation. In addition, D2 MSN activity decreases whereas D1 MSN activity increases when sniffing the pair-bonded partner.

The authors do not provide justification for why they only use males in the current study, without discussing sex as a biological variable these data can only inform readers about one sex (which in pair-bonded animals by definition have 2 sexes). In addition, the authors do not use an isosbestic control wavelength in photometry experiments, although they do use EGFP control mice which show no effects of these interventions, a within-subject control such as an isosbestic excitation wavelength could give more confidence in these data and rule out motion artefacts within subjects.

There is an existing literature (cited in this manuscript) from Aragona et al., (particularly Aragona et al., 2006) which has highlighted key differences in the roles of rostral versus caudal NAc shell dopamine in pair bond formation and maintenance. Specifically, they report that dopamine transmission promoting pair bonding only occurs in the rostral shell and not the caudal shell or core regions. Given that the authors have targeted more caudally a discussion of how these results fit with previous work and why there may be differences in these areas is warranted.

The authors could discuss the differences between pair bond formation and pair bond maintenance more deeply.

The authors have successfully characterised the involvement of dopamine release, changes in D1 and D2 MSNs, and projections to the VP in pair bonding voles. Their conclusions are supported by their data and they make a number of very reasonable discussion points acknowledging various limitations.

Reviewer #2 (Public review):

Summary:

Using in vivo fiber-photometry the authors first establish that DA release when contacting their partner mouse increases with days of cohabitation while this increase is not observed when contacting a stranger mouse. Similar effects are found in D1-MSNs and D2-MSNs with the D1-MSN responses increasing and D2-MSN responses decreasing with days of cohabitation. They then use slice physiology to identify underlying plasticity/adaptation mechanisms that could contribute to the changes in D1/D2-MSN responses. Last, to address causality the authors use chemogenetic tools to selectively inhibit or activate NAc shell D1 or D2 neurons that project to the ventral pallidum. They found that D2 inhibition facilitates bond formation while D2 excitation inhibits bond formation. In contrast, both D1-MSN activation and inhibition inhibit bond formation.

Strengths:

The strength of the manuscript lies in combining in vivo physiology to demonstrate circuit engagement and chemogenetic manipulation studies to address circuit involvement in pair bond formation in a monogamous vole.

Weaknesses:

Weaknesses include that a large set of experiments within the manuscript are dependent on using short promoters for D1 and D2 receptors in viral vectors. As the authors acknowledge this approach can lead to ectopic expression and the presented immunohistochemistry supports this notion. It seems to me that the presented quantification underestimates the degree of ectopic expression that is observed by eye when looking at the presented immunohistochemistry. However, given that Cre transgenic animals are not available for Microtus mandarinus and given the distinct physiological and behavioral outcomes when imaging and manipulating both viral-targeted populations this concern is minor.

The slice physiology experiments provide some interesting outcomes but it is unclear how they can be linked to the in vivo physiological outcomes and some of the outcomes don't match intuitively (e.g. cohabitation enhances excitatory/inhibitory balance in D2-MSNs but the degree of contact-induced inhibition is enhanced in D2-MSN).

One interesting finding is that the relationship between D2-MSN and pair bond formation is quite clear (inhibition facilitates while excitation inhibits pair bond formation). In contrast, the role of D1-MSNs is more complicated since both excitation and inhibition disrupt pair bond formation. This is not convincingly discussed.

It seemed a missed opportunity that physiological readout is limited to males. I understand though that adding females may be beyond the scope of this manuscript.

Reviewer #3 (Public review):

Summary:

The manuscript is evaluating changes in dopamine signaling in the nucleus accumbens following pair bonding and exposure to various stimuli in mandarin voles. In addition, the authors present chemogenetic data that demonstrate excitation and inhibition of D1 and D2 MSN affect pair bond formation.

Strengths:

The experimental designs are strong. The approaches are innovative and use cutting-edge methods. The manuscript is well written.

Weaknesses:

The statistical results are not presented, and not all statistical analyses are appropriate. Additionally, some details of methods are absent.

Reviewer #1 (Public review):

The present manuscript by Zhou and colleagues investigates the impact of a new combination of compounds termed CHIR99021 and A-485 on stimulating cardiac cell regeneration. This manuscript fits the journal and addresses an important contribution to scientific knowledge.

Comments on latest version:

The authors have addressed all of our comments.

Reviewer #2 (Public review):

Summary:

This manuscript reports that a combination of two small molecules, 2C (CHIR99027 and A-485) enabled to induce the dedifferentiation of hESC-derived cardiomyocytes (CMs) into regenerative cardiac cells (RCC). These RCCs had disassembled sarcomeric structures and elevated expression of embryonic cardiogenic genes such as ISL1, which exhibited proliferative potential and were able to differentiate into cardiomyocytes, endothelial cells, and smooth muscle cells. Lineage tracing further suggested that RCCs originated from TNNT2+ cells, not pre-existing ISL1+ cells. Furthermore, 2C treatment increased the numbers of RCC cells in neonatal rat and adult mouse hearts, and improves cardiac function post-MI in adult mice. Mechanistically, bulk RNA-seq analysis revealed that 2C led to elevated expression of embryonic cardiogenic genes while down-regulation of CM-specific genes. Single-cell RNA-seq data showed that 2C promoted cardiomyocyte transition into an intermediate state that are marked with ACTA2 and COL1A1, which subsequently transform into RCCs. Finally, ChIP-seq analysis demonstrated that CHIR99027 enhanced H3K9Ac and H3K27Ac modifications in embryonic cardiac genes, while A-485 inhibited these modifications in cardiac-specific genes. These combined alterations effectively induced the dedifferentiation of cardiomyocytes into RCCs. Overall, this is an important work, presenting a putative cardiac regenerative cell types that may represent endogenous cardiac regeneration in regenerative animals. With that said, here are suggestions for the authors:

Strengths:

Overall, this work is quite comprehensive and is logically and rigorously designed. The phenotypic and functional data on 2C are strong.

Weaknesses or suggestions:

(1) In Figure 4, the authors should perform additional experiments on analyzing 2C effect on cardiomyocytes, endothelial cells, and fibroblasts in adult mouse hearts after myocardial infarction.<br /> (2) In Figures 5-7, the mechanistic insights of 2C are primarily derived from transcriptomic and genomic datasets without experimental verification.<br /> (3) The authors should compare transcriptomic profiling of the RCCs with other putative cardiac progenitors from public databases.

Reviewer #3 (Public review):

Summary:

The ability of cardiac cells to regenerate has been the object of intense (and sometimes controversial) research in biology. While lower organisms can robustly undergo cardiac regeneration by reactivation of embryonic cardiogenic pathway, this ability is strongly reduced in mice, both temporally and qualitatively. Finding a way to derive precursor cells with regenerative ability from differentiated cells in mammals has been challenging.

Zhou, He and colleagues hypothesized that ISL-1-positive cells would show regenerative capacity and developed a small molecules screen to dedifferentiate cardiomyocytes (CM) to ISL1-positive precursor cells. Using hESC-derived CM, authors found that the combination of both, WNT activation (CHIR99021) and p300 acetyltransferase inhibition (A-485) (named 2C protocol) induces CM dedifferentiation to regenerative cardiac cells (RCCs). RCCs are proliferative and re-express embryonic cardiogenic genes while decreasing expression of more mature cardiac genes, bringing them towards a more precursor-like state. RCCs were able to differentiate to CM, smooth muscle cells and endothelial cells, highlighting their multipotent property. In vivo administration of 2C in rats and mice had protective effects upon myocardial infarction.

Mechanistically, authors report that 2C protocol drives CM-specific transcriptional and epigenetic changes.

Strengths:

The authors made a great effort to validate their data using orthogonal ways, and several hESC lines. The use of lineage tracing convincingly showed a dedifferentiation from CM. They translate their findings into an in vivo model of myocardial injury, and show functional cardiac regeneration post injury. They also showed that 2C could surprisingly be used as preventive treatment. Together their data may suggest a regenerative effect of 2C both in vitro and in vivo settings. If confirmed, this study might unlock therapeutic strategy for cardiac regeneration.

Weaknesses:

Updated General comments:

Experimental design & Interpretation

(1) The titration provided by the author following the first round of revision is puzzling to me. Based on the authors explanation, the initial screen was performed using 10uM of A-485, allowing the authors to choose CHIR + A-485 as a combination of drugs increasing Isl1-positive cells. However, in the titration provided, the combination of CHIR + 10uM of A-485 (used during the screen) shows *no* increase of the percentage of Isl-1-positive cells compared to DMSO control. How is that possible? Can the authors provide a transparent explanation of the experimental design for their screen. How was A-485 isolated from the 4000+ compounds tested if it does not show any effect on the titration? This titration raises significant concerns about the rational of following up with the combination of compounds.

(2) The authors have not really addressed the concern raised earlier. If only ~1% of the cells de-differentiate and become Isl-positive, how can anybody quantify a nuclear/cytosolic ratio at the global population and show statistical significant when only 1% of the cells should be different?

(3) Authors now provide a quantification of the effect of I-BET-762 (Supp 1H). While the authors state " [the combination of CHIR + I-BET-762] was less effective than A-485 in combination with CHIR99021", the figure provided does not test that. A side-by-side comparaison of the effect of A485 and I-BET should have been performed on the same graph. I-BET increases by 4 fold, while A-485 increases by 5-fold, which, based on the variation of their data, will unlikely be statistically different. The rational for disregarding the effect of I-BET-762 is therefore weakened.

(4) Why NR2F2 is statistically significant in one set of experiments (Fig 2 - Fig. supplement 1) and then non-significant in another set (Fig. 1G) using the exact same experiment design (NC vs 2C for 60h) and similar statistical test applied?

Statistics & Data Acquisition

(1) Authors should refrain from deriving statistics from 2 biological repeats (Figure 3G).<br /> (2) Authors still do not state whether the normality of their data was tested.<br /> (3) What is the rational for using a two-way ANOVA for Fig 3G? Authors are only comparing the effect of their treatment for each marker. Same question for most panels from Figure 1, Fig 2C, 2F, and throughout the manuscript. This needs clarification/justification especially because in other experiments, they used multiple unpaired t-test (Fig 2 - Fig. supplement 1).

Others

(1) Authors should try to make their manuscript colorblind-friendly: No modification added following this comment.

Reviewer #1 (Public review):

Summary:

The study investigates the impact of Clonal Hematopoiesis of Indeterminate Potential (CHIP) on Immune Checkpoint Inhibitor (ICI) therapy outcomes in NSCLC patients, analyzing blood samples from 100 patients pre- and post-ICI therapy for CHIP, and conducting single-cell RNA sequencing (scRNA-seq) of PBMCs in 63 samples, with validation in 180 more patients through whole exome sequencing. Findings show no significant CHIP influence on ICI response, but a higher CHIP prevalence in NSCLC compared to controls and a notable CHIP burden in squamous cell carcinoma. Severely affected CHIP groups showed NF-kB pathway gene enrichment in myeloid clusters.

Strengths:

The study is commendable for analyzing a significant cohort of 100 patients for CHIP and utilizing scRNA-seq on 63 samples, showcasing the use of cutting-edge technology.

The study tackles the vital clinical question of predicting ICI therapy outcomes in NSCLC.

Weaknesses:

The study groups, comprising NSCLC patients and healthy controls, exhibit notable differences in sex distribution and smoking status. Given that smoking is a well-established factor influencing CHIP status, this introduces potential confounding variables that may impact the study's conclusions. The authors have appropriately acknowledged these disparities and provided a transparent discussion of their implications.

Comments on revised submission:

The authors thoroughly addressed all my concerns. Thank you very much for your additional work.

Reviewer #1 (Public review):

Summary:

The present work from Velloso and collaborators investigated the transcription profiles of resident and recruited hypothalamic microglia. They found sex-dependent differences between males and females and identified the protective role of chemokine receptor CXCR3 against diet-induced obesity.

Strengths:

(1) Novelty<br /> (2) Relevance, since this work provides evidence about a subset of recruited microglia that has a protective effect against DIO. This provides a new concept in hypothalamic inflammation and obesity.

Comments on revised version:

All my comments have been addressed.

Reviewer #2 (Public review):

Summary:

This study by Mendes et al provides novel key insights in the role of chemotaxis and immune cell recruitment into the hypothalamus in the development of diet-induced obesity. Specifically, the authors first revealed that although transcriptional changes in hypothalamic resident microglia following exposure to high-fat feeding are minor, there are compelling transcriptomic differences between resident microglia and microglia recruited to the hypothalamus, and these are sexually dimorphic. Using independent loss-of-function studies, the authors also demonstrate an important role of CXCR3 and hypothalamic CXCL10 in the hypothalamic recruitment of CCR2+ positive cells on metabolism following exposure to high-fat diet-feeding in mice. This manuscript puts forth conceptually novel evidence that inhibition of chemotaxis-mediated immune cell recruitment accelerates body weight gain in high-fat diet-feeding, suggesting that a subset of microglia which express CXCR3 may confer protective, anti-obesogenic effects.

Strengths:

The work is exciting and relevant given the prevalence of obesity and the consequences of inflammation in the brain on perturbations of energy metabolism and ensuant metabolic diseases. Hypothalamic inflammation is associated with disrupted energy balance, and activated microglia within the hypothalamus resulting from excessive caloric intake and saturated fatty acids are often thought to be mediators of impairment of hypothalamic regulation of metabolism. The present work reports a novel notion in which immune cells recruited into the hypothalamus which express chemokine receptor CXCR3 may have a protective role against diet-induced obesity. In vivo studies reported herein demonstrate that inhibition of CXCR3 exacerbates high-fat diet-induced body weight gain, increases circulating triglycerides and fasting glucose levels, worsens glucose tolerance, and increases the expression of orexigenic neuropeptides, at least in female mice.

This work provides a highly interesting and needed overview of preclinical and clinical brain inflammation, which is relevant to readers with an interest in metabolism and immunometabolism in the context of obesity.

Using flow cytometry, cell sorting, and transcriptomics including RNA-sequencing, the manuscript provides novel insights on transcriptional landscapes of resident and recruited microglia in the hypothalamus. Importantly, sex differences are investigated.

Overall, the manuscript is perceived to be highly interesting, relevant, and timely. The discussion is thoughtful, well-articulated, and a pleasure to read and felt to be of interest to a broad audience.

Weaknesses:

There were no major weaknesses perceived. Some comments for potential textual additions to the results/discussion are provided below.

Could the authors comment on the choice of peripheral administration of CXCR3 antagonist as opposed to central (e.g. icv) administration? Indeed, systemic inhibition of CXCR3 produced significant alterations in body weight gain and glucose tolerance in female mice given high-fat diet and reduced CCR2 and CXCR3 immunostaining in the hypothalamus. Could changes to peripheral (e.g. WAT, liver) immune responses to the diet underlie the metabolic changes observed?

Besides hypothalamic mRNA levels of chemokines and chemokine receptors, does systemic CXCR3 antagonism affect other aspects linked to diet-induced impairments of hypothalamic regulation of energy homeostasis, like inflammation, ER stress and/or mitochondrial dynamics/function? It would be interesting to reveal the consequence of reduced CCR2+ microglial migration to the hypothalamus with chronic high-fat diet exposure.

Reviewer #1 (Public review):

Summary:

The manuscript by Zhou et al offers new high resolution Cryo-EM structures of two human biotin-dependent enzymes: propionyl-CoA carboxylase (PCC) and methycrotonyl-CoA carboxylase (MCC). While X-ray crystal structures and Cryo-EM structures have previously been reported for bacterial and trypanosomal versions of MCC and for bacterial versions of PCC, this marks one of the first high resolution Cryo-EM structures of the human version of these enzymes. Using the biotin cofactor as an affinity tag, this team purified a group of four different human biotin-dependent carboxylases from cultured human Expi 293F (kidney) cells (PCC, MCC, acetyl-CoA carboxylase (ACC), and pyruvate carboxylase). Following further enrichment by size-exclusion chromatography, they were able to vitrify the sample and pick enough particles of MCC and PCC to separately refine the structures of both enzymes to relatively high average resolutions (the Cryo-EM structure of ACC also appears to have been determined from these same micrographs, though this is the subject of a separate publication). To determine the impact of substrate binding on the structure of these enzymes and to gain insights into substrate selectivity, they also separately incubated with propionyl-CoA and acetyl-CoA and vitrified the samples under active turnover conditions, yielding a set of cryo-EM structures for both MCC and PCC in the presence and absence of substrates and substrate analogues.

Strengths:

The manuscript has several strengths. It is clearly written, the figures are clear and the sample preparation methods appear to be well described. This study demonstrates that Cryo-EM is an ideal structural method to investigate the structure of these heterogeneous samples of large biotin-dependent enzymes. As a consequence, many new Cryo-EM structures of biotin-dependent enzymes are emerging, thanks to the natural inclusion of a built-in biotin affinity tag. While the authors report no major differences between the human and bacterial forms of these enzymes, it remains an important finding that they demonstrate how/if the structure of the human enzymes are or are not distinct from the bacterial enzymes. The MCC structures also provide evidence for a transition for BCCP-biotin from an exo-binding site to an endo-binding site in response to acetyl-CoA binding. This contributes to a growing number of biotin-dependent carboxylase structures that reveal BCCP-biotin binding at locations both inside (endo-) and outside (exo-) of the active site.

Weaknesses:

There are some minor weaknesses. Notably, there are not a lot of new insights coming from this paper. The structural comparisons between MCC and PCC have already been described in the literature and there were not a lot of significant changes (outside of the exo- to endo- transition) in the presence vs. absence of substrate analogues. There are sections of this manuscript that do not sufficiently clarify what represents a new insight from the current set of structures (there are few of them), vs. what is largely recapitulating what has been seen in previous structures.

There is not a great deal of depth of analysis in the discussion. For example, no new insights were gained with respect to the factors contributing to substrate selectivity (the factors contributing to selectivity for propionyl-CoA vs. acetyl-CoA in PCC). The authors acknowledge that they are limited in their interpretations as a consequence of the acyl groups being unresolved in all of the structures. They offer a simple, overarching and not particularly insightful explanation that the longer acyl group in propionyl-CoA may mediate stronger hydrophobic interactions that stabilize the alpha carbon of the acyl group at the proper position. The authors did not take the opportunity to describe the specific interactions that may be responsible for the stronger hydrophobic interaction nor do they offer any plausible explanation for how these might account for an astounding difference in the selectivity for propionyl-CoA vs. acetyl-CoA. Essentially, the authors concede that these cryo-EM structures offer no new insights into the structural basis for substrate selectivity in PCC, confirming that these structures do not yet fully capture the proper conformational states.

Some of these minor deficiencies aside, the overall aim of contributing new cryo-EM structures of the human MCC and PCC has been achieved. While I am not a cryo-EM expert, I see no flaws in the methodology or approach. While the contributions from these structures are somewhat incremental, it is nevertheless important to have these representative examples of the human enzymes and it is noteworthy to see a new example of the exo-binding site in a biotin-dependent enzyme.

Reviewer #2 (Public review):

Summary:

This paper reports the structures of two human biotin-dependent carboxylases. The authors used endogenously purified proteins and solved the structures in high resolutions. Based on the structures, they defined the binding site for acyl-CoA and biotin and reported the potential conformational changes in biotin position.

Strengths:

The authors effectively utilized the biotin of the two proteins and obtained homogeneous proteins from human cells. They determined the high-resolution structures of the two enzymes in apo and substrate-bound states.

Comments and questions to the manuscripts:

(1) I'm quite impressed with the protein purification and structure determination, but I think some functional characterization of the purified proteins should be included in the manuscript. The activity of enzymes should be the foundation of all structures and other speculations based on structures.

(2) In Figure 1B, the structure of MCC is shown as two layers of beta units and two layers of alpha units, while there is only one layer of alpha units resolved in the density maps. I suggest the authors show the structures resolved based on the density maps and show the complete structure with the docked layer in the supplementary figure.

(3) In the introduction, I suggest the author provide more information about the previous studies about the structure and reaction mechanisms of BDCs, what is the knowledge gap, and what problem you will resolve with a higher resolution structure. For example, you mentioned in line 52 that G437 and A438 are catalytic residues, are these residues reported as catalytic residues or this is based on your structures? Has the catalytic mechanism been reported before? Has the role of biotin in catalytic reactions revealed in previous studies?

(4) In the discussion, the authors indicate that the movement of biotin could be related to the recognition of acyl-CoA in BDCs, however, they didn't observe a change in the propionyl-CoA bound MCC structure, which is contradictory to their speculation. What could be the explanation for the exception in the MCC structure?

(5) In the discussion, the authors indicate that the selectivity of PCC to different acyl-CoA is determined by the recognition of the acyl chain. However, there are no figures or descriptions about the recognition of the acyl chain by PCC and MCC. It will be more informative if they can show more details about substrate recognition in Figures 3 and 4.

(6) How are the solved structures compared with the latest Alphafold3 prediction?

Reviewer #1 (Public review):

Summary:

DMS-MaP is a sequencing-based method for assessing RNA folding by detecting methyl adducts on unpaired A and C residues created by treatment with dimethylsulfate (DMS). DMS also creates methyl adducts on the N7 position of G, which could be sensitive to tertiary interactions with that atom, but N7-methyl adducts cannot be detected directly by sequencing. In this work, the authors adopt a previously developed method for converting N7-methyl-G to an abasic site to make it detectable by sequencing and then show that the ability of DMS to form an N7-methyl-G adduct is sensitive to RNA structural context. In particular, they look at the G-quadruplex structure motif, which is dense with N7-G interactions, is biologically important, and lacks conclusive methods for in-cell structural analysis.

Strengths:

- The authors clearly show that established methods for detecting N7-methyl-G adducts can be used to detect those adducts from DMS and that the formation of those adducts is sensitive to structural context, particularly G-quadruplexes.

- The authors assess the N7-methyl-G signal through a wide range of useful probing analyses, including standard folding, adduct correlations, mutate-and-map, and single-read clustering.

- The authors show encouraging preliminary results toward the detection of G-quadruplexes in cells using their method. Reliable detection of RNA G-quadruplexes in cells is a major limitation for the field and this result could lead to a significant advance.

- Overall, the work shows convincingly that N7-methyl-G adducts from DMS provide valuable structural information and that established data analyses can be adapted to incorporate the information.

Weaknesses:

- Most of the validation work is done on the spinach aptamer and it and polyUG RNA are the only RNAs tested that have a known 3D structure. Although it is a useful model for validating this method, it does not provide a comprehensive view of what results to expect across varied RNA structures.

- It's not clear from this work what the predictive power of BASH-MaP would be when trying to identify G-quadruplexes in RNA sequences of unknown structure. Although clusters of G's with low reactivity and correlated mutations seem to be a strong signal for G-quadruplexes, no effort was made to test a range of G-rich sequences that are known to form G-quadruplexes or not. Having this information would be critical for assessing the ability of BASH-MaP to identify G-quadruplexes in cells.

- Although the authors present interesting results from various types of analysis, the code currently available on Github lacks the documentation and examples necessary to be useful to the broader community.

- There are aspects of the DAGGER analysis that could limit its robustness or utility for different RNAs:

(1) Folding of the RNA based on individual reads does not represent single-molecule folding since each read contains only a small fraction of the possible adducts that could have formed on that molecule. As a result, each fold will largely be driven by the naive folding algorithm. The DANCE-MaP algorithm that was also used by the authors addresses this concern.<br /> (2) G residues in a loop will have a different impact on RNA folding than those in a G-quadruplex. This difference could reduce the accuracy of CONTRAfold predictions when forcing G-quadruplex residues to be unpaired. That said, predicting secondary structure around G-quadruplexes is a challenge for folding algorithms.<br /> (3) Incorporation of the G mutations requires prior knowledge of the RNA 3D structure, limiting the utility of the method to predicting alternative conformations in structures that are already well characterized.

Reviewer #3 (Public review):

Summary:

In this study the authors aim to develop an experimental/computational pipeline to assess the modification status of an RNA following treatment with dimethylsulfate (DMS). Building upon the more common DMS Map method, which predominantly assesses the modification status of the Watson-Crick-Franklin face of A's and C's, the authors insert a chemical processing step in the workflow prior to deep sequencing that enables detection of methylation at the N7 position of guanosine residues. This approach, termed BASH MaP, provides a more complete assessment of the true modification status of an RNA following DMS treatment, and this new information provides a powerful set of constraints for assessing the secondary structure and conformational state of an RNA. In developing this work, the authors use Spinach as a model RNA. Spinach is a fluorogenic RNA that binds and activates the fluorescence of a small molecule ligand. Crystal structures of this RNA with ligand bound show that it contains a G-quadruplex motif. In applying BASH MaP to Spinach, the authors also perform the more standard DMS MaP for comparison. They show that the BASH MaP workflow appears to retain the information yielded by DMS MaP while providing new information about guanosine modifications. In Spinach, the G-quadruplex G's have the least reactive N7 positions, consistent with the engagement of N7 in hydrogen bonding interactions at G's involved in quadruplex formation. Moreover, because the inclusion of data corresponding to G increases the number of misincorporations per transcript, BASH MaP is more amenable to analysis of co-occurring misincorporations through statistical analysis, especially in combination with site-specific mutations. These co-occurring misincorporations provide information regarding what nucleotides are structurally coupled within an RNA conformation. By deploying a likelihood-ratio statistical test on BASH MaP data, the authors can identify Gs in G-quadruplexes, deconvolute G-G correlation networks, base-triple interactions and even stacking interactions. Further, the authors develop a pipeline to use the BASH MaP-derived G-modification data to assist in the prediction of RNA secondary structure and identify alternative conformations adopted by a particular RNA. This seems to help with the prediction of secondary structure for Spinach RNA.

Strengths:

The BASH Map procedure and downstream data analysis pipeline more fully identifies the complement of methylations to be identified from DMS treatment of RNA, thereby enriching the information content. This in turn allows for more robust computational/statistical analysis, which likely will lead to more accurate structure predictions. This seems to be the case for the Spinach RNA.

Weaknesses:

The authors demonstrate that their method can detect G-quadruplexes in Spinach and some other RNAs both in vitro and in cells. While application to other RNAs is beyond the scope of the current manuscript, the performance of BASH MaP and associated computational analysis in the context of other RNAs remains to be determined.

Reviewer #1 (Public review):

Using a knock-out mutant strain, the authors tried to decipher the role of the last gene in the mycofactocin operon, mftG. They found that MftG was essential for growth in the presence of ethanol as the sole carbon source, but not for the metabolism of ethanol, evidenced by the equal production of acetaldehyde in the mutant and wild type strains when grown with ethanol (Fig 3). The phenotypic characterization of ΔmftG cells revealed a growth-arrest phenotype in ethanol, reminiscent of starvation conditions (Fig 4). Investigation of cofactor metabolism revealed that MftG was not required to maintain redox balance via NADH/NAD+, but was important for energy production (ATP) in ethanol. Since mycobacteria cannot grow via substrate-level phosphorylation alone, this pointed to a role of MftG in respiration during ethanol metabolism. The accumulation of reduced mycofactocin points to impaired cofactor cycling in the absence of MftG, which would impact the availability of reducing equivalents to feed into the electron transport chain for respiration (Fig 5). This was confirmed when looking at oxygen consumption in membrane preparations from the mutant and would type strains with reduced mycofactocin electron donors (Fig 7). The transcriptional analysis supported the starvation phenotype, as well as perturbations in energy metabolism, and may be beneficial if described prior to respiratory activity data.<br /> The data and conclusions support the role of MftG in ethanol metabolism.

Reviewer #3 (Public review):

Summary:

The work by Graca et al. describes a GMC flavoprotein dehydrogenase (MftG) in the ethanol metabolism of mycobacteria and provides evidence that it shuttles electrons from the mycofactocin redox cofactor to the electron transport chain.

Strengths:

Overall, this study is compelling, exceptionally well designed and thoroughly conducted. An impressively diverse set of different experimental approaches is combined to pin down the role of this enzyme and scrutinize the effects of its presence or absence in mycobacteria cells growing on ethanol and other substrates. Other strengths of this work are the clear writing style and stellar data presentation in the figures, which makes it easy also for non-experts to follow the logic of the paper. Overall, this work therefore closes an important gap in our understanding of ethanol oxidation in mycobacteria, with possible implications for the future treatment of bacterial infections.

Weaknesses:

I see no major weaknesses of this work, which in my opinion leaves no doubt about the role of MftG.

Reviewer #4 (Public review):

Summary:

The manuscript by Graça et al. explores the role of MftG in the ethanol metabolism of mycobacteria. The authors hypothesise that MftG functions as a mycofactocin dehydrogenase, regenerating mycofactocin by shuttling electrons to the respiratory chain of mycobacteria. Although the study primarily uses M. smegmatis as a model microorganism, the findings have more general implications for understanding mycobacterial metabolism. Identifying the specific partner to which MftG transfers its electrons within the respiratory chain of mycobacteria would be an important next step, as pointed out by the authors.

Strengths:

The authors have used a wide range of tools to support their hypothesis, including co-occurrence analyses, gene knockout and complementation experiments, as well as biochemical assays and transcriptomics studies.<br /> An interesting observation that the mftG deletion mutant grown on ethanol as the sole carbon source exhibited a growth defect resembling a starvation phenotype.<br /> MftG was shown to catalyse the electron transfer from mycofactocinol to components of the respiratory chain, highlighting the flexibility and complexity of mycobacterial redox metabolism.

Weaknesses:

Could the authors elaborate more on the differences between the WT strains in Fig. 3C and 3E? in Fig. 3C, the ethanol concentration for the WT strain is similar to that of WT-mftG and ∆mftG-mftG, whereas the acetate concentration in thw WT strain differs significantly from the other two strains. How this observation relates to ethanol oxidation, as indicated on page 12.<br /> The authors conclude from their functional assays that MftG catalyses single-turnover reactions, likely using FAD present in the active site as an electron acceptor. While this is plausible, the current experimental set up doesn't fully support this conclusions, and the language around this claim should be softened.<br /> The authors suggest in the manuscript that the quinone pool (page 24) may act as the electron acceptor from mycofactocinol, but later in in the discussion section (page 30) they propose cytochromes as the potential recipients. If the authors consider both possibilities valid, I suggest discussing both options in the manuscript.

Reviewer #1 (Public review):

The authors sought to determine the impact of early antiretroviral treatment on the size, composition, and decay of the HIV latent reservoir. This reservoir represents the source of viral rebound upon treatment interruption and therefore constitutes the greatest challenge to achieving an HIV cure. A particular strength of this study is that it reports on reservoir characteristics in African women, a significantly understudied population, of whom some have initiated treatment within days of acute HIV diagnosis. With the use of highly sensitive and current technologies, including digital droplet PCR and near full-length genome next-generation sequencing, the authors generated a valuable dataset for investigation of proviral dynamics in women initiating early treatment compared to those initiating treatment in chronic infection. The authors confirm previous reports that early antiretroviral treatment restricts reservoir size, but further show that this restriction extends to defective viral genomes, where late treatment initiation was associated with a greater frequency of defective genomes. Furthermore, an additional strength of this study is the longitudinal comparison of viral dynamics post-treatment, wherein early treatment was shown to be associated with a more rapid rate of decay in proviral genomes, regardless of intactness, over a period of one year post-treatment. While it is indicated that intact genomes were not detected after one year following early treatment initiation, sampling depth is noted as a limitation of the study by the authors, and caution should thus be taken with interpretation where sequence numbers are low. Defective genomes are more abundant than intact genomes and are therefore more likely to be sampled. Early treatment was also associated with reduced proviral diversity and fewer instances of polymorphisms associated with cytotoxic T-lymphocyte immune selection. This is expected given that rapid evolution and extensive immune selection are synonymous with HIV infection in the absence of treatment, yet points to an additional benefit of early treatment in the context of immune therapies to restrict the reservoir.

This is one of the first studies to report the mapping of longitudinal intactness of proviral genomes in the globally dominant subtype C. The data and findings from this study therefore represent a much-needed resource in furthering our understanding of HIV persistence and informing broadly impactful cure strategies. The analysis on clonal expansion of proviral genomes may be limited by higher sequence homogeneity in hyperacute infection i.e., cells with different proviral integration sites may have a higher likelihood of containing identical genomes compared to chronic infection.

Overall, these data demonstrate the distinct benefits of early treatment initiation at reducing the barrier to a functional cure for HIV, not only by restricting viral abundance and diversity but also potentially through the preservation of immune function and limiting immune escape. It therefore provides clues to curative strategies even in settings where early diagnosis and treatment may be unlikely.

Reviewer #2 (Public review):

HIV infection is characterized by viral integration into permissive host cells - an event that occurs very early in viral-host encounter. This constitutes the HIV proviral reservoir and is a feature of HIV infection that provides the greatest challenge for eradicating HIV-1 infection once an individual is infected.

This study looks at how starting HIV treatment very early after infection, which substantially reduces the peak viral load detectable (compared to untreated infection), affects the amount and characteristics of the viral reservoir. The authors studied 35 women in South Africa who were at high risk of getting HIV. Some of these women started HIV treatment very soon after getting infected, while others started later. This study is well designed and has as its focus a very well characterized cohort. Comparison groups are appropriately selected to address proviral DNA characterization and dynamics in the context of acute and chronic treated HIV-1. The amount of HIV and various characteristics of the genetic makeup of the virus (intact/defective proviral genome) was evaluated over one year of treatment. Methods employed for proviral DNA characterization are state of the art and provide in-depth insights into the reservoir in peripheral blood.

While starting treatment early didn't reduce the amount of HIV DNA at the outset, it did lead to a gradual decrease in total HIV DNA quantity over time. In contrast, those who started treatment later didn't see much change in this parameter. Starting treatment early led to a faster decrease in intact provirus (a measure of replication-competence), compared to starting treatment later. Additionally, early treatment reduced genetic diversity of the viral DNA and resulted in fewer immune escape variants within intact genomes. This suggests that collectively having a smaller intact replication-competent reservoir, less viral variability, and less opportunity for virus to evade the immune system - are all features that are likely to facilitate more effective clearance of viral reservoir, especially when combined with other intervention strategies.

Major strengths of the study include the cohort of very early treated persons with HIV and the depth of study. These are important findings, particularly as the study was conducted in HIV-1 subtype C infected women (more cure studies have focussed on men and with subtype B infection)- and in populations most affected by HIV and in need of HIV cure interventions. This is highly relevant because it cannot be assumed that any interventions employed for reducing/clearing the HIV reservoir would perform similarly in men and women or across different populations. Other factors also deserve consideration and include age, and environment (e.g. other comorbidities and coinfections).

Reviewer #1 (Public review):

Summary:

The present study's main aim is to investigate the mechanism of how VirR controls the magnitude of MEV release in Mtb. The authors used various techniques, including genetics, transcriptomics, proteomics, and ultrastructural and biochemical methods. Several observations were made to link VirR-mediated vesiculogenesis with PG metabolism, lipid metabolism, and cell wall permeability. Finally, the authors presented evidence of a direct physical interaction of VirR with the LCP proteins involved in linking PG with AG, providing clues that VirR might act as a scaffold for LCP proteins and remodel the cell wall of Mtb. Since the Mtb cell wall provides a formidable anatomical barrier for the entry of antibiotics, targeting VirR might weaken the permeability of the pathogen along with the stimulation of the immune system due to enhanced vesiculogenesis. Therefore, VirR could be an excellent drug target. Overall, the study is an essential area of TB biology.

Strengths:

The authors have done a commendable job of comprehensively examining the phenotypes associated with the VirR mutant using various techniques. Application of Cryo-EM technology confirmed increased thickness and altered arrangement of CM-L1 layer. The authors also confirmed that increased vesicle release in the mutant was not due to cell lysis, which contrasts with studies in other bacterial species.

Another strength of the manuscript is that biochemical experiments show altered permeability and PG turnover in the mutant, which fits with later experiments where authors provide evidence of a direct physical interaction of VirR with LCP proteins.

Transcriptomics and proteomics data were helpful in making connections with lipid metabolism, which the authors confirmed by analyzing the lipids and metabolites of the mutant.

Lastly, using three approaches, the authors confirm that VirR interacts with LCP proteins in Mtb via the LytR_C terminal domain.

Altogether, the work is comprehensive, experiments are designed well, and conclusions were made based on the data generated after verification using multiple complementary approaches.

Weaknesses:

The major weakness is that the mechanism of VirR-mediated EV release remains enigmatic. Most of the findings are observational and only associate enhanced vesiculogenesis observed in the VirR mutant with cell wall permeability and PG metabolism. Authors suggest that EV release occurs during cell division when PG is most fragile. However, this has yet to be tested in the manuscript - the AFM of the VirR mutant, which produces thicker PG with more pore density, displays enhanced vesiculogenesis. No evidence was presented to show that the PG of the mutant is fragile, and there are differences in cell division to explain increased vesiculogenesis. These observations, counterintuitive to the authors' hypothesis, need detailed experimental verification.

Transcriptomic data only adds a little substantial. Transcriptomic data do not correlate with the proteomics data. It remains unclear how VirR deregulates transcription. TLCs of lipids are not quantitative. For example, the TLC image of PDIM is poor; quantitative estimation needs metabolic labeling of lipids with radioactive precursors. Further, change in PDIMs is likely to affect other lipids (SL-1, PAT/DAT) that share a common precursor (propionyl- CoA).

The connection of cholesterol with cell wall permeability is tenuous. Cholesterol will serve as a carbon source and contribute to the biosynthesis of methyl-branched lipids such as PDIM, SL-1, and PAD/DAT. Carbon sources also affect other aspects of physiology (redox, respiration, ATP), which can directly affect permeability and import/export of drugs. Authors should investigate whether restoration of the normal level of permeability and EV release is not due to the maintenance of cell wall lipid balance upon cholesterol exposure of the VirR mutant.

Finally, protein interaction data is based on experiments done once without statistical analysis. If the interaction between VirR and LCP protein is expected on the mycobacterial membrane, how SPLIT_GFP system expressed in the cytoplasm is physiologically relevant. No explanation was provided as to why VirR interacts with the truncated version of LCP proteins and not with the full-length proteins.

Reviewer #2 (Public review):

Summary:

In this work, Vivian Salgueiro et al. have comprehensively investigated the role of VirR in the vesicle production process in Mtb using state-of-the-art omics, imaging, and several biochemical assays. From the present study, authors have drawn a positive correlation between cell membrane permeability and vasculogenesis and implicated VirR in affecting membrane permeability, thereby impacting vasculogenesis.

Strengths:

The authors have discovered a critical factor (i.e. membrane permeability) that affects vesicle production and release in Mycobacteria, which can broadly be applied to other bacteria and may be of significant interest to other scientists in the field. Through omics and multiple targeted assays such as targeted metabolomics, PG isolation, analysis of Diaminopimelic acid and glycosyl composition of the cell wall, and, importantly, molecular interactions with PG-AG ligating canonical LCP proteins, the authors have established that VirR is a central scaffold at the cell envelope remodelling process which is critical for MEV production.

Weaknesses:

Throughout the study, the authors have utilized a CRISPR knockout of VirR. VirR is a non-essential gene for the growth of Mtb; a null mutant of VirR would have been a better choice for the study.

Comments on the revised version:

Concerns flagged about using CRISPR -guide RNA mediated knockdown of viral has yet to be addressed entirely. I understand that the authors could not get knock out despite attempts and hence they have guide RNA mediated knockdown strategy. However, I wondered if the authors looked at the levels of the downstream genes in this knockdown.

Authors have used the virmut-Comp strain for some of the experiments. However, the materials and methods must describe how this strain was generated. Given the mutant is a CRISPR-guide RNA mediated knockdown. The CRISPR construct may have taken up the L5 loci. Did authors use episomal construct for complementation? If so, what is the expression level of virR in the complementation construct? What are the expression levels of downstream genes in mutant and complementation strains? This is important because the transcriptome analysis was redone by considering complementation strain. The complemented strain is written as virmut-C or virmut-Comp. This has to be consistent.

Reviewer #1 (Public review):

Summary:

In this paper, Hackwell and colleagues performed technically impressive, long-term, GCaMP fiber photometry recordings from Kiss1 neurons in the arcuate nucleus of mice during multiple reproductive states. The data show an immediate suppression of activity of arc Kiss1 neuronal activity during pregnancy that is maintained during lactation. In the absence of any apparent change in suckling stimulus or milk production, mice lacking prolactin receptors in arcuate Kiss1 neurons regained Kiss1 episodic activity and estrous cyclicity faster than control mice, demonstrating that direct prolactin action on Kiss1 neurons is at least partially responsible for suppressing fertility in this species. The effect of loss of prolactin receptors from CamK2a expressing neurons was even greater, indicating either that prolactin sensitivity in Kiss1 neurons of the RP3V contributes to lactational infertility or that other prolactin-sensitive neurons are involved. These data demonstrate the important role of prolactin in suppressing Kiss1 neuron activity and thereby fertility during the lactational period in the mouse.

Strengths:

This is the first study to monitor activity of the GnRH pulse-generating system across different reproductive states in the same animal. Another strength in the study design is that it isolated the effects of prolactin by maintaining normal lactation and suckling (assessed indirectly using pup growth curves). The study also offers insight into the phenomenon of postpartum ovulation in mice. The results showed a brief reactivation of arcuate Kiss1 activity immediately prior to parturition, attributed to falling progesterone levels at the end of pregnancy. This hypothesis will be of interest to the field and is likely to inspire testing in future studies. With the exceptions mentioned below, the conclusions of the paper are well supported by the data and the aims of the study were achieved. This paper is likely to raise the standard for technical expectations in the field and spark new interest in the direct impact of prolactin on Kiss1 neurons during lactation in other species.

Weaknesses:

A weakness in the approach is the use of genetic models that do not offer complete deletion of the prolactin receptor from targeted neuronal populations. A substantial proportion of Kiss1 neurons in both models retains the receptor. As a result, it is not clear whether the partial maintenance of cyclicity during lactation in the genetic models is due to incomplete deletion or to the involvement of other factors. In addition, results showing no impact of progesterone on LH secretion during lactation are surprising, given the effectiveness of progesterone-containing birth control in lactating women. While the authors assert their findings may reflect an important role for prolactin in lactational infertility in other mammalian species, that remains to be seen. Hyperprolactinemia is known to suppress GnRH release, but its importance in the suppression of cyclicity during the lactation is controversial. Indeed, in several species, the stimulus of suckling is considered to be the main driver of lactational fertility suppression. Data from rats shows that exogenous prolactin was unable to suppress LH release in dams deprived of their pups shortly after birth; both suckling and prolactin were necessary to suppress a post-ovariectomy rise in LH levels. The duration of amenorrhea does not correlate with average prolactin levels in humans, and suckling but not prolactin was required to suppress the postpartum rise in LH in the rhesus monkey. The protocol of this or other studies might result in discordant results; alternatively, mice may be an outlier in their mechanism of cycle suppression.

Comments on revised version:

I remain enthusiastic about this article, which has been substantially improved in this revision. However, I didn't feel the authors responded to any of the points I raised previously in my public review (see Weaknesses), for example by adding to the manuscript's discussion section. These are the larger, conceptual issues that speak to the value of the paper in the context of the existing literature. The authors could also state they feel they have addressed the issues raised sufficiently in the text.

Reviewer #2 (Public review):

Summary:

The overall goal of Eleni et al. is to determine if the suppression of LH pulses during lactation is mediated by prolactin signaling at kisspeptin neurons. To address this, the authors used GCaMP fiber photometry and serial blood sampling to reveal that in vivo episodic arcuate kisspeptin neuron activity and LH pulses are suppressed throughout pregnancy and lactation. The authors further utilized knockout models to demonstrate that the loss of prolactin receptor signaling at kisspeptin cells prevents the suppression of kisspeptin cell activity and results in the early reestablishment of fertility during lactation. The work demonstrates exemplary design and technique, and the outcomes of these experiments are sophistically discussed.

Strengths:

This manuscript demonstrates exceptional skill with powerful techniques and reveals a key role for arcuate kisspeptin neurons in maintaining lactation-induced infertility in mice. In a difficult feat, the authors used fiber photometry to map the activity of arcuate kisspeptin cells into lactation and weaning without disrupting parturition, lactation, or maternal behavior. The authors used a knockout approach to identify if the inhibition of fertility by prolactin is mediated via direct signaling at arcuate kisspeptin cells. Although the model does not perfectly eliminate prolactin receptor expression in all kisspeptin neurons, results from the achieved knockdown support the conclusion that prolactin signaling at kisspeptin neurons is required to maintain lactational infertility. The methods are advanced and appropriate for the aims, the study is rigorously conducted, and the conclusions are thoughtfully discussed.

Comments on the latest version:

All comments and suggestions have been addressed by the authors in this revision.

Reviewer #1 (Public review):

Summary:

Wang and colleagues presented an investigation of pig-origin bacteria Bacillus velezensis HBXN2020, for its released genome sequence, in vivo safety issue, probiotic effects in vitro, and protection against Salmonella infection in a murine model. Various techniques and assays are performed; the main results are all descriptive, without new insight advancing the field or a mechanistic understanding of the observed protection.

Strengths:

An extensive study on the probiotic properties of the Bacillus velezensis strain HBXN2020

Weaknesses:

The main results are descriptive without mechanistic insight. Additionally, most of the results and analysis parts are separated without a link or a story-telling way to deliver a concise message.

Now the manuscript has made appropriate and considerable improvements.

Joint Public Review:

When the left-right asymmetry of an animal body is established, a barrier that prevents the mixing of signals or cells across the midline is essential. Such midline barrier preventing the spreading of asymmetric Nodal signaling during early left-right patterning has been identified. However, midline barriers during later asymmetric organogenesis have remained largely unknown, except in the brain. In this study, the authors discovered an unexpected structure in the midline of the developing midgut in the chick. Using immunofluorescence, they convincingly show the chemical composition of this midline structure as a double basement membrane and its transient existence during the left-right patterning of the dorsal mesentery, that authors showed previously to be essential for forming the gut loop and guiding local vasculogenesis. Labelling experiments demonstrate a physical and chemical barrier function, to cell mixing and signal diffusion in the dorsal mesentery. Cell labelling and graft experiments rule out a cellular composition of the midline from dorsal mesenchyme or endoderm origin and rule out an inducing role by the notochord. Based on laminin expression pattern and Ntn4 resistance, the authors propose a model, whereby the midline basement membrane is progressively deposited by the descending endoderm. Observations of a transient midline basement membrane in the veiled chameleon suggest a conserved mechanism in birds and reptiles.

Laterality defects encompass severe malformations of visceral organs, with a heterogenous spectrum that remains poorly understood, by lack of knowledge of the different players of left-right asymmetry. This fundamental work significantly advances our understanding of left-right asymmetric organogenesis, by identifying an organ-specific and stage-specific midline barrier. The complexities of basement membrane assembly, maintenance and function are of importance in several other contexts, as for example in the kidney and brain. Thus, this original work is of broad interest.

Overall, reviewers refer to a strong and elegant paper discovering a novel midline structure, combining classic but challenging techniques, and well thought tools, to show the dynamics, chemical and physical properties of the midline. Reviewers also indicate that further work will be necessary to conclude on the origin and impact of the midline for asymmetric organogenesis. They acknowledge that this is currently technically challenging and that authors have made several attempts to answer these questions by different means. The article includes an interesting discussion about these points and the mechanism of midline breakdown.

Reviewer #2 (Public review):

The fledgling field of epitranscriptomics has encountered various technical roadblocks with implications as to the validity of early epitranscriptomics mapping data. As a prime example, the low specificity of (supposedly) modification-specific antibodies for the enrichment of modified RNAs, has been ignored for quite some time and is only now recognized for its dismal reproducibility (between different labs), which necessitates the development of alternative methods for modification detection.

Furthermore, early attempts to map individual epitranscriptomes using sequencing-based techniques are largely characterized by the deliberate avoidance of orthogonal approaches aimed at confirming the existence of RNA modifications that have been originally identified.

Improved methodology, the inclusion of various controls, and better mapping algorithms as well as the application of robust statistics for the identification of false-positive RNA modification calls have allowed revisiting original (seminal) publications whose early mapping data allowed making hyperbolic claims about the number, localization and importance of RNA modifications, especially in mRNA. Besides the existence of m6A in mRNA, the detectable incidence of RNA modifications in mRNAs has drastically dropped.

As for m5C, the subject of the manuscript submitted by Zhou et al., its identification in mRNA goes back to Squires et al., 2012 reporting on >10.000 sites in mRNA of a human cancer cell line, followed by intermittent findings reporting on pretty much every number between 0 to > 100.000 m5C sites in different human cell-derived mRNA transcriptomes. The reason for such discrepancy is most likely of a technical nature. Importantly, all studies reporting on actual transcript numbers that were m5C-modified relied on RNA bisulfite sequencing, an NGS-based method, that can discriminate between methylated and non-methylated Cs after chemical deamination of C but not m5C. RNA bisulfite sequencing has a notoriously high background due to deamination artifacts, which occur largely due to incomplete denaturation of double-stranded regions (denaturing-resistant) of RNA molecules. Furthermore, m5C sites in mRNAs have now been mapped to regions that have not only sequence identity but also structural features of tRNAs. Various studies revealed that the highly conserved m5C RNA methyltransferases NSUN2 and NSUN6 do not only accept tRNAs but also other RNAs (including mRNAs) as methylation substrates, which in combination account for most of the RNA bisulfite-mapped m5C sites in human mRNA transcriptomes. Is m5C in mRNA only a result of the Star activity of tRNA or rRNA modification enzymes, or is their low stoichiometry biologically relevant?<br /> In light of the short-comings of existing tools to robustly determine m5C in transcriptomes, other methods, like DRAM-seq, allowing to map m5C independently of ex situ RNA treatment with chemicals, are needed to arrive at a more solid "ground state", from which it will be possible to state and test various hypotheses as to the biological function of m5C, especially in lowly abundant RNAs such as mRNA.

Importantly, the identification of >10.000 sites containing m5C increases through DRAM-Seq, increases the number of potential m5C marks in human cancer cells from a couple of 100 (after rigorous post-hoc analysis of RNA bisulfite sequencing data) by orders of magnitude. This begs the question, whether or not the application of these editing tools results in editing artefacts overstating the number of actual m5C sites in the human cancer transcriptome.

Remaining comments after resubmission:

(1) The use of two m5C reader proteins is likely a reason for the high number of edits introduced by the DRAM-Seq method. Both ALYREF and YBX1 are ubiquitous proteins with multiple roles in RNA metabolism including splicing and mRNA export. It is reasonable to assume that both ALYREF and YBX1 bind to many mRNAs that do not contain m5C.<br /> To substantiate the author's claim that ALYREF or YBX1 binds m5C-modified RNAs to an extent that would allow distinguishing its binding to non-modified RNAs from binding to m5C-modified RNAs, it would be recommendable to provide data on the affinity of these, supposedly proven, m5C readers to non-modified versus m5C-modified RNAs. To do so, this reviewer suggests performing experiments as described in Slama et al., 2020 (doi: 10.1016/j.ymeth.2018.10.020). Mind you that using dot blots like in so many published studies to show modification-specific antibody or protein binding, is insufficient as an argument because no antibody, nor protein encounters nanograms to micrograms of a specific RNA identity in a cell. This issue remains a major caveat in all studies using so-called RNA modification reader proteins as bait for detecting RNA modifications in epitranscriptomics research and becomes a pertinent problem, if used as a platform for base-editing similar to the work presented in this manuscript.

(2) Using sodium arsenite treatment of cells as a means to change the m5C status of transcripts through the downregulation of the two major m5C writer proteins NSUN2 and NSUN6 is problematic and the conclusions from these experiments are not warranted. Sodium arsenite is a chemical that poisons every protein containing thiol groups. Not only do NSUN proteins contain cysteines but also the base editor fusion proteins. Arsenite will inactivate these proteins, hence the editing frequency will drop, as observed in the experiments shown in Figure 5, which the authors explain with fewer m5C sites to be detected by the fusion proteins.

(3) The authors should move high-confidence editing site data contained in Supplementary Tables 2 and 3 into one of the main Figures to substantiate what is discussed in Figure 4A. However, the data needs to be visualized in another way then excel format. Furthermore, Supplementary Table 2 does not contain a description of the columns, while Supplementary Table 3 contains a single row with letters and numbers.

Reviewer #1 (Public review):

Summary:

The authors use analysis of existing data, mathematical modelling, and new experiments, to explore the relationship between protein expression noise, translation efficiency, and transcriptional bursting.

Strengths:

The analysis of the old data and the new data presented is interesting and mostly convincing.

Weaknesses:

(1) My main concern is the analysis presented in Figure 4. This is the core of mechanistic analysis that suggests ribosomal demand can explain the observed phenomenon. I am both confused by the assumptions used here and the details of the mathematical modelling used in this section. Firstly, the authors' assumption that the fluctuations of a single gene mRNA levels will significantly affect ribosome demand is puzzling. On average the total level of mRNA across all genes would stay very constant and therefore there are no big fluctuations in the ribosome demand due to the burstiness of transcription of individual genes. Secondly, the analysis uses 19 mathematical functions that are in Table S1, but there are not really enough details for me to understand how this is used, are these included in a TASEP simulation? In what way are mRNA-prev and mRNA-curr used? What is the mechanistic meaning of different terms and exponents? As the authors use this analysis to argue ribosomal demand is at play, I would like this section to be very much clarified.

(2) Overall, the paper is very long and as there are analytical expressions for protein noise (e.g. see Paulsson Nature 2004), some of these results do not need to rely on Gillespie simulations. Protein CV (noise) can be written as three terms representing protein noise contribution, mRNA expression contribution, and bursty transcription contribution. For example, the results in panel 1 are fully consistent with the parameter regime, protein noise is negligible compared to transcriptional noise.

Reviewer #2 (Public review):

This work by Pal et al. studied the relationship between protein expression noise and translational efficiency. They proposed a model based on ribosome demand to explain the positive correlation between them, which is new as far as I realize. Nevertheless, I found the evidence of the main idea that it is the ribosome demand generating this correlation is weak. Below are my major and minor comments.

Major comments:

(1) Besides a hypothetical numerical model, I did not find any direct experimental evidence supporting the ribosome demand model. Therefore, I think the main conclusions of this work are a bit overstated.

(2) I found that the enhancement of protein noise due to high translational efficiency is quite mild, as shown in Figure 6A-B, which makes the biological significance of this effect unclear.

(3) The captions for most of the figures are short and do not provide much explanation, making the figures difficult to read.

(4) It would be helpful if the authors could define the meanings of noise (e.g., coefficient of variation?) and translational efficiency in the very beginning to avoid any confusion. It is also unclear to me whether the noise from the experimental data is defined according to protein numbers or concentrations, which is presumably important since budding yeasts are growing cells.

(5) The conclusions from Figures 1D and 1E are not new. For example, the constant protein noise as a function of mean protein expression is a known result of the two-state model of gene expression, e.g., see Equation (4) in Paulsson, Physics of Life Reviews 2005.

(6) In Figure 4C-D, it is unclear to me how the authors changed the mean protein expression if the translation initiation rate is a function of variation in mRNA number and other random variables.

(7) If I understand correctly, the authors somehow changed the translation initiation rate to change the mean protein expression in Figures 4C-D. However, the authors changed the protein sequences in the experimental data of Figure 6. I am not sure if the comparison between simulations and experimental data is appropriate.

Reviewer #1 (Public review):

Summary:

Numerous mechanism and structural studies reported the cooperative role of Oct4 and Sox2 during the establishment of pluripotency during reprogramming. Due to the difficulty in sample collection and RNA-seq with low-number cells, the precise mechanisms remain in early embryos. This manuscript reported the role of OCT4 and SOX2 in mouse early embryos using knockout models with low-input ATAC-seq and RNA-seq. Compared to the control, chromatin accessibility and transcriptome were affected when Oct4 and Sox2 were deleted in early ICM. Specifically, decreased ATAC-seq peaks showed enrichment of Motifs of TF such as OCT, SOX, and OCT-SOX, indicating their importance during early development. Moreover, by deep analysis of ATAC-seq and RNA-seq data, they found Oct4 and Sox2 target enhancer to activate their downstream genes. In addition, they also uncovered the role of OS during development from the morula to ICM, which provided the scientific community with a more comprehensive understanding.

Strengths:

On the whole, the manuscript is innovative, and the conclusions of this paper are mostly well supported by data, however, there are some issues that need to be addressed.

Weaknesses:

Major Points:

(1) In Figure 1, a more detailed description of the knockout strategy should be provided to clarify itself. The knockout strategy in Fig1 is somewhat obscure, such as how is OCT4 inactivated in Oct4mKO2 heterozygotes. As shown in Figure 1, the exon of OCT4 is not deleted, and its promoter is not destroyed. Therefore, how does OCT4 inactivate to form heterozygotes?

(2) Is ZP 3-Cre expressed in the zygotes? Is there any residual protein?

(3) What motifs are enriched in the rising ATAC-seq peaks after knocking out of OCT4 and SOX2?

(4) The ordinate of Fig4c is lost.

(5) Signals of H3K4me1, H3K27ac, and so on are usually used to define enhancers, and the loci of enhancers vary greatly in different cells. In the manuscript, the authors defined ATAC-seq peaks far from the TSS as enhancers. The definition in this manuscript is not strictly an enhancer.

(6) If Oct4 and Sox2 truly activate sap 30 and Uhrf 1, what effect does interfering with both genes have on gene expression and chromatin accessibility？

Reviewer #2 (Public review):

In this manuscript, Hou et al. investigate the interplay between OCT4 and SOX2 in driving the pluripotent state during early embryonic lineage development. Using knockout (KO) embryos, the authors specifically analyze the transcriptome and chromatin state within the ICM-to-EPI developmental trajectory. They emphasize the critical role of OCT4 and the supportive function of SOX2, along with other factors, in promoting embryonic fate. Although the paper presents high-quality data, several key claims are not well-supported, and direct evidence is generally lacking.

Major Points:

(1) Although the authors claim that both maternal KO and maternal KO/zygotic hetero KO mice develop normally, the molecular changes in these groups appear overestimated. A wildtype control is recommended for a more robust comparison.

(2) The authors assert that OCT4 and SOX2 activate the pluripotent network via the OCT-SOX enhancer. However, the definition of this enhancer is based solely on proximity to TSSs, which is a rough approximation. Canonical enhancers are typically located in intronic and intergenic regions and marked by H3K4me1 or H3K27ac. Re-analyzing enhancer regions with these standards could be beneficial. Additionally, the definitions of "close to" or "near" in lines 183-184 are unclear and not defined in the legends or methods.

(3) There is no evidence that the decreased peaks/enhancers could be the direct targets of Oct4 and Sox2 throughout this manuscript. Figures 2 and 4 show only minimal peak annotations related to OCT and SOX motifs, and there is a lack of chromatin IP data. Therefore, claims about direct targets are not substantiated and should be appropriately revised.

(4) Lines 143-146 lack direct data to support the claim. Actually, the main difference in cluster I, 11 and 3, 8, 14 is whether the peak contains OCT-SOX motif. However, the reviewer cannot get any information of peaks activated by OCT4 rather than SOX2 in cluster I, 11.

Minor Points:

(1) Lines 153-159: The figure panel does not show obvious enrichment of SOX2 signals or significant differences in H3K27ac signals across clusters, thus not supporting the claim.

(2) Lines 189-190: The term "identify" is overstated for the integrative analysis of RNA-seq and ATAC-seq, which typically helps infer TF targets rather than definitively identifying them.

(3) The Discussion is lengthy and should be condensed.

Reviewer #1 (Public review):

Summary:

This study makes use of the EM reconstruction of the fly brain to investigate the morphology and topography of the synapses between retinotopic, loom-sensitive visual projection neurons (VPNs) and downstream descending neurons (DNs). The authors analyzed the distribution of synapses on the dendritic trees of DNs and performed multi-compartmental modelling to study the implications of the synaptic arrangements for neuronal integration of input signals.

Until recently, it has been unclear how spatial information is passed from retinotopic loom-sensitive neurons to descending neurons because the axons of the VPNs terminate in small optic glomeruli with no apparent topographic organization. It has recently been shown that synaptic weight gradients of VPNs connecting to DNs are the main mechanisms that allow for directed behavioral output (Dombrovski et al.). This study now goes one step further to determine if precise synapse location on the dendritic tree contributes further to the information processing. The study suggests that (1) none of the VPNs investigated show a retinotopic organization of synapses on DN dendrites. (2) Synapses of single VPNs are locally clustered. (3) Initial EPSPs at the synaptic location have, as expected, varying amplitudes but the amplitudes are passively normalized and only cover a small range when measured at the SIZ. (4) A near random distribution of synapses allows for linear integration of synaptic inputs when only a few VPNs are activated.

Strengths:

This study provides a detailed picture of the synapse distribution for a set of VPN and DN pairs, in combination with multi-compartmental modelling fitted to electrophysiological data. The data and methods are clear. The findings are overall interesting. The computational pipeline, which should ideally be made publicly available, will allow the community to make similar analyses on different neuronal classes, which will facilitate the detection of more general mechanisms of dendritic computation.

Weaknesses:

- In my opinion, we need more detail on the electrophysiological data and the fitting of the multi-compartmental model, which is the foundation of large parts of the study.<br /> - The study shows that the synapses of an individual VPN are locally clustered and suggests this as evidence for clustering of synapses of similar tuning (as has been shown previously in other systems). I am not fully convinced by the arguments here, since synapses of a single neuron are by necessity not randomly distributed in space.<br /> - As written, it was in parts unclear to me what the main hypotheses and conclusions were - e.g., how would a retinotopic distribution of synapses on dendritic trees contribute to information processing? Are the model predictions in line with the presumed behavioural role of these neurons?

Reviewer #2 (Public review):

Summary:

This article investigates the distribution of synapses on the dendritic arbors of descending neurons in the looming circuit of the fly visual system. The authors use publicly available EM reconstruction data of the adult fly brain to identify the positions of synapses from several types of visual projection neuron (VPN) to descending neuron (DN) connections. VPN dendrites are retinotopically organized, and axons from different VPN populations innervate distinct optic glomeruli. Yet the authors did not find any retinotopic organization of the synapses in the VPN-DN pairs they analyzed. They then constructed passive electrical models of the DNs with their structures extracted from the EM reconstructions. They focused on two specific DNs and parameterized their models by conducting whole-cell recordings within a voltage range below spiking threshold. Simulation of these passive models showed that irrespective of the location of a synapse, EPSPs became very similar at the spike initiation zone. This is consistent with the idea of synaptic democracy where EPSPs at far away synapses have higher amplitude compared to those nearer to the spike initiation zone so that they all attenuate to similar amplitudes while reaching there. The authors found that activating synapses from individual VPNs have the same effect as activating a random set of synapses. They conclude that despite some clustering of VPN synapses at small scale, they are distributed randomly over the dendritic arbor of DNs so that their EPSP amplitude encode the number of activated synapses, avoiding sublinearity from shunting effect.

Strengths:

- Experimental confirmation of the location of the spike initiation zone in the DN arbors is interesting and may provide better understanding of signal processing in these neurons.<br /> - Passive parameters obtained through electrophysiological recordings are useful.<br /> - These morphologically detailed single neuron models, if made available publicly, will be beneficial for building more complete models to understand the fly visual circuit.<br /> - The authors have complemented the work of Dombrovski et al by analyzing the distribution of synapses in more detail from EM data for a different set of neurons.

Weaknesses:

DNs are upstream of motorneurons, and one would expect, as demonstrated by Dombrovski et al, that specific DNs being activated by input from specific regions of the visual field will activate motoneurons so that the fly moves away from a looming object.

The current work analyzed the synapse distribution on two DNs that do not seem to have such role, and emphasize the lack of retinotopy. However, it is not clear why one would expect retinotopy in synapse location on the dendritic arbor. The comparison with mammalian visual circuits is not appropriate because those layers are extracting more and more complex visual features, whereas Drosophila DNs are supposed to drive motoneurons to generate suitable escape behavior.

- The authors do not suggest the functional roles of these DNs in controlling the movement of the fly. They argue that the synapse distribution and the passive electrotonic structure of these neurons are optimized to make the composite EPSP encode the number of activated synapses, but do not explain why this is important.

- Although DNs are spiking neurons, the authors limit their work to the subthreshold passive domain. If the EPSP at the spike initiation zone crosses spiking threshold, will encoding the number of synapses in EPSP amplitude still matter? Will it matter either if the composite EPSP remains subthreshold?

- The temporal aspect of the input has been ignored by the authors in their simulations. First, it is not clear all the synapses from a single VPN should get activated together. One would expect a spike in a VPN to arrive at different synapses with different time delays depending on their electrotonic distance from the spike initiation zone and the signal propagation speed in the neurites.

A looming stimulus should be expanding with time, but from the description of the simulations it does not seem that the authors have tried to incorporate this aspect in their design of the synaptic activation.

- The suggestion in the abstract that linear encoding of synapse number is default strategy which is then tuned by active properties and plasticity seems strange. Developmentally active properties do not get inserted into passive neurons.

- Much of the analysis (Figures 4, 5, 12) show relationships with physical distance along dendrite. In studying passive neurons it is more informative to use electrotonic distance which provides better insight.

Reviewer #1 (Public review):

In the manuscript entitled "A VgrG2b fragment cleaved by caspase-11/4 promotes Pseudomonas aeruginosa infection through suppressing the NLRP3 inflammasome", Qian et al. found an activation of the non-canonical inflammasome, but not the downstream NLRP3 inflammasome, during the infection of macrophage by P. aeruginosa, which is in sharp contrast to that by E. coli (Figure 1). In realizing that the suppression of the NLRP3 inflammasome is Caspase-11 dependent, the authors performed a screening among P. aeruginosa proteins and identified VgrG2b being a major substrate of Caspase-11 (Figure 2). Next, the authors mapped the cleavage site on VgrG2b to D883, and demonstrated that cleavage of VgrG2b by Caspase-11 is essential for the suppression of the NLRP3 inflammasome (Figure 3). Furthermore, they found that a binding between the C-terminal fragment of the cleaved VgrG2b and NLRP3 existed (Figure 4), which was then proved to block the association of NLRP3 with NEK7 (Figure 5). Finally, the authors demonstrated that blocking of VgrG2b cleavage, by either mutation of the D883 or administration of a designed peptide, effectively improved the survival rate of the P. aeruginosa-infected mice (Figure 6). This is a well-designed and executed study, with the results clearly presented and stated.

Reviewer #2 (Public review):

Summary:

In their manuscript, Quian and colleagues identified a novel mechanism by which Pseudomonas control inflammatory responses upon inflammasome activation. They identified a caspase-11 substrate (VgrG2b) which, upon cleavage, binds and inhibits the NLRP3 to reduce the production of pro-inflammatory cytokines. This is a unique mechanism that allows for the tailoring of the innate immune response upon bacterial recognition.

Strengths:

The authors are presenting here a novel conceptual framework in host-pathogen interactions. Their work is supported by a range of approaches (biochemical, cellular immunology, microbiology, animal models), and their conclusions are supported by multiple independent evidences. The work is likely to have an important impact on the innate immunity field and host-pathogen interactions field and may guide the development of novel inhibitors.

Weaknesses:

Although quite exhaustive, a few of the authors' conclusions are not fully supported (e.g., caspase-11 directly cleaving VgrG2b, the unique affinity of VgrG2b-C for NLRP3) and would require complementary approaches to validate their findings fully. This is minimal.

Reviewer #1 (Public review):

Summary:

Wang, Po-Kai, et al., utilized the de novo polarization of MDCK cells cultured in Matrigel to assess the interdependence between polarity protein localization, centrosome positioning, and apical membrane formation. They show that the inhibition of Plk4 with Centrinone does not prevent apical membrane formation, but does result in its delay, a phenotype the authors attribute to the loss of centrosomes due to the inhibition of centriole duplication. However, the targeted mutagenesis of specific centrosome proteins implicated in the positioning of centrosomes in other cell types (CEP164, ODF2, PCNT, and CEP120) did not affect centrosome positioning in 3D cultured MDCK cells. A screen of proteins previously implicated in MDCK polarization revealed that the polarity protein Par-3 was upstream of centrosome positioning, similar to other cell types.

Strengths:

The investigation into the temporal requirement and interdependence of previously proposed regulators of cell polarization and lumen formation is valuable to the community. Wang et al., have provided a detailed analysis of many of these components at defined stages of polarity establishment. Furthermore, the generation of PCNT, p53, ODF2, Cep120, and Cep164 knockout MDCK cell lines is likely valuable to the community.

Weaknesses:

Additional quantifications would highly improve this manuscript, for example it is unclear whether the centrosome perturbation affects gamma tubulin levels and therefore microtubule nucleation, it is also not clear how they affect the localization of the trafficking machinery/polarity proteins. For example, in Figure 4, the authors measure the intensity of Gp134 at the apical membrane initiation site following cytokinesis, but there is no measure of Gp134 at the centrosome prior to this.

Reviewer #2 (Public review):

Summary:

The authors decoupled several players that are thought to contribute to the establishment of epithelial polarity and determined their causal relationship. This provides a new picture of the respective roles of junctional proteins (Par3), the centrosome, and endomembrane compartments (Cdc42, Rab11, Gp135) from upstream to downstream.<br /> Their conclusions are based on live imaging of all players during the early steps of polarity establishment and on the knock-down of their expression in the simplest ever model of epithelial polarity: a cell doublet surrounded by ECM.

The position of the centrosome is often taken as a readout for the orientation of the cell polarity axis. There is a long-standing debate about the actual role of the centrosome in the establishment of this polarity axis. Here, using a minimal model of epithelial polarization, a doublet of daugthers MDCK cultured in Matrigel, the authors made several key observations that bring new light to our understanding of a mechanism that has been studied for many years without being fully explained:

(1) They showed that centriole can reach their polarized position without most of their microtubule-anchoring structures. These observations challenge the standard model according to which centrosomes are moved by the production and transmission of forces along microtubules.

(2) (However) they showed that epithelial polarity can be established in the absence of centriole.

(3) (Somehow more expectedly) they also showed that epithelial polarity can't be established in the absence of Par3.

(4) They found that most other polarity players that are transported through the cytoplasm in lipid vesicles, and finally fused to the basal or apical pole of epithelial cells, are moved along an axis which is defined by the position of centrosome and orientation of microtubules.

(5) Surprisingly, two non-daughters cells that were brought in contact (for 6h) could partially polarize by recruiting a few Par3 molecules but not the other polarity markers.

(6) Even more surprisingly, in the absence of ECM, Par 3 and centrosomes could move to their proper position close to the intercellular junction after cytokinesis but other polarity markers (at least GP135) localized to the opposite, non-adhesive, side. So the polarity of the centrosome-microtubule network could be dissociated from the localisation of GP135 (which was believed to be transported along this network).

Strengths:

(1) The simplicity and reproducibility of the system allow a very quantitative description of cell polarity and protein localisation.

(2) The experiments are quite straightforward, well-executed, and properly analyzed.

(3) The writing is clear and conclusions are convincing.

Weaknesses:

(1) The simplicity of the system may not capture some of the mechanisms involved in the establishment of cell polarity in more physiological conditions (fluid flow, electrical potential, ion gradients,...).

(2) The absence of centriole in centrinone-treated cells might not prevent the coalescence of centrosomal protein in a kind of MTOC which might still orient microtubules and intracellular traffic. How are microtubules organized in the absence of centriole? If they still form a radial array, the absence of a centriole at the center of it somehow does not conflict with classical views in the field.

(3) The mechanism is still far from clear and this study shines some light on our lack of understanding. Basic and key questions remain:<br /> a) How is the centrosome moved toward the Par3-rich pole? This is particularly difficult to answer if the mechanism does not imply the anchoring of MTs to the centriole or PCM.<br /> b) What happens during cytokinesis that organises Par3 and intercellular junction in a way that can't be achieved by simply bringing two cells together? In larger epithelia cells have neighbours that are not daughters, still, they can form tight junctions with Par3 which participates in the establishment of cell polarity as much as those that are closer to the cytokinetic bridge (as judged by the overall cell symmetry). Is the protocol of cell aggregation fully capturing the interaction mechanism of non-daughter cells?

Reviewer #3 (Public review):

Here, Wang et al. aim to clarify the role of the centrosome and conserved polarity regulators in apical membrane formation during the polarization of MDCK cells cultured in 3D. Through well-presented and rigorous studies, the authors focused on the emergence of polarity as a single MDCK cell divided in 3D culture to form a two-cell cyst with a nascent lumen. Focusing on these very initial stages, rather than in later large cyst formation as in most studies, is a real strength of this study. The authors found that conserved polarity regulators Gp135/podocalyxin, Crb3, Cdc42, and the recycling endosome component Rab11a all localize to the centrosome before localizing to the apical membrane initiation site (AMIS) following cytokinesis. This protein relocalization was concomitant with a repositioning of centrosomes towards the AMIS. In contrast, Par3, aPKC, and the junctional components E-cadherin and ZO1 localize directly to the AMIS without first localizing to the centrosome. Based on the timing of the localization of these proteins, these observational studies suggested that Par3 is upstream of centrosome repositioning towards the AMIS and that the centrosome might be required for delivery of apical/luminal proteins to the AMIS.

To test this hypothesis, the authors generated numerous new cell lines and/or employed pharmacological inhibitors to determine the hierarchy of localization among these components. They found that removal of the centrosome via centrinone treatment severely delayed and weakened the delivery of Gp135 to the AMIS and single lumen formation, although normal lumenogenesis was apparently rescued with time. This effect was not due to the presence of CEP164, ODF2, CEP120, or Pericentrin. Par3 depletion perturbed the repositioning of the centrosome towards the AMIS and the relocalization of the Gp135 and Rab11 to the AMIS, causing these proteins to get stuck at the centrosome. Finally, the authors culture the MDCK cells in several ways (forced aggregation and ECM depleted) to try and further uncouple localization of the pertinent components, finding that Par3 can localize to the cell-cell interface in the absence of cell division. Par3 localized to the edge of the cell-cell contacts in the absence of ECM and this localization was not sufficient to orient the centrosomes to this site, indicating the importance of other factors in centrosome recruitment.

Together, these data suggest a model where Par3 positions the centrosome at the AMIS and is required for the efficient transfer of more downstream polarity determinants (Gp135 and Rab11) to the apical membrane from the centrosome. The authors present solid and compelling data and are well-positioned to directly test this model with their existing system and tools. In particular, one obvious mechanism here is that centrosome-based microtubules help to efficiently direct the transport of molecules required to reinforce polarity and/or promote lumenogenesis. This model is not really explored by the authors except by Pericentrin and subdistal appendage depletion and the authors do not test whether these perturbations affect centrosomal microtubules. Exploring the role of microtubules in this process could considerably add to the mechanisms presented here. In its current state, this paper is a careful observation of the events of MCDK polarization and will fill a knowledge gap in this field. However, the mechanism could be significantly bolstered with existing tools, thereby elevating our understanding of how polarity emerges in this system.

Reviewer #1 (Public review):

Previous studies have highlighted some of these paracrine activities of Toxoplasma - and Rasogi et al (mBio, 2020) used a single cell sequencing approach of cells infected in vitro with the WT or MYR KO parasites - and one of their conclusions was that MYR-1 dependent paracrine activities counteract ROP-dependent processes. Similarly, Chen et al (JEM 2020) highlighted that a particular rhoptry protein (ROP16) could be injected into uninfected macrophages and move them to an anti-inflammatory state that might benefit the parasite.

There are caveats around immunity and as yet no insight into how this works. In Figure 2 there is a marked defect in the ability of the parasites to expand at day 2 and day 5. Together, these data sets suggest that this paracrine effect mediated by MYR-1 works early - well before the development of adaptive responses.

Reviewer #2 (Public review):

Summary:

In this manuscript by Torelli et al., the authors propose that the major function of MYR1 and MYR1-dependent secreted proteins is to contribute to parasite survival in a paracrine manner rather than to protect parasites from cell-autonomous immune response. The authors conclude that these paracrine effects rescue ∆MYR1 or knockouts of MYR1-dependent effectors within pooled in vivo CRISPR screens.

Strengths:

The authors raised a more general concern that pooled CRISPR screens (not only in Toxoplasma but also other microbes or cancers) would miss important genes by "paracrine masking effect". Although there is no doubt that pooled CRISPR screens (especially in vivo CRISPR screens) are powerful techniques, I think this topic could be of interest to those fields and researchers.

Weaknesses:

In this version, the reviewer is not entirely convinced of the 'paracrine masking effect' because the in vivo experiments should include appropriate controls (see major point 2).

(1) It is convincing that co-infection of WT and ∆MYR1 parasites could rescue the growth of ∆MYR1 in mice shown by in vivo luciferase imaging. Also, this is consistent with ∆MYR1 parasites showing no in vivo fitness defect in the in vivo CRISPR screens conducted by several groups. Meanwhile, it has been reported previously and shown in this manuscript that ∆MYR1 parasites have an in vitro growth defect; however, ∆MYR1 parasites show no in vitro fitness defect the in vitro pooled CRISPR screen. The authors show that the competition defect of ∆MYR1 parasites cannot be rescued by co-infection with WT parasites in Figure 1c, which might indicate that no paracrine rescue occurred in an in vitro environment. The authors seem not to mention these discrepancies between in vitro CRISPR screens and in vitro competition assays. Why do ∆MYR1 parasites possess neutral in vitro fitness scores in in vitro CRISPR screens? Could the authors describe a reasonable hypothesis?

(2) The authors developed a mixed infection assay with an inoculum containing a 20:80 ratio of ΔMYR1-Luc parasites with either WT parasites or ΔMYR1 mutants not expressing luciferase, showing that the in vivo growth defect of ∆MYR1 parasites is rescued by the presence of WT parasites. Since this experiment lacks appropriate controls, interpretation could be difficult. Is this phenomenon specific to MYR1? If a co-inoculum of ∆GRA12-Luc with either WT parasites or GRA12 parasites not expressing luciferase is included, the data could be appropriately interpreted.

(3) In the Discussion part, the authors argue that the rescue phenotype of mixed infection is not due to co-infection of host cells (lines 307-310). This data is important to support the authors' paracrine hypothesis and should be shown in the main figure.

(4) In the Discussion part, the authors assume that the rescue phenotype is the result of multiple MYR1-dependent effectors. I admit that this hypothesis could be possible since a recently published paper described the concerted action of numerous MYR1-dependent or independent effectors contributing to the hypermigration of infected cells (Ten Hoeve et al., mBio, 2024). I think this paragraph would be kind of overstated since the authors did not test any of the candidate effectors. Since the authors possess ∆IST parasites, they can test whether IST is involved in the "paracrine masking effect" or not to support their claim.

Reviewer #1 (Public review):

Hotinger et al. explore the population dynamics of Salmonella enterica serovar Typhimurium in mice using genetically tagged bacteria. In addition to physiological observations, pathology assessments, and CFU measurements, the study emphasizes quantifying host bottleneck sizes that limit Salmonella colonization and dissemination. The authors also investigate the genetic distances between bacterial populations at various infection sites within the host.

Initially, the study confirms that pretreatment with the antibiotic streptomycin before inoculation via orogastric gavage increases the bacterial burden in the gastrointestinal (GI) tract, leading to more severe symptoms and heightened fecal shedding of bacteria. This pretreatment also significantly reduces between-animal variation in bacterial burden and fecal shedding. The authors then calculate founding population sizes across different organs, discovering a severe bottleneck in the intestine, with founding populations reduced by approximately 10^6-fold compared to the inoculum size. Streptomycin pretreatment increases the founding population size and bacterial replication in the GI tract. Moreover, by calculating genetic distances between populations, the authors demonstrate that, in untreated mice, Salmonella populations within the GI tract are genetically dissimilar, suggesting limited exchange between colonization sites. In contrast, streptomycin pretreatment reduces genetic distances, indicating increased exchange.

In extraintestinal organs, the bacterial burden is generally not substantially increased by streptomycin pretreatment, with significant differences observed only in the mesenteric lymph nodes and bile. However, the founding population sizes in these organs are increased. By comparing genetic distances between organs, the authors provide evidence that subpopulations colonizing extraintestinal organs diverge early after infection from those in the GI tract. This hypothesis is further tested by measuring bacterial burden and founding population sizes in the liver and GI tract at 5 and 120 hours post-infection. Additionally, they compare orogastric gavage infection with the less injurious method of infection via drinking, finding similar results for CFUs, founding populations, and genetic distances. These results argue against injuries during gavage as a route of direct infection.

To bypass bottlenecks associated with the GI tract, the authors compare intravenous (IV) and intraperitoneal (IP) routes of infection. They find approximately a 10-fold increase in bacterial burden and founding population size in immune-rich organs with IV/IP routes compared to orogastric gavage in streptomycin-pretreated animals. This difference is interpreted as a result of "extra steps required to reach systemic organs."

While IP and IV routes yield similar results in immune-rich organs, IP infections lead to higher bacterial burdens in nearby sites, such as the pancreas, adipose tissue, and intraperitoneal wash, as well as somewhat increased founding population sizes. The authors correlate these findings with the presence of white lesions in adipose tissue. Genetic distance comparisons reveal that, apart from the spleen and liver, IP infections lead to genetically distinct populations in infected organs, whereas IV infections generally result in higher genetic similarity.

Finally, the authors investigate GI tract reseeding, identifying two distinct routes. They observe that the GI tracts of IP/IV-infected mice are colonized either by a clonal or a diversely tagged bacterial population. In clonally reseeded animals, the genetic distance within the GI tract is very low (often zero) compared to the bile population, which is predominantly clonal or pauciclonal. These animals also display pathological signs, such as cloudy/hardened bile and increased bacterial burden, leading the authors to conclude that the GI tract was reseeded by bacteria from the gallbladder bile. In contrast, animals reseeded by more complex bacterial populations show that bile contributes only a minor fraction of the tags. Given the large founding population size in these animals' GI tracts, which is larger than in orogastrically infected animals, the authors suggest a highly permissive second reseeding route, largely independent of bile. They speculate that this route may involve a reversal of known mechanisms that the pathogen uses to escape from the intestine.

The manuscript presents a substantial body of work that offers a meticulously detailed understanding of the population dynamics of S. Typhimurium in mice. It quantifies the processes shaping the within-host dynamics of this pathogen and provides new insights into its spread, including previously unrecognized dissemination routes. The methodology is appropriate and carefully executed, and the manuscript is well-written, clearly presented, and concise. The authors' conclusions are well-supported by experimental results and thoroughly discussed. This work underscores the power of using highly diverse barcoded pathogens to uncover the within-host population dynamics of infections and will likely inspire further investigations into the molecular mechanisms underlying the bottlenecks and dissemination routes described here.

Major point:

Substantial conclusions in the manuscript rely on genetic distance measurements using the Cavalli-Sforza chord distance. However, it is unclear whether these genetic distance measurements are independent of the founding population size. I would anticipate that in populations with larger founding population sizes, where the relative tag frequencies are closer to those in the inoculum, the genetic distances would appear smaller compared to populations with smaller founding sizes independent of their actual relatedness. This potential dependency could have implications for the interpretation of findings, such as those in Figures 2B and 2D, where antibiotic-pretreated animals consistently exhibit higher founding population sizes and smaller genetic distances compared to untreated animals.

Reviewer #2 (Public review):

In this paper, Hotinger et. al. propose an improved barcoded library system, called STAMPR, to study Salmonella population dynamics during infection. Using this system, the authors demonstrate significant diversity in the colonization of different Salmonella clones (defined by the presence of different barcodes) not only across different organs (liver, spleen, adipose tissues, pancreas, and gall bladder) but also within different compartments of the same gastrointestinal tissue. Additionally, this system revealed that microbiota competition is the major bottleneck in Salmonella intestinal colonization, which can be mitigated by streptomycin treatment. However, this has been demonstrated previously in numerous publications. They also show that there was minimal sharing between populations found in the intestine and those in the other organs. Upon IV and IP infection to bypass the intestinal bottleneck, they were able to demonstrate, using this library, that Salmonella can renter the intestine through two possible routes. One route is essentially the reverse path used to escape the gut, leading to a diverse intestinal population; while the other, through the bile, typically results in a clonal population. Although the authors showed that the STAMPR pipeline improved the ability to identify founder populations and their diversity within the same animal during infections, some of the conclusions appear speculative and not fully supported.

(1) It's particularly interesting how the authors, using this system, demonstrate the dominant role of the microbiota bottleneck in Salmonella colonization and how it is widened by antibiotic treatment (Figure 1). Additionally, the ability to track Salmonella reseeding of the gut from other organs starting with IV and IP injections of the pathogen provides a new tool to study population dynamics (Figure 5). However, I don't think it is possible to argue that the proximal and distal small intestine, Peyer's patches (PPs), cecum, colon, and feces have different founder populations for reasons other than stochastic variations. All the barcoded Salmonella clones have the same fitness and the fact that some are found or expanded in one region of the gastrointestinal tract rather than another likely results from random chance - such as being forced in a specific region of the gut for physical or spatial reasons-and subsequent expansion, rather than any inherent biological cause. For example, some bacteria may randomly adhere to the mucus, some may swim toward the epithelial layer, while others remain in the lumen; all will proliferate in those respective sites. In this way, different founder populations arise based on random localization during movement through the gastrointestinal tract, which is an observation, but it doesn't significantly contribute to understanding pathogen colonization dynamics or pathogenesis. Therefore, I would suggest placing less emphasis on describing these differences or better discussing this aspect, especially in the context of the gastrointestinal tract.

(2) I do think that STAMPR is useful for studying the dynamics of pathogen spread to organs where Salmonella likely resides intracellularly (Figure 3). The observation that the liver is colonized by an early intestinal population, which continues to proliferate at a steady rate throughout the infection, is very interesting and may be due to the unique nature of the organ compared to the mucosal environment. What is the biological relevance during infection? Do the authors observe the same pattern (Figures 3C and G) when normalizing the population data for the spleen and mesenteric lymph nodes (mLN)? If not, what do the authors think is driving this different distribution?

(3) Figure 6: Could the bile pathology be due to increased general bacterial translocation rather than Salmonella colonization specifically? Did the authors check for the presence of other bacteria (potentially also proliferating) in the bile? Do the authors know whether Salmonella's metabolic activity in the bile could be responsible for gallbladder pathology?

Reviewer #1 (Public review):

Summary:

The investigators in this study analyzed the dataset assembly from 540 Salmonella isolates, and those from 45 recent isolates from Zhejiang University of China. The analysis and comparison of the resistome and mobilome of these isolates identified a significantly higher rate of cross-region dissemination compared to localized propagation. This study highlights the key role of the resistome in driving the transition and evolutionary history of S. Gallinarum.

Strengths:

The isolates included in this study were from 16 countries in the past century (1920 to 2023). While the study uses S. Gallinarun as the prototype, the conclusion from this work will likely apply to other Salmonella serotypes and other pathogens.

Weaknesses:

While the isolates came from 16 countries, most strains in this study were originally from China.

Reviewer #2 (Public review):

Summary:

The authors sequence 45 new samples of S. Gallinarum, a commensal Salmonella found in chickens, which can sometimes cause disease. They combine these sequences with around 500 from public databases, determine the population structure of the pathogen, and coarse relationships of lineages with geography. The authors further investigate known anti-microbial genes found in these genomes, how they associate with each other, whether they have been horizontally transferred, and date the emergence of clades.

Strengths:

(1) It doesn't seem that much is known about this serovar, so publicly available new sequences from a high-burden region are a valuable addition to the literature.

(2) Combining these sequences with publicly available sequences is a good way to better contextualise any findings.

Weaknesses:

There are many issues with the genomic analysis that undermine the conclusions, the major ones I identified being:

(1) Recombination removal using gubbins was not presented fully anywhere. In this diversity of species, it is usually impossible to remove recombination in this way. A phylogeny with genetic scale and the gubbins results is needed. Critically, results on timing the emergence (fig2) depend on this, and cannot be trusted given the data presented.

(2) The use of BEAST was also only briefly presented, but is the basis of a major conclusion of the paper. Plot S3 (root-to-tip regression) is unconvincing as a basis of this data fitting a molecular clock model. We would need more information on this analysis, including convergence and credible intervals.

(3) Using a distance of 100 SNPs for a transmission is completely arbitrary. This would at least need to be justified in terms of the evolutionary rate and serial interval.

(4) The HGT definition is non-standard, and phylogeny (vertical inheritance) is not controlled for.<br /> The cited method:<br /> 'In this study, potentially recently transferred ARGs were defined as those with perfect identity (more than 99% nucleotide identity and 100% coverage) in distinct plasmids in distinct host bacteria using BLASTn (E-value {less than or equal to}10−5)'<br /> This clearly does not apply here, as the application of distinct hosts and plasmids cannot be used. Subsequent analysis using this method is likely invalid, and some of it (e.g. Figure 6c) is statistically very poor.

(5) Associations between lineages, resistome, mobilome, etc do not control for the effect of genetic background/phylogeny. So e.g. the claim 'the resistome also demonstrated a lineage-preferential distribution' is not well-supported.

(6) The invasiveness index is not well described, and the difference in means is not biologically convincing as although it appears significant, it is very small.

(7) 'In more detail, both the resistome and mobilome exhibited a steady decline until the 1980s, followed by a consistent increase from the 1980s to the 2010s. However, after the 2010s, a subsequent decrease was identified.'<br /> Where is the data/plot to support this? Is it a significant change? Is this due to sampling or phylogenetics?

(8) It is not clear what the burden of disease this pathogen causes in the population, or how significant it is to agricultural policy. The article claims to 'provide valuable insights for targeted policy interventions.', but no such interventions are described.

(9) The abstract mentions stepwise evolution as a main aim, but no results refer to this.

(10) The authors attribute changes in population dynamics to normalisation in China-EU relations and hen fever. However, even if the date is correct, this is not a strongly supported causal claim, as many other reasons are also possible (for example other industrial processes which may have changed during this period).

(11) No acknowledgment of potential undersampling outside of China is made, for example, 'Notably, all bvSP isolates from Asia were exclusively found in China, which can be manually divided into three distinct regions (southern, eastern, and northern).'. Perhaps we just haven't looked in other places?

(12) Many of the conclusions are highly speculative and not supported by the data.

(13) The figures are not always the best presentation of the data:<br /> a. Stacked bar plots in Figure 1 are hard to interpret, the total numbers need to be shown. Panel C conveys little information.<br /> b. Figure 4B: stacked bars are hard to read and do not show totals.<br /> c. Figure 5 has no obvious interpretation or significance.

In summary, the quality of analysis is poor and likely flawed (although there is not always enough information on methods present to confidently assess this or provide recommendations for how it might be improved). So, the stated conclusions are not supported.

Reviewer #1 (Public review):

Summary:

In the manuscript "Heat Shock Factor Regulation of Antimicrobial Peptides Expression Suggests a Conserved Defense Mechanism Induced by Febrile Temperature in Arthropods," Xiao and colleagues examine the role of the shrimp Litopenaeus vannamei HSF1 ortholog (LvHSF1) in the response to viral infection. The authors provide compelling support for their conclusions that the activation of LvHSF1 limits viral load at high temperatures. Specifically, the authors convincingly show that (i) LvHSF1 mRNA and protein are induced in response to viral infection at high temperatures, (ii) increased LvHSF1 levels can directly induce the expression of the nSWD (and directly or indirectly other antibacterial peptides, AMPs), (ii) nSWD's antimicrobial activities can limit viral load, and, (iv) LvHSF1 protects survival at high temperatures following virus infection. These data thus provide a model by which an increase in HSF1 levels limits viral load through the transcription of antimicrobial peptides and provides a rationale for the febrile response as a conserved response to viral infection.

Strengths:

The large body of careful time series experiments, tissue profiling, and validation of RNA-seq data is convincing. Several experimental methodologies are used to support the authors' conclusions that nSWD is an LvHSf1 target and increased LvHSF1 alone can explain increased levels of nSWD. Similar carefully conducted experiments also conclusively implicate nSWD protein in limiting WSSV viral loads.

Weaknesses:

Despite this compelling data regarding the protective role of HSF1 in the febrile response, what remains unexplained and complicates the authors' model is the observation that losing LvHSF1 at 'normal' temperatures of 25C is not detrimental to survival, even though viral loads increase and nSWD is likely still subject to LvHSF1 regulation. These observations suggest that WSSV infection may have other detrimental effects on the cell not reflected by viral load and that LvHSF1 may play additional roles in protecting the organism from these effects of WSSV infection, such as perhaps, perturbations to protein homeostasis. This is worth discussing, especially in light of the rather complicated roles of hormesis in protection from infection, the role of HSF1 in hormesis responses, and the findings from other groups that the authors discuss.

Reviewer #2 (Public review):

Temperature is a critical factor affecting the progression of viral diseases in vertebrates and invertebrates. In the current study, the authors investigate mechanisms by which high temperatures promote anti-viral resistance in shrimp. They show that high temperatures induce HSF1 expression, which in turn upregulates AMPs. The AMPs target viral envelope proteins and inhibit viral infection/replication. The authors confirm this process in drosophila and suggest that there may be a conserved mechanism of high-temperature mediated anti-viral response in arthropods. These findings will enhance our understanding of how high temperature improves resistance to viral infection in animals.

The conclusions of this paper are mostly well supported by data, but some aspects of data analysis need to be clarified and extended. Further investigation on how WSSV infection is affected by AMP would have strengthened the study.

Reviewer #3 (Public review):

In the manuscript titled "Heat Shock Factor Regulation of Antimicrobial Peptides Expression Suggests a Conserved Defense Mechanism Induced by Febrile Temperature in Arthropods", the authors investigate the role of heat shock factor 1 (HSF1) in regulating antimicrobial peptides (AMPs) in response to viral infections, particularly focusing on febrile temperatures. Using shrimp (Litopenaeus vannamei) and Drosophila S2 cells as models, this study shows that HSF1 induces the expression of AMPs, which in turn inhibit viral replication, offering insights into how febrile temperatures enhance immune responses. The study demonstrates that HSF1 binds to heat shock elements (HSE) in AMPs, suggesting a conserved antiviral defense mechanism in arthropods. The findings are informative for understanding innate immunity against viral infections, particularly in aquaculture. However the logical flow of the paper can be improved.

Reviewer #1 (Public review):

Summary:

Dr. Santamaria's group previously utilized antigen-specific nanomedicines to induce immune tolerance in treating autoimmune diseases. The success of this therapeutic strategy has been linked to expanded regulatory mechanisms, particularly the role of T-regulatory type-1 (TR1) cells. However, the differentiation program of TR1 cells remained largely unclear. Previous work from the authors suggested that TR1 cells originate from T follicular helper (TFH) cells. In the current study, the authors aimed to investigate the epigenetic mechanisms underlying the transdifferentiation of TFH cells into IL-10-producing TR1 cells. Specifically, they sought to determine whether this process involves extensive chromatin remodeling or is driven by pre-existing epigenetic modifications. Their goal was to understand the transcriptional and epigenetic changes facilitating this transition and to explore the potential therapeutic implications of manipulating this pathway.

The authors successfully demonstrated that the TFH-to-TR1 transdifferentiation process is driven by pre-existing epigenetic modifications rather than extensive new chromatin remodeling. The comprehensive transcriptional and epigenetic analyses provide robust evidence supporting their conclusions.

Strengths:

(1) The study employs a broad range of bulk and single-cell transcriptional and epigenetic tools, including RNA-seq, ATAC-seq, ChIP-seq, and DNA methylation analysis. This comprehensive approach provides a detailed examination of the epigenetic landscape during the TFH-to-TR1 transition.

(2) The use of high-throughput sequencing technologies and sophisticated bioinformatics analyses strengthens the foundation for the conclusions drawn.

(3) The data generated can serve as a valuable resource for the scientific community, offering insights into the epigenetic regulation of T cell plasticity.

(4) The findings have significant implications for developing new therapeutic strategies for autoimmune diseases, making the research highly relevant and impactful.

Weaknesses:

(1) While the study focuses on transcriptional and epigenetic analyses, the authors are currently undertaking efforts to validate these findings functionally. Ongoing research aims to further explore the roles of key transcription factors in the TFH-to-TR1 transition, reflecting the authors' commitment to building on the insights gained from this study.

(2) The identification of key transcription factors and epigenetic marks is a strong foundation for future work. The authors are actively investigating how these factors drive chromatin remodeling, which will enhance the mechanistic understanding of the TFH-to-TR1 process in future studies.

(3) Although the study provides a valuable snapshot of the epigenetic landscape, the authors are pursuing additional research to assess the dynamics of these changes over time. These ongoing efforts will contribute to a deeper understanding of the stability and progression of the observed epigenetic modifications.

Comments on revised version:

The authors have effectively discussed and addressed all previously raised questions. There are no further concerns.

Reviewer #2 (Public review):

Summary:

This study, based on their previous findings that TFH cells can be converted into TR1 cells, conducted a highly detailed and comprehensive epigenetic investigation to answer whether TR1 differentiation from TFH is driven by epigenetic changes. Their evidence indicated that the downregulation of TFH-related genes during the TFH to TR1 transition depends on chromatin closure, while the upregulation of TR1-related genes does not depend on epigenetic changes.

Strengths:

A significant advantage of their approach lies in its detailed and comprehensive assessment of epigenetics. Their analysis of epigenetics covers chromatin open regions, histone modifications, DNA methylation, and using both single-cell and bulk techniques to validate their findings. As for their results, observations from different epigenetic perspectives mutually supported each other, lending greater credibility to their conclusions. This study effectively demonstrates that 1. the TFH-to-TR1 differentiation process is associated with massive closure of OCRs, and 2. the TR1-poised epigenome of TFH cells is a key enabler of this transdifferentiation process. Considering the extensive changes in epigenetic patterns involved in other CD4+ T lineage commitment processes, the similarity between TFH and TR1 in their epigenetics is intriguing.

They performed correlation analysis to answer the association between "pMHC-NP-induced epigenetic change" and "gene expression change in TR1". Also, they have made their raw data publicly available, providing a comprehensive epigenomic database of pMHC-NP induced TR1 cells. This will serve as a valuable reference for future research.

Weaknesses:

A major limitation is that this study heavily relies on a premise from the previous studies performed by the same group on pMHC-NP-induced T cell responses. This significantly limits the relevance of their conclusion to a broader perspective. Specifically, differential OCRs between Tet+ and naïve T cells were limited to only 821, as compared to 10,919 differential OCRs between KLH-TFH and naïve T cells (Fig. 2A), indicating that the precursors and T cell clonotypes that responded to pMHC-NP were extremely limited. I acknowledge that this limitation has been added and discussed in the Discussion section of the revised manuscript.

Reviewer #1 (Public review):

Summary:

The authors have developed a valuable method based on a fully cell-free system to express a channel protein and integrated it into a membrane vesicle in order to characterize it biophysically. The study presents a useful alternative to study channels that are not amenable to be studied by more traditional methods.

Strengths:

The evidence supporting the claims of the authors is solid and convincing. The method will be of interest to researchers working on ionic channels, allowing to study a wide range of ion channel functions such as those involved in transport, interaction with lipids or pharmacology.

Weaknesses:

The inclusion of a mechanistic interpretation how the channel protein folds into a protomer or a tetramer to become functional into the membrane, would strengthen the study.

Comments on revised version:

In the revised version, the authors did not experimentally addressed how tetrameric or protomeric proteins are actually produced. However, they performed new experiments to assess the amount of tetramers that are being actually formed. They used a size-exclusion chromatography to conclude that the protomers and tetramers species of complexes are formed and assembled.

The authors have addressed most of my minor concerns and have modified or updated the manuscript following my recommendations, so I have no further comments.

Reviewer #2 (Public review):

It is challenging to study the biophysical properties of organelle channels using conventional electrophysiology. The conventional reconstitution methods requires multiple steps and can be contaminated by endogenous ionophores from the host cell lines after purification. To overcome this challenge, in this manuscript, Larmore et al. described a fully synthetic method to assay the functional properties of the TRPP channel family. The TRPP channels are an important organelle ion channel family that natively traffic to primary cilia and ER organelles. The authors utilized cell-free protein expression and reconstitution of the synthetic channel protein into giant unilamellar vesicles (GUV), the single channel properties can be measured using voltage-clamp electrophysiology. Using this innovative method, the authors characterized their membrane integration, orientation, and conductance, comparing the results to those of endogenous channels. The manuscript is well-written and may present broad interest to the ion channel community studying organelle ion channels. Particularly because of the challenges of patching native cilia cells, the functional characterization is highly concentrated in very few labs. This method may provide an alternative approach to investigate other channels resistant to biophysical analysis and pharmacological characterization.

Comments on revised version:

The authors have addressed my concerns. This excellent method manuscript would benefit the study of organelle channels.

Reviewer #1 (Public review):

In this paper, the authors show that disruption of calcineurin, which is encoded by tax-6 in C. elegans, results in increased susceptibility to P. aeruginosa but extends lifespan. In exploring the mechanisms involved, the authors show that disruption of tax-6 decreases the rate of defecation leading to intestinal accumulation of bacteria and distension of the intestinal lumen. The authors further show that the lifespan extension is dependent on hlh-30, which may be involved in breaking down lipids following deficits in defecation, and nhr-8, whose levels are increased by deficits in defecation. The authors propose a model in which disruption of the defecation motor program is responsible for the effect of calcineurin on pathogen susceptibility and lifespan, but do not exclude the possibility that calcineurin affects these phenotypes independently of defecation.

Reviewer #2 (Public review):

The relationships between genes and phenotypes are complex and the impact of deleting or a gene can often have multifaceted and unforeseen consequences. This paper dissected the role of calcineurin, encoded by tax-6, in various phenotypes in C. elegans, including lifespan, pathogen susceptibility, the defecation motor program, and nutrient absorption or calorie restriction, through a series of genetic and behavioral analyses. Many genes in these pathways were tested yielding robust results. Classic epistasis analyses were used to distinguish between genes operating in the same or separate pathways. Researchers in the related fields will be very interested in looking through the data presented in this paper in great detail and benefit from it.

Overall, this paper supports a model in which the increased lifespan and heightened pathogen susceptibility observed following calcineurin inhibition result from the disruptions in the defecation motor program but through distinct pathways. A defective defecation motor program leads to intestine bloating and compromised nutrient absorption. Calorie restriction resulting from poor nutrient absorption affects lifespan, whereas increased colonization in the bloated intestine heightens pathogen susceptibility. The observation that knockdown of several other DMP-related genes also results in increased lifespan and pathogen susceptibility further reinforces the proposed model.

Reviewer #1 (Public review):

The authors present the cryo-EM structure of PSI-fucoxanthin chlorophyll a/c-binding proteins (FCPs) supercomplex from the diatom Thalassiosira pseudonana CCMP1335 at a global resolution of 2.3 Å. This exceptional resolution allows the authors to construct a near-atomic model of the entire supercomplex and elucidate the molecular details of FCPs arrangement. The high-resolution structure reveals subunits not previously identified in earlier reconstructions and models, as well as sequence analysis of PSI-FCPIs from other diatoms and red algae. Additionally, the authors use their model in conjunction with a phylogenetic analysis to compare and contrast the structural features of the T. pseudonana supercomplex with those of Chaetoceros gracilis, uncovering key structural features that contribute to the efficiency of light energy conversion in diatoms.

The study employs the advanced technique of single particle cryo-electron microscopy to visualize the complex architecture of the PSI supercomplex at near-atomic resolution and analyze the specific roles of FCPs in enhancing photosynthetic performance in diatoms.

Overall, the approach and data are both compelling and of high quality. The paper is well written and will be of wide interest for comprehending the molecular mechanisms of photosynthesis in diatoms. This work provides valuable insights for applications in bioenergy, environmental conservation, plant physiology, and membrane protein structural biology.

Reviewer #1 (Public review):

Summary:

The authors aim at dissecting the relationship between hair-cell directional mechanosensation and orientation-linked synaptic selectivity, using mice and the zebrafish. They find that Gpr156 mutant animals homogenize the orientation of hair cells without affecting the selectivity of afferent neurons, suggesting that hair-cell orientation is not the feature that determines synaptic selectivity. Therefore, the process of Emx2-dependent synaptic selectivity bifurcates downstream of Gpr156.

Strengths:

This is an interesting and solid paper. It solves an interesting problem and establishes a framework for the following studies. That is, to ask what are the putative targets of Emx2 that affect synaptic selectivity.<br /> The quality of the data is generally excellent.

Weaknesses:

The feeling is that the advance derived from the results is very limited.

Comments on revised version:

I am happy with the authors' reply and do not wish to modify my initial assessment.

Reviewer #2 (Public Review):

Summary:

The authors inquire in particular whether the receptor Gpr156, which is necessary for hair cells to reverse their polarities in the zebrafish lateral line and mammalian otolith organs downstream of the differential expression of the transcription factor Emx2, also controls the mechanosensitive properties of hair cells and ultimately an animal's behavior. This study thoroughly addresses the issue by analyzing the morphology, electrophysiological responses, and afferent connections of hair cells found in different regions of the mammalian utricle and the Ca2+ responses of lateral line neuromasts in both wild-type animals and gpr156 mutants. Although many features of hair cell function are preserved in the mutants-such as development of the mechanosensory organs and the Emx2-dependent, polarity-specific afferent wiring and synaptic pairing-there are a few key changes. In the zebrafish neuromast, the magnitude of responses of all hair cells to water flow resembles that of the wild-type hair cells that respond to flow arriving from the tail. These responses are larger than those observed in hair cells that are sensitive to flow arriving from the head and resemble effects previously observed in Emx2 mutants. The authors note that this behavior suggests that the Emx2-GPR156 signaling axis also impinges on hair cell mechanotransduction. Although mutant mice exhibit normal posture and balance, they display defects in swimming behavior. Moreover, their vestibulo-ocular reflexes are perturbed. The authors note that the gpr156 mutant is a good model to study the role of opposing hair cell polarity in the vestibular system, for the wiring patterns follow the expression patterns of Emx2, even though hair cells are all of the same polarity. This paper excels at describing the effects of gpr156 perturbation in mouse and zebrafish models and will be of interest to those studying the vestibular system, hair cell polarity, and the role of inner-ear organs in animal behavior.

The study is exceptional in including, not only morphological and immunohistochemical indices of cellular identity but also electrophysiological properties. The mutant hair cells of murine maculæ display essentially normal mechanoelectrical transduction and adaptation-with two or even three kinetic components-as well as normal voltage-activated ionic currents.

Reviewer #1 (Public review):

Summary:

This work proposes a new method, DyNetCP, for inferring dynamic functional connectivity between neurons from spike data. DyNetCP is based on a neural network model with a two-stage model architecture of static and dynamic functional connectivity.<br /> This work evaluates the accuracy of the synaptic connectivity inference and shows that DyNetCP can infer the excitatory synaptic connectivity more accurately than a state-of-the-art model (GLMCC) by analyzing the simulated spike trains. Furthermore, it is shown that the inference results obtained by DyNetCP from large-scale in-vivo recordings are similar to the results obtained by the existing methods (jitter-corrected CCG and JPSTH). Finally, this work investigates the dynamic connectivity in the primary visual area VISp and in the visual areas using DyNetCP.

Strengths:

The strength of the paper is that it proposes a method to extract the dynamics of functional connectivity from spike trains of multiple neurons. The method is potentially useful for analyzing parallel spike trains in general, as there are only a few methods (e.g. Aertsen et al., J. Neurophysiol., 1989, Shimazaki et al., PLoS Comput Biol 2012) that infer the dynamic connectivity from spikes. Furthermore, the approach of DyNetCP is different from the existing methods: while the proposed method is based on the neural network, the previous methods are based on either the descriptive statistics (JSPH) or the Ising model.

Weaknesses:

Although the paper proposes a new method, DyNetCP, for inferring the dynamic functional connectivity, its strengths are neither clear nor directly demonstrated in this paper. That is, insufficient analyses are performed to support the usefulness of DyNetCP.<br /> First, this paper attempts to show the superiority of DyNetCP by comparing the performance of synaptic connectivity inference with GLMCC (Fig. 2). However, the improvement in the synaptic connectivity inference does not seem to be convincing. While this paper compares the performance of DyNetCP with a state-of-the-art method (GLMCC), there are several problems with the comparison. For example,

(1) It is unclear how accurately the proposed method can infer the dynamic connectivity.<br /> (2) This paper does not compare with existing approach (e.g., classical JPSTH: Aertsen et al., J. Neurophysiol., 1989, and other methods : Stevenson and Koerding, NIPS, 2011; Linderman et al., NIPS, 2014; Song et al., J. Neurosci. Methods, 2015), and<br /> (3) only a population of neurons generated from the Hodgkin-Huxley model was evaluated.

Thus, the results in this paper are not sufficient to conclude the superiority of DyNetCP in the estimation of synaptic connections. In addition, this paper compares the proposed method with the standard statistical methods Jitter-corrected CCG (Fig. 3) and JPSTH (Fig. 4). Unfortunately, these results do not show the superiority of the proposed method. It only shows that the results obtained by the proposed method are consistent with those obtained by the existing methods (CCG or JPSTH). This paper also compares the proposed method with the standard statistical methods, such as jitter-corrected CCG (Fig. 3) and JPSTH (Fig. 4). It only shows that the results obtained by the proposed method are consistent with those obtained by the existing methods (CCG or JPSTH), which does not show the superiority of the proposed method.

In summary, although DyNetCP has the potential to infer the dynamic (time-dependent) correlation more accurately than existing methods, the paper does not provide sufficient analysis to make this claim. It is also unclear whether the proposed method is superior to the existing methods for estimating functional connectivity, such as JPSTH and statistical approach (Stevenson and Koerding, NIPS, 2011; Linderman et al., NIPS, 2014). Thus, the strength of DyNetCP is unclear.

Reviewer #2 (Public review):

Summary:

Here the authors describe a model for tracking time-varying coupling between neurons from multi-electrode spike recordings. Their approach extends a GLM with static coupling between neurons to include dynamic weights, learned by a long-short-term-memory (LSTM) model. Each connection has a corresponding LSTM embedding and is read-out by a multi-layer perceptron to predict the time-varying weight.

Strengths:

This is an interesting approach to an open problem in neural data analysis. I think, in general, the method would be interesting to computational neuroscientists.

Weaknesses:

It is somewhat difficult to interpret what the model is doing. I think it would be worthwhile to add some additional results that make it more clear what types of patterns are being described and how.

Major Issues:

Simulation for dynamic connectivity. It certainly seems doable to simulate a recurrent spiking network whose weights change over time, and I think this would be a worthwhile validation for this DyNetCP model. In particular, I think it would be valuable to understand how much the model overfits, and how accurately it can track known changes in coupling strength. If the only goal is "smoothing" time-varying CCGs, there are much easier statistical methods to do this (c.f. McKenzie et al. Neuron, 2021. Ren, Wei, Ghanbari, Stevenson. J Neurosci, 2022), and simulations could be useful to illustrate what the model adds beyond smoothing.

Stimulus vs noise correlations. For studying correlations between neurons in sensory systems that are strongly driven by stimuli, it's common to use shuffling over trials to distinguish between stimulus correlations and "noise" correlations or putative synaptic connections. This would be a valuable comparison for Fig 5 to show if these are dynamic stimulus correlations or noise correlations. I would also suggest just plotting the CCGs calculated with a moving window to better illustrate how (and if) the dynamic weights differ from the data.

Minor Issues:

Introduction - it may be useful to mention that there have been some previous attempts to describe time-varying connectivity from spikes both with probabilistic models: Stevenson and Kording, Neurips (2011), Linderman, Stock, and Adams, Neurips (2014), Robinson, Berger, and Song, Neural Computation (2016), Wei and Stevenson, Neural Comp (2021) ... and with descriptive statistics: Fujisawa et al. Nat Neuroscience (2008), English et al. Neuron (2017), McKenzie et al. Neuron (2021).

In the sections "Static DyNetCP ...reproduce". It may be useful to have some additional context to interpret the CCG-DyNetCP correlations and CCG-GLMCC correlations (for simulation). If I understand right, these are on training data (not cross-validated) and the DyNetCP model is using NM+1 parameters to predict ~100 data points (It would also be good to say what N and M are for the results here). The GLMCC model has 2 or 3 parameters (if I remember right?).

In the section "Static connectivity inferred by the DyNetCP from in-vivo recordings is biologically interpretable"... I may have missed it, but how is the "functional delay" calculated? And am I understanding right that for the DyNetCP you are just using [w_i\toj, w_j\toi] in place of the CCG?

Reviewer #1 (Public review):

Summary:

In this work, authors utilize recurrent neural networks (RNNs) to explore the question of when and how neural dynamics and the network's output are related from a geometrical point of view. The authors found that RNNs operate between two extremes: an 'aligned' regime in which the weights and the largest PCs are strongly correlated and an 'oblique' regime where the output weights and the largest PCs are poorly correlated. Large output weights led to oblique dynamics, and small output weights to aligned dynamics. This feature impacts whether networks are robust to perturbation along output directions. Results were linked to experimental data by showing that these different regimes can be identified in neural recordings from several experiments.

Strengths:

Diverse set of relevant tasks<br /> Similarity measure well chosen<br /> Explored various hyperparameter settings

Weaknesses:

One of the major connections to found BCI data with neural variance aligned to the outputs. Maybe I was confused about something, but doesn't this have to be the case based on the design of the experiment? The outputs of the BCI are chosen to align with the largest principal components of the data.

Proposed experiments maybe have already been done (New neural activity patterns emerge with long-term learning, Oby et al. 2019). My understanding of these results is that activity moved to be aligned as the manifold changed, but more analyses could be done to more fully understand the relationship between those experiments and this work.

Analysis of networks was thorough, but connections to neural data were weak. I am thoroughly convinced of the reported effect of large or small output weights in networks. I also think this framing could aid in future studies of interactions between brain regions.

This is an interesting framing to consider the relationship between upstream activity and downstream outputs. As more labs record from several brain regions simultaneously, this work will provide an important theoretical framework for thinking about the relative geometries of neural representations between brain regions.

It will be interesting to compare the relationship between geometries of representations and neural dynamics across connected different brain areas that are closer to the periphery vs. more central.

Exciting to think about the versatility of the oblique regime for shared representations and network dynamics across different computations.

Versatility of oblique regime could lead to differences between subjects in neural data.

Reviewer #2 (Public review):

Summary:

This paper tackles the problem of understanding when the dynamics of neural population activity do and do not align with some target output, such as an arm movement. The authors develop a theoretical framework based on RNNs showing that an alignment of neural dynamics to an output can be simply controlled by the magnitude of the read-out weight vector while the RNN is being trained: small magnitude vectors result in aligned dynamics, where low-dimensional neural activity recapitulates the target; large magnitude vectors result in "oblique" dynamics, where encoding is spread across many dimensions. The paper further explores how the aligned and oblique regimes differ, in particular that the oblique regime allows degenerate solutions for the same target output.

Strengths:

- A really interesting new idea that different dynamics of neural circuits can arise simply from the initial magnitude of the output weight vector: once written out (Eq 3) it becomes obvious, which I take as the mark of a genuinely insightful idea

- The offered framework potentially unifies a collection of separate experimental results and ideas, largely from studies of motor cortex in primate: the idea that much of the ongoing dynamics do not encode movement parameters; the existence of the "null space" of preparatory activity; and that ongoing dynamics of motor cortex can rotate in the same direction even when the arm movement is rotating in opposite directions.

- The main text is well written, with a wide-ranging set of key results synthesised and illustrated well and concisely

- Shows the occurrence of the aligned and oblique regimes generalises across a range of simulated behavioural tasks

- A deep analytical investigation of when the regimes occur and how they evolve over training

- Shows where the oblique regime may be advantageous: allows multiple solutions to the same problem; and differs in sensitivity to perturbation and noise

- An insightful corollary result that noise in training is needed to obtain the oblique regime

- Tests whether the aligned and oblique regimes can be seen in neural recordings from primate cortex in a range of motor control tasks

- The revised text offers greater clarity and precision about when the aligned and oblique regimes occur and in the interpretation of the analyses of neural data

Weaknesses:

- The depth of analytical treatment in the Methods is impressive; however, the paper and the Methods analyses are largely independent, with the numerous results in the latter not being mentioned in the Results or Discussion. It in effect operates as two papers.

Reviewer #1 (Public review):

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

While the title of the manuscript is mostly supported by data of solid quality, many conclusions, as well as the final model, cannot be derived from the results presented. Importantly, the data do not support that GluA2 levels change upon TTX treatment in control cultures, rendering conclusions regarding Rab3A's role in TTX-dependent GluA2 modulation spurious. Other aspects of the model, such as a Rab3A-dependent release of a tropic factor, cannot be derived from the data.

The following points should be addressed:

(1) There is no (significant) increase in GluA2 levels (intensity, area, or integral) upon TTX treatment in controls (Fig. 5). Conclusions regarding Rab3As role in TTX-dependent GluA2 modulation should be revised accordingly. Hence, the data shown in Fig. 4 - 7 do not allow drawing conclusions in the context of Rab3A-dependent GluA2 modulation and scaling.

(2) The effects of Rab3A on TTX-induced mini frequency modulation remains unclear, because TTX does not induce a change in mini frequency in the Rab3A+/Ebd control (Fig. 2). The respective conclusions should be revised accordingly (l. 427).

(3) The model is still not supported by the data. In particular, data supporting a negative regulation of Rab3A by APs, Rab3A-dependent release of a tropic factor, or a Rab3A-dependent increase in GluA2 abundance are not presented.

(4) Data points are not overlapping and appear "quantal" in most box plots. How were the data rounded?

Reviewer #2 (Public review):

In the revised manuscript, the authors investigated the role of a presynaptic protein, Rab3A, in the homeostatic synaptic plasticity in cultured cortical neurons. The study was motivated by their previous findings that Rab3A is required for expression of similar homeostatic mechanisms at the neuromuscular junction. The authors first show that untreated WT neurons express homeostatic synaptic plasticity in response to 48h of TTX treatment (upregulation of both mEPSC amplitude and frequency), whereas neurons lacking Rab3A or carrying a dominant negative mutated Rab3A (earlybird) do not. They also demonstrate that only neuronal, but not glial Rab3A is responsible for this defect. Furthermore, they confirm the increased mEPSC amplitudes in WT neurons reflect the addition of GluA2-containing AMPA receptors rather than calcium-permeable ones, as previously reported by multiple labs. However, the increase in mEPSC amplitude is not accompanied by a corresponding upregulation of GluA2 synaptic clusters according to their IHC data (cluster size and intensity trend slightly upwards but not reaching significance). They further show that this modest upward trend is absent in Rab3A KO neurons, and conclude that Rab3A is involved in postsynaptic GluA2 upregulation during homeostatic synaptic plasticity.

When compared to the original version, the authors have done an admirable job in switching to more established ways to assess homeostatic synaptic plasticity by comparing the mean mEPSC amplitude and frequency, which has greatly improved the legibility of the manuscript to the public. Their data in Figures 1,2, and 8 clearly demonstrate that functional Rab3A in cortical neurons is required for the homeostatic regulation of mEPSCs.

However, the authors still have not provided further investigation of the mechanisms behind the role of Rab3A in this form of plasticity, and the revision therefore has added little to the significance of the study. Moreover, the experimental design for the investigation of the mismatch between mEPSC amplitude and GluA2 cluster fluorescence remains questionable, making it difficult to draw any credible conclusions from groups of data that not only look similar to the eye but also show no significance statistically.

A major claim the authors want to make is that Rab3A, although a presynaptic protein, regulates postsynaptic GluA2, and they do this by showing in Figure 5 that the upward trend of GluA2 cluster size and intensity is absent in Rab3A KO neurons. First, it is difficult to convince readers that this upward trend is real in Figures 5B-D without getting more samples. Second, the authors pick GluA2 clusters on the primary dendrites, whereas mEPSC events come from a much larger synapse population (e.g., more distal), therefore it makes sense that these two forms of measurement do not show matching changes, and this caveat could be addressed by sampling more diverse dendritic locations. Without a convincing phenotype in WT neurons, the support for this claim is weak.

Another claim of the authors is that this mismatch between mEPSC amplitude and GluA2 cluster sizes with the same culture suggests there are other factors contributing to the mEPSC amplitude. They do this by comparing results from individual culture dissociations, which greatly suffer from undersampling (Figure 6). In particular, they point out that 2 out of 3 dissociations show "matching" upward trends in mEPSC and GluA2 cluster (figure 6A and 6B) while the third one shows opposite trends, and use this to support their claim. Anyone who has done culture preparation would know the high variability between dissociations, which is why culture data are always pooled for assessment of any population trend. Anything could have happened to this particular dissociation (culture #3, figure 6C), and drawing conclusion from this single incident does little to support this claim. At least, they should double the dissociation numbers, and their claim would be much more convincing if a similar phenomenon occurs again. Besides, as mentioned above, all these mismatching trends could just be due to sampling differences.

In summary, this study establishes that neuronal Rab3A plays a role in homeostatic synaptic plasticity, but so do a number of other molecules that have been implicated in homeostatic synaptic plasticity in the past two decades (only will grow with the new techniques such as RNAseq). Without going beyond this finding and demonstrating how exactly Rab3A participates in the induction and/or expression of this form of plasticity, or maybe the potential Rab3A-mediated functional and behavioral defects in vivo, the contribution of the current study to the field is limited. However, given the presynaptic location of Rab3A, this finding could serve as a starting point for researchers interested in pre-postsynaptic cross-talk during homeostatic plasticity in general.

Reviewer #3 (Public review):

This manuscript presents a number of interesting findings that have the potential to increase our understanding of the mechanism underlying homeostatic synaptic plasticity (HSP). The data broadly support that Rab3A plays a role in HSP, although the site and mechanism of action remain uncertain.

The authors clearly demonstrate the Rab3A plays a role in HSP at excitatory synapses, with substantially less plasticity occurring in the Rab3A KO neurons. There is also no apparent HSP in the Earlybird Rab3A mutation, although baseline synaptic strength seems already elevated. In this context, it is unclear if the plasticity is absent or just occluded by a ceiling effect due the synapses already being strengthened. Occlusion may also occur in the mixed cultures, with Rab3A missing from neurons but not astrocytes. The authors do appropriately discuss both options. There are also differences in genetic background between the Rab3A KO and Earlybird mutants that could also impact the results, which are also noted. The authors have solid data showing that Rab3A is unlikely to be active in astrocytes, Finally, they attempt to study the linkage between synaptic strength during HSP and AMPA receptor trafficking and conclude that trafficking may not be solely responsible for the changes in synaptic strength.

Strengths:

This work adds another player into the mechanisms underlying an important form of synaptic plasticity. The plasticity is likely only reduced, suggesting Rab3A is only partially required and perhaps multiple mechanisms contribute. The authors speculate about some possible novel mechanisms.

However, the conclusions on the partial dissociation of AMPAR trafficking and synaptic response are made from somewhat weaker data. On average, across 3 culture sets, they saw similar magnitude of change in mEPSC amplitude and GluA2 cluster area and integral, but the GluA2 data was not significant. This is likely due to the nature of the datasets. Their imaging method involves only assessing puncta pairs (GluA2/VGlut1) clearly associated with a MAP2 labeled dendrite. This is a small subset of synapses, with usually less than 20 synapses per neuron analyzed (as stated by the authors). The mEPSC recordings will be averaging across several hundred events, which likely represent a hundred or more synapses given reasonable expectations on release probability. It has been reported, in work from this lab as well as by direct monitoring of tagged AMPARs during HSP (Wang, et al., 2019), that individual synapses are quite variable in their response. So there will almost necessarily be higher variability in the imaging data due to the smaller number of synapses sampled. The overall trends, though, are in alignment with previous data implicating receptor trafficking as the mechanism for HSP. However, the authors go on to evaluate each of the individual cultures, where 2 show similar changes between the mEPSC data and GluA2 clusters, and 1 culture showing little/no change in GluA2 clusters. The n's are very low here, and none of the datasets are significant. They want to conclude for this culture, there was a change in mEPSC amplitude that was not accompanied by a change in GluA2 at synaptic sites. But these data are collected from different coverslips, and due to the low n's, the potential under-sampling of the GluA2 clusters, and neuron-to-neuron variability, it is very hard to distinguish if this apparent difference is a methodological issue rather than a biological one. Much stronger data would be necessary to conclude that additional factors beyond receptor trafficking are required for HSP.

Other questions arise from the NASPM experiments, used to justify looking at GluA2 (and not GluA1) in the immunostaining. First, there is a frequency effect that is unclear in origin. One would expect NASPM to merely block some fraction of the post-synaptic current, and not affect pre-synaptic release or block whole synapses. However the change in frequency seems to argue (as the authors do) that some synapses only have CP-AMPARs, while the rest of the synapses have few or none. Another possibility is that there are pre-synaptic NASPM-sensitive receptors that influence release probability. Further, the amplitude data show a strong trend towards smaller amplitude following NASPM treatment (Fig 3B). The p value for both control and TTX neurons was 0.08 - it is very difficult to argue that there is no effect. The decrease on average is larger in the TTX neurons, and some cells show a strong effect. It is possible there is some heterogeneity between neurons on whether GluA1/A2 heteromers or GluA1 homomers are added during HSP. This would impact the weakly supported conclusions about the GluA2 imaging vs mEPSC amplitude data.

Unaddressed issues that would greatly increase the impact of the paper:

(1) Is Rab3A acting pre-synaptically, post-synaptically or both? The authors provide good evidence that Rab3A is acting within neurons and not astrocytes. But where it is acting (pre or post) would aid substantially in understanding its role. They could use sparse knock-down of Rab3A, or simply mix cultures from KO and WT mice (with appropriate tags/labels). The general view in the field has been that HSP is regulated post-synaptically via regulation of AMPAR trafficking, and considerable evidence supports this view. The more support for their suggestion of a pre-synaptic site of control, the better.

(2) Rab3A is also found at inhibitory synapses. It would be very informative to know if HSP at inhibitory synapses is similarly affected. This is particularly relevant as at inhibitory synapses, one expects a removal of GABARs (ie the opposite of whatever is happening at excitatory synapses). If both processes are regulated by Rab3A, this might suggest a role for this protein more upstream in the signaling; an effect only at excitatory synapses would argue for a more specific role just at these synapses.

Reviewer #1 (Public review):

Summary:

The authors conducted a study on one of the fundamental research topics in neuroscience: neural mechanisms of credit assignment. Building on the original studies of Walton and his colleagues and subsequent studies on the same topic, the authors extended the research into the delayed credit assignment problem with clever task design, which compared the non-delayed (direct) and delayed (indirect) credit assignment processes. Their primary goal was to elucidate the neural basis of these processes in humans, advancing our understanding beyond previous studies.

Strengths:

(1) Innovative task design distinguishing between direct and indirect credit assignment.

(2) Use of sophisticated multivariate pattern analysis to identify neural correlates of pending representations.

(3) Well-executed study with clear presentation of results.

(4) Extension of previous research to human subjects, providing valuable comparative insights.

Considerations for Future Research:

(1) The task design, while clear and effective, might be further developed to capture more real-world complexity in credit assignment.

(2) There's potential for deeper exploration of the role of task structure understanding in credit assignment processes.

(3) The interpretation of lateral orbitofrontal cortex (lOFC) involvement could be expanded to consider its role in both credit assignment and task structure representation.

Achievement of Aims and Support of Conclusions:

The authors successfully achieved their aim of investigating direct and indirect credit assignment processes in humans. Their results provide valuable insights into the neural representations involved in these processes. The study's conclusions are generally well-supported by the data, particularly in identifying neural correlates of pending representations crucial for delayed credit assignment.

Impact on the Field and Utility of Methods:

This study makes a significant contribution to the field of credit assignment research by bridging animal and human studies. The methods, particularly the multivariate pattern analysis approach, provide a robust template for future investigations in this area. The data generated offers valuable insights for researchers comparing human and animal models of credit assignment, as well as those studying the neural basis of decision-making and learning.

The study's focus on the lOFC and its role in credit assignment adds to our understanding of this brain region's function.

Additional Context and Future Directions:

(1) Temporal ambiguity in credit assignment: While the current design provides clear task conditions, future studies could explore more ambiguous scenarios to further reflect real-world complexity.

(2) Role of task structure understanding: The difference in task comprehension between human subjects in this study and animal subjects in previous studies offers an interesting point of comparison.

(3) The authors used a sophisticated method of multivariate pattern analysis to find the neural correlate of the pending representation of the previous choice, which will be used for the credit assignment process in the later trials. The authors tend to use expressions that these representations are maintained throughout this intervening period. However, the analysis period is specifically at the feedback period, which is irrelevant to the credit assignment of the immediately preceding choice. This task period can interfere with the ongoing credit assignment process. Thus, rather than the passive process of maintaining the information of the previous choice, the activity of this specific period can mean the active process of protecting the information from interfering and irrelevant information. It would be great if the authors could comment on this important interpretational issue.

(4) Broader neural involvement: While the focus on specific regions of interest (ROIs) provided clear results, future studies could benefit from a whole-brain analysis approach to provide a more comprehensive understanding of the neural networks involved in credit assignment.

Reviewer #2 (Public review):

Summary:

The present manuscript addresses a longstanding challenge in neuroscience: how the brain assigns credit for delayed outcomes, especially in real-world learning scenarios where decisions and outcomes are separated by time. The authors focus on the lateral orbitofrontal cortex and hippocampus, key regions involved in contingent learning. By integrating fMRI data and behavioral tasks, the authors examined how neural circuits maintain a causal link between past decisions and delayed outcomes. Their findings offer insights into mechanisms that could have critical implications for understanding human decision-making.

Strengths:

(1) The experimental designs were extremely well thought-out. The authors successfully coupled behavioral data and neural measures (through fMRI) to explore the neural mechanisms of contingent learning. This integration adds robustness to the findings and strengthens their relevance.

(2) The emphasis on the interaction between the lateral orbitofrontal cortex (lOFC) and hippocampus (HC) in this study is very well-targeted. The reported findings regarding their dynamic interactions provide valuable insights into contingent learning in humans.

(3) The use of an advanced modeling framework and analytical techniques allowed the authors to uncover new mechanistic insights regarding a complex case of the decision-making process. The methods developed will also benefit analyses of future neuroimaging data on a range of decision-making tasks as well.

Weaknesses:

Given the limited temporal resolution of fMRI and that the measured signal is an indirect measure of neural activity, it is unclear the extent to which the reported causality reflects the true relationship/interactions between neurons in different regions.

Reviewer #3 (Public review):

The authors apply multivoxel decoding analyses from fMRI during reward feedback about the cues previously chosen that led to that feedback. They compare two versions of the task - one in which the feedback is provided about the current trial, and one in which the feedback is provided about the previous trial. Reward probability changes slowly over time, so subjects need to identify which cues are leading to reward at a given time. They find that evidence for recall of the cue in the lateral orbitofrontal cortex (lOFC) and hippocampus (HC). They also find that in the second condition, where feedback is for the one-back trial, this representation is mediated by the lateral frontal pole (FPl).

Overall, the analyses are clean and elegant and seem to be complete. I have only a few comments.

(1) They do find (not surprisingly) that the one-back task is harder. It would be good to ensure that the reason that they had more trouble detecting direct HC & lOFC effects on the harder task was not because the task is harder and thus that there are more learning failures on the harder one-back task. (I suspect their explanation that it is mediated by FPl is likely to be correct. But it would be nice to do some subsampling of the zero-back task [matched to the success rate of the one-back task] to ensure that they still see the direct HC and lOFC there).

(2) The evidence that they present in the main text (Figure 3) that the HC and lOFC are mediated by FPl is a correlation. I found the evidence presented in Supplemental Figure 7 to be much more convincing. As I understand it, what they are showing in SF7 is that when FPl decodes the cue, then (and only then) HC and lOFC decode the cue. If my understanding is correct, then this is a much cleaner explanation for what is going on than the secondary correlation analysis. If my understanding here is incorrect, then they should provide a better explanation of what is going on so as to not confuse the reader.

(3) I like the idea of "credit spreading" across trials (Figure 1E). I think that credit spreading in each direction (into the past [lower left] and into the future [upper right]) is not equivalent. This can be seen in Figure 1D, where the two tasks show credit spreading differently. I think a lot more could be studied here. Does credit spreading in each of these directions decode in interesting ways in different places in the brain?

Reviewer #1 (Public review):

In this study, Deshmukh et al. provide an elegant illustration of Haldane's sieve, the population genetics concept stating that novel advantageous alleles are more likely to fix if dominant because dominant alleles are more readily exposed to selection. To achieve this, the authors rely on a uniquely suited study system, the female-polymorphic butterfly Papilio polytes.

Deshmukh et al. first reconstruct the chronology of allele evolution in the P. polytes species group, clearly establishing the non-mimetic cyrus allele as ancestral, followed by the origin of the mimetic allele polytes/theseus, via a previously characterized inversion of the dsx locus, and most recently, the origin of the romulus allele in the P. polytes lineage, after its split from P. javanus. The authors then examine the two crucial predictions of Haldane's sieve, using the three alleles of P. polytes (cyrus, polytes, and romulus). First, they report with compelling evidence that these alleles are sequentially dominant, or put in other words, novel adaptive alleles either are or quickly become dominant upon their origin. Second, the authors find a robust signature of positive selection at the dsx locus, across all five species that share the polytes allele.

In addition to exquisitely exemplifying Haldane's sieve, this study characterizes the genetic differences (or lack thereof) between mimetic alleles at the dsx locus. Remarkably, the polytes and romulus alleles are profoundly differentiated, despite their short divergence time (< 0.5 my), whereas the polytes and theseus alleles are indistinguishable across both coding and intronic sequences of dsx. Finally, the study reports incidental evidence of exon swaps between the polytes and romulus alleles. These exon swaps caused intermediate colour patterns and suggest that (rare) recombination might be a mechanism by which novel morphs evolve.

This study advances our understanding of the evolution of the mimicry polymorphism in Papilio butterflies. This is an important contribution to a system already at the forefront of research on the genetic and developmental basis of sex-specific phenotypic morphs, which are common in insects. More generally, the findings of this study have important implications for how we think about the molecular dynamics of adaptation. In particular, I found that finding extensive genetic divergence between the polytes and romulus alleles is striking, and it challenges the way I used to think about the evolution of this and other otherwise conserved developmental genes. I think that this study is also a great resource for teaching evolution. By linking classic population genetic theory to modern genomic methods, while using visually appealing traits (colour patterns), this study provides a simple yet compelling example to bring to a classroom.

In general, I think that the conclusions of the study, in terms of the evolutionary history of the locus, the dominance relationships between P. polytes alleles, and the inference of a selective sweep in spite of contemporary balancing selection, are strongly supported; the data set is impressive and the analyses are all rigorous. I nonetheless think that there are a few ways in which the current presentation of these data could lead to confusion, and should be clarified and potentially also expanded.

(1) The study is presented as addressing a paradox related to the evolution of phenotypic novelty in "highly constrained genetic architectures". If I understand correctly, these constraints are assumed to arise because the dsx inversion acts as a barrier to recombination. I agree that recombination in the mimicry locus is reduced and that recombination can be a source of phenotypic novelty. However, I'm not convinced that the presence of a structural variant necessarily constrains the potential evolution of novel discrete phenotypes. Instead, I'm having a hard time coming up with examples of discrete phenotypic polymorphisms that do not involve structural variants. If there is a paradox here, I think it should be more clearly justified, including an explanation of what a constrained genetic architecture means. I also think that the Discussion would be the place to return to this supposed paradox, and tell us exactly how the observations of exon swaps and the genetic characterization of the different mimicry alleles help resolve it.

(2) While Haldane's sieve is clearly demonstrated in the P. polytes lineage (with cyrus, polytes, and romulus alleles), there is another allele trio (cyrus, polytes, and theseus) for which Haldane's sieve could also be expected. However, the chronological order in which polytes and theseus evolved remains unresolved, precluding a similar investigation of sequential dominance. Likewise, the locus that differentiates polytes from theseus is unknown, so it's not currently feasible to identify a signature of positive selection shared by P. javanus and P. alphenor at this locus. I, therefore, think that it is premature to conclude that the evolution of these mimicry polymorphisms generally follows Haldane's sieve; of two allele trios, only one currently shows the expected pattern.

Reviewer #2 (Public review):

Summary:

Deshmukh and colleagues studied the evolution of mimetic morphs in the Papilio polytes species group. They investigate the timing of origin of haplotypes associated with different morphs, their dominance relationships, associations with different isoform expressions, and evidence for selection and recombination in the sequence data. P. polytes is a textbook example of a Batesian mimic, and this study provides important nuanced insights into its evolution, and will therefore be relevant to many evolutionary biologists. I find the results regarding dominance and the sequence of events generally convincing, but I have some concerns about the motivation and interpretation of some other analyses, particularly the tests for selection.

Strengths:

This study uses widespread sampling, large sample sizes from crossing experiments, and a wide range of data sources.

Weaknesses:

(1) Purpose and premise of selective sweep analysis

A major narrative of the paper is that new mimetic alleles have arisen and spread to high frequency, and their dominance over the pre-existing alleles is consistent with Haldane's sieve. It would therefore make sense to test for selective sweep signatures within each morph (and its corresponding dsx haplotype), rather than at the species level. This would allow a test of the prediction that those morphs that arose most recently would have the strongest sweep signatures.

Sweep signatures erode over time - see Figure 2 of Moest et al. 2020 (https://doi.org/10.1371/journal.pbio.3000597), and it is unclear whether we expect the signatures of the original sweeps of these haplotypes to still be detectable at all. Moest et al show that sweep signatures are completely eroded by 1N generations after the event, and probably not detectable much sooner than that, so assuming effective population sizes of these species of a few million, at what time scale can we expect to detect sweeps? If these putative sweeps are in fact more recent than the origin of the different morphs, perhaps they would more likely be associated with the refinement of mimicry, but not necessarily providing evidence for or against a Haldane's sieve process in the origin of the morphs.

(2) Selective sweep methods

A tool called RAiSD was used to detect signatures of selective sweeps, but this manuscript does not describe what signatures this tool considers (reduced diversity, skewed frequency spectrum, increased LD, all of the above?). Given the comment above, would this tool be sensitive to incomplete sweeps that affect only one morph in a species-level dataset? It is also not clear how RAiSD could identify signatures of selective sweeps at individual SNPs (line 206). Sweeps occur over tracts of the genome and it is often difficult to associate a sweep with a single gene.

(3) Episodic diversification

Very little information is provided about the Branch-site Unrestricted Statistical Test for Episodic Diversification (BUSTED) and Mixed Effects Model of Evolution (MEME), and what hypothesis the authors were testing by applying these methods. Although it is not mentioned in the manuscript, a quick search reveals that these are methods to study codon evolution along branches of a phylogeny. Without this information, it is difficult to understand the motivation for this analysis.

(4) GWAS for form romulus

The authors argue that the lack of SNP associations within dsx for form romulus is caused by poor read mapping in the inverted region itself (line 125). If this is true, we would expect strong association in the regions immediately outside the inversion. From Figure S3, there are four discrete peaks of association, and the location of dsx and the inversion are not indicated, so it is difficult to understand the authors' interpretation in light of this figure.

(5) Form theseus

Since there appears to be only one sequence available for form theseus (actually it is said to be "P. javanus f. polytes/theseus"), is it reasonable to conclude that "the dsx coding sequence of f. theseus was identical to that of f. polytes in both P. javanus and P. alphenor" (Line 151)? Looking at the Clarke and Sheppard (1972) paper cited in the statement that "f. polytes and f. theseus show equal dominance" (line 153), it seems to me that their definition of theseus is quite different from that here. Without addressing this discrepancy, the results are difficult to interpret.

Reviewer #1 (Public review):

Summary:

The authors compared four types of hiPSCs and four types of hESCs at the proteome level to determine their differences. Semiquantitative calculations of protein copy number revealed increased protein content in iPSCs. In particular, the results suggest that mitochondria- and cytoplasm-associated proteins in iPSCs reflect to some extent the state of the original differentiated cells. Basically, it contains responses to almost all comments and adds text mainly to the discussion. No additional experiments were performed in the revision, but I believe that future validation using methods other than proteomics would provide more support for the results.

Pros:

Mitochondrial function was verified by high-resolution respirometry, indicating increased ATP-producing capacity of the phosphorylation system in iPSCs.

Weaknesses:

The proteome data in this study may be the result of a simple examination of differences between the clones, and proteome data should be verified using various methods in the future.

Reviewer #2 (Public review):

Summary:

Pluripotent stem cells are powerful tools for understanding development, differentiation, and disease modeling. The capacity of stem cells to differentiate into various cell types holds great promise for therapeutic applications. However, ethical concerns restrict the use of human embryonic stem cells (hESCs). Consequently, induced human pluripotent stem cells (ihPSCs) offer an attractive alternative for modeling rare diseases, drug screening, and regenerative medicine. A comprehensive understanding of ihPSCs is crucial to establish their similarities and differences compared to hESCs. This work demonstrates systematic differences in the reprogramming of nuclear and non-nuclear proteomes in ihPSCs.

Strengths:

The authors employed quantitative mass spectrometry to compare protein expression differences between independently derived ihPSC and hESC cell lines. Qualitatively, protein expression profiles in ihPSC and hESC were found to be very similar. However, when comparing protein concentration at a cellular level, it became evident that ihPSCs express higher levels of proteins in the cytoplasm, mitochondria, and plasma membrane, while the expression of nuclear proteins is similar between ihPSCs and hESCs. A higher expression of proteins in ihPSCs was verified by an independent approach, and flow cytometry confirmed that ihPSCs had larger cell size than hESCs. The differences in protein expression were reflected in functional distinctions. For instance, the higher expression of mitochondrial metabolic enzymes, glutamine transporters, and lipid biosynthesis enzymes in ihPSCs was associated with enhanced mitochondrial potential, increased ability to uptake glutamine, and increased ability to form lipid droplets.

Weaknesses:

While this finding is intriguing and interesting, the study falls short of explaining the mechanistic reasons for the observed quantitative proteome differences. It remains unclear whether the increased expression of proteins in ihPSCs is due to enhanced transcription of the genes encoding this group of proteins or due to other reasons, for example, differences in mRNA translation efficiency. Another unresolved question pertains to how the cell type origin influences ihPSC proteomes. For instance, whether ihPSCs derived from fibroblasts, lymphocytes, and other cell types all exhibit differences in their cell size and increased expression of cytoplasmic and mitochondrial proteins. Analyzing ihPSCs derived from different cell types and by different investigators would be necessary to address these questions.

Reviewer #3 (Public review):

This study provides a useful insight into the proteomic analysis of several human induced pluripotent (hiPSC) and human embryonic stem cell (hESC) lines. Although the study is largely descriptive with limited validation of the differences found in the proteomic screen, the findings provide a solid platform for further mechanistic discovery.

Reviewer #1 (Public review):

The molecular interactions which determine infection (and disease) trajectory following human exposure to Mycobacterium tuberculosis (Mtb) are critical to understanding mycobacterial pathogenicity and tuberculosis (TB), a global public health threat which disproportionately impacts a number of high-burden countries and, owing to the emergence of multidrug-resistant Mtb strains, is a major contributor to antimicrobial resistance (AMR). In this submission, Qin and colleagues extend their own previous work which identified a potential role for host galectin-9 in recognizing the major Mtb cell wall component, arabinogalactan (AG). First, the authors present data indicating that galectin-9 inhibits mycobacterial growth during in vitro culture in liquid and on solid media, and that the inhibition depends on carbohydrate recognition by galectin-9. Next, the authors identify anti-AG antibodies in sera of TB patients and use this observation to inform isolation of monoclonal anti-AG antibodies (mAbs) via an in vitro screen. Finally, they apply the identified anti-AG mAbs to inhibit Mtb growth in vitro via a mechanism which proteomic and microscopic analyses suggest is dependent on disruption of cell wall structure. In summary, the dual observation of (i) the apparent role of naturally arising host anti-AG antibodies to control infection and (ii) the potential utility of anti-AG monoclonal antibodies as novel anti-Mtb therapeutics is compelling; however, as noted in the comments below, the evidence presented to support these insights is not adequate and the authors should address the following:

(1) The experiment which utilizes lactose or glucose supplementation to infer the importance of carbohydrate recognition by galectin-9 cannot be interpreted unequivocally owing to the growth-enhancing effect of lactose supplementation on Mtb during liquid culture in vitro.

(2) Similar to the comment above, the apparent dose-independent effect of galectin-9 on Mtb growth in vitro is difficult to reconcile with the interpretation that galectin is functioning as claimed.

(3) The claimed differences in galectin-9 concentration in sera from tuberculin skin test (TST)-negative or TST-positive non-TB cases versus active TB patients are not immediately apparent from the data presented.

(4) Neither fluorescence microscopy nor electron microscopy analyses are supported by high-quality, interpretable images which, in the absence of supporting quantitative data, renders any claims of anti-AG mAb specificity (fluorescence microscopy) or putative mAb-mediated cell wall swelling (electron microscopy) highly speculative.

(5) Finally, the absence of any discussion of how anti-AG antibodies (similarly, galectin-9) gain access to the AG layer in the outer membrane of intact Mtb bacilli (which may additionally possess an extracellular capsule/coat) is a critical omission - situating these results in the context of current knowledge about Mtb cellular structure (especially the mycobacterial outer membrane) is essential for plausibility of the inferred galectin-9 and anti-AG mAb activities.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors work to extend their previous observation that galectin-9 interacts with arabinogalactans of Mtb in their EMBO reports 2021 manuscript. Here they provide evidence for the CARD2 domain of galectin-9 can inhibit the growth of Mtb in culture. In addition, antibodies that also bind to AG appear to inhibit Mtb growth in culture. These data indicate that independent of the common cell-associated responses to galectin-9 and antibodies, interaction of these proteins with AG of mycobacteria may have consequences for bacterial growth.

Strengths:

The authors provided several lines of evidence in culture media that the introduction of galectin-9 proteins and antibodies inhibit the growth rate of Mtb.

Weaknesses:

The methodology for generating and screening the anti-AG antibodies lacks pertinent details for recapitulating and interpreting the results.

The figure legends and methods associated with the microscopy assays lack sufficient details to appropriately interpret the experiments conducted.

The galectin-9 measured in the sera of TB patients does not approach the concentrations required for Mtb growth restriction in the in vitro assays performed by the authors. It remains difficult to envision how greater levels of galectin-9 release might contribute to Mtb control in severe forms of TB, since higher levels of serum Gal9 has been observed in other human studies and correlate with poorly controlled infection. The authors over-interpret the role of Gal9 in bacterial control during disease/infection without any evidence of impact on in vivo (animal model) control.

Reviewer #1 (Public review):

Summary:

This paper investigates the relationship between ocular drift - eye movements long thought to be random - and visual acuity. This is a fundamental issue for how vision works. The work uses adaptive optics retinal imaging to monitor eye movements and where a target object is in the cone photoreceptor array. The surprising result is that ocular drift is systematic - causing the object to move to the center of the cone mosaic over the course of each perceptual trial. The tools used to reach this conclusion are state-of-the-art and the evidence presented is convincing.

Strengths

The central question of the paper is interesting, as far as I know, it has not been answered in past work, and the approaches employed in this work are appropriate and provide clear answers.

The central finding - that ocular drift is not a completely random process - is important and has a broad impact on how we think about the relationship between eye movements and visual perception.

The presentation is quite nice: the figures clearly illustrate key points and have a nice mix of primary and analyzed data, and the writing (with one important exception) is generally clear.

Weaknesses

The primary concern I had about the previous version of the manuscript was how the Nyquist limit was described. The changes the authors made have improved this substantially in the current version.

Reviewer #2 (Public review):

Summary:

In this work, Witten et al. assess visual acuity, cone density, and fixational behavior in the central foveal region in a large number of subjects.<br /> This work elegantly presents a number of important findings, and I can see this becoming a landmark work in the field. First, it shows that acuity is determined by the cone mosaic, hence, subjects characterized by higher cone densities show higher acuity in diffraction limited settings. Second, it shows that humans can achieve higher visual resolution than what is dictated by cone sampling, suggesting that this is likely the result of fixational drift, which constantly moves the stimuli over the cone mosaic. Third, the study reports a correlation between the amplitude of fixational motion and acuity, namely, subjects with smaller drifts have higher acuities and higher cone density. Fourth, it is shown that humans tend to move the fixated object toward the region of higher cone density in the retina, lending further support to the idea that drift is not a random process, but is likely controlled. This is a beautiful and unique work that furthers our understanding of the visuomotor system and the interplay of anatomy, oculomotor behavior, and visual acuity.

Strengths:

The work is rigorously conducted, it uses state-of-the-art technology to record fixational eye movements while imaging the central fovea at high resolution, and examines exactly where the viewed stimulus falls on individuals' foveal cone mosaic with respect to different anatomical landmarks in this region. Figures are clear and nicely packaged. It is important to emphasize that this study is a real tour-de-force in which the authors collected a massive amount of data on 20 subjects. This is particularly remarkable considering how challenging it is to run psychophysics experiments using this sophisticated technology. Most of the studies using psychophysics with AO are, indeed, limited to a few subjects. Therefore, this work shows a unique set of data, filling a gap in the literature.

Weaknesses:

Data analysis has been improved after the first round of review. The revised version of the manuscript is solid, and there are no weaknesses that should be addressed. The authors added more statistical tests and analyses, reported comparable effects even when different metrics are used (e.g., diffusion constant), and removed the confusing text on myopia. I think this work represents a significant scientific contribution to vision science.

Reviewer #3 (Public review):

Summary:

The manuscript by Witten et al., aims to investigate the link between acuity thresholds (and hyperacuity) and retinal sampling. Specifically, using in vivo foveal cone-resolved imaging and simultaneous microscopic photo stimulation, the researchers examined visual acuity thresholds in 16 volunteers and correlated them with each individual's retinal sampling capacity and the characteristics of ocular drift.

First, the authors found that although visual acuity was highly correlated with the individual spatial arrangement of cones, for all participants, visual resolution exceeded the Nyquist sampling.

Thus, the researchers hypothesized that this increase in acuity, which could not be explained in terms of spatial encoding mechanisms, might result from exploiting the spatiotemporal characteristics of the visual input associated with the dynamics of the fixational eye movements (and ocular drift in particular).

The authors reported a correlation between acuity threshold and drift amplitude, suggesting that the visual system benefits from transforming spatial input into a spatiotemporal flow. Finally, they showed that drift, contrary to the traditional view of it as random involuntary movement, appears to exhibit directionality: drift tends to move stimuli to higher cone density areas, therefore enhancing visual resolution.

I find the work of broad interest, its methods are clear, and the results solid.

Reviewer #1 (Public review):

In this study, Rosenblum et al introduce a novel and automatic way of calculating sleep cycles from human EEG. Previous results have shown that the slope of the non-oscillatory component of the power spectrum (called the aperiodic or fractal component) changes with sleep stage. Building on this, the authors present an algorithm that extracts the continuous-time fluctuations in the fractal slope and propose that peaks in this variable can be used to identify sleep cycle limits. Cycles defined in this way are termed "fractal cycles". The main focus of the article is a comparison of "fractal" and "classical" (ie defined manually based on the hypnogram) sleep cycles in numerous datasets.

The manuscript amply illustrates through examples the strong overlap between fractal and classical cycle identification. Accordingly, a high percentage (81%) can be matched one-to-one between methods and sleep cycle duration is well correlated (around R = 0.5). Moreover, the methods track certain global changes in sleep structure in different populations: shorter cycles in children and longer cycles in patients medicated with REM-suppressing anti-depressants. Finally, a major strength of the results is that they show similar agreement between fractal and classical sleep cycle length in 5 different data sets, showing that it is robust to changes in recording settings and methods.

The match between fractal and classical cycles is not one-to-one. For example, the fractal method identifies a correlation between age and cycle duration in adults that is not apparent with the classical method.<br /> The difference between the fractal and classical methods appear to be linked to the uncertain definition of sleep cycles since they are tied to when exactly the cycle begins/ends and whether or not to count cycles during fractured sleep architecture at sleep onset. Moreover, the discrepancies between the two are on the order of that found between classical cycles defined manually or via an automatic algorithm.

Overall the fractal cycle is an attractive method to study sleep architecture since it dispenses with time-consuming and potentially subjective manual identification of sleep cycles. However, given its difference from the classical method, it is unlikely that fractal scoring will be able to replace classical scoring directly. By providing a complementary quantification, it will likely contribute to refining the definition of sleep cycles that is currently ambiguous in certain cases. Moreover, it has the potential to be applied to animal studies which rarely deal with sleep cycle structure.

Reviewer #2 (Public review):

Summary:

This study focused on using strictly the slope of the power spectral density (PSD) to perform automated sleep scoring and evaluation of the durations of sleep cycles. The method appears to work well because the slope of the PSD is highest during slow-wave sleep, and lowest during waking and REM sleep. Therefore, when smoothed and analyzed across time,there are cyclical variations in the slope of the PSD, fit using an IRASA (Irregularly resampled auto-spectral analysis) algorithm proposed by Wen & Liu (2016).

Strengths:

The main novelty of the study is that the non-fractal (oscillatory) components of the PSD that are more typically used during sleep scoring can be essentially ignored because the key information is already contained within the fractal (slope) component. The authors show that for the most part, results are fairly consistent between this and conventional sleep scoring, but in some cases show disagreements that may be scientifically interesting.

Weaknesses:

The previous weaknesses were well-addressed by the authors in the revised manuscript. I will note that from the fractal cycle perspective, waking and REM sleep are not very dissimilar. Combining these states underlies some of the key results of this study.

Reviewer #1 (Public review):

Summary:

Liu and colleagues applied the hidden Markov model on fMRI to show three brain states underlying speech comprehension. Many interesting findings were presented: brain state dynamics were related to various speech and semantic properties, timely expression of brain states (rather than their occurrence probabilities) was correlated with better comprehension, and the estimated brain states were specific to speech comprehension but not at rest or when listening to non-comprehensible speech.

Strengths:

Recently, the HMM has been applied to many fMRI studies, including movie watching and rest. The authors cleverly used the HMM to test the external/linguistic/internal processing theory that was suggested in comprehension literature. I appreciated the way the authors theoretically grounded their hypotheses and reviewed relevant papers that used the HMM on other naturalistic datasets. The manuscript was well written, the analyses were sound, and the results had clear implications.

Weaknesses:

Further details are needed for the experimental procedure, adjustments needed for statistics/analyses, and the interpretation/rationale is needed for the results.

Reviewer #2 (Public review):

Liu et al. applied hidden Markov models (HMM) to fMRI data from 64 participants listening to audio stories. The authors identified three brain states, characterized by specific patterns of activity and connectivity, that the brain transitions between during story listening. Drawing on a theoretical framework proposed by Berwick et al. (TICS 2023), the authors interpret these states as corresponding to external sensory-motor processing (State 1), lexical processing (State 2), and internal mental representations (State 3). States 1 and 3 were more likely to transition to State 2 than between one another, suggesting that State 2 acts as a transition hub between states. Participants whose brain state trajectories closely matched those of an individual with high comprehension scores tended to have higher comprehension scores themselves, suggesting that optimal transitions between brain states facilitated narrative comprehension.

Overall, the conclusions of the paper are well-supported by the data. Several recent studies (e.g., Song, Shim, and Rosenberg, eLife, 2023) have found that the brain transitions between a small number of states; however, the functional role of these states remains under-explored. An important contribution of this paper is that it relates the expression of brain states to specific features of the stimulus in a manner that is consistent with theoretical predictions.

(1) It is worth noting, however, that the correlation between narrative features and brain state expression (as shown in Figure 3) is relatively low (~0.03). Additionally, it was unclear if the temporal correlation of the brain state expression was considered when generating the null distribution. It would be helpful to clarify whether the brain state expression time courses were circularly shifted when generating the null.

(2) A strength of the paper is that the authors repeated the HMM analyses across different tasks (Figure 5) and an independent dataset (Figure S3) and found that the data was consistently best fit by 3 brain states. However, it was not entirely clear to me how well the 3 states identified in these other analyses matched the brain states reported in the main analyses. In particular, the confusion matrices shown in Figure 5 and Figure S3 suggests that that states were confusable across studies (State 2 vs. State 3 in Fig. 5A and S3A, State 1 vs. State 2 in Figure 5B). I don't think this takes away from the main results, but it does call into question the generalizability of the brain states across tasks and populations.

(3) The three states identified in the manuscript correspond rather well to areas with short, medium, and long temporal timescales (see Hasson, Chen & Honey, TiCs, 2015). Given the relationship with behavior, where State 1 responds to acoustic properties, State 2 responds to word-level properties, and State 3 responds to clause-level properties, the authors may want to consider a "single-process" account where the states differ in terms of the temporal window for which one needs to integrate information over, rather than a multi-process account where the states correspond to distinct processes.

Joint Public Review:

Summary:

The study by Akita B. Jaykumar et al. explores an interesting and relevant hypothesis whether serine/threonine With-No-lysine (K) kinases (WNK)-1, -2, -3, and -4 engage in insulin-dependent glucose transporter-4 (GLUT4) signaling in the murine central nervous system. The authors especially focused on the hippocampus as this brain region exhibits high expression of insulin and GLUT4. Additionally, disrupted glucose metabolism in the hippocampus has been associated with anxiety disorders, while impaired WNK signaling has been linked to hypertension, learning disabilities, psychiatric disorders, or Alzheimer's disease. The study took advantage of selective pan-WNK inhibitor WNK 643 as the main tool to manipulate WNK 1-4 activity both in vivo by daily, per-oral drug administration to wild-type mice, and in vitro by treating either adult murine brain synaptosomes, hippocampal slices, primary cortical cultures, and human cell lines (HEK293, SH-SY5Y). Using a battery of standard behavior paradigms such as open field test, elevated plus maze test, and fear conditioning, the authors convincingly demonstrate that the inhibition of WNK1-4 results in behavior changes, especially in enhanced learning and memory of WNK643-treated mice. To shed light on the underlying molecular mechanism, the authors implemented multiple biochemical approaches including immunoprecipitation, glucose-uptake assay, surface biotylination assay, immunoblotting, and immunofluorescence. The data suggest that simultaneous insulin stimulation and WNK1-4 inhibition results in increased glucose uptake and the activity of insulin's downstream effectors, phosphorylated Akt and phosphorylated AS160. Moreover, the authors demonstrate that insulin treatment enhances the physical interaction of the WNK effector OSR1/SPAK with Akt substrate AS160. As a result, combined treatment with insulin and the WNK643 inhibitor synergistically increases the targeting of GLUT4 to the plasma membrane. Collectively, these data strongly support the initial hypothesis that neuronal insulin- and WNK-dependent pathways do interact and engage in cognitive functions.

Strengths:

The insulin-dependent signaling in the central nervous system is relatively understudied. This explorative study delves into several interesting and clinically relevant possibilities, examining how insulin-dependent signaling and its crosstalk with WNK kinases might affect brain circuits involved in memory formation and/or anxiety. Therefore, these findings might inspire follow-up studies performed in disease models for disorders that exhibit impaired glucose metabolism, deficient memory, or anxiety, such as Diabetes mellitus, Alzheimer's disease, or most psychiatric disorders.

The graphical presentation of the figures is of high quality, which helps the reader to obtain a good overview and easily understand the experimental design, results, and conclusions.

The behavioral studies are well conducted and provide valuable insights into the role of WNK kinases in glucose metabolism and their effect on learning and memory. Additionally, the authors evaluate the levels of basal and induced anxiety in Figures 1 and 2, enhancing our understanding of how WNK signaling might engage in cognitive function and anxiety-like behavior, particularly in the context of altered glucose metabolism.

Weaknesses:

The study used a WNK643 inhibitor as the only tool to manipulate WNK1-4 activity. This inhibitor seems selective; however, it has been reported that it exhibits different efficiency in inhibiting the individual WNK kinases among each other (e.g. PMID: 31017050, PMID: 36712947). Additionally, the authors do not analyze nor report the expression profiles or activity levels of WNK1, WNK2, WNK3, and WNK4 within the relevant brain regions (i.e. hippocampus, cortex, amygdala). Combined, these weaknesses raise concerns about the direct involvement of WNK kinases within the selected brain regions and behavior circuits. It would be beneficial if the authors provided gene profiling for WNK1, 2, 3, and -4 (e.g. using Allen brain atlas). To confirm the observations, the authors should either add results from using other WNK inhibitors or, preferentially, analyze knock-down or knock-out animals/tissue targeting the single kinases.

The authors do not report any data on whether the global inhibition of WNKs affects insulin levels. Since the authors wish to demonstrate the synergistic effect of simultaneous insulin treatment and WNK1-4 inhibition, such data are missing.

The study discovered that the Sortilin receptor binds to OSR1, leading the authors to speculate that Sortilin may be involved in the insulin-dependent GLUT4 surface trafficking. However, the authors do not provide any evidence supporting Sortilin's involvement in insulin- or WNK-dependent GLUT4 trafficking. Thus, this conclusion should be qualified, rephrased, or additional data included.

Reviewer #1 (Public review):

Summary:

This paper examines plasticity in early cortical (V1-V3) areas in an impressively large number of rod monochromats (individuals with achromatopia). The paper examines three things:

(1) Cortical thickness. It is now well established that early complete blindness leads to increases in cortical thickness. This paper shows increased thickness confined to the foveal projection zone within achromats. This paper replicates the work by Molz (2022) and Lowndes (2021), but the detailed mapping of cortical thickness as a function of eccentricity and the inclusion of higher visual areas is particularly elegant.

(2) Failure to show largescale reorganization of early visual areas using retinotopic mapping. This is a replication of a very recent study by Molz et al. but I believe, given anatomical variability (and the very large n in this study) and how susceptible pRF findings are to small changes in procedure, this replication is also of interest.

(3) Connective field modelling, examining the connections between V3-V1. The paper finds changes in the pattern of connections, and smaller connective fields in individuals with achromatopsia than normally sighted controls, and suggests that these reflect compensatory plasticity, with V3 compensating for the lower resolution V1 signal in individuals with achromatopsia.

Strengths:

This is a carefully done study (both in terms of data collection and analysis) that is an impressive amount of work. I have a number of methodological comments but I hope they will be considered as constructive engagement - this work is highly technical with a large number of factors to consider.

Weaknesses:

(1) Effects of eye-movements

I have some concerns with how the effects of eye-movements are being examined. There are two main reasons the authors give for excluding eye-movements as a factor in their results. Both explanations have limitations.

a) The first is that R2 values are similar across groups in the foveal confluence. This is fine as far as it goes, but R2 values are going to be low in that region. So this shows that eye-movements don't affect coverage (the number of voxels that generate a reliable pRF), but doesn't show that eye-movements aren't impacting their other measures.

b) The authors don't see a clear relationship between coverage and fixation stability. This seems to rest on a few ad hoc examples. (What happens if one plots mean fixation deviation vs. coverage (and sets the individuals who could not be calibrated as the highest value of calibrated fixation deviation. Does a relationship then emerge?).

In any case, I wouldn't expect coverage to be particularly susceptible to eye-movements. If a voxel in the cortex entirely projects to the scotoma then it should be robustly silent. The effects of eye-movements will be to distort the size and eccentricity estimates of voxels that are not entirely silent.

There are many places in the paper where eye-movements might be playing an important role.

Examples include the larger pRF sizes observed in achromats. Are those related to fixation instability? Given that fixation instability is expected to increase pRF size by a fixed amount, that would explain why ratios are close to 1 in V3 (Figure 4).

(2) Topography

The claim of no change in topography is a little confusing given that you do see a change in eccentricity mapping in achromats.

Either this result is real, in which case there *is* a change in topography, albeit subtle, or it's an artifact.

Perhaps these results need a little bit of additional scrutiny.

One reason for concern is that you see different functions relating eccentricity to V1 segments depending on the stimulus. That almost certainly reflects biases in the modelling, not reorganization - the curves of Figure 2D are exactly what Binda et al. predict.

Another reason for concern is that I'm very surprised that you see so little effect of including/not including the scotoma - the differences seem more like what I'd expect from simply repeating the same code twice. (The quickest sanity check is just to increase the size of the estimated scotoma to be even bigger?).

I'd also look at voxels that pass an R2>0.2 threshold for both the non-selective and selective stimulus. Are the pRF sizes the same for both stimuli? Are the eccentricity estimates? If not, that's another clear warning sign.

(3) Connective field modelling

Let's imagine a voxel on the edge of the scotoma. It will tend to have a connective field that borders the scotoma, and will be reduced in size (since it will likely exclude the cortical region of V1 that is solely driven by resting state activity). This predicts your rod monochromat data. The interesting question is why this doesn't happen for controls. One possibility is that there is top-down 'predictive' activity that smooths out the border of the scotoma (there's some hint of that in the data), e.g., Masuda and Wandell.

One thing that concerns me is that the smaller connective fields don't make sense intuitively. When there is a visual stimulus, connective fields are predominantly driven by the visual signal. In achromats, there is a large swath of cortex (between 1-2.5 degrees) which shows relatively flat tuning as regards eccentricity. The curves for controls are much steeper, See Figure 2b. This predicts that visually driven connective fields should be larger for achromats. So, what's going on? The beta parameter is not described (and I believe it can alter connective field sizes). Similarly, it's possible to get very small connective fields, but there wasn't a minimum size described in the thresholding. I might be missing something obvious, but I'm just deeply confused as to how the visual maps and the connectome maps can provide contradictory results given that the connectome maps are predominantly determined by the visual signal. Some intuition would be helpful.

Some analyses might also help provide the reader with insight. For example, doing analyses separately on V3 voxels that project entirely to scotoma regions, project entirely to stimulus-driven regions, and V3 voxels that project to 'mixed' regions.

The finding that pRF sizes are larger in achromats by a constant factor as a function of eccentricity is what differences in eye-movements would predict. It would be worth examining the relationship between pRF sizes and fixation stability.

Reviewer #2 (Public review):

Summary:

The authors inspect the stability and compensatory plasticity in the retinotopic mapping in patients with congenital achromatopsia. They report an increased cortical thickness in central (eccentricities 0-2 deg) in V1 and the expansion of this effect to V2 (trend) and V3 in a cohort with an average age of adolescents.

In analyzing the receptive fields, they show that V1 had increased receptive field sizes in achromats, but there were no clear signs of reorganization filling in the rod-free area.<br /> In contrast, V3 showed an altered readout of V1 receptive fields. V3 of achromats oversampled the receptive fields bordering the rod-free zone, presumably to compensate and arrive at similar receptive fields as in the controls.

These findings support a retention of peripheral-V1 connectivity, but a reorganization of later hierarchical stages of the visual system to compensate for the loss, highlighting a balance between stability and compensation in different stages of the visual hierarchy.

Strengths:

The experiment is carefully analyzed, and the data convey a clear and interesting message about the capacities of plasticity.

Weaknesses:

The existence of unstable fixation and nystagmus in the patient group is alluded to, but not quantified or modeled out in the analyses. The authors may want to address this possible confound with a quantitative approach.

Reviewer #1 (Public review):

The findings of Ziolkowska and colleagues show that a specific projection from the nucleus reuniens of the thalamus (RE) to dorsal hippocampal CA1 neurons plays an important role in fear extinction learning in male and female mice. In and of itself, this is not a particularly new finding, although the authors' identification of structural alterations from within dorsal CA1 stratum lacunosum moleculare (SLM) as a candidate mechanism for the learning-related plasticity is potentially novel and exciting. The authors use a range of anatomical and functional approaches to demonstrate structural synaptic changes in dorsal CA1 that parallel the necessary role of RE inputs in modulating extinction learning. Yet, the significance of these findings is substantially limited by several technical shortcomings in the experimental design, and the authors' central interpretation. Otherwise, there remain several strengths in the design and interpretation that offset some of these concerns.

Given that much is already known about the role of RE and hippocampus in modulating fear learning and extinction, it remains unclear whether addressing these concerns would substantially increase the impact of this study beyond the specific area of speciality. Below, several major weaknesses will be highlighted, followed by several miscellaneous comments.

Methodological:

One major methodological weakness in the experimental design involves the widespread misapplication of Ns used for the statistical analyses. Much of the anatomical analyses of structural synaptic changes in the RE-CA1 pathway use N = number of axons (Figs. 1, 2), N = number of dendrites (Figs. 3, 4), and N = number of sections (Fig. 7; note that there are 7 figures in total). In every instance, N = animal number should be used. It is unclear which of these results would remain significant if N = animal number were used in each or how many more animals would be required. This is problematic since these data comprise the main evidence for the authors' central conclusion that specific structural synaptic changes are associated with fear extinction learning.

There is a lack of specific information regarding what constitutes learning with respect to behavioral freezing. It is never clearly stated what specific intervals are used over which freezing is measured during acquisition, extinction, and in extinction retrieval tests. Additionally, assessment of freezing during retrieval at 5- and 30-min time points doesn't lay to rest the possibility that there were differences in the decay rate over the 30-min period (also see below).

A minor-to-moderate methodological weakness concerns the authors' decision to utilize saline injected groups as controls for the chemogenetics experiments (Figs. 5, 6). The correct design is to have a CNO-only group with the same viral procedure sans hM4Di. This concern is partly mitigated by the inclusion of a CNO vs. saline injection control experiment (Fig. 6).

In the electron microscopic analyses of dendritic spines (Fig. 5), comparison of only the fear acquisition versus extinction training, and the lack of inclusion of a naïve control group, makes it difficult to understand how these structural synaptic changes are occurring relative to baseline. It is noteworthy that the authors utilize the tripartite design in other anatomical analyses (Fig. 2-4).

Interpretation:

The main interpretive weakness in the study is the authors' claim that their data shows a role for the RE-CA1 pathway in memory consolidation (i.e., see Abstract). This claim is based on the premise that, although RE-CA1 pathway inactivation with CNO treatment 30 min prior to contextual fear extinction did not affect freezing at 5- and 30-min time points relative to saline controls, these rats showed greater freezing when tested on extinction retrieval 24 h thereafter. First, the data do not rule out possible differences in the decay rate of freezing during extinction training due to CNO administration. Next, the fact that CNO is given prior to training still leaves open the possibility that acquisition was affected, even if there were not any frank differences in freezing. Support for this latter possibility derives from the fact that mice tested for extinction retrieval as early as 5 min after extinction training (Fig. 6C) showed the same impairments as mice tested 24 h later (Figs. 6A). Further, all the structural synaptic changes argued to underlie consolidation were based on analysis at a time point immediately following extinction training, which is too early to allow for any long-term changes that would underlie memory consolidation, but instead would confer changes associated with the extinction training event.

Reviewer #2 (Public review):

Summary:

Ziółkowska et al. characterize the synaptic mechanisms at the basis of the REdCA1 contribution to the consolidation of fear memory extinction. In particular, they describe a layer specific modulation of RE-dCA1 excitatory synapses modulation associated to contextual fear extinction which is impaired by transient chemogenetic inhibition of this pathway. These results indicate that RE activity-mediated modulation of synaptic morphology contributes to the consolidation of contextual fear extinction

Strengths:

The manuscript is well conceived, the statistical analysis is solid and methodology appropriate. The strength of this work is that it nicely builds up on existing literature and provides new molecular insight on a thalamo-hippocampal circuit previously known for its role in fear extinction. In addition, the quantification of pre- and post-synapses is particularly thorough.

Weaknesses:

The findings in this paper are well supported by the data more detailed description of the methods is needed.

(1) In the paragraph Analysis of dCA1 synapses after contextual fear extinction (CFE), more experimental and methodological data should be given in the text: -how was PSD95 used for the analysis, what was the difference between RE. Even if Thy1-GFP mice were used in Fig.2, it appears they were not used for bouton size analysis. To improve clarity, I suggest moving panel 2C to Figure 3. It is not clear whether all RE axons were indiscriminately analysed in Fig. 2 or if only the ones displaying colocalization with both PSD95 and GFP were analysed. If GFP was not taken into account here, analysed boutons could reflect synapses onto inhibitory neurons and this potential scenario should be discussed<br /> (2) in the methods: The volume of intra-hippocampal CNO injections should be indicated. The concentration of 3 uM seems pretty low in comparison with previous studies. More details of what software/algorithm was used to score freezing should be included. CNO source is missing. Antibody dilutions for IHC should be indicated. Secondary antibody incubation time should be indicated

No statement about code and data availability is present.

Reviewer #3 (Public review):

Summary:

This paper examined the role of nucleus reuniens (RE) projections to dorsal CA1 neurons in context fear extinction learning. First, they show that RE neurons send excitatory projections to the stratum oriens (SO) and the stratum lacunosum moleculare (SLM), but not the stratum radiatum (SR). After context fear conditioning, the synaptic connections between RE and dCA1 neurons in the SLM (but not the SO) are weakened (reduced bouton and spine density) after mice undergo context fear conditioning. This weakening is reversed by extinction learning, which leads to enhanced synaptic connectivity between RE inputs and dendrites in the SLM. Control experiments demonstrate that the observed changes are due to extinction and not caused by simple exposure to the context. Extinction learning also induced increases in the size (volume and surface area) of the post-synaptic density (PSD) in SLM. To establish the functional role of RE inputs to dCA1, the researchers used an inhibitory DREADD to silence this pathway during extinction learning. They observe that extinction memory (measured 2-hours or 24-hours later) is impaired by this inhibition. Control experiments show that the extinction memory deficit is not simply due to increased freezing caused by inactivation of the pathway or injections of CNO. Inhibiting the RO projection during extinction learning also reduced the levels of PSD-95 protein levels in the spines of dCA1 neurons.

Strengths:

Based on their results, the authors conclude that, "the RE→SLM pathway participates in the updating of fearful context value by actively regulating CFE-induced molecular and structural synaptic plasticity in the SLM.". I believe the data are generally consistent with this hypothesis, although there is an important control condition missing from the behavioral experiments.

Weaknesses:

(1) A defining feature of extinction learning is that it is context specific (Bouton, 2004). It is expressed where it was learned, but not in other environments. Similarly, it has been shown that internal contexts (or states) also modulate the expression of extinction (Bouton, 1990). For example, if a drug is administered during extinction learning, it can induce a specific internal state. If this state is not present during subsequent testing, the expression of extinction is impaired just as it is when the physical context is altered (Bouton, 2004). It is possible that something similar is happening in Figure 6. In these experiments, CNO is administered to inactivate the RE-dCA1 projection during extinction learning. The authors observe that this manipulation impairs the expression of extinction the next day (or 2-hours later). However, the drug is not given again during the test. Therefore, it is possible that CNO (and/or inactivation of the RE-dCA1 pathway) induces a state change during extinction that is not present during subsequent testing. Based on the literature cited above, this would be expected to disrupt fear extinction as the authors observed. To determine if this alternative explanation is correct, the researchers need to add groups that receive CNO during extinction training and subsequent extinction testing. If the deficits in extinction expression reported in Figure 6 result from a state change, then these groups should not exhibit an impairment. In contrast, if the authors' account is correct, then the expression of extinction should still be disrupted in mice that receive CNO during training and testing.

(2) In their analysis of dCA1 synapses after contextual fear extinction (CFE) (Figure 4), the authors should have compared Ctx and Ctx-Ctx animals against naïve animals (as they did in Figure 3) when comparing 5US and Ext with naïve animals. Otherwise, the authors cannot make the following conclusion; "since changes of SLM synapses were not observed in the animals exposed to the familiar context that was not associated with the USs, our data support the role of the described structural plasticity at the RE→SLM synapses in CFE, rather than in processing contextual information in general.".

(3) In the materials and methods section, the description of cannula placements is confusing and needs to be rewritten.

Reviewer #1 (Public review):

Summary:

This study investigates an intriguing question in cognitive control from a temporal dynamics perspective: why does concurrent verbal working memory load eliminate the color-word Stroop effect? Through a series of thorough data analyses, the authors propose that verbal working memory load occupies the stimulus-response mapping resources represented by theta-band activity, thereby disrupting the mapping process for task-irrelevant distractors. This reduces the response tendency to the distractors, ultimately leading to the elimination of the Stroop effect.

Strengths:

The behavioral and neural evidence presented in the manuscript is solid, and the findings have valuable theoretical implications for research on Stroop conflict processing.

Weaknesses:

There are several areas where the manuscript could be improved.

Major Comments:

(1) In the Results section, the rationale behind selecting the beta band for the central (C3, CP3, Cz, CP4, C4) regions and the theta band for the fronto-central (Fz, FCz, Cz) regions is not clearly explained in the main text. This information is only mentioned in the figure captions. Additionally, why was the beta band chosen for the S-ROI fronto-central region and the theta band for the S-ROI central region? Was this choice influenced by the MVPA results?

(2) In the Data Analysis section, line 424 states: "Only trials that were correct in both the memory task and the Stroop task were included in all subsequent analyses. In addition, trials in which response times (RTs) deviated by more than three standard deviations from the condition mean were excluded from behavioral analyses." The percentage of excluded trials should be reported. Also, for the EEG-related analyses, were the same trials excluded, or were different criteria applied?

(3) In the Methods section, line 493 mentions: "A 400-200 ms pre-stimulus time window was selected as the baseline time window." What is the justification in the literature for choosing the 400-200 ms pre-stimulus window as the baseline? Why was the 200-0 ms pre-stimulus period not considered?

(4) Is the primary innovation of this study limited to the methodology, such as employing MVPA and RSA to establish the relationship between late theta activity and behavior?

(5) On page 14, lines 280-287, the authors discuss a specific pattern observed in the alpha band. However, the manuscript does not provide the corresponding results to substantiate this discussion. It is recommended to include these results as supplementary material.

(6) On page 16, lines 323-328, the authors provide a generalized explanation of the findings. According to load theory, stimuli compete for resources only when represented in the same form. Since the pre-memorized Chinese characters are represented semantically in working memory, this explanation lacks a critical premise: that semantic-response mapping is also represented semantically during processing.

(7) The classic Stroop task includes both a manual and a vocal version. Since stimulus-response mapping in the vocal version is more automatic than in the manual version, it is unclear whether the findings of this study would generalize to the impact of working memory load on the Stroop effect in the vocal version.

(8) While the discussion section provides a comprehensive analysis of the study's results, the authors could further elaborate on the theoretical and practical contributions of this work.

Reviewer #2 (Public review):

Summary:

Li et al. explored which stage of Stroop conflict processing was influenced by working memory loads. Participants completed a single task (Stroop task) and a dual task (the Sternberg working memory task combined with the Stroop task) while their EEG data was recorded. They adopted the event-related potential (ERP), and multivariate pattern analyses (MVPA) to investigate the interaction effect of task (single/dual) and congruency (congruent/incongruent). The results showed that the interaction effect was significant on the sustained potential (SP; 650-950 ms), the late theta (740-820 ms), and beta (920-1040 ms) power but not significant on the early P1 potential (110-150 ms). They used the representational similarity analyses (RSA) method to explore the correlation between behavioral and neural data, and the results revealed a significant contribution of late theta activity.

Strengths:

(1) The experiment is well-designed.

(2) The data were analyzed in depth from both time and frequency domain perspectives by combining several methods.

Weaknesses:

(1) As the researchers mentioned, a previous study reported a diminished Stroop effect with concurrent working memory tasks to memorize meaningless visual shapes rather than memorize Chinese characters as in the study. My main concern is that lower-level graphic processing when memorizing visual shapes also influences the Stroop effect. The stage of Stroop conflict processing affected by the working memory load may depend on the specific content of the concurrent working memory task. If that's the case, I sense that the generalization of this finding may be limited.

(2) The P1 and N450 components are sensitive to congruency in previous studies as mentioned by the researchers, but the results in the present study did not replicate them. This raised concerns about data quality and needs to be explained.

Reviewer #1 (Public review):

Summary:

McDougal et al. aimed to characterize the antiviral activity of mammalian IFIT1 orthologs. They first performed three different evolutionary selection analyses within each major mammalian clade and identified some overlapping positive selection sites in IFIT1. They found that one site that is positively selected in primates is in the RNA-binding exit tunnel of IFIT1 and is tolerant of mutations to amino acids with similar biochemical properties. They then tested 9 diverse mammalian IFIT1 proteins against VEEV, VSV, PIV3, and SINV and found that each ortholog has distinct antiviral activities. Lastly, they compared human and chimpanzee IFIT1 and found that the determinant of their differential anti-VEEV activity may be partly attributed to their ability to bind Cap0 RNA.

Strengths:

The study is one of the first to test the antiviral activity of IFIT1 from diverse mammalian clades against VEEV, VSV, PIV3, and SINV. Cloning and expressing these 39 IFIT1 orthologs in addition to single and combinatorial mutants is not a trivial task. The positive connection between anti-VEEV activity and Cap0 RNA binding is interesting, suggesting that differences in RNA binding may explain differences in antiviral activity.

Weaknesses:

The evolutionary selection analyses yielded interesting results, but were not used to inform follow-up studies except for a positively selected site identified in primates. Since positive selection is one of the two major angles the authors proposed to investigate mammalian IFIT1 orthologs with, they should integrate the positive selection results with the rest of the paper more seamlessly, such as discussing the positive selection results and their implications, rather than just pointing out that positively selected sites were identified. The paper should elaborate on how the positive selection analyses PAML, FUBAR, and MEME complement one another to explain why the tests gave them different results. Interestingly, MEME which usually provides more sites did not identify site 193 in primates that was identified by both PAML and FUBAR. The authors should also provide the rationale for choosing to focus on the 3 sites identified in primates only. One of those sites, 193, was also found to be positively selected in bats, although the authors did not discuss or integrate that finding into the study. In Figure 1A, they also showed a dN/dS < 1 from PAML, which is confusing and would suggest negative selection instead of positive selection. Importantly, since the authors focused on the rapidly evolving site 193 in primates, they should test the IFIT1 orthologs against viruses that are known to infect primates to directly investigate the impact of the evolutionary arms race at this site on IFIT1 function.

Some of the data interpretation is not accurate. For example:

(1) Lines 232-234: "...western blot analysis revealed that the expression of IFIT1 orthologs was relatively uniform, except for the higher expression of orca IFIT1 and notably lower expression of pangolin IFIT1 (Figure 4B)." In fact, most of the orthologs are not expressed in a "relatively uniform" manner e.g. big brown bat vs. shrew are quite different.

(2) Line 245: "...mammalian IFIT1 species-specific differences in viral suppression are largely independent of expression differences." While it is true that there is no correlation between protein expression and antiviral activity in each species, the authors cannot definitively conclude that the species-specific differences are independent of expression differences. Since the orthologs are clearly not expressed in the same amounts, it is impossible to fully assess their true antiviral activity. At the very least, the authors should acknowledge that the protein expression can affect antiviral activity. They should also consider quantifying the IFIT1 protein bands and normalizing each to GAPDH for readers to better compare protein expression and antiviral activity. The same issue is in Line 267.

(3) Line 263: "SINV... was modestly suppressed by pangolin, sheep, and chinchilla IFIT1 (Figure 4E)..." The term "modestly suppressed" does not seem fitting if there is 60-70% infection in cells expressing pangolin and chinchilla IFIT1.

(4) The study can be significantly improved if the authors can find a thread to connect each piece of data together, so the readers can form a cohesive story about mammalian IFIT1.

Reviewer #2 (Public review):

McDougal et al. describe the surprising finding that IFIT1 proteins from different mammalian species inhibit the replication of different viruses, indicating that the evolution of IFIT1 across mammals has resulted in host species-specific antiviral specificity. Before this work, research into the antiviral activity and specificity of IFIT1 had mostly focused on the human ortholog, which was described to inhibit viruses including vesicular stomatitis virus (VSV) and Venezuelan equine encephalitis virus (VEEV) but not other viruses including Sindbis virus (SINV) and parainfluenza virus type 3 (PIV3). In the current work, the authors first perform evolutionary analyses on IFIT1 genes across a wide range of mammalian species and reveal that IFIT1 genes have evolved under positive selection in primates, bats, carnivores, and ungulates. Based on these data, they hypothesize that IFIT1 proteins from these diverse mammalian groups may show distinct antiviral specificities against a panel of viruses. By generating human cells that express IFIT1 proteins from different mammalian species, the authors show a wide range of antiviral activities of mammalian IFIT1s. Most strikingly, they find several IFIT1 proteins that have completely different antiviral specificities relative to human IFIT1, including IFIT1s that fail to inhibit VSV or VEEV, but strongly inhibit PIV3 or SINV. These results indicate that there is potential for IFIT1 to inhibit a much wider range of viruses than human IFIT1 inhibits. Electrophoretic mobility shift assays (EMSAs) suggest that some of these changes in antiviral specificity can be ascribed to changes in the direct binding of viral RNAs. Interestingly, they also find that chimpanzee IFIT1, which is >98% identical to human IFIT1, fails to inhibit any tested virus. Replacing three residues from chimpanzee IFIT1 with those from human IFIT1, one of which has evolved under positive selection in primates, restores activity to chimpanzee IFIT1. Together, these data reveal a vast diversity of IFIT1 antiviral specificity encoded by mammals, consistent with an IFIT1-virus evolutionary "arms race".

Overall, this is a very interesting and well-written manuscript that combines evolutionary and functional approaches to provide new insight into IFIT1 antiviral activity and species-specific antiviral immunity. The conclusion that IFIT1 genes in several mammalian lineages are evolving under positive selection is supported by the data, although there are some important analyses that need to be done to remove any confounding effects from gene recombination that has previously been described between IFIT1 and its paralog IFIT1B. The virology results, which convincingly show that IFIT1s from different species have distinct antiviral specificity, are the most surprising and exciting part of the paper. As such, this paper will be interesting for researchers studying mechanisms of innate antiviral immunity, as well as those interested in species-specific antiviral immunity. Moreover, it may prompt others to test a wide range of orthologs of antiviral factors beyond those from humans or mice, which could further the concept of host-specific innate antiviral specificity. Additional areas for improvement, which are mostly to clarify the presentation of data and conclusions, are described below.

Strengths:

(1) This paper is a very strong demonstration of the concept that orthologous innate immune proteins can evolve distinct antiviral specificities. Specifically, the authors show that IFIT1 proteins from different mammalian species are able to inhibit the replication of distinct groups of viruses, which is most clearly illustrated in Figure 4G. This is an unexpected finding, as the mechanism by which IFIT1 inhibits viral replication was assumed to be similar across orthologs. While the molecular basis for these differences remains unresolved, this is a clear indication that IFIT1 evolution functionally impacts host-specific antiviral immunity and that IFIT1 has the potential to inhibit a much wider range of viruses than previously described.

(2) By revealing these differences in antiviral specificity across IFIT1 orthologs, the authors highlight the importance of sampling antiviral proteins from different mammalian species to understand what functions are conserved and what functions are lineage- or species-specific. These results might therefore prompt similar investigations with other antiviral proteins, which could reveal a previously undiscovered diversity of specificities for other antiviral immunity proteins.

(3) The authors also surprisingly reveal that chimpanzee IFIT1 shows no antiviral activity against any tested virus despite only differing from human IFIT1 by eight amino acids. By mapping this loss of function to three residues on one helix of the protein, the authors shed new light on a region of the protein with no previously known function.

(4) Combined with evolutionary analyses that indicate that IFIT1 genes are evolving under positive selection in several mammalian groups, these functional data indicate that IFIT1 is engaged in an evolutionary "arms race" with viruses, which results in distinct antiviral specificities of IFIT1 proteins from different species.

Weaknesses:

(1) The evolutionary analyses the authors perform appear to indicate that IFIT1 genes in several mammalian groups have evolved under positive selection. However, IFIT1 has previously been shown to have undergone recurrent instances of recombination with the paralogous IFIT1B, which can confound positive selection analyses such as the ones the authors perform. The authors should analyze their alignments for evidence of recombination using a tool such as GARD (in the same HyPhy package along with MEME and FUBAR). Detection of recombination in these alignments would invalidate their positive selection inferences, in which case the authors need to either analyze individual non-recombining domains or limit the number of species to those that are not undergoing recombination. While it is likely that these analyses will still reveal a signature of positive selection, this step is necessary to ensure that the signatures of selection and sites of positive selection are accurate.

(2) The choice of IFIT1 homologs chosen for study needs to be described in more detail. Many mammalian species encode IFIT1 and IFIT1B proteins, which have been shown to have different antiviral specificity, and the evolutionary relationship between IFIT1 and IFIT1B paralogs is complicated by recombination. As such, the assertion that the proteins studied in this manuscript are IFIT1 orthologs requires additional support than the percent identity plot shown in Figure 3B.

(3) Some of the results and discussion text could be more focused on the model of evolution-driven changes in IFIT1 specificity. In particular, the chimpanzee data are interesting, but it would appear that this protein has lost all antiviral function, rather than changing its antiviral specificity like some other examples in this paper. As such, the connection between the functional mapping of individual residues with the positive selection analysis is somewhat confusing. It would be more clear to discuss this as a natural loss of function of this IFIT1, which has occurred elsewhere repeatedly across the mammalian tree.

(4) In other places in the manuscript, the strength of the differences in antiviral specificity could be highlighted to a greater degree. Specifically, the text describes a number of interesting examples of differences in inhibition of VSV versus VEEV from Figure 3C and 3D, but it is difficult for a reader to assess this as most of the dots are unlabeled and the primary data are not uploaded. A few potential suggestions would be to have a table of each ortholog with % infection by VSV and % infection by VEEV. Another possibility would be to plot these data as an XY scatter plot. This would highlight any species that deviate from the expected linear relationship between the inhibition of these two viruses, which would provide a larger panel of interesting IFIT1 antiviral specificities than the smaller number of species shown in Figure 4.

Reviewer #3 (Public review):

Summary:

This manuscript by McDougal et al, demonstrates species-specific activities of diverse IFIT1 orthologs and seeks to utilize evolutionary analysis to identify key amino acids under positive selection that contribute to the antiviral activity of this host factor. While the authors identify amino acid residues as important for the antiviral activity of some orthologs and propose a possible mechanism by which these residues may function, the significance or applicability of these findings to other orthologs is unclear. However, the subject matter is of interest to the field, and these findings could be significantly strengthened with additional data.

Strengths:

Assessment of multiple IFIT1 orthologs shows the wide variety of antiviral activity of IFIT1, and identification of residues outside of the known RNA binding pocket in the protein suggests additional novel mechanisms that may regulate IFIT1 activity.

Weaknesses:

Consideration of alternative hypotheses that might explain the variable and seemingly inconsistent antiviral activity of IFIT1 orthologs was not really considered. For example, studies show that IFIT1 activity may be regulated by interaction with other IFIT proteins but was not assessed in this study.

Given that there appears to be very little overlap observed in orthologs that inhibited the viruses tested, it's possible that other amino acids may be key drivers of antiviral activity in these other orthologs. Thus, it's difficult to conclude whether the findings that residues 362/4/6 are important for IFIT1 activity can be broadly applied to other orthologs, or whether these are unique to human and chimpanzee IFIT1. Similarly, while the hypothesis that these residues impact IFIT1 activity in an allosteric manner is an attractive one, there is no data to support this.

Reviewer #1 (Public review):

Summary:

The authors analyze the roles of PD-1 in the early stages (pre-activation) of T cell differentiation and show that naïve CD4+ T cell differentiation is altered, especially Th2 differentiation is strongly impaired, upon early PD-1 stimulation. The results have important implications for the immunotherapy area, but I think the manuscript requires some revisions.

Strengths:

(1) Novel Insights into PD-1 in Early T Cell Differentiation:<br /> The study provides new insights into the role of PD-1 during the pre-activation phase of T cell differentiation, particularly its impact on naïve CD4+ T cells and Th2 differentiation. This is a significant contribution to immunotherapy research.

(2) Relevance to Immunotherapy:<br /> The findings have potential implications for the development of immunotherapies by demonstrating how PD-1 signaling affects specific T cell subsets early in differentiation.

Weaknesses:

(1) Inconsistent and Confusing Data:<br /> There are contradictions between the figures and the conclusions, particularly regarding IL-4 and IFNgamma production in PD-1-expressing cells. This raises concerns about data interpretation and experimental accuracy.

(2) Unclear Experimental Rationale:<br /> The reviewer questions the rationale behind key methodological choices, such as the high concentration of PDL-1 antibody and varying OVA peptide concentrations. These decisions need more justification.

Reviewer #2 (Public review):

Summary:

The authors try to demonstrate that PD-1 regulates not only the quantity but also the quality of the immune response determining the Th differentiation. The authors suggest that the ability of PD-1 agonists to dampen Th2 differentiation could be exploited in allergies or classical Th2-mediated disease as a therapeutical approach.

Strengths:<br /> The authors performed a series of elegant experiments using OVA-specific CD4 T cells from mice, showing a strong reduction of Th2 differentiation in vitro. They also perform some experiments with a model of allergies, showing an amelioration of the phenotype after administration of PD-1 agonist with a reduction of Th2 cells.

Weaknesses:

The authors perform all the experiments using DO11.10 mouse cells. Such cells have a TCR with very high affinity, it would be relevant to repeat at least some of the in vitro assays in a more physiological setting (you can immunise mice with ova to increase the pool of OVA-specific T cells, and then repeat the restimulation experiment). Also, a longer kinetic would be of interest to see the effect of the agonist on Th1 cells.

Another drawback is the lack of experiments with human cells. It would be really important to repeat the experiments with CD4 T cells from healthy donors (the antibody that the authors use as PD-1 agonist is human, so it would not be a complicated experiment).

It would be also interesting to show in the allergic disease model the effect of the agonism on the T cell response in general.

Reviewer #1 (Public review):

Summary:

This paper reports fossil soft-tissue structures (tail vanes) of pterosaurs, and attempts to relate this to flight performance and other proposed functions for the tail

Strengths:

The paper presents new evidence for soft-tissue strengthening of vanes using exciting new methods.

Weaknesses:

There seems to be no discussion of bias in the sample selection method - even a simple consideration of whether discarded specimens were likely not to have had the cross-linking lattice, or if it was not visible.

There seems to be no supporting evidence or theory to show how the lattice could have functioned, other than a narrative description. Moreover, there is no comparison to extant organisms where a comparison of function might be drawn.

Reviewer #2 (Public review):

Summary:

The authors have set out to investigate and explain how early members of the Pterosauria were able to maintain stiffness in the vane of their tails. This stiffness, it is said, was crucial for flight in early members of this clade. Through the use Laser-Stimulated Fluorescence imaging, the authors have revealed that certain pterosaurs had a sophisticated dynamic tensioning system that has previously been unappreciated.

Strengths:

The choice of method of investigation for the key question is sound enough, and the execution of the same is excellent. Overall the paper is well written and well presented, and provides a very succinct, accessible and clear conclusion.

Weaknesses:

None

Joint Public Review

This work investigates numerically the propagation of subthreshold waves in a model neural network that is derived from the C. elegans connectome. Using a scattering formalism and tight-binding description of the network -- approximations which are commonplace in condensed matter physics -- this work attempts to show the relevance of interference phenomena, such as wavenumber-dependent propagation, for the dynamics of subthreshold waves propagating in a network of electrical synapses.

The primary strength of the work is in trying to use theoretical tools from a far-away corner of fundamental physics to shed light on the properties of a real neural system.<br /> While a system composed of neurons and synapses is classical in nature, there are occasions in which interference or localization effects are useful for understanding wave propagation in complex media [review, van Rossum & Nieuwenhuizen, 1999]. However, it is expected that localization effects only have an impact in some parameter regimes and with low phase dissipation. The authors should have addressed the existence of this validity regime in detail prior to assuming that interference effects are important.

An additional approximation that was made without adequate justification is the use of a tight-binding Hamiltonian. This can be a reasonable approximation, even for classical waves, in particular in the presence of high-quality-factor resonators, where most of the wave amplitude is concentrated on the nodes of the network, and nodes are coupled evanescently with each other. Neither of these conditions were verified for this study.

The motivation for this work is to understand the basic mechanisms underlying subthreshold intrinsic oscillations in the inferior olive, but detailed connectivity patterns in this brain area are not available. The connectome is known for C elegans, but sub-threshold oscillations have not been observed there, and the implications of this work for C elegans neuroscience remain unclear. The authors should also give more evidence for the claim that their study may give a mechanism for synchronized rhythmic activity in the mammalian inferior olive nucleus, or refrain from making this conclusion.

In the same vein, since the work emphasizes the dependence on the wavenumber for the propagation of subthreshold oscillations, they should make an attempt at estimating the wavenumber of subthreshold oscillations in C elegans if they were to exist and be observed. Next, the presence of two "mobility edges" in the transmission coefficient calculated in this work is unmistakably due to the discrete nature of the system, coming from the tight-binding approximation, and it is unclear if this approximation is justified in the current system.

Similarly, it is possible that the wavenumber-dependent transmission observed depends strongly on the addition of a large number of virtual nodes (VNs) in the network, which the authors give little to no motivation for. As these nodes are not present in the C elegans connectome, the authors should explain the motivation for their inclusion in the model and should discuss their consequences on the transmission properties of the network.

As it stands, the work would only have a very limited impact on the understanding of subthreshold oscillations in the rat or in C elegans. Indeed, the preprint falls short of relating its numerical results to any phenomena which could be observed in the lab.

Reviewer #1 (Public review):

Summary:

In this study, Avila et al. tested the hypothesis that chronic pain states are associated with changes in the excitability of the medial prefrontal cortex (mPFC). The authors used the slope of the aperiodic component of the EEG power spectrum (= the aperiodic exponent) as a novel, non-invasive proxy for the cortical excitation-inhibition ratio. They performed source localization to estimate the EEG signals generated specifically by the mPFC. By pooling resting-state EEG recordings from three existing datasets, the authors were able to compare the aperiodic exponent in the mPFC and across the whole brain (at all modeled cortical sources) between 149 chronic pain patients and 115 healthy controls. Additionally, they assessed the relationship between the aperiodic exponent and pain intensity reported by the patients. To account for heterogeneity in pain etiology, the analysis was also performed separately for two patient subgroups with different chronic pain conditions (chronic back pain and chronic widespread pain). The study found robust evidence against differences in the aperiodic exponent in the mPFC between people with chronic pain and healthy participants, and no correlation was observed between the aperiodic exponent and pain intensity. These findings were consistent across different patient subgroups and were corroborated by the whole-brain analysis.

Strengths:

The study is based on sound scientific reasoning and rigorously employs suitable methods to test the hypothesis. It follows a pre-registered protocol, which greatly increases the transparency and, consequently, the credibility of the reported results. In addition to the planned steps, the authors used a multiverse analysis to ensure the robustness of the results across different methodological choices. I find this particularly interesting, as the EEG aperiodic exponent has only recently been linked to network excitability, and the most appropriate methods for its extraction and analysis are still being determined. The methods are clearly and comprehensively described, making this paper very useful for researchers planning similar studies. The results are convincing, and supported by informative figures, and the lack of the expected difference in mPFC excitability between the tested groups is thoroughly and constructively discussed.

Weaknesses:

Firstly, although I appreciate the relatively large sample size, pooling data recorded by different researchers using different experimental protocols inevitably increases sample variability and may limit the availability of certain measures, as was the case here with the reports of pain intensity in the patient group. Secondly, the analysis heavily relies on the estimation of cortical sources, an approach that offers many advantages but may yield imprecise results, especially when default conduction models, source models, and electrode coordinates are used. In my opinion, this point should be discussed as well.

Reviewer #2 (Public review):

Summary:

This study evaluated the aperiodic component in the medial prefrontal cortex (mPFC) using resting-state EEG recordings from 149 individuals with chronic pain and 115 healthy participants. The findings showed no significant differences in the aperiodic component of the mPFC between the two groups, nor was there any correlation between the aperiodic component and pain intensity. These results were consistent across various chronic pain subtypes and were corroborated by whole-brain analyses. The study's robustness was further reinforced by preregistration and multiverse analyses, which accounted for a wide range of methodological choices.

Strengths:

This study was rigorously conducted, yielding clear and conclusive results. Furthermore, it adhered to stringent open and reproducible science practices, including preregistration, blinded data analysis, and Bayesian hypothesis testing. All data and code have been made openly available, underscoring the study's commitment to transparency and reproducibility.

Weaknesses:

The aperiodic exponent of the EEG power spectrum is often regarded as an indicator of the excitatory/inhibitory (E/I) balance. However, this measure may not be the most accurate or optimal for quantifying E/I balance, a limitation that the authors might consider addressing in the future.

Reviewer #1 (Public review):

Summary:

This work represents a new development in the theory of odor coding and recognition, based on mapping odor mixtures in low-dimensional hyperbolic spaces. The authors describe the dynamics of odor mapping, across stages of ripening and fermentation (trajectories in odor space), which, surprisingly, generalize across fruit types.

Strengths:

The approach provides a remarkably concise and clear description of the odor dynamics. As a model, the approach is mathematically exhaustive and generalizable. The analyses are technically correct and statistically robust.

Weaknesses:

None.

Reviewer #2 (Public review):

This article presents an analysis of the chemical composition of head-space generated by fruit at differing stages of ripeness. The authors used gas chromatography-mass spectrometry (GC-MS) to record the chemical makeup of the respective head-space samples. The authors process the data and present it in a low dimensional space. They then draw conclusions from the geometry of that representation about the process of fermentation.

I have a number of major concerns with some of the stages in the argument advanced by the authors:

(1) As far as I understand, the authors restrict their analysis to 13 molecules which appear in samples of all three levels of ripeness. This choice causes the analysis to overlook the very likely (and meaningful) possibility that different molecules present at different levels of ripeness are informative and might support different results.

(2) It is unclear what was used as control? Empty bag? Please include the control results in your supplementary table, or indicate in the text if you eliminated compounds that were found in the control.

(3) It is not clear that Figure 2-H _looks_ like a spiral. The authors should provide a quantifiable measure of the quality of the fit of a spiral rather than other paths. Furthermore, in the section "collective spiral ..." the end of paragraph one, "the points were best fitted by a two parameter archemedian spiral" best out of what? best out of all two parameter spirals? Please explain

(4) In the section "estimating odor source phenotype ... " the authors write: "we first calculated the association of odorant compounds with different phenotypes in this dataset" how was that done?

(5) Even if hyperbolic space MDS is slightly better, an R^2 value for Euclidean MDS of 0.797 is very good and one could say that Euclidean MDS is also an option.

(6) In the section "collective spiral ..." near end of paragraph two: " we removed outlier samples for days 10 and 17 for two reasons...". Why does a smaller number of samples should make a certain day an outlier.

(7) In section titles "collective spiral progression of multiple..." the authors write: the hyperbolic t-sne embedding exhibited batch effects across runs that amounted to rotation of the data. To compensate for these effects and combine data across runs we performed Procrustes analysis to align data across runs".

Can we be sure that this process does itself not manufacture an alignment of data? The authors should apply the same process to random or shuffled data and see if the result is different from the actual data.

Reviewer #2 (Public review):

Goldstein et al. provide a thorough characterization of the interaction of attention and eye movement planning. These processes have been thought to be intertwined since at least the development of the Premotor Theory of Attention in 1987, and their relationship has been a continual source of debate and research for decades. Here, Goldstein et al. capitalize on their novel urgent saccade task to dissociate the effects of endogenous and exogenous attention on saccades towards and away from the cue. They find that attention and eye movements are, to some extent, linked to one another but that this link is transient and depends on the nature of the task. A primary strength of the work is that the researchers are able to carefully measure the time course of the interaction between attention and eye movements in various well-controlled experimental conditions. As a result, the behavioral interplay of two forms of attention (endogenous and exogenous) are illustrated at the level of tens of milliseconds as they interact with the planning and execution of saccades towards and away from the cued location. Overall, the results allow the authors to make meaningful claims about the time course of visual behavior, attention, and the potential neural mechanisms at a timescale relevant to everyday human behavior.

Reviewer #3 (Public review):

The present study used an experimental procedure involving time-pressure for responding, in order to uncover how the control of saccades by exogenous and endogenous attention unfolds over time. The findings of the study indicate that saccade planning is influenced by the locus of endogenous attention, but that this influence was short-lasting and could be overcome quickly. Taken together, the present findings reveal new dynamics between endogenous attention and eye movement control and lead the way for studying them using experiments under time-pressure.

The results achieved by the present study advance our understanding of vision, eye movements, and their control by brain mechanisms for attention. In addition, they demonstrate how tasks involving time-pressure can be used to study the dynamics of cognitive processes. Therefore, the present study seems highly important not only for vision science, but also for psychology, (cognitive) neuroscience, and related research fields in general.

I think the authors' addressed all of the reviewers' points successfully and in detail, so that I don't have any further suggestions or comments.

Reviewer #1 (Public review):

Summary:

In this technical paper, the authors introduce an important variation on the fully automated multi-electrode patch-clamp recording technique for probing synaptic connections that they term "patch-walking". The patch-walking approach involves coordinated pipette route-planning and automated pipette cleaning procedures for pipette reuse to improve recording throughput efficiency, which the authors argue can theoretically yield almost twice the number of connections to be probed by paired recordings on a multi-patch electrophysiology setup for a given number of cells compared to conventional manual patch-clamping approaches used in brain slices in vitro. The authors show convincing results from recordings in mouse in vitro cortical slices, demonstrating the efficient recording of dozens of paired neurons with a dual patch pipette configuration for paired recordings and detection of synaptic connections. This approach will be of interest and valuable to neuroscientists conducting automated multi-patch in vitro electrophysiology experiments and seeking to increase efficiency of neuron connectivity detection while avoiding the more complex recording configurations (e.g., 8 pipette multi-patch recording configurations) used by several laboratories that are not readily implementable by most of the neuroscience community.

Strengths:

(1) The authors introduce the theory and methods and show experimental results for a fully automated electrophysiology dual patch-clamp recording approach with a coordinated patch-clamp pipette route-planning and automated pipette cleaning procedures to "patch-walk" across an in vitro brain slice.

(2) The patch-walking approach offers throughput efficiency improvements over manual patch clamp recording approaches, especially for investigators looking to utilize paired patch electrode recordings in electrophysiology experiments in vitro.

(3) Experimental results are presented from in vitro mouse cortical slices demonstrating the efficiency of recording dozens of paired neurons with a two-patch pipette configuration for paired recordings and detection of synaptic connections, demonstrating the feasibility and efficiency of the patch-walking approach.

(4) The authors suggest extensions of their technique while keeping the number of recording pipettes employed and recording rig complexity low, which are important practical technical considerations for investigators wanting to avoid the more complex recording configurations (e.g., 8-10 pipette multi-patch recording configurations) used by several laboratories that are not readily implementable by most of the neuroscience community.

Reviewer #2 (Public review):

Summary:

In this study, the authors aim to combine automated whole-cell patch clamp recording simultaneously from multiple cells. Using a 2-electrode approach, they are able to sample as many cells (and connections) from one slice, as would be achieved with a more technically demanding and materially expensive 8-electrode patch clamp system. They provide data to show that this approach is able to successfully record from 52% of attempted cells, which was able to detect 3 pairs in 71 screened neurons. The authors state that this is a step forward in our ability to record from randomly connected ensembles of neurons.

Strengths:

The conceptual approach of recording multiple partner cells from another in a step wise manner indeed increases the number of tested connections. An approach that is widely applicable to both automated and manual approaches. Such a method could be adopted for many connectivity studies using dual recording electrodes.

The implementation of automated robotic whole-cell patch-clamp techniques from multiple cells simultaneously is a useful addition to the multiple techniques available to ex vivo slice electrophysiologists.

The approach using 2 electrodes, which are washed between cells is economically favourable, as this reduces equipment costs for recording multiple cells, and limits the wastage of capillary glass that would otherwise be used once.

Weaknesses:

(1) Based on the revised manuscript - a discussion of the implementation of this approach to manual methods is still lacking,

(2) A comparison of measurements shown in Figure 2 to other methods has not been addressed adequately.

(3) The morphological identification of neurons is understandably outside the remit of this project - but should be discussed and/or addressed. It was not suggested to perform detailed anatomical analysis - but to highlight the importance of this, and it should still be discussed

(4) The revised manuscript does not clearly state which cells were included in the analysis as far as I can see - and indeed cells with Access Resistance >40 MOhm appear to still be included in the data.

Reviewer #3 (Public review):

Summary:

In this manuscript, Yip and colleagues incorporated the pipette cleaning technique into their existing dual-patch robotic system, "the PatcherBot", to allow sequential patching of more cells for synaptic connection detection in living brain slices. During dual-patching, instead of retracting all two electrodes after each recording attempt, the system cleaned just one of the electrodes and reused it to obtain another recording while maintaining the other. With one new patch clamp recording attempt, new connections can be probed. By placing one pipette in front of the other in this way, one can "walk" across the tissue, termed "patch-walking." This application could allow for probing additional neurons to test the connectivity using the same pipette in the same preparation.

Strengths:

Compared to regular dual-patch recordings, this new approach could allow for probing more possible connections in brain slices with dual-patch recordings, thus having the potential to improve the efficiency of identifying synaptic connections

Weaknesses:

While this new approach offers the potential to increase efficiency, it has several limitations that could curtail its widespread use.

Loss of Morphological Information: Unlike traditional multi-patch recording, this approach likely loses all detailed morphology of each recorded neuron. This loss is significant because morphology can be crucial for cell type verification and understanding connectivity patterns by morphological cell type.

Spatial Restrictions: The robotic system appears primarily suited to probing connections between neurons with greater spatial separation (~100µm ISD). This means it may not reliably detect connections between neurons in close proximity, a potential drawback given that the connectivity is much higher between spatially close neurons. This limitation could help explain the low connectivity rate (5%) reported in the study.

Limited Applicability: While the approach might be valuable in specific research contexts, its overall applicability seems limited. It's important to consider scenarios where the trade-off between efficiency and specific questions that are asked.<br /> Scalability Challenges: Scaling this method beyond a two-pipette setup may be difficult. Additional pipettes would introduce significant technical and logistical complexities.

Reviewer #1 (Public review):

Summary:

As the scientific community identifies increasing numbers of genes and genetic variants that cause rare human diseases, a challenge in the field quickly identify pharmacological interventions to address known deficits. The authors point out that defining phenotypic outcomes required for drug screen assays is often a bottleneck, and emphasize how invertebrate models can be used for quick ID of compounds that may address genetic deficits. A major contribution of this work is to establish a framework for potential intervention drug screening based on quantitative imaging of morphology and mobility behavior, using methods that the authors show can define subtle phenotypes in a high proportion of disease gene knockout mutants. Overall, the work constitutes an elegant combination of previously developed high-volume imaging with highly detailed quantitative phenotyping (and some paring down to specific phenotypes) to establish proof of principle on how the combined applications can contribute to screens for compounds that may address specific genetic deficits, which can, in turn, suggest both mechanism and therapy.

In brief, the authors selected 25 genes for which loss of function is implicated in human neuro-muscular disease and engineered deletions in the corresponding C. elegans homologs. The authors then imaged morphological features and behaviors prior to, during, and after blue light stimuli, quantitating features, and clustering outcomes as they elegantly developed previously (PMID 35322206; 30171234; 30201839). In doing so, phenotypes in 23/25 tested mutants could be separated enough to distinguish WT from mutant and half of those with adequate robustness to permit high-throughput screens, an outcome that supports the utility of related general efforts to ID phenotypes in C. elegans disease orthologs. A detailed discussion of 4 ciliopathy gene defects, and NACLN-related channelopathy mutants reveals both expected and novel phenotypes, validating the basic approach to modeling vetted targets and underscoring that quantitative imaging approaches reiterate known biology.

The authors then screened a library of nearly 750 FDA-approved drugs for the capacity to shift the unc-80 NACLN channel-disrupted phenotype closer to the wild type. Top "mover" compounds shift outcome in the experimental outcome space; and also reveal how "side effects" can be evaluated to prioritize compounds that confer the fewest changes of other parameters away from the center.

Strengths:

Although the imaging and data analysis approaches have been reported and the screen is restricted in scope and intervention exposure, it is impressive, encouraging and important that the authors strongly combine tools to demonstrate how quantitative imaging phenotypes can be integrated with C. elegans genetics to accelerate the identification of potential modulators of disease (easily extendable to other goals). Generation of deletion alleles and documentation of their associated phenotypes (available in supplemental data) provide potentially useful reagents/data to the field. The capacity to identify "over-shooting" of compound applications with suggestions for scale back and to sort efficacious interventions to minimize other changes to behavioral and physical profiles is a strong contribution.

Weaknesses:

The work does not have major weaknesses, and in revision, the authors have expanded the discussion to potential utility and application in the field.

The authors have also taken into account minor modifications in writing.

Reviewer #2 (Public review):

Summary and strengths:

O'Brien et al. present a compelling strategy to both understand rare disease that could have a neuronal focus and discover drugs for repurposing that can affect rare disease phenotypes. Using C. elegans, they optimize the Brown lab worm tracker and Tierpsy analysis platform to look at movement behaviors of 25 knockout strains. These gene knockouts were chosen based on a process to identify human orthologs that could underlie rare diseases. I found the manuscript interesting and a powerful approach to make genotype-phenotype connections using C. elegans. Given the rate that rare Mendelian diseases are found and candidate genes suggested, human geneticists need to consider orthologous approaches to understand the disease and seek treatments on a rapid time scale. This approach is one such way. Overall, I have a few minor suggestions and some specific edits.

Weaknesses:

(1) Throughout the text on figures, labels are nearly impossible to read. I had to zoom into the PDF to determine what the figure was showing. Please make text in all figures a minimum of 10 point font. Similarly, Figure 2D point type is impossible to read. Points should be larger in all figures. Gene names should be in italics in all figures, following C. elegans convention.

(2) I have a strong bias against the second point in Figure 1A. Sequencing of trios, cohorts, or individuals NEVER identifies causal genes in the disease. This technique proposes a candidate gene. Future experiments (oftentimes in model organisms) are required to make those connections to causality. Please edit this figure and parts of the text.

(3) How were the high-confidence orthologs filtered from 767 to 543 (lines 128-131)? Also, the choice of the final list of 25 genes is not well justified. Please expand more about how these choices were made.

(4) Figures 3 and 4, why show all 8289 features? It might be easier to understand and read if only the 256 Tierpsy features were plotted in the heat maps.

(5) The unc-80 mutant screen is clever. In the feature space, it is likely better to focus on the 256 less-redundant Tierpsy features instead of just a number of features. It is unclear to me how many of these features are correlated and not providing more information. In other words, the "worsening" of less-redundant features is far more of a concern than "worsening" of 1000 correlated features.Reviewer #2 (Public review):

Summary and strengths:

O'Brien et al. present a compelling strategy to both understand rare disease that could have a neuronal focus and discover drugs for repurposing that can affect rare disease phenotypes. Using C. elegans, they optimize the Brown lab worm tracker and Tierpsy analysis platform to look at movement behaviors of 25 knockout strains. These gene knockouts were chosen based on a process to identify human orthologs that could underlie rare diseases. I found the manuscript interesting and a powerful approach to make genotype-phenotype connections using C. elegans. Given the rate that rare Mendelian diseases are found and candidate genes suggested, human geneticists need to consider orthologous approaches to understand the disease and seek treatments on a rapid time scale. This approach is one such way. Overall, I have a few minor suggestions and some specific edits.

Weaknesses:

(1) Throughout the text on figures, labels are nearly impossible to read. I had to zoom into the PDF to determine what the figure was showing. Please make text in all figures a minimum of 10 point font. Similarly, Figure 2D point type is impossible to read. Points should be larger in all figures. Gene names should be in italics in all figures, following C. elegans convention.

(2) I have a strong bias against the second point in Figure 1A. Sequencing of trios, cohorts, or individuals NEVER identifies causal genes in the disease. This technique proposes a candidate gene. Future experiments (oftentimes in model organisms) are required to make those connections to causality. Please edit this figure and parts of the text.

(3) How were the high-confidence orthologs filtered from 767 to 543 (lines 128-131)? Also, the choice of the final list of 25 genes is not well justified. Please expand more about how these choices were made.

(4) Figures 3 and 4, why show all 8289 features? It might be easier to understand and read if only the 256 Tierpsy features were plotted in the heat maps.

(5) The unc-80 mutant screen is clever. In the feature space, it is likely better to focus on the 256 less-redundant Tierpsy features instead of just a number of features. It is unclear to me how many of these features are correlated and not providing more information. In other words, the "worsening" of less-redundant features is far more of a concern than "worsening" of 1000 correlated features.

Reviewer #3 (Public review):

In this study, O'Brien et al. address the need for scalable and cost-effective approaches to finding lead compounds for the treatment of the growing number of Mendelian diseases. They used state-of-the-art phenotypic screening based on an established high-dimensional phenotypic analysis pipeline in the nematode C. elegans.

First, a panel of 25 C. elegans models was created by generating CRISPR/Cas9 knock-out lines for conserved human disease genes. These mutant strains underwent behavioral analysis using the group's published methodology. Clustering analysis revealed common features for genes likely operating in similar genetic pathways or biological functions. The study also presents results from a more focused examination of ciliopathy disease models.

Subsequently, the study focuses on the NALCN channel gene family, comparing the phenotypes of mutants of nca-1, unc-77, and unc-80. This initial characterization identifies three behavioral parameters that exhibit significant differences from the wild type and could serve as indicators for pharmacological modulation.

As a proof-of-concept, O'Brien et al. present a drug repurposing screen using an FDA-approved compound library, identifying two compounds capable of rescuing the behavioral phenotype in a model with UNC80 deficiency. The relatively short time and low cost associated with creating and phenotyping these strains suggest that high-throughput worm tracking could serve as a scalable approach for drug repurposing, addressing the multitude of Mendelian diseases. Interestingly, by measuring a wide range of behavioural parameters, this strategy also simultaneously reveals deleterious side effects of tested drugs that may confound the analysis.

Considering the wealth of data generated in this study regarding important human disease genes, it is regrettable that the data is not made accessible to researchers less versed in data analysis methods. This diminishes the study's utility. It would have a far greater impact if an accessible and user-friendly online interface were established to facilitate data querying and feature extraction for specific mutants. This would empower researchers to compare their findings with the extensive dataset created here.

Another technical limitation of the study is the use of single alleles. Large deletion alleles were generated by CRISPR/Cas9 gene editing. At first glance, this seems like a good idea because it limits the risk that background mutations, present in chemically-generated alleles, will affect behavioral parameters. However, these large deletions can also remove non-coding RNAs or other regulatory genetic elements, as found, for example, in introns. Therefore, it would be prudent to validate the behavioral effects by testing additional loss-of-function alleles produced through early stop codons or targeted deletion of key functional domains.

Reviewer #1 (Public review):

Summary:

This study explores the sequence characteristics and features of high-occupancy target (HOT) loci across the human genome. The computational analyses presented in this paper provide information into the correlation of TF binding and regulatory networks at HOT loci that were regarded as lacking sequence specificity.

By leveraging hundreds of ChIP-seq datasets from the ENCODE Project to delineate HOT loci in HepG2, K562, and H1-hESC cells, the investigators identified the regulatory significance and participation in 3D chromatin interactions of HOT loci. Subsequent exploration focused on the interaction of DNA-associated proteins (DAPs) with HOT loci using computational models. The models established that the potential formation of HOT loci is likely embedded in their DNA sequences and is significantly influenced by GC contents. Further inquiry exposed contrasting roles of HOT loci in housekeeping and tissue-specific functions spanning various cell types, with distinctions between embryonic and differentiated states, including instances of polymorphic variability. The authors conclude with a speculative model that HOT loci serve as anchors where phase-separated transcriptional condensates form. The findings presented here open avenues for future research, encouraging more exploration of the functional implications of HOT loci.

Strengths:

The concept of using computational models to define characteristics of HOT loci is refreshing and allows researchers to take a different approach in identifying potential targets. The major strengths of the study lie in the very large number of datasets analyzed, with hundreds of ChIP-seq data sets for both HepG2 and K562 cells as part of the ENCODE project. Such quantitative power allowed the authors to delve deeply into HOT loci, which were previously thought to be artifacts.

Weaknesses:

While this study contributes to our knowledge of HOT loci, there are critical weaknesses that need to be addressed. There are questions on the validity of the assumptions made for certain analyses. The speculative nature of the proposed model involving transcriptional condensates needs either further validation or be toned down. Furthermore, some apparent contradictions exist among the main conclusions, and these either need to be better explained or corrected. Lastly, several figure panels could be better explained or described in the figure legends.

Update After Revisions:

The authors have addressed the above comments and concerns appropriately. The addition of the new Figure 9 is particularly compelling and strengthens the authors' conclusions. This reviewer has no further concerns.

Reviewer #2 (Public review):

Summary:

The paper by Hydaiberdiev and Ovcharenko offers comprehensive analyses and insights about the 'high-occupancy target' (HOT) loci in the human genome. These are considered genomic regions that overlap with transcription factor binding sites. The authors provided very comprehensive analyses of the TF composition characteristics of these HOT loci. They showed that these HOT loci tend to overlap with annotated promoters and enhancers, GC-rich regions, open chromatin signals, and highly conserved regions and that these loci are also enriched with potentially causal variants with different traits.

Strengths:

Overall, the HOT loci' definition is clear and the data of HOT regions across the genome can be a useful dataset for studies that use HepG2 or K562 as a model. I appreciate the authors' efforts in presenting many analyses and plots backing up each statement.

Comments on revised version:

In the second round of review, I think the authors have sufficiently addressed all of my previous comments. The study itself is very comprehensive, tackling all aspects of the HOT loci, though I still find the paper to be unnecessarily long and long-winded. That said, being consistent with the long and detailed paper, the provided Github repository and Zenodo archive is well-documented. I appreciate that the authors include detailed readme about the different datafiles available for readers. The list of HOT loci is probably the most useful asset in this manuscript and the authors did a good job documenting data availability in both Github and Zenodo.

Reviewer #3 (Public review):

Summary:

Hudaiberdiev and Ovcharenko investigate regions within the genome where a high abundance of DNA associated proteins are located and identify DNA sequence feature enriched in these regions, their conservation in evolution, and variation in disease. Using ChIP-seq binding profiles of over 1,000 proteins in three human cell lines (HepG2, K562, and H1) as a data source they're able to identify nearly 44,000 high-occupancy target loci (HOT) that form at promoter and enhancer regions, thus suggesting these HOT loci regulate housekeeping and cell identity genes. Their primary investigative tool is HepG2 cells, but they employ K562 and H1 cells as tools to validate these assertions in other human cell types. Their analyses use RNA pol II signal, super enhancer, regular enhancer and epigentic marks to support the identification of these regions. The work is notable, in that it identifies a set of proteins that are invariantly associated with high-occupancy enhancers and promoters and argues for the integration of these molecules at different genomic loci. These observations are leveraged by the authors to argue HOT loci as potential sites of transcriptional condensates, a claim that they provide information in support of. Transcriptional condensates are an important "family" of condensates, regulating different types of genes and this work supports the hypothesis that they possess similar protein partner molecules as those thought to define such bodies.

Reviewer #1 (Public Review):

Summary:

Wang and colleagues identify biallelic variants of DNAH3 in four unrelated Han Chinese infertile men through whole-exome sequencing, which contributes to abnormal sperm flagellar morphology and ultrastructure. To investigate the importance of DNAH3 in male infertility, the authors generated crispant Dnah3 knockout (KO) male mice. They observed that KO mice are also infertile, showing a severe reduction in sperm movement with abnormal IDA (inner dynein arms) and mitochondrion structure. Moreover, nonfunctional DNAH3 expression decreased the expression of IDA-associated proteins in the spermatozoa of patients and KO mice, which are involved in the disruption of sperm motility. Interestingly, the infertility of patients and KO mice is rescued by intracytoplasmic sperm injection (ICSI). Taken together, the authors propose that DNAH3 is a novel pathogenic gene for asthenoterozoospermia and male infertility.

Strengths:

This work investigates the role of DNAH3 in sperm mobility and male infertility. By using gold-standard molecular biology techniques, the authors demonstrate with exquisite resolution the importance of DNAH3 in sperm morphology, showing strong evidence of its role in male infertility. Overall, this is a very interesting, well-written, and appealing article. All aspects of the study design and methods are well described and appropriate to address the main question of the manuscript. The conclusions drawn are consistent with the analyses conducted and supported by the data.

Weaknesses:

The paper is solid, and in its current form, I have not detected relevant weaknesses.

Reviewer #2 (Public Review):

Wang et al. investigated the role of dynein axonemal heavy chain 3 (DNAH3) in male infertility. They found that variants of DNAH3 were present in four infertile men, and the deficiency of DNAH3 in sperm affects sperm mobility. Additionally, they showed that Dnah3 knockout male mice are infertile. Furthermore, they demonstrated that DNAH3 influences inner dynein arms by regulating several DNAH proteins. Importantly, they showed that intracytoplasmic sperm injection (ICSI) can rescue the infertility in Dnah3 knockout mice and two patients with DNAH3 variants.

Strengths:

The conclusions of this paper are well-supported by data.

Weaknesses:

The sample/patient size is small; however, the findings are consistent with those of a recent study on DNAH3 in male infertility with 432 patients.

Reviewer #3 (Public Review):

Summary:

(1) To further explore the genetic basis of asthenoteratozoospermia, the authors performed whole-exome sequencing analyses among infertile males affected by asthenoteratozoospermia. Four unrelated Han Chinese patients were found to carry biallelic variations of DNAH3, a gene encoding IDA-associated protein.<br /> (2) To verify the function of IDA associated protein DNAH3, the authors generated a Dnah3-KO mouse model and revealed that the loss of DNAH3 leads to severe male infertility as a result of the severe reduction in sperm movement with the abnormal IDA and mitochondrion structures.<br /> (3) Mechanically, they confirmed decreased expression of IDA-associated proteins (including DNAH1, DNAH6 and DNALI1) in the spermatozoa from patients with DNAH3 mutations and Dnah3-KO male mice.<br /> (4) Then, they also found that male infertility caused by DNAH3 deficiency could be rescued by intracytoplasmic sperm injection (ICSI) treatment in humans and mice.

Strengths:

(1) In addition to existing research, the authors provided novel variants of DNAH3 as important factors leading to asthenoteratozoospermia. This further expands the spectrum of pathogenic variants in asthenoteratozoospermia.<br /> (2) By mechanistic studies, they found that DNAH3 deficiency led to decreased expression of IDA-associated proteins, which may be used to explain the disruption of sperm motility and reduced fertility caused by DNAH3 deficiency.<br /> (3) Then, successful ICSI outcomes were observed in patients with DNAH3 mutations and Dnah3 KO mice, which will provide an important reference for genetic counselling and clinical treatment of male infertility.

Reviewer #1 (Public Review):

The authors showed that autophagy-related genes are involved in plant immunity by regulating the protein level of the salicylic acid receptor, NPR1.

The experiments are carefully designed and the data is convincing. The authors did a good job of understanding the relationship between ATG6 and NRP1.

Comments on latest version:

The authors have already addressed all my comments. I have no further issues with the manuscript.

Reviewer #2 (Public Review):

The manuscript by Zhang et al. explores the effect of autophagy regulator ATG6 on NPR1-mediated immunity. The authors propose that ATG6 directly interacts with NPR1 in the nucleus to increase its stability and promote NPR1-dependent immune gene expression and pathogen resistance. This novel role of ATG6 is proposed to be independent of its role in autophagy in the cytoplasm. The authors demonstrate through biochemical analysis that ATG6 interacts with NPR1 in yeast and very weakly in vitro. They further demonstrate using overexpression transgenic plants that in the presence of ATG6-mcherry the stability of NPR1-GFP and its nuclear pool is increased.

Comments on latest version:

The term "invasion" has to be replaced with infection, as it doesn't have much meaning to this particular study. I already explained this point in the first review, but authors did not address it throughout the manuscript.

In fig. 1e there's no statistical analysis. How can one show measurements from multiple samples without statistical analysis? All the data points have to be shown in the graph and statistics performed. In the arg6-npr1 and snrk-npr1 pairs no nuclear marker is included. How can one know where the nucleus is, particularly in such poor quality low res. images? The nucleus marker has to be included in this analysis and shown. This is an important aspect of the study as nuclear localization of ATG6 is proposed to be essential for its new function. Co-localization provided in the fig. S2 cannot complement this analysis, particularly since no cytoplasmic fraction is present for NPR1-GFP in fig. S2.

In the alignment in fig 2c, it is not explained what are the species the atg6 is taken from. The predicted NLS has to be shown in the context of either the entire protein sequence alignment or at least individual domain alignment with the indication of conserved residues (consensus). They have to include more species in the analysis, instead of including 3 proteins from a single species. Also, the predicted NLS in atg6 doesn't really have the classical type architecture, which might be an indication that it is a weak NLS, consistent with the fact that the protein has significant cytoplasmic accumulation. They also need to provide the NLS prediction cut-off score, as this parameter is a measure of NLS strength.

Line 150: the NLS sequence "FLKEKKKKK" is a wrong sequence.

In fig. 3d no explanation for the error bars is included, and what type of statistical analysis is performed is not explained.

Reviewer #1 (Public review):

Freas et al. investigated if the exceedingly dim polarization pattern produced by the moon can be used by animal to guide a genuine navigational task. The sun and moon are celestial beacons for directional information, but they can be obscured by clouds, canopy, or the horizon. However, even when hidden from view, these celestial bodies provide directional information through the polarized light patterns in the sky. While the sun's polarization pattern is famously used by many animals for compass orientation, until now it has never been shown that the extremely dim polarization pattern of the moon can be used for navigation. To test this, Freas et al. studied nocturnal bull ants, by placing a linear polarizer in the homing path on a freely navigating ant 45 degrees shifted to the moon's natural polarization pattern. They recorded the homing direction of an ant before entering the polarizer, under the polarizer, and again after leaving the area covered by the polarizer. The results very clearly show, that ants walking under the linear polarizer change their homing direction by about 45 degrees in comparison to the homing direction under the natural polarization pattern and change it back after leaving the area covered by the polarizer again. These results can be repeated throughout the lunar month, showing that bull ants can use the moon's polarization pattern even under crescent moon conditions. Finally, the authors show, that the degree in which the ants change their homing direction is dependent on the length of their home vector, just as it is for the solar polarization pattern.

The behavioral experiments are very well designed, and the statistical analyses are appropriate for the data presented. The authors' conclusions are nicely supported by the data and clearly show nocturnal bull ants use the dim polarization pattern of the moon for homing, in the same way many animals use the sun's polarization pattern during the day. This is the first proof of the use of the lunar polarization pattern in any animal.

Reviewer #2 (Public review):

Summary:

The authors aimed to understand whether polarised moonlight could be used as a directional cue for nocturnal animals homing at night, particularly at times of night when polarised light is not available from the sun. To do this, the authors used nocturnal ants, and previously established methods, to show that the walking paths of ants can be altered predictably when the angle of polarised moonlight illuminating them from above is turned by a known angle (here +/- 45 degrees).

Strengths:

The behavioural data are very clear and unambiguous. The results clearly show that when the angle of downwelling polarised moonlight is turned, ants turn in the same direction. The data also clearly show that this result is maintained even for different phases (and intensities) of the moon, although during the waning cycle of the moon the ants' turn is considerably less than may be expected.

Weaknesses:

The final section of the results - concerning the weighting of polarised light cues into the path integrator - lacks clarity and should be re-worked and expanded in both the Methods and the Results (also possibly with an extra methods figure). I was really unsure of what these experiments were trying to show or what the meaning of the results actually are.

Impact:

The authors have discovered that nocturnal bull ants, while homing back to their nest holes at night, are able to use the dim polarised light pattern formed around the moon for path integration. Even though similar methods have previously shown the ability of dung beetles to orient along straight trajectories for short distances using polarised moonlight, this the first evidence of an animal that uses polarised moonlight in homing. This is quite significant, and their findings are well supported by their data.

Reviewer #3 (Public review):

Summary:

This manuscript presents a series of experiments aimed at investigating orientation to polarized lunar skylight in a nocturnal ant, the first report of its kind that I am aware of.

Strengths:

The study was conducted carefully and is clearly explained here.

Weaknesses:

The revised manuscript is much improved.

Reviewer #1 (Public review):

Summary:

The authors aim to investigate the role of ORMDL3 in regulating Type 1 interferon (IFN) responses and its effect on tumor growth inhibition. The study focuses on the mechanisms involving the RIG-I pathway and USP10-mediated degradation and attempts to establish a link between ORMDL3 expression and the effectiveness of cancer therapy. The authors also explore the broader implications of ORMDL3 in immune signaling, particularly within the context of Type 1 IFN signaling and its therapeutic potential.

Strengths:

• The manuscript explores a novel aspect of cancer immunology by examining the relationship between ORMDL3 and Type 1 IFN signaling, potentially offering new therapeutic avenues.<br /> • A variety of experimental approaches are employed, including knockdown models, overexpression assays, and protein interaction analyses, to elucidate the role of ORMDL3 in modulating immune responses.<br /> • The findings suggest a potential mechanism by which ORMDL3 affects the tumor microenvironment and immune responses, which could have significant implications for understanding cancer progression and therapy.

Weaknesses:

• The study does not clearly establish the relationship between Type 1 IFN and cancer therapy, and more robust data are needed to support the claim that tumor growth inhibition occurs via Type 1 IFN upregulation following ORMDL3 knockdown.<br /> • There is ambiguity regarding whether ORMDL3 has a positive or negative role in the Type 1 IFN pathway, especially given conflicting findings in the literature that link higher ORMDL3 levels to increased Type 1 IFN expression.<br /> • The use of certain experimental models, such as HEK293T cells (which are not typical Type 1 IFN producers), raises concerns about the validity and generalizability of the results. Further clarity is needed regarding the rationale for using the same tag in overexpression experiments.<br /> • The manuscript contains several inconsistencies and lacks detailed explanations of critical areas, such as the mechanism by which ORMDL3 facilitates USP10 transfer to RIG-I despite no direct interaction between ORMDL3 and RIG-I.

Reviewer #2 (Public review):

Summary:

The authors identified ORMDL3 as a negative regulator of the RLR pathway and anti-tumor immunity. Mechanistically, ORMDL3 interacts with MAVS and further promotes RIG-I for proteasome degradation. In addition, the deubiquitinating enzyme USP10 stabilizes RIG-I and ORMDL3 disturbs this process. Moreover, in subcutaneous syngeneic tumor models in C57BL/6 mice, they showed that inhibition of ORMDL3 enhances anti-tumor efficacy by augmenting the proportion of cytotoxic CD8-positive T cells and IFN production in the tumor microenvironment (TME).

Strengths:

The paper has a clearly arranged structure and the English is easy to understand. It is well written. The results are clearly supporting the conclusion.

Reviewer #1 (Public review):

Aging is associated with a number of physiologic changes including perturbed circadian rhythms. However, mechanisms by which rhythms are altered remain unknown. Here authors tested the hypothesis that age-dependent factors in the sera affect the core clock or outputs of the core clock in cultured fibroblasts. They find that both sera from young and old donors are equally potent at driving robust ~24h oscillations in gene expression, and report the surprising finding that the cyclic transcriptome after stimulation by young or old sera differs markedly. In particular, genes involved in the cell cycle and transcription/translation remain rhythmic in both conditions, while genes associated with oxidative phosphorylation and Alzheimer's Disease lose rhythmicity in the aged condition. Also, the expression of cycling genes associated with cholesterol biosynthesis increases in the cells entrained with old serum. Together, the findings suggest that age-dependent blood-borne factors, yet to be identified, affect circadian rhythms in the periphery. The most interesting aspect of the paper is that the data suggest that the same system (BJ-5TA), may significantly change its rhythmic transcriptome depending on how the cells are synchronized. While there is a succinct discussion point on this, it should be expanded and described whether there are parallels with previous works, as well as what would be possible mechanisms for such an effect.

Comments on revised version:

The authors have done a thorough revision of their manuscripts and provided convincing answers to all of my points. In particular, I applaud the authors for having added raw luminescence traces, and for providing Figure S5 on the amplitudes. Perhaps the authors could add a comment in the final text that the amplitudes are fairly low, 10^0.1 = 1.25 which means that the bulk of those genes has rhythms of at most 25%, which could reflect that the synchronization of the cells is partial.

Reviewer #2 (Public review):

Summary:

In this study, the authors study intraflagellar transport (IFT) in cilia of diverse organs in zebrafish. They elucidate that IFT88-GFP (an IFT-B core complex protein) can substitute for endogenous IFT88 in promoting ciliogenesis and use it as a reporter to visualize IFT dynamics in living zebrafish embryo. They observe striking differences in cilia lengths and velocity of IFT trains in different cilia types, with smaller cilia length correlating with lower IFT speed. They generate several mutants and show that disrupting function of different kinesin-2 motors and BBSome or altering post translational modifications of tubulin does not have a significant impact on IFT velocity. They however observe that when the amount of IFT88 is reduced it impacts the cilia length, IFT velocity as well as the number and size of IFT trains. They also show that IFT train size is slightly smaller in one of the organs with shorter cilia (spinal cord). Based on their observations they propose that IFT velocity determines cilia length and go one step further to propose that IFT velocity is regulated by the size of IFT trains.

Strengths:

The main highlight of this study is the direct visualization of IFT dynamics in multiple organs of a living complex multi-cellular organism, zebrafish. The quality of the imaging is really good. Further, the authors have developed phenomenal resources to study IFT in zebrafish which would allow us to explore several mechanisms involved in IFT regulation in future studies. They make some interesting findings in mutants with disrupted function of kinesin-2, BBSome and tubulin modifying enzymes which are interesting to compare with cilia studies in other model organisms. Also, there observation of a possible link between cilia length and IFT speed is potentially fascinating.

Weaknesses:

The central hypothesis of the manuscript, which is cilia length regulation occurs via controlling IFT speed through the modulation of the size of the IFT complex, is supported only with preliminary data and needs stronger evidence.<br /> The authors have robustly shown that the cilia length and IFT train speeds are highly variable between organs and have a strong correlation. With this they hypothesize that IFT train speeds could play a role in determining ciliary length, which is an interesting hypothesis that merits discussion. However, the claim that the cilia length (and IFT velocity) in different organs is different due to difference in the sizes of IFT trains is based on weak evidence. This is based on a marginal difference of IFT train sizes they observe between cilia of crista and spinal cord in immunofluorescence experiments (Fig. 5C). Inferring that this minor difference is key to the striking difference in cilia length and IFT velocity is too bold in my opinion.<br /> To back this hypothesis, they look at ift88 morphants where there is a reduced pool of IFT88 (part of the IFTB1 complex which forms the core of IFT trains, based on multiple cryo-EM studies of IFT trains). Disruption (or reduced number) of IFTB1 complex could indeed lead to IFT trains not being formed properly, which can have an impact on IFT (train size, speed, frequency, etc.) and ciliary structure, as shown by the authors. However, this does not directly imply that under wild-type conditions, cilia in spinal cord have poorly formed slightly shorter IFT trains (cilia length ˜0.9 µm in spinal cord vs ˜1.2 µm in cristae; Fig. 3G) which results in strikingly lower speeds (˜0.4 µm/s in spinal cord vs ˜1.6 µm/s in cristae; Fig. 3G) and shorter cilia (˜3µm in spinal cord vs ˜26µm in cristae; Fig. 3H). Such a claim would require much stronger evidence.

Finally, if IFT train speeds directly correlate with size of IFT train, the authors should be able to see this within the same cilia, i.e., the velocity of a brighter IFT train (larger train) would be higher than the velocity of a dimmer IFT train (smaller train) within the same cilia. This is not apparent from the movies and such a correlation should be verified to make their claim stronger.

Impact:

Overall, I think this work develops an exciting new multicellular model organism to study IFT mechanisms. Zebrafish is a vertebrate where we can perform genetic modifications with relative ease. This could be an ideal model to study not just the role of IFT in connection with ciliary function but also ciliopathies. Further, from an evolutionary perspective, it is fascinating to compare IFT mechanisms in zebrafish with unicellular protists like Chlamydomonas, simple multicellular organisms like C elegans and primary mammalian cell cultures. Having said that, the central hypothesis of the manuscript in not backed with strong evidence and I would recommend the authors to not give too much weight on the hypothesis that IFT train velocity is determined by the size of IFT trains. Given the technological advancements made in this study, I think it is fine if it is a descriptive manuscript and doesn't necessarily need a breakthrough hypothesis based on the marginal correlation they observe.

Reviewer #3 (Public review):

Summary:

An interesting feature of cilia in vertebrates and many, if not all, invertebrates is the striking heterogeneity of their lengths among different cell types. As mutations interfering with ciliary length usually impair ciliary functions, ciliary length appears to be tuned for proper ciliary functions in a given type of cells. Although ciliary length is known to be affected by multiple factors, including intraflagellar transport (IFT), a cilia-specific, train-like bidirectional transportation, and ciliary proteins regulating microtubule dynamics, how it is intrinsically controlled remains largely elusive.

In the manuscript, the authors addressed this question from the angle of IFT by using zebrafish as a model organism. They demonstrated that ectopically expressed Ift88-GFP induced by heat shock treatment was able to sustain the normal development of and the cilia formation in ovl-/- zebrafish that would otherwise be dead by 7 dpf and lack of cilia due to the lack of Ift88, a critical component of IFT-B complex, suggesting a full function of the exogenous protein. They next live imaged Ift88-GFP in wild-type zebrafish larvae to visualize the IFT. Interestingly, they found that both anterograde and retrograde velocities of Ift88-GFP puncta differed in cilia of different cell types (crista, neuromast, pronephric duct, spinal chord, and epidermal cells) and displayed a positive correlation with the inherent length of the cilia. Similar results were obtained with ectopically expressed tdTomato-Ift43 driven by a beta-actin promoter. In the same cell type, however, the velocities of Ift88-GFP puncta did not alter in cilia of different lengths or at different developmental stages. Depletion of proteins such as Bbs4, Ttll3, Ttll6, and Ccp5 did not substantially alter the IFT velocities, excluding contributions of the BBSome or the enzymes involved in tubulin glycylation or glutamylation. They also used a cilia-localized ATP reporter to exclude the possibility of different ciliary ATP concentrations. When they compared the size of Ift88-GFP puncta in crista cilia, which are inherently long, and spinal chord cilia, which are relatively short, by imaging with a STED super-resolution microscope, they noticed a positive correlation between the puncta size, which presumably reflected the size of IFT trains, and the length of the cilia. Furthermore, in morphant larvae with slightly decreased Ift88 levels, judged by the grossly normal body axis, IFT particle sizes, their velocities, and ciliary lengths were all reduced as compared to control morphants. Therefore, they proposed that longer IFT trains facilitate faster IFT to result in longer cilia.

Strengths:

The authors demonstrated that: (1) both anterograde and retrograde IFT velocities can differ markedly in cilia of different cell types in zebrafish larvae; (2) specific IFT velocities are intrinsic to cell types; (3) IFT velocities in different types of cells are positively correlated with inherent ciliary lengths; and (4) IFT velocities are positively correlated with the size of IFT trains. These findings provide both new knowledge on IFT properties in zebrafish and insights that would facilitate understandings on mechanisms underlying the diversity of ciliary lengths in multicellular organisms. The experiments were carefully done and results are generally convincing. The imaging methods for tracing IFT in cilia of multiple cell types in zebrafish larvae are expected to be useful to other researchers in the field.

Weaknesses:

(1) Although the proposed model is reasonable, it is largely based on correlations.<br /> (2) The effects of anti-sense RNA-induced Ift88 downregulation on IFT and ciliary length are artificial. It is unclear whether the levels of one or more IFT components are indeed regulated to control IFT train sizes and ciliary lengths in physiological conditions. Similarly, whether IFT velocities are indeed dictated by the size of IFT trains remains to be clarified.<br /> (3) In the Discussion section, Kif17 is described as an important motor for IFT in mouse olfactory cilia. In the cited literature (Williams et al., 2014), however, Kif17 is reported to be dispensable for IFT in mouse olfactory cilia. This makes the discussions on Kif17 absurd.

Reviewer #1 (Public review):

Summary:

In the manuscript titled "Benchmarking tRNA-Seq quantification approaches by realistic tRNA-Seq data simulation identifies two novel approaches with higher accuracy," Tom Smith and colleagues conducted a comparative evaluation of various sequencing-based tRNA quantification methods. The inherent challenges in accurately quantifying tRNA transcriptional levels, stemming from their short sequences (70-100nt), extensive redundancy (~600 copies in human genomes with numerous isoacceptors and isodecoders), and potential for over 100 post-transcriptional chemical modifications, necessitate sophisticated approaches. Several wet-experimental methods (QuantM-tRNA, mim-tRNA, YAMAT, DM-tRNA, and ALL-tRNA) combined with bioinformatics tools (bowtie2-based, SHRiMP, and mimseq) have been proposed for this purpose. However, their practical strengths and weaknesses have not been comprehensively explored to date. In this study, the authors systematically assessed and compared these methods, considering factors such as incorrect alignments, multiple alignments, misincorporated bases (experimental errors), truncated reads, and correct assignments. Additionally, the authors introduced their own bioinformatic approaches (referred to as Decision and Salmon), which, while not without flaws (as perfection is unattainable), exhibit significant improvements over existing methods.

Strengths:

The manuscript meticulously compares tRNA quantification methods, offering a comprehensive exploration of each method's relative performance using standardized evaluation criteria. Recognizing the absence of "ground-truth" data, the authors generated in silico datasets mirroring common error profiles observed in real tRNA-seq data. Through the utilization of these datasets, the authors gained insights into prevalent sources of tRNA read misalignment and their implications for accurate quantification. Lastly, the authors proposed their own downstream analysis pipelines (Salmon and Decision), enhancing the manuscript's utility.

Reviewer #2 (Public review):

Summary:

The authors provided benchmarking study results on tRNA-seq in terms of read alignment and quantification software with optimal parameterization. This result can be a useful guideline for choosing optimal parameters for tRNA-seq read alignment and quantification.

Strengths:

Benchmarking results for read alignment can be a useful guideline for choosing optimal parameters and mapping strategy (mapping to amino acid) for various tRNAseq.

Weaknesses:

Some explanation on sequencing data analysis pipeline is not clear for general readers.

Reviewer #1 (Public review):

This paper describes proteome solubility analysis (PISA) of 96 compounds in living cells and 70 compounds in cell lysates. A wealth of information related to on- and off-target engagement is uncovered. This work fits well the eLife profile, will be of interest to a large community of proteomics researchers, and thus is likely to be reasonably highly cited.

Reviewer #3 (Public review):

Summary:

This work aims to demonstrate how recent advances in thermal stability assays can be utilised to screen chemical libraries and determine compound mechanism of action. Focusing on 96 compounds with known mechanisms of action, they use the PISA assay to measure changes in protein stability upon treatment with a high dose (10uM) in live K562 cells and whole cell lysates from K562 or HCT116. They intend this work to showcase a robust workflow which can serve as a roadmap for future studies.

Strengths:

The major strength of this study is the combination of live and whole cell lysates experiments. This allows the authors to compare the results from these two approaches to identify novel ligand-induced changes in thermal stability with greater confidence. More usefully, this also enables the authors to separate primary and secondary effects of the compounds within the live cell assay.

The study also benefits from the number of compounds tested within the same framework, which allows the authors to make direct comparisons between compounds.

These two strengths are combined when they compare between CHEK1 inhibitors and suggest that AZD-7762 likely induces secondary destabilisation of CRKL through off-target engagement with tyrosine kinases.

Weaknesses:

One of the stated benefits of PISA compared to the TPP in the original publication (Gaetani et al 2019) was that the reduced number of samples required allows more replicate experiments to be performed. Despite this, the authors of this study performed only duplicate experiments. They acknowledge this precludes use of frequentist statistical tests to identify significant changes in protein stability. Instead, they apply an 'empirically derived framework' in which they apply two thresholds to the fold change vs DMSO: absolute z-score (calculated from all compounds for a protein) > 3.5 and absolute log2 fold-change > 0.2. They state that the fold-change threshold was necessary to exclude non-specific interactors. While the thresholds appear relatively stringent, this approach will likely reduce the robustness of their findings in comparison to an experimental design incorporating more replicates. Firstly, the magnitude of the effect size should not be taken as a proxy for the importance of the effect. They acknowledge this and demonstrate it using their own data for PIK3CB and p38α inhibitors (Figure 2B-C). They have thus likely missed many small, but biological relevant changes in thermal stability due to the fold-change threshold. Secondly, this approach relies upon the fold-changes between DMSO and compound for each protein being comparable, despite them being drawn from samples spread across 16 TMT multiplexes. Each multiplex necessitates a separate MS run and the quantification of a distinct set of peptides, from which the protein-level abundances are estimated. Thus, it is unlikely the fold-changes for unaffected proteins are drawn from the same distribution, which is an unstated assumption of their thresholding approach. The authors could alleviate the second concern by demonstrating that there is very little or no batch effect across the TMT multiplexes. However, the first concern would remain. The limitations of their approach could have been avoided with more replicates and use of an appropriate statistical test. It would be helpful if the authors could clarify if any of the missed targets passed the z-score threshold but fell below the fold-change threshold.

The authors use a single, high, concentration of 10uM for all compounds. Given that many of the compounds may have low nM IC50s, this concentration could be orders of magnitude above the one at which they inhibit their target. This makes it difficult to assess the relevance of the off-target effects identified to clinical applications of the compounds or biological experiments. The authors acknowledge this and use ranges of concentrations for follow-up studies (e.g. Figure 2E-F). Nonetheless, this weakness is present for the vast bulk of the data presented.

Aims achieved, impact and utility:

The authors have achieved their main aim of presenting a workflow which serves to demonstrate the potential value of this approach. However, by using a single high dose of each compound and failing to adequately replicate their experiments and instead applying heuristic thresholds, they have limited the impact of their findings. Their results will be a useful resource for researchers wishing to explore potential off-target interactions and/or mechanisms of action for these 96 compounds but are expected to be superseded by more robust datasets in the near future. The most valuable aspect of the study is the demonstration that combining live cell and whole cell lysate PISA assays across multiple related compounds can help to elucidate the mechanisms of action.

Reviewer #1 (Public review):

Summary:

The manuscript of Odermatt et al. investigates the volatiles released by two species of Desmodium plants and the response of herbivores to maize plants alone or in combination with these species. The results show that Desmodium releases volatiles in both the laboratory and the field. Maize grown in the laboratory also released volatiles, in a similar range. While female moths preferred to oviposit on maize, the authors found no evidence that Desmodium volatiles played a role in lowering attraction to or oviposition on maize.

Strengths:

The manuscript is a response to recently published papers that presented conflicting results with respect to whether Desmodium releases volatiles constitutively or in response to biotic stress, the level at which such volatiles are released, and the behavioral effect it has on the fall armyworm. These questions are relevant as Desmodium is used in a textbook example of pest-suppressive sustainable intercropping technology called push-pull, which has supported tens of thousands of smallholder farmers in suppressing moth pests in maize. A large number of research papers over more than two decades have implied that Desmodium suppresses herbivores in push-pull intercropping through the release of large amounts of volatiles that repel herbivores. This premise has been questioned in recent papers. Odermatt et al. thus contribute to this discussion by testing the role of odors in oviposition choice. The paper confirms that ovipositing FAW preferred maize, and also confirmed that odors released from Desmodium appeared not important in their bioassays.

The paper is a welcome addition to the literature and adds quality headspace analyses of Desmodium from the laboratory and the field. Furthermore, the authors, some of whom have since long contributed to developing push-pull, also find that Desmodium odors are not significant in their choice between maize plants. This advances our knowledge of the mechanisms through which push-pull suppresses herbivores, which is critically important to evolving the technique to fit different farming systems and translating this mechanism to fit with other crops and in other geographical areas.

Weaknesses:

Below I outline the major concerns:

(1) Clear induction of the experimental plants, and lack of reflective discussion around this: from literature data and previous studies of maize and Desmodium, it is clear that the plants used in this study, particularly the Desmodium, were induced. Maize appeared to be primarily manually damaged, possibly due to sampling (release of GLV, but little to no terpenoids, which is indicative of mostly physical stress and damage, for example, one of the coauthor's own paper Tamiru et al. 2011), whereas Desmodium releases a blend of many compounds (many terpenoids indicative of herbivore induction). Erdei et al. also clearly show that under controlled conditions maize, silver leaf and green leaf Desmodium release volatiles in very low amounts. While the condition of the plants in Odermatt et al. may be reflective of situations in push-pull fields, the authors should elaborate on the above in the discussion (see comments) such that the readers understand that the plant's condition during the experiments. This is particularly important because it has been assumed that Desmodium releases typical herbivore-induced volatiles constitutively, which is not the case (see Erdei et al. 2024). This reflection is currently lacking in the manuscript.

(2) Lack of controls that would have provided context to the data: The experiments lack important controls that would have helped in the interpretation:

(2a) The authors did not control the conditions of the plants. To understand the release of volatiles and their importance in the field, the authors should have included controlled herbivory in both maize and Desmodium. This would have placed the current volatile profiles in a herbivory context. Now the volatile measurements hang in midair, leading to discussions that are not well anchored (and should be rephrased thoroughly, see eg lines 183-188). It is well known that maize releases only very low levels of volatiles without abiotic and biotic stressors. However, this changes upon stress (GLVs by direct, physical damage and eg terpenoids upon herbivory, see above). Erdei et al. confirm this pattern in Desmodium. Not having these controls, means that the authors need to put the data in the context of what has been published (see above).

(2b) It would also have been better if the authors had sampled maize from the field while sampling Desmodium. Together with the above point (inclusion of herbivore-induced maize and Desmodium), the levels of volatile release by Desmodium would have been placed into context.

(2c) To put the volatiles release in the context of push-pull, it would have been important to sample other plants which are frequently used as intercrop by smallholder farmers, but which are not considered effective as push crops, particularly edible legumes. Sampling the headspace of these plants, both 'clean' and herbivore-induced, would have provided a context to the volatiles that Desmodium (induced) releases in the field - one would expect unsuccessful push crops to not release any of these 'bioactive' volatiles (although 'bioactive' should be avoided) if these odors are responsible for the pest suppressive effect of Desmodium. Many edible intercrops have been tested to increase the adoption of push-pull technology but with little success.

Because of the lack of the above, the conclusions the authors can draw from their data are weakened. The data are still valuable in the current discussion around push-pull, provided that a proper context is given in the discussion along the points above.

(3) 'Tendency' of the authors to accept the odor hypothesis (i.e. that Desmodium odors are responsible for repelling FAW and thereby reduce infestation in maize under push-pull management) in spite of their own data: The authors tested the effects of odor in oviposition choice, both in a cage assay and in a 'wind tunnel'. From the cage experiments, it is clear that FAW preferred maize over Desmodium, confirming other reports (including Erdei et al. 2024). However, when choosing between two maize plants, one of which was placed next to Desmodium to which FAW has no tactile (taste, structure, etc), FAW chose equally. Similarly in their wind tunnel setup (this term should not be used to describe the assay, see below), no preference was found either between maize odor in the presence or absence of Desmodium. This too confirms results obtained by Erdei et al. (but add an important element to it by using Desmodium plants that had been induced and released volatiles, contrary to Erdei et al. 2024). Even though no support was found for repellency by Desmodium odors, the authors in many instances in the manuscript (lines 30-33, 164-169, 202, 279, 284, 304-307, 311-312, 320) appear to elevate non-significant tendencies as being important. This is misleading readers into thinking that these interactions were significant and in fact confirming this in the discussion. The authors should stay true to their own data obtained when testing the hypothesis of whether odors play a role in the pest-suppressive effect of push-pull.

(4) Oviposition bioassay: with so many assays in close proximity, it is hard to certify that the experiments are independent. Please discuss this in the appropriate place in the discussion.

(5) The wind tunnel has a number of issues (besides being poorly detailed):

(5a) The setup which the authors refer to as a 'wind tunnel' does not qualify as a wind tunnel. First, there is no directional flow: there are two flows entering the setup at opposite sides. Second, the flow is way too low for moths to orient in (in a wind tunnel wind should be presented as a directional cue. Only around 1.5 l/min enters the wind tunnel in a volume of 90 l approximately, which does not create any directional flow. Solution: change 'wind tunnel' throughout the text to a dual choice setup /assay.

(5b) There is no control over the flows in the flight section of the setup. It is very well possible that moths at the release point may only sense one of the 'options'. Please discuss this.

(5c) Too low a flow (1,5 l per minute) implies a largely stagnant air, which means cross-contamination between experiments. An experiment takes 5 minutes, but it takes minimally 1.5 hours at these flows to replace the flight chamber air (but in reality much longer as the fresh air does not replace the old air, but mixes with it). The setup does not seem to be equipped with e.g. fans to quickly vent the air out of the setup. See comments in the text. Please discuss the limitations of the experimental setup at the appropriate place in the discussion.

(5d) The stimulus air enters through a tube (what type of tube, diameter, length, etc) containing pressurized air (how was the air obtained into bags (type of bag, how is it sealed?), and the efflux directly into the flight chamber (how, nozzle?). However, it seems that there is no control of the efflux. How was leakage prevented, particularly how the bags were airtight sealed around the plants?

(5e) The plants were bagged in very narrowly fitting bags. The maize plants look bent and damaged, which probably explains the GLVs found in the samples. The Desmodium in the picture (Figure 5 supplement), which we should assume is at least a representative picture?) appears to be rather crammed into the bag with maize and looks in rather poor condition to start with (perhaps also indicating why they release these volatiles?). It would be good to describe the sampling of the plants in detail and explain that the way they were handled may have caused the release of GLVs.

(6) Figure 1 seems redundant as a main figure in the text. Much of the information is not pertinent to the paper. It can be used in a review on the topic. Or perhaps if the authors strongly wish to keep it, it could be placed in the supplemental material.

Reviewer #2 (Public review):

Based on the controversy of whether the Desmodium intercrop emits bioactive volatiles that repel the fall armyworm, the authors conducted this study to assess the effects of the volatiles from Desmodium plants in the push-pull system on behavior of FAW oviposition. This topic is interesting and the results are valuable for understanding the push-pull system for the management of FAW, the serious pest. The methodology used in this study is valid, leading to reliable results and conclusions. I just have a few concerns and suggestions for improvement of this paper:

(1) The volatiles emitted from D. incanum were analyzed and their effects on the oviposition behavior of FAW moth were confirmed. However, it would be better and useful to identify the specific compounds that are crucial for the success of the push-pull system.

(2) That would be good to add "symbols" of significance in Figure 4 (D).

(3) Figure A is difficult for readers to understand.

(4) It will be good to deeply discuss the functions of important volatile compounds identified here with comparison with results in previous studies in the discussion better.

Reviewer #1 (Public review):

Summary & Assessment:

The catalytic core of the eukaryotic decapping complex consists of the decapping enzyme DCP2 and its key activator DCP1. In humans, there are two paralogs of DCP1, DCP1a and DCP1b, that are known to interact with DCP2 and recruit additional cofactors or coactivators to the decapping complex; however, the mechanisms by which DCP1 activates decapping and the specific roles of DCP1a versus DCP1b, remain poorly defined. In this manuscript, the authors used CRISPR/Cas9-generated DCP1a/b knockout cells to begin to unravel some of the differential roles for human DCP1a and DCP1b in mRNA decapping, gene regulation, and cellular metabolism. While this manuscript presents some new and interesting observations on human DCP1 (e.g. human DCP1a/b KO cells are viable and can be used to investigate DCP1 function; only the EVH1 domain, and not its disordered C-terminal region which recruits many decapping cofactors, is apparently required for efficient decapping in cells; DCP1a and b target different subsets of mRNAs for decay and may regulate different aspects of metabolism), there is one key claim about the role of DCP1 in regulating DCP2-mediated decapping that is still incompletely or inconsistently supported by the presented data in this revised version of the manuscript.

Strengths & well-supported claims:

• Through in vivo tethering assays in CRISPR/Cas9-generated DCP1a/b knockout cells, the authors show that DCP1 depletion leads to significant defects in decapping and the accumulation of capped, deadenylated mRNA decay intermediates.<br /> • DCP1 truncation experiments reveal that only the EVH1 domain of DCP1 is necessary to rescue decapping defects in DCP1a/b KO cells.<br /> • RNA and protein immunoprecipitation experiments suggest that DCP1 acts as a scaffold to help recruit multiple decapping cofactors to the decapping complex (e.g. EDC3, DDX6, PATL1 PNRC1, and PNRC2), but that none of these cofactors are essential for DCP2-mediated decapping in cells.<br /> • The authors investigated the differential roles of DCP1a and DCP1b in gene regulation through transcriptomic and metabolomic analysis and found that these DCP1 paralogs target different mRNA transcripts for decapping and have different roles in cellular metabolism and their apparent links to human cancers. (Although I will note that I can't comment on the experimental details and/or rigor of the transcriptomic and metabolomic analyses, as these are outside my expertise.)

Weaknesses & incompletely supported claims:

(1) One of the key mechanistic claims of the paper is that "DCP1a can regulate DCP2's cellular decapping activity by enhancing DCP2's affinity to RNA, in addition to bridging the interactions of DCP2 with other decapping factors. This represents a pivotal molecular mechanism by which DCP1a exerts its regulatory control over the mRNA decapping process." Similar versions of this claim are repeated in the abstract and discussion sections. However, this claim appears to be at odds with the observations that: (a) in vitro decapping assays with immunoprecipitated DCP2 show that DCP1 knockout does not significantly affect the enzymatic activity of DCP2 (Fig 2C&D; I note that there may be a very small change in DCP2 activity shown in panel D, but this may be due to slightly different amounts of immunoprecipitated DCP2 used in the assay); and (b) the authors show only weak changes in relative RNA levels immunoprecipitated by DCP2 with versus without DCP1 (~2-3 fold change in Fig 3H, where expression of the EVH1 domain, previously shown in this manuscript to fully rescue the DCP1 KO decapping defects in cells, looks to be almost within error of the control in terms of increasing RNA binding). If DCP1 pivotally regulates decapping activity by enhancing RNA binding to DCP2, why is no difference in in vitro decapping activity observed in the absence of DCP1, and very little change observed in the amounts of RNA immunoprecipitated by DCP2 with the addition of the DCP1 EVH1 domain?

In the revised manuscript and in their response to initial reviews, the authors rightly point out that in vivo effects may not always be fully reflected by or recapitulated in in vitro experiments due to the lack of cellular cofactors and simpler environment for the in vitro experiment, as compared to the complex environment in the cell. I fully agree with this of course! And further completely agree with the authors that this highlights the critical importance of in cell experiments to investigate biological functions and mechanisms! However, because the in vitro kinetic and IP/binding data both suggest that the DCP1 EVH1 domain has minimal to no effects on RNA decapping or binding affinity, while the in cell data suggest the EVH1 domain alone is sufficient to rescue large decapping defects in DCP1a/b KO cells (and that all the decapping cofactors tested were dispensable for this), I would argue there is insufficient evidence here to make a claim that (maybe weakly) enhanced RNA binding induced by DCP1 is what is regulating the cellular decapping activity. Maybe there are as-yet-untested cellular cofactors that bind to the EVH1 domain of DCP1 that change either RNA recruitment or the kinetics of RNA decapping in cells; we can't really tell from the presented data so far. Furthermore, even if it is the case that the EVH1 domain modestly enhances RNA binding to DCP2, the authors haven't shown that this effect is what actually regulates the large change in DCP2 activity upon DCP1 KO observed in the cell.

Overall, while I absolutely appreciate that there are many possible reasons for the differences observed in the in vitro versus in cell RNA decapping and binding assays, because this discrepancy between those data exists, it seems difficult to draw any clear conclusions about the actual mechanisms by which DCP1 helps regulate RNA decapping by DCP2. For example, in the cell it could be that DCP1 enhances RNA binding, or recruits unidentified cofactors that themselves enhance RNA binding, or that DCP1 allosterically enhances DCP2-mediated decapping kinetics, or a combination of these, etc; my point is that without in vitro data that clearly support one of those mechanisms and links this mechanism back to cellular DCP2 decapping activity (for example, in cell data that show EVH1 mutants that impair RNA binding fail to rescue DCP1 KO decapping defects), it's difficult to attribute the observed in cell effects of DCP1a/b KO and rescue by the EVH1 domain directly to enhancement of RNA binding (precisely because, as the authors describe, the decapping process and regulation may be very complex in the cell!).

This contradiction between the in vitro and in-cell decapping data undercuts one of the main mechanistic takeaways from the first half of the paper; I still think this conclusion is overstated in the revised manuscript.

Additional minor comment:

• Related to point (1) above, the kinetic analysis presented in Fig 2C shows that the large majority of transcript is mostly decapped at the first 5 minute timepoint; it may be that DCP2-mediated decapping activity is actually different in vitro with or without DCP1, but that this is being missed because the reaction is basically done in less than 5 minutes under the conditions being assayed (i.e. these are basically endpoint assays under these conditions). It may be that if kinetics were done under conditions to slow down the reaction somewhat (e.g. lower Dcp2 concentration, lower temperatures), so that more of the kinetic behavior is captured, the apparent discrepancy between in vitro and in-cell data would be much less. Indeed, previous studies have shown that in yeast, Dcp1 strongly activates the catalytic step (kcat) of decapping by ~10-fold, and reduces the KM by only ~2 fold (Floor et al, NSMB 2010). It might be beneficial to use purified proteins here, if possible, to better control reaction conditions.

In their response to initial reviews, the authors comment that they tried to purify human DCP2 from E coli, but were unable to obtain active enzyme in this way. Fair enough! I will only comment that just varying the relative concentration of immunoprecipitated DCP2 would likely be enough to slow down the reaction and see if activity differences are seen in different kinetic regimes, without the need to obtain fully purified / recombinant Dcp2.

Reviewer #1 (Public review):

Summary

Das and Menon describe an analysis of a large open-source iEEG dataset (UPENN-RAM). From encoding and recall phases of memory tasks, they analyzed power and phase-transfer entropy as a measure of directed information flow in regions across a hypothesized tripartite network system. The anterior insula (AI) was found to have heightened high gamma power during encoding and retrieval, which corresponded to suppression of high gamma power in medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) during encoding but not recall. In contrast, directed information flow from (but not to) AI to mPFC and PCC is high during both time periods when PTE is analyzed with broadband but not narrowband activity. They claim that these findings significantly advance an understanding of how network communication facilitates cognitive operations during memory tasks, and that the AI of the salience network (SN) is responsible for influencing both the frontoparietal network (FPN) and default-mode network (DMN) during memory encoding and retrieval.

I find this question interesting and important and agree with the authors that iEEG presents a unique opportunity to investigate the temporal dynamics within network nodes. Their findings convey intriguing information about the structure and order of communication between network regions during on-task cognition in general (though, perhaps not specific to memory - see Weaknesses), with the AI of the SN ostensibly playing an important role in possibly influencing the DMN and FPN.

Strengths

- The authors present results from an impressively-sized iEEG sample. For reader context, this type of invasive human data is difficult and time-consuming to collect and many similar studies in high-level journals include 5-20 participants, typically not all of whom have electrodes in all regions of interest. It is excellent that they have been able to leverage open-source data in this way.<br /> - Preprocessing of iEEG data also seems sensible and appropriate based on field standards.<br /> - The authors tackle the replication issues inherent in much of the literature by replicating findings across task contexts, demonstrating that the principles of network communication evidenced by their results generalize in multiple task memory contexts. Again, the number of iEEG patients who have multiple tasks' worth of data is impressive.<br /> - Though the revised manuscript presents a broader and more novel investigation of the tripartite network's role in memory encoding and retrieval (as opposed to cognitive control of memory) the authors now thoroughly review the literature motivating this investigation of open-source data.

Weaknesses

- As the authors discuss, it is currently unclear if the directed information flow from AI to DMN and FPN nodes truly arises from memory-associated processes as opposed to more general attentional and cognitive demands, especially given that information flow does not relate meaningfully to task performance (whether memory retrieval is successful or not). I also note this is a concern because - though the authors have now demonstrated that information flow is increased compared to an off-task baseline - influences of AI on DMN or FPN were not increased relative to baseline epochs during the task in the original preprint version, again suggesting these effects may not be specific to the memory component of the analyzed tasks. The authors have thoughtfully noted in the Discussion several ways that experimental design can be improved in future studies to address this limitation.

Reviewer #1 (Public review):

The authors survey the ultrastructural organization of glutamatergic synapses by cryo-ET and image processing tools using two complementary experimental approaches. The first approach employs so-called "ultra-fresh" preparations of brain homogenates from a knock-in mouse expressing a GFP-tagged version of PSD-95, allowing Peukes and colleagues to specifically target excitatory glutamatergic synapses. In the second approach, direct in-tissue (using cortical and hippocampal regions) targeting of the glutamatergic synapses employing the same mouse model is presented. In order to ascertain whether the isolation procedure causes any significant changes in the ultrastructural organization (and possibly synaptic macromolecular organization) the authors compare their findings using both of these approaches. The quantitation of the synaptic cleft height reveals an unexpected variability, while the STA analysis of the ionotropic receptors provides insights into their distribution with respect to the synaptic cleft.

The main novelty of this study lies in the continuous claims by the authors that the sample preservation methods developed here are superior to any others previously used. This leads them as well to systematically downplay or directly ignore a substantial body of previous cryo-ET studies of synaptic structure. Without comparisons with the cryo-ET literature, it is very hard to judge the impact of this work in the field. Furthermore, the data does not show any better preservation in the so-called "ultra-fresh" preparation than in the literature, perhaps to the contrary as synapses with strangely elongated vesicles are often seen. Such synapses have been regularly discarded for further analysis in previous synaptosome studies (e.g. Martinez-Sanchez 2021). Whilst the targeting approach using a fluorescent PSD95 marker is novel and seems sufficiently precise, the authors use a somewhat outdated approach (cryo-sectioning) to generate in-tissue tomograms of poor quality. To what extent such tomograms can be interpreted in molecular terms is highly questionable. The authors also don't discuss the physiological influence of 20% dextran used for high-pressure freezing of these "very native" specimens.

Lastly, a large part of the paper is devoted to image analysis of the PSD which is not convincing (including a somewhat forced comparison with the fixed and heavy-metal staining room temperature approach). Despite being a technically challenging study, the results fall short of expectations.

Reviewer #2 (Public review):

Summary:

The authors set out to visualize the molecular architecture of the adult forebrain glutamatergic synapses in a near-native state. To this end, they use a rapid workflow to extract and plunge-freeze mouse synapses for cryo-electron tomography. In addition, the authors use knockin mice expression PSD95-GFP in order to perform correlated light and electron microscopy to clearly identify pre- and synaptic membranes. By thorough quantification of tomograms from plunge- and high-pressure frozen samples, the authors show that the previously reported 'post-synaptic density' does not occur at high frequency and therefore not a defining feature of a glutamatergic synapse.

Subsequently, the authors are able to reproduce the frequency of post-synaptic density when preparing conventional electron microscopy samples, thus indicating that density prevalence is an artifact of sample preparation. The authors go on to describe the arrangement of cytoskeletal components, membraneous compartments, and ionotropic receptor clusters across synapses.

Demonstrating that the frequency of the post-synaptic density in prior work is likely an artifact and not a defining feature of glutamatergic synapses is significant. The descriptions of distributions and morphologies of proteins and membranes in this work may serve as a basis for the future of investigation for readers interested in these features.

Strengths:

The authors perform a rigorous quantification of the molecular density profiles across synapses to determine the frequency of the post-synaptic density. They prepare samples using two cryogenic electron microscopy sample preparation methods, as well as one set of samples using conventional electron microscopy methods. The authors can reproduce previous reports of the frequency of the post-synaptic density by conventional sample preparation, but not by either of the cryogenic methods, thus strongly supporting their claim.

Reviewer #3 (Public review):

Summary:

The authors use cryo-electron tomography to thoroughly investigate the complexity of purified, excitatory synapses. They make several major interesting discoveries: polyhedral vesicles that have not been observed before in neurons; analysis of the intermembrane distance, and a link to potentiation, essentially updating distances reported from plastic-embedded specimen; and find that the postsynaptic density does not appear as a dense accumulation of proteins in all vitrified samples (less than half), a feature which served as a hallmark feature to identify excitatory plastic-embedded synapses.

Strengths:

(1) The presented work is thorough: the authors compare purified, endogenously labeled synapses to wild-type synapses to exclude artifacts that could arise through the homogenation step, and, in addition, analyse plastic embedded, stained synapses prepared using the same quick workflow, to ensure their findings have not been caused by way of purification of the synapses. Interestingly, the 'thick lines of PSD' are evident in most of their stained synapses.

(2) I commend the authors on the exceptional technical achievement of preparing frozen specimens from a mouse within two minutes.

(3) The approaches highlighted here can be used in other fields studying cell-cell junctions.

(4) The tomograms will be deposited upon publication which will enable neurobiologists and researchers from other fields to carry on data evaluation in their field of expertise since tomography is still a specialized skill and they collected and reconstructed over 100 excellent tomograms of synapses, which generates a wealth of information to be also used in future studies.

(5) The authors have identified ionotropic receptor positions and that they are linked to actin filaments, and appear to be associated with membrane and other cytosolic scaffolds, which is highly exciting.

(6) The authors achieved their aims to study neuronal excitatory synapses in great detail, were thorough in their experiments, and made multiple fascinating discoveries. They challenge dogmas that have been in place for decades and highlight the benefit of implementing and developing new methods to carefully understand the underlying molecular machines of synapses.

Weaknesses:

The authors show informative segmentations in their figures but none have been overlayed with any of the tomograms in the submitted videos. It would be helpful for data evaluation to a broad audience to be able to view these together as videos to study these tomograms and extract more information. Deposition of segmentations associated with the tomgrams would be tremendously helpful to Neurobiologists, cryo-ET method developers, and others to push the boundaries.

Impact on community:

The findings presented by Peukes et al. pertaining to synapse biology change dogmas about the fundamental understanding of synaptic ultrastructure. The work presented by the authors, particularly the associated change of intermembrane distance with potentiation and the distinct appearance of the PSD as an irregular amorphous 'cloud' will provide food for thought and an incentive for more analysis and additional studies, as will the discovery of large membranous and cytosolic protein complexes linked to ionotropic receptors within and outside of the synaptic cleft, which are ripe for investigation. The findings and tomograms available will carry far in the synapse fields and the approach and methods will move other fields outside of neurobiology forward. The method and impactful results of preparing cryogenic, unlabeled, unstained, near-native synapses may enable the study of how synapses function at high resolution in the future.

Joint Public Review:

Summary

Based on i) the documented role of FMNL1 proteins in IS formation; ii) their ability to regulate F-actin dynamics; iii) the implication of PKCdelta in MVB polarization to the IS and FMNL1beta phosphorylation; and iv) the homology of the C-terminal DAD domain of FMNL1beta with FMNL2, where a phosphorylatable serine residue regulating its auto-inhibitory function had been previously identified, the authors have addressed the role of S1086 in the FMNL1beta DAD domain in F-actin dynamics, MVB polarization and exosome secretion, and investigated the potential implication of PKCdelta, which they had previously shown to regulate these processes, in FMNL1beta S1086 phosphorylation. They demonstrate that FMNL1beta is indeed phosphorylated on S1086 in a PKCdelta-dependent manner and that S1086-phosphorylated FMNL1beta acts downstream of PKCdelta to regulate centrosome and MVB polarization to the IS and exosome release. They provide evidence that FMNL1beta accumulates at the IS where it promotes F-actin clearance from the IS center, thus allowing for MVB secretion.

Strengths

The work is based on a solid rationale, which includes previous findings by the authors establishing a link between PKCdelta, FMNL1beta phosphorylation, synaptic F-actin clearance and MVB polarization to the IS. The authors have thoroughly addressed the working hypotheses using robust tools. Among these, of particular value is an expression vector that allows for simultaneous RNAi-based knockdown of the endogenous protein of interest (here all FMNL1 isoforms) and expression of wild-type or mutated versions of the protein as YFP-tagged proteins to facilitate imaging studies. The imaging analyses, which are the core of the manuscript, have been complemented by immunoblot and immunoprecipitation studies, as well as by the measurement of exosome release (using a transfected MVB/exosome reporter to discriminate exosomes secreted by T cells).

Weaknesses

As stated in the title of the article, the main findings have been obtained in clones of Jurkat cells and have not been confirmed in primary T cells.

Reviewer #1 (Public review):

Summary:

This is an important contribution to the field of molecular embryology of the lung. The authors introduce a novel mesenchymally expressed molecule Svep1. Knocking it out in mice produces a profoundly hypoplastic phenotype which can be rescued in vitro. Svep1 interacts with the FGF signaling complex to control differentiation and expression of smooth muscle in lung mesenchyme, thereby affecting proximal-distal patterning of the airway branches by acting as a putative branch suppressor.

Strengths:

The study shows strong evidence in mouse knockouts, in vitro embryonic lung culture as well as gene expression and in vitro rescue studies that confirm a key role for Svep1. It is a beautiful piece of work and an important contribution to our understanding of early lung branching morphogenesis.

Weaknesses:

Claiming a possible therapeutic role for this gene is a bit far-fetched at the present state of the art.

Reviewer #2 (Public review):

Summary:

In an effort to elucidate the role of the ECM protein Svep1 in lung development, Foxworth and colleagues have generated a Svep1 mutant (lacking exon 8). Based on their developmental analyses of branching morphogenesis and expression of epithelial, mesenchymal, and mesothelial markers in these mutants, the authors conclude that Svep1 is essential for normal lung growth, morphogenesis, and patterning. They propose that the Svep1 protein regulates, in part, FGF9 signalling. Overall, the paper demonstrates that the ECM is important for lung development and tries to implicate the ECM in the regulation of epithelial-mesenchymal interactions during lung development.

Strengths:

The strengths of this paper are the careful spatiotemporal characterization of 1) lung growth 2) branching morphogenesis 3) epithelial marker expression. The differential perturbation of growth and branching morphogenesis along the D-V axis and the progressive perturbation of branching morphogenesis are both very interesting and noteworthy phenotypes.

Weaknesses:

The weakness of this paper is that it does not present a convincing explanation for how Svep1 regulates any of the phenotypes described. In this regard, a demonstration of a genetic interaction between Svep1 and FGF9 mutants or a careful characterization of a tissue-specific knockdown of Svep1, could be insightful. In addition, a comparison of the phenotype of Svep1 mutants and the phenotypes of other mutants affecting ECM components would be worthwhile.

A minor weakness is that the title of the paper is not fully supported by the data presented. While the defects in the morphogenesis of the distal lung in Svep1 mutants presage a defect in alveolar differentiation, this cannot be formally demonstrated since the animals die soon after birth.

Reviewer #1 (Public review):

Summary:

The manuscript by Zhang et al. analyzed 17 specimens of Cindarella eucalla with 3D technology and discussed the anatomical findings, the relationship to other artiopods, and the ecology of the animal. The results are excellent and the findings are very interesting. However, the discussion needs to be extended, as the point the authors are trying to make is not always clear. I also recommend some restructuring of the discussion. Overall this is an important manuscript, and I'm looking forward to reading the edited version.

Strengths:

The analyses, the 3D data is excellent and provides new information.

Weaknesses:

The discussion - the authors provide information for the findings, but do not discuss them in detail. More information is needed.

Reviewer #2 (Public review):

Summary:

Zhang et al. present very well-illustrated specimens of the artiopodan Cinderella eucalla from the Chengjiang Biota. Multiple specimens are shown with preserved appendages, which is rare for artiopodans and will greatly help our understanding of this taxon. The authors use CT scanning to reveal the ventral organization of this taxon. The description of the taxon needs some modification, specifically expansion of the gut and limb morphology. The conclusion that Cinderella was a fast-moving animal is very weak, comparisons with extant fast animals and possibly FEA analyses are necessary to support such a claim. Although the potential insights provided by such well-preserved fossils could be valuable, the claims made are tenuous and based on the available evidence presented herein.

Strengths:

The images produced through CT scanning specimens reveal the very fine detail of the appendages and are well illustrated. Specimens preserve guts and limbs, which are informative both for the phylogenetic position and ecology of this taxon. The limbs are very well preserved, with protopodite, exopodite, and endopodites visible. Addressing the weaknesses below will make the most of this compelling data that demonstrates the morphology of the limbs well.

Weaknesses:

Although this paper includes very well-illustrated fossils, including new information on the eyes, guts, and limbs of Cinderella, the data are not fully explained, and the conclusions are weakly supported.

The authors suggest the preservation of complex ramifying diverticular, but it should be better illustrated and the discussion of the gut diverticulae should be longer, especially as gut morphology can provide insights into the feeding strategy.

The conclusion that Cinderella eucalla was fast, sediment feeding in a muddy environment, is not well supported. These claims seem to be tenuously made without any evidence to support them. The authors should add a new section in the discussion focused on feeding ecology where they explicitly compare the morphology to suspension-feeding artiopodans to justify whether it fed that way or not. To further explore feeding, the protopodite morphology needs to be more carefully described and compared to other known taxa. The function of endites on the endopodite to stir up sediment for particle feeding in a muddy environment would also need to be more thoroughly discussed and compared with modern analogs. The impact of their findings is not highlighted in the discussion, which is currently more of a review of what has been previously said and should focus more on what insights are provided by the great fossils illustrated by the authors.

The authors argue that their data supports fast escaping capabilities, but it is not clear how they reached that conclusion based on the data available. Is there a way this can be further evaluated? The data is impressive, so including comparisons with extant taxa that display fast escaping strategies would help the authors make their case more compelling. The authors also claim that the limbs of Cinderella are strong, again this conclusion is unclear. Comparison with the limbs of other taxa to show their robustness would be useful. To actually test how these limbs deal with the force and strain applied to them by a sudden burst of movement, the authors could conduct Finite Element Analyses.

Reviewer #3 (Public review):

This paper provides an interesting description of the ventral parts of the Cambrian xandarellid Cindarella eucalla, derived from exceptionally preserved specimens of the Chengjiang Biota. These morphological data are useful for our broad understanding and future research on Xandarellida, and are generally well-represented in the description and accompanying figures. The strengths of this work rest in this morphological description of exceptional fossil material, and this is generally well supported. In addition, the authors put this description in the context of the morphology of other xandarellids and Cambrian arthropod groups, with most of these parallels being useful and reasonably supported, though in several places homology is assumed and this currently lacks evidence. The manuscript goes on to use these morphological data and comparisons to other groups (particularly trilobites) to make suggestions for the ecology of Cindarella eucalla and other xandarellids. The majority of my comments on this work relate to this latter aim - the ecological conclusions drawn are generally derived through morphological comparisons, where a specific morphology has been suggested as an adaption to a particular ecological function in another extinct arthropod group. However, the original suggestions for ecological function are untested, and so remain hypotheses. Despite this, they are frequently presented as truisms to enable ecological conclusions to be drawn for Cindarella eucalla. I have listed my comments and queries on the study below for the authors to address or respond to, and I hope they are useful to the authors.

Comments:

There are a number of ecological and functional morphology conclusions stated that seem put too strongly to be considered sufficiently supported by the evidence given. These relate to both the description of C. eucalla, and comparisons to other extinct arthropod taxa (notably trilobites). Many of these latter statements are assumptions of functional morphology, and should not be repeated as truisms, rather than they represent suggested functions and ecologies based on the known morphological descriptions. This aspect occurs throughout the article, and, for me, is the primary concern.

Reviewer #1 (Public review):

Summary:

In this work, a screening platform is presented for rapid and cost-effective screening of candidate genes involved in Fragile Bone Disorders. The authors validate the approach of using crispants, generating FO mosaic mutants, to evaluate the function of specific target genes in this particular condition. The design of the guide RNAs is convincingly described, while the effectiveness of the method is evaluated to 60% to 92% of the respective target genes being presumably inactivated. Thus, injected F0 larvae can be directly used to investigate the consequences of this inactivation.

Skeletal formation is then evaluated at 7dpf and 14dpf, first using a transgenic reporter line revealing fluorescent osteoblasts, and second using alizarin-red staining of mineralized structures. In general, it appears that the osteoblast-positive areas are more often affected in the crispants compared to the mineralized areas, an observation that appears to correlate with the observed reduced expression of bglap, a marker for mature osteoblasts, and the increased expression of col1a1a in more immature osteoblasts.

Finally, the injected fish (except two lines that revealed high mortality) are also analyzed at 90dpf, using alizarin red staining and micro-CT analysis, revealing an increased incidence of skeletal deformities in the vertebral arches, fractures, as well as vertebral fusions and compressions for all crispants except those for daam2. Finally, the Tissue Mineral Density (TMD) as determined by micro-CT is proposed as an important marker for investigating genes involved in osteoporosis.

Taken together, this manuscript is well presented, the data are clear and well analyzed, and the methods are well described. It makes a compelling case for using the crispant technology to screen the function of candidate genes in a specific condition, as shown here for bone disorders.

Strengths:

Strengths are the clever combination of existing technologies from different fields to build a screening platform. All the required methods are comprehensively described.

Weaknesses:

One may have wished to bring one or two of the crispants to the stage of bona fide mutants, to confirm the results of the screening, however, this is done for some of the tested genes as laid out in the discussion.

Reviewer #2 (Public review):

Summary:

More and more genes and genetic loci are being linked to bone fragility disorders like osteoporosis and osteogenesis imperfecta through GWAS and clinical sequencing. In this study, the authors seek to develop a pipeline for validating these new candidate genes using crispant screening in zebrafish. Candidates were selected based on GWAS bone density evidence (4 genes) or linkage to OI cases plus some aspect of bone biology (6 genes). NGS was performed on embryos injected with different gRNAs/Cas9 to confirm high mutagenic efficacy and off-target cutting was verified to be low. Bone growth, mineralization, density, and gene expression levels were carefully measured and compared across crispants using a battery of assays at three different stages.

Strengths:

(1) The pipeline would be straightforward to replicate in other labs, and the study could thus make a real contribution towards resolving the major bottleneck of candidate gene validation.

(2) The study is clearly written and extensively quantified.

(3) The discussion attempts to place the phenotypes of different crispant lines into the context of what is already known about each gene's function.

(4) There is added value in seeing the results for the different crispant lines side by side for each assay.

Weaknesses:

(1) The study uses only well-established methods and is strategy-driven rather than question/hypothesis-driven.

(2) Some of the measurements are inadequately normalized and not as specific to bone as suggested:

(a) The measurements of surface area covered by osteoblasts or mineralized bone (Figure 1) should be normalized to body size. The authors note that such measures provide "insight into the formation of new skeletal tissue during early development" and reflect "the quantity of osteoblasts within a given structure and [is] a measure of the formation of bone matrix." I agree in principle, but these measures are also secondarily impacted by the overall growth and health of the larva. The surface area data are normalized to the control but not to the size/length of each fish - the esr1 line in particular appears quite developmentally advanced in some of the images shown, which could easily explain the larger bone areas. The fact that the images in Figure S5 were not all taken at the same magnification further complicates this interpretation.

(b) Some of the genes evaluated by RT-PCR in Figure 2 are expressed in other tissues in addition to bone (as are the candidate genes themselves); because whole-body samples were used for these assays, there is a nonzero possibility that observed changes may be rooted in other, non-skeletal cell types.

(3) Though the assays evaluate bone development and quality at several levels, it is still difficult to synthesize all the results for a given gene into a coherent model of its requirement.

(4) Several additional caveats to crispant analyses are worth noting:

(a) False negatives, i.e. individual fish may not carry many (or any!) mutant alleles. The crispant individuals used for most assays here were not directly genotyped, and no control appears to have been used to confirm successful injection. The authors therefore cannot rule out that some individuals were not, in fact, mutagenized at the loci of interest, potentially due to human error. While this doesn't invalidate the results, it is worth acknowledging the limitation.

(b) Many/most loci identified through GWAS are non-coding and not easily associated with a nearby gene. The authors should discuss whether their coding gene-focused pipeline could be applied in such cases and how that might work.

Reviewer #3 (Public review):

Summary:

The manuscript "Crispant analysis in zebrafish as a tool for rapid functional screening of disease-causing genes for bone fragility" describes the use of CRISPR gene editing coupled with phenotyping mosaic zebrafish larvae to characterize functions of genes implicated in heritable fragile bone disorders (FBDs). The authors targeted six high-confident candidate genes implicated in severe recessive forms of FBDs and four Osteoporosis GWAS-implicated genes and observed varied developmental phenotypes across all crispants, in addition to adult skeletal phenotypes.

A major strength of the paper is the streamlined method that produced significant phenotypes for all candidate genes tested.

A major weakness is a lack of new insights into underlying mechanisms that may contribute to disease phenotypes, nor any clear commonalities across gene sets. This was most evident in the qRT-PCR analysis of select skeletal developmental genes, which all showed varied changes in fold and direction, but with little insight into the implications of the results.

Ultimately, the authors were able to show their approach is capable of connecting candidate genes with perturbation of skeletal phenotypes. It was surprising that all four GWAS candidate genes (which presumably were lower confidence) also produced a result. These authors have previously demonstrated that crispants recapitulate skeletal phenotypes of stable mutant lines for a single gene, somewhat reducing the novelty of the study.