Reviewer #2 (Public Review):

Schwann cells actively repair and regenerate peripheral nerves following tissue injury. Central to this process is the collective cell migration of 'cords' of Schwann cells, which guide the regenerating axons across an injury site. Previously published research from the Lloyd lab shows that at the injury site, Schwann cell cords are maintained via N-cadherin-based cell-cell adhesions; however, when cultured under low density conditions, Schwann cells display cell repulsion and contact inhibition of locomotion (CIL) phenotypes, suggesting Schwann cell behaviour is plastic. In this study, Hoving, Lloyd and colleagues build upon their previous work to show that Slit2/3/Robo signalling triggers cell repulsion between Schwann cells in an N-cadherin-dependent manner. This in turn induces contact inhibition of locomotion to propel Schwann cells to migrate collectively and with direction. The authors show that N-cadherin has a dual function in Schwann cell migration: to keep migrating Schwann cells together as a group, and concomitantly present Slit2/3 repulsive cues to cells to trigger cell repulsion locally. Their data also show that extracellular N-cadherin is required for cell repulsion, independent of cell-cell adhesion functions. The authors use a combination of in vitro Schwann cell cultures and live cell imaging, with an ex vivo precision cut tissue slice system to show that Slit2/3-dependent CIL underpins proper Schwann cell migration in an injury model.

This is a very well executed and important study, which provides new insights into mechanisms of CIL and places CIL in the context of tissue repair and regeneration in adult tissues. The experiments are well designed, and the main findings and conclusions are based on robust and convincing data.

Reviewer #3 (Public Review):

The submitted paper by Hoving et al addresses the role of N-cadherin in Schwann cell collective cell migration and its previously unknown relationship with the slit/robo signaling pathway. The main conclusion is that N-cadherin has two distinct functions. One that is dependent on its classical role as a cell-cell junction protein promoting cell clustering and one that promotes cell repulsion and polarity independently of the formation of cell adhesion complexes. The second function is mediated by the Slit/Robo pathway. It is proposed that N-cadherin and Glypican-4 act together to present Slit2/3 at the surface of Schwann cells in order to trigger Robo signaling on neighboring cells.

The data about N-cadherin loss of function and the associated rescue experiments with the various truncated forms of N-cadherin are well substantiated by proper controls for efficiency and specificity. They show that the extracellular domain of Ncadherin is the one required for the repulsive effect. The experiments performed to distinguish the roles in adhesion and repulsion seem clear and conclusive. In addition, the fact the slit signal needs to be provided in a polarized manner for directional migration to occur is also clearly demonstrated in vitro and on slice assays. Overall the model that Ncadherin plays two different roles, a repulsive one via presentation of slit at the cell surface and a cell adhesion one via formation of adherens junctions, is well supported by the data and will be of interest beyond the subfield of the authors.

However, other parts of the manuscript seem weaker. If N-cadherin presentation of the Slit signal is so critical why are repulsion rates still very high in cells without N-cadherin? Same is observed with Glypican4 knockdowns. In both loss of function 50% of cell collisions lead to repulsion (compared to 70% amongst control cells). While significant such drop remains modest. The authors propose a cooperative role of Glypican-4 and N-cadherin at the cell surface as co-binding factors for Slit2/3 but they have not checked whether double knockdown of N-cad and Glypican4 might have a stronger effect. Could Glypican and N-cadherin present Slit at the cell surface independently in a somewhat redundant manner? Can Glypican and Slit interact physically in absence of N-cadherin? They also have not further analyzed the putative colocalization fo Ncad and Glypican at the cell surface.

The data supporting a role for N-cadherin in Slit's trafficking to the cell surface seem also circumstantial. While western blot data seem to indicate no change in Slit protein level after N-cad knockdown, immunostaining for Slit in such condition show a dramatic loss of Slit signal. These two independent data sets are difficult to reconcile and are not designed to address whether Slit reaches the cell surface in control or N-cadherin knockdown conditions.

If Slit signaling is so critical for repulsion why in double sit2/3 knockdown 40% of collisions still lead to repulsion. Also, no analysis of cell collision are provided upon Robo1/2 knockdown for comparison with Slit knockdowns. Altogether, these relatively mild effects of n-cad, slit or glypican knockdown on repulsion seem to indicate that other signals might contribute to contact-inhibition and polarization/repulsion of cells upon physical contact but this is unfortunately not discussed. All statements related to cell polarity stem from the overall cell morphology without being substantiated by actual polarity analysis (using markers such as detection of Rac-GTP or using a proxy such as the golgi-nucleus axis). The authors present the cell cluster generated after Sox2 expression and Sox2 + exposure to recombinant Slit2 as lacking polarity, however in one case cells do not present any flat membrane at their free edge whereas in the other case they do. This suggests a minimal cell polarity with a protrusive-like organization away from the contact. Finally, Robo1/2 siRNA knockdown are used but contrary to the other loss of functions it seems that controls for knockdown efficiency/specificity were not provided.

Therefore, while the study is overall well documented and based on solid data, some weaknesses exist.

The overall topic is clearly of broad interest as N-cadherin is protein essential in various biological settings from development to disease but the range of its biological functions remains to be fully explored. This study clearly adds to the current knowledge and how N-cadherin might act in vivo and in particular how it could mediate crosstalks between various signaling pathways.

Reviewer #1(Public Review):

In this manuscript the authors report an experiment to assess how training on a perceptual task may not only increase performance on that task but impact on the appearance of the trained stimuli. They compare discrimination performance, coherence thresholds, and estimation biases for random dot motion direction relative to horizontal rightward in three groups of observers before and after 3 days in which they either trained on a discrimination task, an estimation task, or did not train. The authors report significant increases in discrimination performance post training compared to not training. They also report increases in estimation biases when assessed as the average estimate (over a bimodal distribution that crosses 0) but not when assessed as the mode of the bimodal distribution. They conclude that training resulted in "increases in already-large estimation biases away from horizontal".

The methods and results are strengthened by the combination of classical psychophysical techniques and sophisticated computational modelling. One weakness is the possibility is misleading summary statistics when dealing with bimodal distributions. Convincing evidence that observers perceived stimulus directions as further from horizontal (in the absolute sense) following training is not presented in the current manuscript. Irrespective, this work is likely to impact the field.

Reviewer #2 (Public Review):

It is well-known that repeated exposure to perceptual stimuli improves discrimination performance, but less is known about the effects on perceptual appearance. In the present work, the authors tackle this question and focus on one particular effect on perceptual appearance termed boundary avoidance, i.e. the tendency to perceive (or report) a stimulus as biased away from a discrimination boundary.

In the study, participants performed either a motion discrimination task (clockwise or counterclockwise with respect to a reference axis) or an estimation task (reproducing the orientation of the motion stimulus). Participants were divided in three groups which either i) trained on the discrimination task, ii) trained on the estimation task or iii) received no training (control group). Performance in both tasks was assessed prior and after training. The main behavioral finding is that training (which did not involve feedback) improved discrimination performance and increased estimation precision, but at the same time appeared to increase the boundary avoidance effect. Thus, the authors conclude that perceptual learning improved performance at the cost of appearance.

To explain these effects, the authors created a computational model in which performance improvements were implemented as a gain increase of neurons sensitive to the trained motion directions. Repulsive biases away from the reference orientation were implemented by a combination of two modeling choices: i) Even during estimation, participants perform an implicit categorization such that they assume that their percept was created by a stimulus in line with their categorization (clockwise or counterclockwise). This effectively biases their response away from the boundary. ii) There is an abundance of neurons tuned to the horizontal reference axis (the "boundary") which likewise leads to a repulsive bias. Overall, the authors conclude that the model was able to explain the major behavioral effects, including the a priori presence of repulsive biases, the increase in performance, the increase in estimation precision and the increase of the repulsive bias.

It is well-known that repeated exposure to perceptual stimuli improves discrimination performance, but less is known about the effects on perceptual appearance. In the present work, the authors tackle this question and focus on one particular effect on perceptual appearance termed boundary avoidance, i.e. the tendency to perceive (or report) a stimulus as biased away from a discrimination boundary. On first glance, it was a pleasure reading this paper due to a number of aspects the authors got quite right in my opinion:<br /> - A clear and well-explained research question.<br /> - The results are generally well-presented. Much effort and expertise was put into the Figures and many helpful auxiliary Figures are included as a Supplement.<br /> - The writing was concise and clear.

However, as outlined below, I'm afraid that the main conclusion of the study and the main motivation for computational modeling are not backed up by the data.

(1) No evidence for a change in overestimation<br /> Overestimation is (rightly) defined by the authors as a bias of the perceived orientations towards more extreme values (visualized also in Fig. 2F). However, as acknowledged by the authors, there is nearly no evidence for such an effect. The modal estimation response (correct trials) doesn't change significantly between the sessions. The mean, which is the primary measure used by the authors, is not an appropriate measure for an overestimation, as it is severely biased by accuracy. It was unclear to me why it was chosen as the primary measure for nearly all figures and analyses, given that the authors were aware of (and reported) a more suited measure.

In my opinion, the mode of the correct responses would be the best way to quantify the overestimation bias. An alternative would be looking at the average absolute (unsigned) distance from the boundary, possibly including both correct and incorrect responses. However, such a "mean of absolute differences" approach would be affected by lucky guessing trials, which could manifest in a probability mass close to the boundary (and the proportion of which changes with overall accuracy). Therefore I see the mode as the strongest and least confounded measure.

(2) Nature of the biases<br /> Although, as outlined in 1), there might actually be no evidence for a *change* in overestimation bias, there clearly was a baseline overestimation bias. However, the reported biases appear extremely large. For instance, for the 2{degree sign} orientation the modal estimation is close to 20{degree sign}. To me this raises the question whether we're really dealing with a pure perceptual effect (18{degree sign} misperception seems quite suboptimal) or whether there are some other psychological effects at work that could be rather classified as a response bias.

In particular, I wondered whether the baseline bias is partly explained by participants "wanting to make sure" they indicate the correct category in estimation and therefore bias their estimation response away from the ambiguous proximity of the cardinal axes? Does it require more effort to set estimation orientation close to a cardinal axis while still making sure that it has the correct categorical orientation. I guess there was no horizontal reference line on the screen which would help with this?

The overall discrimination-focused task design might have contributed to this bias. First, because the participants trained on estimation also performed a discrimination task (pre/post) which very likely could have affected their response style. Second, the presented orientations during estimation were likewise 50:50 around the horizontal reference which could shift the focus towards "getting the sign right" rather than "getting the precise orientation right".

(3) The mechanism of the model<br /> As a disclaimer a priori, I am not very familiar with this particular modeling literature (but this may be the case for other readers as well). For this reason I could have used a bit more guidance about how the model works. My understanding is that there a three key mechanisms: 1) Gain modulation which explains the improvement in discrimination; 2) Warping which partly explains boundary avoidance; 3) Implicit categorization which likewise partly explains boundary avoidance. In addition, there are two levels of analysis: 1) the pre-training state (a priori presence of a repulsive bias) and 2) learning effects (bias and performance increase through training). If the models were to be kept as part of a revised manuscript, my suggestion would be to structure the corresponding section in the Results ("Observer Model") a bit more along these anchors. I suggest also providing a bit more explanation already at this point. For instance, I consider the fact that implicit categorization effectively works through Bayes rule by assuming a uniform(?) prior over either the negative or positive orientation axis, as very relevant. I assume that other priors would have been conceivable for conditioning on the response, e.g. taking into account the actual (objective or subjective) distribution of orientations for the particular choice category, so this is a non-trivial modeling choice.<br /> Intuitively, I would have also thought that if more resources are devoted to the cardinal directions (and the decoder is unaware of this), this would lead to a bias *towards* the cardinal directions. If more neurons fire particularly strong to near-cardinal orientations (such as the +-4{degree sign} in training), why would the decoder be repulsed *away* from the cardinal orientation? I trust the authors that the presentation is correct, but to me, this was not obvious and I would have wished for some guidance.

Reviewer #1 (Public Review):

Identifying individual BCR/Ab chain sequences that are members of the same clone is a long-standing problem in the analysis of BCR/Ab repertoire sequencing data. The authors propose a new method designed to be scalable for application to huge repertoire data sets without sacrificing accuracy. Their approach utilizes Hamming Distance between CDR3 sequences followed by clustering for a fast, high-precision approach to classifying pairs of sequences as related or not, and then refines the classification using mutation information from germline-encoded regions. They compare their method with other state-of-the-art methods using synthetic data.

The authors address an important problem in an interesting, innovative, and rigorous way, using probabilistic representations of CDR3 differences, frequencies of shared and not-shared mutations, and the relationships between the two under hypotheses of related pairs and unrelated pairs, and from these develop an approach for determining thresholds for classification and lineage assignment. Benchmarking shows that the proposed method, the complete method including both steps, outperforms other methods.

Strengths of the method include its theoretical underpinnings which are consistent with an immunologist's intuition about how related and unrelated sequences would compare with each other in terms of the metrics to use and how those metrics are related to each other.

I have two high-level concerns:<br /> (1) It isn't clear how the real and synthetic data are being used to estimate parameters for the classifier and evaluate the classifier to avoid circularity. It seems like the approach is used to assign lineages in the data from [1], and then properties of this set of lineages are used to estimate parameters that are then used to refine the approach and generate synthetic data that is used to evaluate the approach. This may not be a problem with the approach but rather with its presentation, but it isn't entirely clear what data is being used and where for what purpose. An understanding of this is necessary in order to truly evaluate the method and results.<br /> (2) Regarding the data used for benchmarking - given the intertwined fashion by which the classification approach and synthetic data generation approach appear to have been developed, it is not surprising that the proposed approach outperforms the other methods when evaluated on the synthetic data presented here. It would be better to include in the benchmark the data used by the other methods to benchmark themselves or also generate synthetic data using their data generation procedures.

An improved method for BCR/Ab sequence lineage assignment would be a methodologic advancement that would enable more rigorous analyses of BCR/Ab repertoires across many fields, including infectious disease, cancer, autoimmune disease, etc., and in turn, enable advancement in our understanding of humoral immune responses. The methods would have utility to a broad community of researchers.

Reviewer #2 (Public Review):

This manuscript describes a new algorithm for clonal family inference based on V and J gene identity, sequence divergence in the CDR3 region, and shared mutations outside the CDR3. Specifically, the algorithm starts by grouping sequences that have the same V and J genes and the same CDR3 length. It then performs single-linkage clustering on these groups based on CDR3 Hamming distance, then further refines these groups based on shared mutations.

Although there are a number of algorithms that use a similar overall strategy, a couple of aspects make this work unique. First, a persistent challenge for algorithms such as this one is how to set a cutoff for single-linkage clustering: if it is too low, then one separates clusters that should be together, and if too high one joins together clusters that should be separate. Here the authors leverage a rich collection of probabilistic tools to make an optimal choice. Specifically, they model the probability distributions of within- and between-cluster CDR3 Hamming distances, with parameters depending on CDR3 length and the "prevalence" of clonal sequence pairs (i.e. family size distribution). This allows the algorithm to make optimal choices for separating clusters, given the particular chosen distance metric, and assuming the sample in question has been accurately modeled. Second, the algorithm uses a highly efficient means of doing single-linkage clustering on nucleotide sequences.

This leads to a fast and highly performant algorithm on data meant to replicate the original sample used in algorithm design. The ideas are new and beautifully developed. The application to real data is interesting, especially the point about dN/dS.

However, the paper leaves open the question of how this inference algorithm works on samples other than the one used for simulation and as a template for validation. If I understand the simulation procedure correctly - that one takes a collection of inferred trees from the real data, then re-draws the root sequence and the identity of the mutations on the branches - then the simulated data should be very close to the data used to develop the methods in the paper. This consideration seems especially important given that key methods in this paper use mutation counts and overall mutation counts are preserved.

Repertoires come in all shapes and sizes: infants to adults, healthy to cancerous, and naive to memory to plasma-cell-just-after-vaccination. If this is being proposed as a general-purpose clonal inference algorithm rather than one just for this sample, then a more diverse set of validations are needed.

It is unclear how to run the code. The software repo has a nice readme explaining the file layout, dependencies, and input file format, but the repo seems to be lacking an `inference.ipynb` mentioned there which runs an analysis. Perhaps this is a typo and refers to `inference.py`, which in addition to the documented cdr3 clustering, seems to have functions to run both clustering methods. However, it does not seem to have any documentation or help messages about how to run these functions.

The results are not currently reproducible, because the simulated data is not available. The data availability statement says that no data have been generated for this manuscript, however simulated data has been generated, and that is a key aspect of the analysis in the paper.

More detail is needed to understand the timing comparisons. The new software is clearly written to use many threads. Were the other software packages run using multiple threads? What type of machine was used for the benchmarks?

Reviewer #3 (Public Review):

B cell receptors are produced through a combination of random V(D)J recombination and somatic hypermutation. Identifying clonal lineages - cells that descend from a common V(D)J rearrangement - is an important part of B cell repertoire analysis. Here, the authors developed a new method to identify clonal lineages from BCR data. This method builds off of prior advances in the field and uses both an adaptive clonal distance threshold and shared somatic hypermutation information to group B cells into clonal lineages.

The major strength of this paper is its thorough quantitative treatment of the subject and integration of multiple improvements into the clonal clustering process. By their simulation results, the method is both highly efficient and accurate.

The only notable weakness we identified is that much of the impact of the method will depend on its superiority to existing approaches, and this is not convincingly demonstrated by Fig. 4. In particular, little detail is given on how the other clonal clustering programs were run, and this can significantly impact their performance. More specifically:

(1) Scoper supports multiple methods for clonal clustering, including both adaptive CDR3 distance thresholds (Nouri and Kleinstein, 2018) and shared V-gene mutations (Nouri and Kleinstein, 2020). It is not clear which method was used for benchmarking. The specific functions and settings used should have been detailed and justified. Spectral clustering with shared V gene mutations would be the most comparable to the authors' method. Similar detail is needed for partis.<br /> (2) It is not clear how the adaptive thresholds and shared mutation analysis in the authors' method differ from prior approaches such as scoper and partis.<br /> (3) The scripts for performing benchmarking analyses, as well as the version numbers of programs tested, are not available.<br /> (4) Similar to above, P. 10 describes single linkage hierarchical clustering with a fixed threshold as a "crude method" that "suffers from inaccuracy as it loses precision in the case of highly-mutated sequences and junctions of short length." As far as we could tell, this statement is not backed up by either citations or analyses in the paper. It should not be difficult for the authors to test this though using their simulations, as this method is also implemented in scoper.

References<br /> Nouri N, Kleinstein SH. 2020. Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data. PLOS Comput Biol 16:e1007977. doi:10.1371/journal.pcbi.1007977<br /> Nouri N, Kleinstein SH. 2018. A spectral clustering-based method for identifying clones from high-throughput B cell repertoire sequencing data. Bioinformatics 34:i341-i349. doi:10.1093/bioinformatics/bty235

Reviewer #1 (Public Review):

Summary:

Doxorubincin has long been known to cause bone loss by increasing osteoclast and suppressing osteoblast activities. The study by Wang et al. reports a comprehensive investigation into the off-target effects of doxorubicin on bone tissues and potential mechanisms.. They used a tumor-free model with wild type mice and found that even a single dose of doxorubicin has a major influence by increasing leukopenia and DAMPs and inflammasomes in macrophages and neutrophils, and inflammation-related cell death (pyroptosis and NETosis). The gene knockout study shows that AIM2 and NLRP3 are the major contributors to bone loss. Overall, the study confirmed previous findings regarding the impact of doxorubicin on tissue inflammation and expands the research further into bone tissue. The presented data presented are consistent; however, a major question remains regarding whether doxorubicin drives inflammation and its related events. Most in vitro study showed that the effect of doxorubincin cannot be demonstrated without LPS priming. This observation raises the question of whether doxorubincin itself could activate the inflammasome and the related events. In vivo study, on the other hand, suggested that it doesn't require LPS. The inconsistency here was not explained further. Moreover, a tumor-free mouse model was used for the study; however, immune responses in tumor bearing models would likely be distinct from tumor-free ones. The justification for using tumor-free models is not well-established.

Strengths:

The paper includes a comprehensive study that shows the effects of doxorubincin on cytokine levels in serum, release of DAMPs and NETosis, and leukopenia using both in vivo and in vitro models. Bone marrow cells, macrophages and neutrophils were isolated from the bone marrow, and the levels of cytokines in serum were also determined.

They employed multiple knockout models with deficiency in Aim 2, Nlirp3, and double deficiencies to dissect the functional involvement of these two inflammasomes.

The experiments in general are well designed. The paper is also logically written, and figures were clearly labeled.

Weaknesses:

Most of the data presented are correlative, and there is not much effort to dissect the underlying molecular mechanism.

It is not entirely clear why a tumor free model is chosen to study immune responses, as immune responses can differ significantly with or without tumor-bearing.

Immune responses in isolated macrophages, neutrophils and bone marrow cells require priming with LPS, while such responses are not observed in vivo. There is no explanation for these differences.

The band intensities on Western blots in Fig. 4 and Fig. 5 are not quantified, and the numbers of repeats are also not provided.

Many abbreviations are used throughout the text, and some of the full names are not provided.

Fig. 5B needs a label on X axis.

Reviewer #2 (Public Review):

Summary:

Wang and collaborators have evaluated the impact of inflammation on bone loss induced by Doxorubicin, which is commonly used in chemotherapy to treat various cancers. In mice, they show that a single injection of Doxorubicin induces systemic inflammation, leukopenia, and a significant bone loss associated with increased bone-resorbing osteoclast numbers. In vitro, the authors show that Doxorubicin activates the AIM2 and NLRP3 inflammasomes in macrophages and neutrophils. Importantly, they show that the full knockouts (germline deletions) of AIM2 (Aim2-/-) and NLRP3 (Nlrp3-/-) and Caspase 1 (Casp1-/-) limit (but do not completely abolish) bone loss induced 4 weeks after a single injection of Doxorubicin in mice. From these results, they conclude that Doxorubicin activates inflammasomes to cause inflammation-associated bone loss.

Strength:

This manuscript provides functional experiments demonstrating that NRLP3 and/or AIM2 loss-of-functions (and thus the systemic impairment of the inflammatory response) prevent bone-loss induced by Doxorubicin in mice.

Weaknesses:

Numerous studies have reported that Doxorubicin induces systemic inflammation and activates the inflammasome in myeloid cells and various other cell types. It is also known that systemic inflammation and Doxorubicin treatment lead to bone loss. Hence, the key conclusions drawn from this work have been known already or were very much expected. Therefore, the novelty appears somewhat limited. One important limitation is the lack of experiments that could determine which cell lineages are involved in bone loss induced by Doxorubicin in vivo, while the tools to do so exist. The characterization of the bone phenotype is incomplete, and unfortunately does not tell us whether the inflammasome is activated in some of the cell lineages present in bones in vivo. Another limitation is that the relative importance of the inflammasomes compared to cell senescence and autophagy, which are also induced by Doxorubicin, has not been evaluated. Hence the main molecular mechanisms responsible for bone loss induced by Doxorubicin in vivo remains unknown. Lastly, it would have been interesting, on a more clinical point of view, to compare the few relevant treatments that could limit the deleterious effect of Doxorubicin on bone loss while preserving the toxicity on tumor cells.

Reviewer #1 (Public Review):

In this manuscript by Buchanan and colleagues, the authors set out to determine if mutations associated with resistance to the Plasmodium apicoplast inhibitor azithromycin (AZ) had a measurable impact on the fitness of Plasmodium berghei and P. falciparum parasites as they traverse both the mosquito host and vertebrate liver.

The Plasmodium endosymbiotic organelles - the mitochondrion and apicoplast - are attractive drug targets as they (1) possess essential functions across the multi-host multi-compartment life cycle of these parasites, and (2) are of bacterial origin and thus are vulnerable to inhibition both to extant antibiotics, and novel drugs with high parasite specificity.

Historically however the high resistance propensity of drug targets encoded in the organellar genomes (most notably atovaquone and doxycycline) has precluded the use of these drugs in an endemic setting, limiting these potent compounds to use in prophylaxis for travelers from non-endemic countries. Several studies in the last decade now fairly definitively show that mutations conferring resistance to atovaquone in the mitochondrial gene cytochrome b are, in a mutation-dependent manner, totally or near-totally compromised in their ability to infect, grow, and escape the mosquito host, leading to a reexamination of the potential utility of this extraordinarily potent drug in endemic settings. Symmetries exist between the Plasmodium mitochondrion and apicoplast, which both appear to have highly fexpanded roles in the mosquito and liver relative to the blood stages. Thus, the authors set out to explore whether mutations in essential apicoplast genes were, in a similar manner to mutations in cytochrome B, associated with fitness effects in the mosquito and/or liver.

Towards this, the authors selected for several AZ-resistant parasite populations, all of which acquired mutations in the apicoplast genome-encoded ribosomal protein Rpl4. Interestingly, the authors observed contrasting fitness effects caused by these mutations, both between mutants within Plasmodium species, and between species. In P. berghei, AZ mutants were compromised in their ability to form oocysts and sporozoites, and a large proportion of sporozoites lacked an intact apicoplast and displayed aberrant gliding behaviour. Similarly, in the liver, Rpl4 mutant P. berghei liver schizonts were smaller, had fewer nuclei, and appeared extremely limited in their ability to cause a patent infection - crucially in particular via mosquito bites. Surprisingly, a P. falciparum Rpl4 mutant (notably in a different position of the protein) had no impact on sporogony but appeared to have a strong impact on liver schizont development in a liver-humanized mouse model, suggesting that establishment of blood stage infection in a subsequent human host would be less likely for mutant parasites.

This is a well-executed study, that presents novel and noteworthy findings. The impact of drug-resistance-conferring mutations in Plasmodium outside of the blood stage is woefully understudied, primarily due to significant challenges associated with studying Plasmodium, especially P. falciparum, in both the mosquito and liver which the authors navigate commendably. The results presented in this manuscript leverage state-of-the-art techniques and clearly support the authors' conclusion that AZ-conferring resistance mutations have a strong negative effect on the ability of Plasmodium parasites to both reinfect and cause symptomatic infection in a subsequent vertebrate host. This could indicate that apicoplast-targeted inhibitors are more attractive as co-drugs for malaria treatment than previously thought, due to the reduced probability of the spread of resistance, which has been a perennial issue in malaria therapeutic care.

Reviewer #2 (Public Review):

Summary:

This manuscript answers an important question about the transmission of Plasmodium parasites resistant to apicoplast inhibitors, specifically azithromycin. This study builds on previous work showing the inability to transmit parasites resistant to mitochondrial inhibitor, atovaquone, based on fitness defects in transmission stages in the mosquito. The transmissibility of drug-resistant parasites is grounded in the basic biology of the Plasmodium lifecycle and has implications for the selection of drug regimens for clinical treatment, so these questions are highly significant. The authors clearly demonstrate severe defects in mosquito stages of azithromycin-resistant (AZR) P. berghei (rodent species) inhibiting transmission of AZR parasites. However, surprisingly AZR P. falciparum (human species) is unaffected in mosquito stages, rather defects are observed in liver-stage development suggesting AZR P. falciparum can transmit but may not mount a productive blood infection. The differences in the observed defects in the 2 species are important and well demonstrated in the results but are obscured in the title/summary of the manuscript. The results demonstrate that AZR parasites are unlikely to spread.

Strengths:

The authors performed experiments with both P. berghei (rodent species) and P. falciparum (human species). P. falciparum is the more relevant species from a clinical standpoint, however, there are limitations to studying the full lifecycle of P. falciparum which only infects humans and some primates, for example requiring humanized mice without intact immune systems. Pberghei is commonly used in lifecycle analyses as a proxy for experimental tractability, however, there are cases where the biology of P. berghei does not reflect that in P. falciparum. So the use of both species is complementary and most informative. Specific modification of the apicoplast genome, where AZR mutations are located, is not currently possible so matched genotypes could not be produced but multiple AZR mutants were analyzed for each species. Acknowledging these limitations in the experimental systems available, the authors perform a thorough set of experiments to pinpoint the specific defects in AZR Pb vs Pf during mosquito and liver developmental stages. The results show phenotypic differences between AZR Pb and Pf in mosquito stages which was not expected but in line with differences in apicoplast biology of Pb vs Pf that are important to document and be aware of when using P. berghei as a model for P. falciparum development.

Weaknesses:

The claim that human AZR malaria parasites (P. falciparum) is not readily transmitted to mosquitoes is incorrect, as stated in the title and abstract. Strictly speaking, transmission refers to the infection of a human host by another via mosquitos. The evidence that AZR Pf is unaffected in mosquito development indicates that transmission is not reduced compared to WT Pf. Rather transmitted AZR Pf has disrupted liver stage development and may not mount a productive blood infection. This distinction between the phenotypes of AZR Pb vs Pf is surprising, significant (suggesting differences between Pb and Pf and/or specific mutations in Rpl4), and should be more accurately represented in the title/abstract. To their credit, the authors performed thorough experiments to pinpoint the specific defects in AZR Pb vs Pf, but the current claim about AZR Pf is misleading.

Additional context:

Clinical trials (MORDOR studies) in several African countries have shown that biannual administration of azithromycin reduces childhood mortality (PMID: 31167050). The mechanism of this survival benefit is unknown and may be multifactorial. The findings in this manuscript can also be considered in the context that azithromycin is a commonly used antibiotic and may be administered for purposes other than malaria treatment. In theory, AZR-resistant parasites could be selected in asymptomatic patients not receiving malaria treatment but receiving azithromycin. This study indicates that mass distribution of azithromycin for other clinical applications would not result in adverse effects on malaria transmissions in the same population.

Reviewer #3 (Public Review):

Summary:

Drug resistance is a perennial problem for malaria control and strategies to prevent the acquisition and spread of drug resistance mutations are desperately needed. One strategy is to identify drug resistance mutations that arise in blood-stage parasites, but cannot be readily spread to a new human host. Since malaria parasites must survive and replicate in mosquitoes in order to be transmitted, mutations with elevated mosquito-stage fitness defects will not spread efficiently. Buchanan and coworkers focus on the drug azithromycin and its known role of inhibiting the ribosomes found in parasite apicoplast organelles. Apicoplast organelles are known to have elevated metabolic activity in mosquito stage parasites and azithromycin resistance mutations could interfere with mosquito stage parasite development and parasite transmission.

To address this hypothesis, azithromycin-resistant P. berghei and P. falciparum parasites were generated and analyzed for transmission defects. All lines had mutations in the apicoplast ribosomal protein Rpl4 consistent with the known role of azithromycin inhibiting the 50S ribosomal subunit. Overall, the three lines (3 berghei and one falciparum) had phenotypes that should limit parasite transmission, however, detailed characterization showed that there were surprising differences between the two parasite species and even between the P. berghei lines. The P. berghei lines produced fewer oocysts and sporozoites with aberrant apicoplast morphology compared to wild-type controls. Sporozoites from azithromycin-resistant lines appeared to have motility defects and typically were not able to infect mice (one strain produced infections when 10,000 sporozoites were injected, but not when 1,000 were).

By contrast, the azithromycin-resistant P. falciparum strain did not display any mosquito-stage phenotypes and produced motile sporozoites with intact apicoplast organelles. These sporozoites, however, developed abnormally in a humanized mouse model with reduced liver-stage nuclear division and abnormal apicoplast morphology. These defects combined with a five-fold lower prevalence suggest that azithromycin-resistant P. falciparum parasites experience significant fitness costs during liver stage development (at least those harboring the G76V mutation).

Strengths:

This work was carefully conducted and transparently presented. It provides a comprehensive view of how parasite development is impacted by azithromycin resistance mutations during the mosquito and liver stages in P. berghei and P. falciparum. It adds a new dimension to the growing literature on the transmissibility of drug-resistant parasites, by showing that mutations in the apicoplast genome can impact transmission.

Weaknesses:

Whether these liver-stage defects in P. falciparum are severe enough to completely block subsequent blood-stage infection remains to be seen and would require experiments with humanized mice continuously grafted with human red blood cells - a difficult and expensive model system.

Reviewer #1 (Public Review):

Mohseni and Elhaik's article offers a critical evaluation of Geometric Morphometrics (GM), a common tool in physical anthropology for studying morphological differences and making phylogenetic inferences. I read their article with great interest, although I am not a geneticist or an expert on PCA theory since the problem of morphology-based classification is at the core of paleoanthropology.

The authors developed a Python package for processing superimposed landmark data with classifier and outlier detection methods, to evaluate the adequacy of the standard approach to shape analysis via modern GM. They call into question the accuracy, robustness, and reproducibility of GM, and demonstrate how PCA introduces statistical artefacts specific to the data, thus challenging its scientific rigor. The authors demonstrate the superiority of machine learning methods in classification and outlier detection tasks. The paper is well-written and provides strong evidence in support of the authors' argument. Thus, in my opinion, it constitutes a major contribution to the field of physical anthropology, as it provides a critical and necessary evaluation of what has become a basic tool for studying morphology, and of the assumptions allowing its application for phylogenetic inferences. Again, I am not an expert in these statistical methods, nor a geneticist, but the authors' contribution is of substantial relevance to our field (physical anthropology). The examples of NR fossils and HLD 6 are cases in point, in line with other notable examples of critical assessment of phylogenetic inferences made on the basis of PCA results of GM analysis. For example, see Lordkipanidze et al.'s (2014) GM analyses of the Dmanisi fossils, suggesting that the five crania represent a single regional variant of Homo erectus; and see Schwartz et al.'s (2014) comment on their findings, claiming that the dental, mandibular, and cranial morphology of these fossils suggest taxic diversity. Schwartz et al. (2014) ask, "Why did the GMA of 78 landmarks not capture the visually obvious differences between the Dmanisi crania and specimens commonly subsumed H. erectus? ... one wonders how phylogenetically reliable a method can be that does not reflect even easily visible gross morphological differences" (p. 360).

As an alternative to the PCA step in GM, the authors tested eight leading supervised learning classifiers and outlier detection methods on three-dimensional datasets. The authors demonstrated inconsistency of PCA clustering with the taxonomy of the species investigated for the reconstruction of their phylogeny, by analyzing a database comprising landmarks of 6 known species that belong to the Old World monkeys tribe Papionini, using PCA for classification. The authors also demonstrated that high explained variance should not be used as an estimate of high accuracy (reliability). Then, the authors altered the dataset in several ways to simulate the characteristic nature of paleontological data.

The authors excluded taxa from the database to study how PCA and alternative classifiers are affected by partial sampling, and the results presented in Figures 4 and 5, among others, are quite remarkable in showing the deviations from the benchmark data. These results expose the perils of applying PCA and GM for interpreting morphological data. Furthermore, they provide evidence showing that the alternative classifiers are superior to PCA, and that they are less susceptible to experimenter intervention. Similar results, i.e., inconsistencies in the PC plots, were obtained in examinations of the effect of removing specimens from the dataset and in the interesting test of removing landmarks to simulate partial morphological data, as is often the case with fossils. To test the combined effect of these data alterations, the authors combined removal of taxa, specific samples, and landmarks from the dataset. In this case, as well, the PCA results indicate deviation from the benchmark data. However, the ML classifiers could not remedy the situation. The authors discuss how these inconsistencies may lead to different interpretations of the data, and in turn, different phylogenetic conclusions. Lastly, the authors simulated the situation of a specimen of unknown taxonomy using outlier detection methods, demonstrating LOF's ability to identify a novelty in the morphospace.

References<br /> Bookstein FL. 1991. Morphometric tools for landmark data: geometry and biology [Orange book]. Cambridge New York: Cambridge University Press.<br /> Cooke SB, and Terhune CE. 2015. Form, function, and geometric morphometrics. The Anatomical Records 298:5-28.<br /> Lordkipanidze D, et al. 2013. A complete skull from Dmanisi, Georgia, and the evolutionary biology of early Homo. Science 342: 326-331.<br /> Schwartz JH, Tattersall I, and Chi Z. 2014. Comment on "A complete skull from Dmanisi, Georgia, and the evolutionary biology of Early Homo". Science 344(6182): 360-a.

Reviewer #2 (Public Review):

I completely agree with the basic thrust of this study. Yes, of course, machine learning is FAR better than any variant of PCA for the paleosciences. I agree with the authors' critique early on that this point is not new per se - it is familiar to most of the founders of the field of GMM, including this reviewer. A crucial aspect is the dependence of ALL of GMM, PCA or otherwise, on the completely unexamined, unformalized praxis by which a landmark configuration is designed in the first place. I must admit that I am stunned by the authors' estimate of over 32K papers that have used PCA with GMM.

But beating a dead horse is not a good way of designing a motor vehicle. I think the manuscript needs to begin with a higher-level view of the pathology of its target disciplines, paleontology and paleoanthropology, along the lines that David Hull demonstrated for numerical taxonomy some decades ago. That many thousands of bad methodologies require some sort of explanation all of their own in terms of (a) the fears of<br /> biologists about advanced mathematics, (b) the need for publications and tenure, (c) the desirability of covers of Nature and Science, and (d) the even greater glory of getting to name a new "species." This cumulative pathology of science results in paleoanthro turning into a branch of the humanities, where no single conclusion is treated as stable beyond the next dig, the next year or so of applied genomics, and the next chemical trace analysis. In short, the field is not cumulative.

It is not obvious that the authors' suggestion of supervised machine learning will remedy this situation, since (a) that field itself is undergoing massive changes month by month with the advent of applications AI, and even more relevant (b) the best ML algorithms, those based on deep neural nets, are (literally) unpublishable - we cannot see how their decisions have actually been computed. Instead, to stabilize, the field will need to figure out how to base its inferences on some syntheses of actual empirical theories.

It's not that this reviewer is cynical, but it is fair to suggest a revision conveying a concern for the truly striking lack of organized skepticism in the literature that is being critiqued here. A revision along those lines would serve as a flagship example of exactly the deeper argument that reference (17) was trying to seed, that the applied literature obviously needs a hundred times more of. Such a review would do the most good if it appeared in one of the same journals - AJBA, Evolution, Journal of Human Evolution, Paleobiology - where the bulk of the most highly cited misuses of PCA themselves have appeared.

Reviewer #3 (Public Review):

Mohseni and Elhaik challenge the widespread use of PCA as an analytical and interpretive tool in the study of geometric morphometrics. The standard approach in geometric morphometrics analysis involves Generalised Procrustes Analysis (GPA) followed by Principal Component Analysis (PCA). Recent research challenges PCA outcomes' accuracy, robustness, and reproducibility in morphometrics analysis. In this paper, the authors demonstrate that PCA is unreliable for such studies. Additionally, they test and compare several Machine-Learning methods and present MORPHIX, a Python package of their making that incorporates the tools necessary to perform morphometrics analysis using ML methods.

Mohseni and Elhaik conducted a set of thorough investigations to test PCA's accuracy, robustness, and reproducibility following renewed recent criticism and publications where this method was abused. Using a set of 2 and 3D morphometric benchmark data, the authors performed a traditional analysis using GPA and PCA, followed by a reanalysis of the data using alternative classifiers and rigorous testing of the different outcomes.

In the current paper, the authors evaluated eight ML methods and compared their classification accuracy to traditional PCA. Additionally, common occurrences in the attempted morphological classification of specimens, such as non-representative partial sampling, missing specimens, and missing landmarks, were simulated, and the performance of PCA vs ML methods was evaluated.

The main problem with this manuscript is that it is three papers rolled into one, and the link doesn't work. The title promises a new Python package, but the actual text of the manuscript spends relatively little time on the Python package itself and barely gives any information about the package and what it includes or its usefulness. It is definitely not the focus of the manuscript. The main thrust of the manuscript, which takes up most of the text, is the analysis of the papionin dataset, which shows very convincingly that PCA underperforms in virtually all conditions tested. In addition, the manuscript includes a rather vicious attack against two specific cases of misuse of PCA in paleoanthropological studies, which does not connect with the rest of the manuscript at all.

If the manuscript is a criticism of PCA techniques, this should be reflected in the title. If it is a report of a new Python package, it should focus on the package. Otherwise, there should be two separate manuscripts here.

The criticism of PCA is valid and important. However, pointing out that it is problematic in specific cases and is sometimes misused does not justify labeling tens of thousands of papers as questionable and does not justify vilifying an entire discipline. The authors do not make a convincing enough case that their criticism of the use of PCA in analyzing primate or hominin skulls is relevant to all its myriad uses in morphometrics. The criticism is largely based on statistical power, but it is framed as though it is a criticism of geometric morphometrics in general.

Joint Public Review:

Roget et al. build on their previous work developing a simple theoretical model to examine whether ageing can be under natural selection, challenging the mainstream view that ageing is merely a byproduct of other biological and evolutionary processes. The authors propose an agent-based model to evaluate the adaptive dynamics of a haploid asexual population with two independent traits: fertility timespan and mortality onset. Through computational simulations, their model demonstrates that ageing can give populations an evolutionary advantage. Notably, this observation arises from the model without invoking any explicit energy tradeoffs, commonly used to explain this relationship.

Additionally, the theoretical model developed here indicates that mortality onset is generally selected to start before the loss of fertility, irrespective of the initial values in the population. The selected relationship between the fertility timespan and mortality onset depends on the strength of fertility and mortality effects, with larger effects resulting in the loss of fertility and mortality onset being closer together. By allowing for a trans-generational effect on ageing in the model, the authors show that this can be advantageous as well, lowering the risk of collapse in the population despite an apparent fitness disadvantage in individuals. Upon closer examination, the authors reveal that this unexpected outcome is a consequence of the trans-generational effect on ageing increasing the evolvability of the population (i.e., allowing a more effective exploration of the parameter landscape), reaching the optimum state faster.

The simplicity of the proposed theoretical model represents both the major strength and weakness of this work. On one hand, with an original and rigorous methodology, the logic of their conclusions can be easily grasped and generalised, yielding surprising results. Using just a handful of parameters and relying on direct competition simulations, the model qualitatively recapitulates the negative correlation between lifespan and fertility without requiring energy tradeoffs. This alone makes this work an important milestone for the rapidly growing field of adaptive dynamics, opening many new avenues of research, both theoretically and empirically.

On the other hand, the simplicity of the model also makes its relationship with living organisms difficult to gauge, leaving open questions about how much the model represents the reality of actual evolution in a natural context. In particular, a more explicit discussion on how the specifics of the model can impact the results and their interpretation is needed. For example, the lack of mechanistic details on the trans-generational effect on ageing makes the results difficult to interpret. Even if analytical results are obtained, most of the observations appear derived from simulations as they are currently presented. Also, the choice of parameters for the simulations shown in the paper and how it relates to our biological knowledge is not fully addressed by the authors. Finally, the conclusions of evolvability are insufficiently supported, as the authors do not show if the wider genotypic variability in populations with the ageing trans-generational effect is, in fact, selected.

Reviewer #1 (Public Review):

Summary:

In this study, Faniyan and colleagues build on their recent finding that renal Glut2 knockout mice display normal fasting blood glucose levels despite massive glucosuria. Renal Glut2 knockout mice were found to exhibit increased endogenous glucose production along with decreased hepatic metabolites associated with glucose metabolism. Crh mRNA levels were higher in the hypothalamus while circulating ACTH and corticosterone was elevated in this model. While these mice were able to maintain normal fasting glucose levels, ablating afferent renal signals to the brain resulted in substantially lower blood glucose levels compared to wildtype mice. In addition, the higher CRH and higher corticosterone levels of the knockout mice were lost following this denervation. Finally, acute phase proteins were altered, plasma Gpx3 was lower, and major urinary protein MUP18 and its gene expression were higher in renal Glut2 knockout mice. Overall, the main conclusion that afferent signaling from the kidney is required for renal glut2 dependent increases in endogenous glucose production is well supported by these findings.

Strengths:

An important strength of the paper is the novelty of the identification of kidney to brain communication as being important for glucose homeostasis. Previous studies had focused on other functions of the kidney modulated by or modulating brain function. This work is likely to promote interest in CNS pathways that respond to afferent renal signals and the response of the HPA axis to glucosuria. Additional strengths of this paper stem from the use of incisive techniques. Specifically, the authors use isotope enabled measurement of endogenous glucose production by GC-MS/MS, capsaicin ablation of afferent renal nerves, and multifiber recording from the renal nerve. The authors also paid excellent attention to rigor in the design and performance of these studies. For example, they used appropriate surgical controls, confirmed denervation through renal pelvic CGRP measurement, and avoided the confounding effects of nerve regrowth over time. These factors strengthen confidence in their results. Finally, humans with glucose transporter mutations and those being treated with SGLT2 inhibitors show a compensatory increase in endogenous glucose production. Therefore, this study strengthens the case for using renal Glut2 knockout mice as a model for understanding the physiology of these patients.

Weaknesses:

A few weaknesses exist. Most concerns relate to the interpretation of this study's findings. The authors state that loss of glucose in urine is sensed as a biological threat based on the HPA axis activation seen in this mouse model. This interpretation is understandable but speculative. Importantly, whether stress hormones mediate the increase in endogenous glucose production in this model and in humans with altered glucose transporter function remains to be demonstrated conclusively. For example, the paper found several other circulating and local factors that could be causal. This model is also unable to shed light on how elevated stress hormones might interact with insulin resistance, which is known to increase endogenous glucose production. That issue is of substantial clinical relevance for patients with T2D and metabolic disease. Finally, while findings from the Glut2 knockout mice are of scientific interest, it should be noted that the Glut2 receptor is critical to the function of pancreatic islets and as such is not a good candidate for pharmacological targeting

Reviewer #2 (Public Review):

Summary:

The authors previously generated renal Glut2 knockout mice, which have high levels of glycosuria but normal fasting glucose. They use this as an opportunity to investigate how compensatory mechanisms are engaged in response to glycosuria. They show that renal and hepatic glucose production, but not metabolism, is elevated in renal Glut2 male mice. They show that renal Glut2 male mice have elevated Crh mRNA in the hypothalamus, and elevated plasma levels of ACTH and corticosterone. They also show that temporary denervation of renal nerves leads to a decrease in fasting and fed blood glucose levels in female renal Glut2 mice, but not control mice. Finally, they perform plasma proteomics in male mice to identify plasma proteins with a greater than 25% (up or down) between the knockouts and controls.

Strengths:

The question that is trying to be addressed is clinically important: enhancing glycosuria is a current treatment for diabetes, but is limited in efficacy because of compensatory increases in glucose production.

Weaknesses:

(1) Although I appreciate that the initial characterization of the mice in another publication showed that both males and females have glycosuria, this does not mean that both sexes have the same mechanisms giving rise to glycosuria. There are many examples of sex differences in HPA activation in response to threat, for example. There is an unfounded assumption here that males and females have the same underlying mechanisms of glycosuria that undermines the significance of the findings.

(2) The authors state that they induced the Glut2 knockout with taxomifen as in their previous publication. The methods of that publication indicate that all experiments were completed within 14 days of inducing the Glut2 knockout. This means that the last dose of tamoxifen was delivered 14 days prior to the experimental endpoint of each experiment. This seems like an important experimental constraint that should be discussed in this manuscript. Is the glycosuria that follows Glut2 knockout only a temporary change? If so, then the long-term change in glycosuria that follows SGLT2 inhibition in humans might not be best modelled by this knockout. Please specify when the surgeries to implant a jugular catheter or ablate the renal nerves performed relative to the Glut2 knockout in the Methods.

(3) I am still unclear what group was used for controls. Are these wild-type mice who receive tamoxifen? Are they KspCadCreERT2;Glut2loxP/loxP mice who do not receive tamoxifen? This is important and needs to be specified.

(4) The authors should report some additional control measures for the renal denervation that could also impact blood glucose and perhaps some of their other measures. The control measures, which one would like to see unimpacted by renal denervation, include body weights, food consumption and water intake, and glycosuria itself.

(5) The graphical abstract shows a causal link between the hypothalamus and the liver that is unsupported by any of the current findings. That arrow should be removed or a question mark should be added next to the arrow.

(6) Though the authors have toned down their language implying a causal link between the HPA measures and compensatory elevation of blood glucose in the face of glycosuria, the title still implies this causal link. It is still the case that their data do not support causation. There are many potential ways to establish a causal link but those experiments are not performed here. The renal afferents are correlated with Crh content of the PVN, but nothing has been done to show that the Crh content is important for elevating blood glucose. In light of this, the title should be toned down. Perhaps something like "Renal nerves maintain blood glucose production and elevated HPA activity in response to glycosuria". The link between HPA and glucose is not shown in this paper.

Reviewer #1 (Public Review):

Summary:

The study investigated how root cap cell corpse removal affects the ability of microbes to colonize Arabidopsis thaliana plants. The findings demonstrate how programmed cell death and its control in root cap cells affect the establishment of symbiotic relationships between plants and fungi. Key details on molecular mechanisms and transcription factors involved are also given. The study suggests reevaluating microbiome assembly from the root tip, thus challenging traditional ideas about this process. While the work presents a key foundation, more research along the root axis is recommended to gain a better understanding of the spatial and temporal aspects of microbiome recruitment.

Reviewer #2 (Public Review):

Summary:

The authors identify the root cap as an important key region for establishing microbial symbioses with roots. By highlighting for the first time the crucial importance of tight regulation of a specific form of programmed cell death of root cap cells and the clearance of their cell corpses, they start unraveling the molecular mechanisms and its regulation at the root cap (e.g. by identifying an important transcription factor) for the establishment of symbioses with fungi (and potentially also bacterial microbiomes).

Strengths:

It is often believed that the recruitment of plant microbiomes occurs from bulk soil to rhizosphere to endosphere. These authors demonstrate that we have to re-think microbiome assembly as a process starting and regulated at the root tip and proceeding along the root axis.

Weaknesses:

The study is a first crucial starting point to investigate the spatial recruitment of beneficial microorganisms along the root axis of plants. It identifies e.g. an important transcription factor for programmed cell death, but more detailed investigations along the root axis are now needed to better understand - spatially and temporally - the orchestration of microbiome recruitment.

Reviewer #1 (Public Review):

Summary:

In this paper, the authors performed molecular dynamics (MD) simulations to investigate the molecular basis of the association of alpha-synuclein chains under molecular crowding and salt conditions. Aggregation of alpha-synuclein is linked to the pathogenesis of Parkinson's disease, and the liquid-liquid phase separation (LLPS) is considered to play an important role in the nucleation step of the alpha-synuclein aggregation. This paper re-tuned the Martini3 coarse-grained force field parameters, which allows long-timescale MD simulations of intrinsically disordered proteins with explicit solvent under diverse environmental perturbation. Their MD simulations showed that alpha-synuclein does not have a high LLPS-forming propensity, but the molecular crowding and salt addition tend to enhance the tendency of droplet formation and therefore modulate the alpha-synuclein aggregation. The MD simulation results also revealed important intra and inter-molecule conformational features of the alpha-synuclein chains in the formed droplets and the key interactions responsible for the stability of the droplets. These MD simulation data add biophysical insights into the molecular mechanism underlying the association of alpha-synuclein chains, which is important for understanding the pathogenesis of Parkinson's disease.

Strengths:

(1) The re-parameterized Martini 3 coarse-grained force field enables the large-scale MD simulations of the intrinsically disordered proteins with explicit solvent, which will be useful for a more realistic description of the molecular basis of LLPS.

(2) This paper showed that molecular crowding and salt contribute to the modulation of the LLPS through different means. The molecular crowding minimally affects surface tension, but adding salt increases surface tension. It is also interesting to show that the aggregation pathway involves the disruption of the intra-chain interactions arising from C-terminal regions, which potentially facilitates the formation of inter-chain interactions.

Weaknesses:

(1) Although the authors emphasized the advantage of the Martini3 force field for its explicit description of solvent, the whole paper did not discuss the water's role in the aggregation and LLPS.

(2) This paper discussed the effects of crowders and salt on the surface tension of the droplets. The calculation of the surface tension relies on the droplet shape. However, for the formed clusters in the MD simulations, the typical size is <10, which may be too small to rigorously define the droplet shape. As shown in previous work cited by this paper [Benayad et al., J. Chem. Theory Comput. 2021, 17, 525−537], the calculated surface tension becomes stable when the chain number is larger than 100.

(3) In this work, the Martini 3 force field was modified by rescaling the LJ parameters \epsilon and \sigma with a common factor \lambda. It has not been very clearly described in the manuscript why these two different parameters can be rescaled by a common factor and why it is necessary to separately tune these two parameters, instead of just tuning the coefficient \epsilon as did in a previous work [Larsen et al., PLoS Comput Biol 16: e1007870].

(4) Both the sizes and volume fractions of the crowders can affect the protein association. It will be interesting to perform MD simulations by adding crowders with various sizes and volume fractions. In addition, in this work, the crowders were modelled by fullerenes, which contribute to protein aggregation mainly by entropic means as discussed in the manuscript. It is not very clear how the crowder effect is sensitive to the chemical nature of the crowders (e.g., inert crowders with excluded volume effect or crowders with non-specific attractive interactions with proteins, etc) and therefore the force field parameters.

Reviewer #2 (Public Review):

In the manuscript "Modulation of α-Synuclein Aggregation Amid Diverse Environmental Perturbation", Wasim et al describe coarse-grained molecular dynamics (cgMD) simulations of α-Synuclein (aSyn) at several concentrations and in the presence of molecular crowding agents or high salt. They begin by bench-marking their cgMD against all-atom simulations by Shaw. They then carry 2.4-4.3 µs cgMD simulations under the above-noted conditions and analyze the data in terms of protein structure, interaction network analysis, and extrapolated fluid mechanics properties. This is an interesting study because a molecular scale understanding of protein droplets is currently lacking, but I have a number of concerns about how it is currently executed and presented.

(1) It is not clear whether the simulations have reached a steady state. If they have not, it invalidates many of their analysis methods and conclusions.

(2) The benchmarking used to validate their cgMD methods is very minimal and fails to utilize a large amount of available all-atom simulation and experimental data.

(3) They also miss opportunities to compare their simulations to experimental data on aSyn protein droplets.

(4) Aspects such as network analysis are not contextualized by comparison to other protein condensed phases.

(5) Data are not made available, which is an emerging standard in the field.

Reviewer #1 (Public Review):

Summary:

The authors' research group had previously demonstrated the release of large multivesicular body-like structures by human colorectal cancer cells. This manuscript expands on their findings, revealing that this phenomenon is not exclusive to colorectal cancer cells but is also observed in various other cell types, including different cultured cell lines, as well as cells in the mouse kidney and liver. Furthermore, the authors argue that these large multivesicular body-like structures originate from intracellular amphisomes, which they term "amphiectosomes." These amphiectosomes release their intraluminal vesicles (ILVs) through a "torn-bag mechanism." Finally, the authors demonstrate that the ILVs of amphiectosomes are either LC3B positive or CD63 positive. This distinction implies that the ILVs either originate from amphisomes or multivesicular bodies, respectively.

Strengths:

The manuscript reports a potential origin of extracellular vesicle (EV) biogenesis. The reported observations are intriguing.

Weaknesses:

It is essential to note that the manuscript has issues with experimental designs and lacks consistency in the presented data. Here is a list of the major concerns:

(1) The authors culture the cells in the presence of fetal bovine serum (FBS) in the culture medium. Given that FBS contains a substantial amount of EVs, this raises a significant issue, as it becomes challenging to differentiate between EVs derived from FBS and those released by the cells. This concern extends to all transmission electron microscopy (TEM) images (Figure 1, 2P-S, S5, Figure 4 P-U) and the quantification of EV numbers in Figure 3. The authors need to use an FBS-free cell culture medium.

(2) The data presented in Figure 2 is not convincingly supportive of the authors' conclusion. The authors argue that "...CD81 was present in the plasma membrane-derived limiting membrane (Figures 2B, D, F), while CD63 was only found inside the MV-lEVs (Fig. 2A, C, E)." However, in Figure 2G, there is an observable CD63 signal in the limiting membrane (overlapping with the green signals), and in Figure 2J, CD81 also exhibits overlap with MV-IEVs.

(3) Following up on the previous concern, the authors argue that CD81 and CD63 are exclusively located on the limiting membrane and MV-IEVs, respectively (Figure 2-A-M). However, in lines 104-106, the authors conclude that "The simultaneous presence of CD63, CD81, TSG101, ALIX, and the autophagosome marker LC3B within the MV-lEVs..." This statement indicates that CD63 and CD81 co-localize to the MV-IEVs. The authors need to address this apparent discrepancy and provide an explanation.

(4) The specificity of the antibodies used in Figure 2 should be validated through knockout or knockdown experiments. Several of the antibodies used in this figure detect multiple bands on western blots, raising doubts about their specificity. Verification through additional experimental approaches is essential to ensure the reliability and accuracy of all the immunostaining data in this manuscript.

(5) In Figures 2P-R, the morphology of the MV-IEVs does not resemble those shown in Figures 1-A, H, and D, indicating a notable inconsistency in the data.

(6) There are no loading controls provided for any of the western blot data. Additionally, for Figures 2-S4B, the authors should run the samples from lanes i-iii in a single gel.

(7) In Figure 2-S4, is there co-localization observed between LC3RFP (LC3A?) with other MV-IFV markers? How about LC3B? Does LC3B co-localize with other MV-IFV markers?

(8) The TEM images presented in Figure 2-S5, specifically F, G, H, and I, do not closely resemble the images in Figure 2-S5 K, L, M, N, and O. Despite this dissimilarity, the authors argue that these images depict the same structures. The authors should provide an explanation for this observed discrepancy to ensure clarity and consistency in the interpretation of the presented data.

(9) For Figures 3C and 3-S1, the authors should include the images used for EV quantification. Considering the concern regarding potential contamination introduced by FBS (concern 1), it is advisable for the authors to employ an independent method to identify EVs, thereby confirming the reliability of the data presented in these figures.

(10) Do the amphiectosomes released from other cell types as well as cells in mouse kidneys or liver contain LC3B positive and CD63 positive ILVs?

Reviewer #2 (Public Review):

Summary:

The authors had previously identified that a colorectal cancer cell line generates small extracellular vesicles (sEVs) via a mechanism where a larger intracellular compartment containing these sEVs is secreted from the surface of the cell and then tears to release its contents. Previous studies have suggested that intraluminal vesicles (ILVs) inside endosomal multivesicular bodies and amphisomes can be secreted by the fusion of the compartment with the plasma membrane. The 'torn bag mechanism' considered in this manuscript is distinctly different because it involves initial budding off of a plasma membrane-enclosed compartment (called the amphiectosome in this manuscript, or MV-lEV). The authors successfully set out to investigate whether this mechanism is common to many cell types and to determine some of the subcellular processes involved.

The strengths of the study are:

(1) The high-quality imaging approaches used, seem to show good examples of the proposed mechanism.

(2) They screen several cell lines for these structures, also search for similar structures in vivo, and show the tearing process by real-time imaging.

(3) Regarding the intracellular mechanisms of ILV production, the authors also try to demonstrate the different stages of amphiectosome production and differently labelled ILVs using immuno-EM.<br /> Several of these techniques are technically challenging to do well, and so these are critical strengths of the manuscript.

The weaknesses are:

(1) Most of the analysis is undertaken with cell lines. In fact, all of the analysis involving the assessment of specific proteins associated with amphiectosomes and ILVs are performed in vitro, so it is unclear whether these processes are really mirrored in vivo. The images shown in vivo only demonstrate putative amphiectosomes in the circulation, which is perhaps surprising if they normally have a short half-life and would need to pass through an endothelium to reach the vessel lumen unless they were secreted by the endothelial cells themselves.

(2) The analysis of the intracellular formation of compartments involved in the secretion process (Figure 2_S5) relies on immuno-EM, which is generally less convincing than high-/super-resolution fluorescence microscopy because the immuno-labelling is inevitably very sporadic and patchy. High-quality EM is challenging for many labs (and seems to be done very well here), but high-/super-resolution fluorescence microscopy techniques are more commonly employed, and the study already shows that these techniques should be applicable to studying the intracellular trafficking processes.

(3) One aspect of the mechanism, which needs some consideration, is what happens to the amphisome membrane, once it has budded off inside the amphiectosome. In the fluorescence images, it seems to be disrupted, but presumably, this must happen after separation from the cell to avoid the release of ILVs inside the cell. There is an additional part of Figure 1 (Figure 1Y onwards), which does not seem to be discussed in the text (and should be), that alludes to amphiectosomes often having a double membrane.

(4) The real-time analysis of the amphiectosome tearing mechanism seemed relatively slow to me (over three minutes), and if this has been observed multiple times, it would be helpful to know if this is typical or whether there is considerable variation.

Overall, I think the authors have been successful in identifying amphiectosomes secreted from multiple cell lines and demonstrating that the ILVs inside them have at least two origins (autophagosome membrane and late endosomal multivesicular body) based on the markers that they carry. The analysis of intracellular compartments producing these structures is rather less convincing and it remains unclear what cells release these structures in vivo.

I think there could be a significant impact on the EV field and consequently on our understanding of cell-cell signalling based on these findings. It will flag the importance of investigating the release of amphiectosomes in other studies, and although the authors do not discuss it, the molecular mechanisms involved in this type of 'ectosomal-style' release will be different from multivesicular compartment fusion to the plasma membrane and should be possible to be manipulated independently. Any experiments that demonstrate this would greatly strengthen the manuscript.

In general, the EV field has struggled to link up analysis of the subcellular biology of sEV secretion and the biochemical/physical analysis of the sEVs themselves, so from that perspective, the manuscript provides a novel angle on this problem.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors describe a novel mode of release of small extracellular vesicles. These small EVs are released via the rupture of the membrane of so-called amphiectosomes that resemble "morphologically" Multivesicular Bodies.

These structures have been initially described by the authors as released by colorectal cancer cells (https://doi.org/10.1080/20013078.2019.1596668). In this manuscript, they provide experiments that allow us to generalize this process to other cells. In brief, amphiectosomes are likely released by ectocytosis of amphisomes that are formed by the fusion of multivesicular endosomes with autophagosomes. The authors propose that their model puts forward the hypothesis that LC3 positive vesicles are formed by "curling" of the autophagosomal membrane which then gives rise to an organelle where both CD63 and LC3 positive small EVs co-exist and would be released then by a budding mechanism at the cell surface that appears similar to the budding of microvesicles /ectosomes. Very correctly the authors make the distinction from migrasomes because these structures appear very similar in morphology.

Strengths:

The findings are interesting despite that it is unclear what would be the functional relevance of such a process and even how it could be induced. It points to a novel mode of release of extracellular vesicles.

Weaknesses:

This reviewer has comments and concerns concerning the interpretation of the data and the proposed model. In addition, in my opinion, some of the results in particular micrographs and immunoblots (even shown as supplementary data) are not of quality to support the conclusions.

Reviewer #1 (Public Review):

Summary:

This study aims to understand how cell fusion contributes to wound healing using a laser-induced injury in the notum epithelium of a developing fruit fly. The authors meticulously characterize the epithelial fusion events using a live imaging approach and report that syncytia arise by 'border breakdown' and 'cell shrinking'. The syncytial epithelial cells also appear to outcompete mononucleated cells and preferentially dissolve their tangential borders, which correlates with the accumulation of actin at the leading edge.

Strengths:

The strength of this study is the authors' live imaging approach to capture these dynamic fusion events that are a fundamental, yet poorly understood biological process.

Weaknesses:

A major weakness is that all the authors' conclusions are based on descriptive studies, in which the role of cell fusion is not directly tested. This is particularly important because other models of wound-induced polyploidization have demonstrated that another cytoskeletal protein, myosin, was upregulated and dependent on endoreplication, and not cell fusion. Therefore it remains unclear to what extent cell fusion, endoreplication, or both are required to outcompete mononucleated cells as well as pool actin as described in this study.

Reviewer #2 (Public Review):

Summary:

Overall, this study provides a thorough description of the formation of syncytia following wounding of the proliferation-competent diploid epithelium of the pupal notum. While this phenomenon has already been described briefly for this particular tissue by the Galko lab in Wang et al 2015, the authors provide a much more detailed description and characterisation of the process providing some novel insights (radial versus tangential border breakdown, cell shrinkage, timings, syncytia outcompeting mononucleated cells, etc.).

Strengths:

This paper provides an elegant, thorough, descriptive characterisation of syncytia-driven wound closure using state-of-the-art confocal live imaging of the pupal notum. The authors show that laser-induced wounding of this diploid, proliferation-competent epithelium results in the formation of syncytia of various sizes in the first few cell rows around the wound edge, which progressively become bigger as healing proceeds. This results in ~50% of cells becoming part of these syncytia. The cell fusion events were convincingly demonstrated by showing the disappearance of p120ctnRFP and E-Cadherin-GFP from cell-cell borders as well as cytoplasmic GFP mixing of GFP-positive cells with a GFP-negative cell.

Apart from cell-cell fusion by border breakdown that mostly happens in the first 2h following wounding, the authors also found that at later stages of wound healing cell shrinkage following cytoplasmic mixing contributed to sycytia formation.

Next, the authors provided some convincing evidence that syncytia outcompete mononuclear cells for being positioned in the first cell row around the wound.

The authors then show that radial border breakdown occurs much less frequently than tangential border breakdown. They suggest that radial border breakdown reduces the requirement for cell-cell intercalations. They also hypothesise that tangential border breakdown might allow fused cells to share resources and provide more resources to be used near the wound edge, e.g. for actomyosin cable formation. To test this, the authors generate single-cell clones that overexpress Actin-GFP. They then show convincingly how a single Actin-GFP-positive cell in the second cell row fuses with one GFP-negative cell in the first cell row. The Actin-GFP signal then spreads in the fused cell and labels some previously unlabelled actin-rich structure near the wound edge which most likely is the actomyosin cable. This provides some evidence for resource sharing by cytoplasmic mixing following fusion.

Weaknesses:

The authors provide some convincing evidence that syncytia outcompete mononuclear cells for being positioned in the first cell row around the wound. The authors suggest that the syncytial cells might be better able to close the wound. However, some genetic studies would need to be done to establish this more convincingly. E.g. Could the authors genetically block syncytia formation and then show that these wounds now heal slower?

The authors suggest that radial border breakdown reduces the requirement for cell intercalation. While this might be true it also raises the question of how the various syncytia facing the wound border change shape to allow the shrinkage of the first cell row over time to allow wound closure. None of the four movies included in the study shows the whole wound healing process until the later stages, making it hard to assess this. It would be good to include one such movie showing the syncytia in the whole wound and comment on this point.

The authors hypothesise that tangential border breakdown might allow fused cells to share resources and provide more resources to be used near the wound edge, e.g. for actomyosin cable formation. They show convincingly through the fusion of a single Actin-GFP-positive cell in the second cell row with a GFP-negative cell in the first cell row that Actin-GFP spreads in the fused cell and labels the previously unlabelled actomyosin cable. While the hypothesis of resource sharing to improve healing is intriguing and makes sense, this experiment doesn't necessarily prove the benefit of resource sharing. It does show cytoplasmic mixing following fusion, now allowing the GFP-labelled actin to diffuse and be incorporated into the actomyosin cable. In a wild-type condition, fusion would not increase the total concentration of resources, although it would increase the total amount of resources within this bigger fused cell. The question is whether resource sharing without increasing the protein concentration is beneficial and increases the efficiency of certain wound healing mechanisms. There might be a benefit of cell fusion, if for example certain resources were only present in limited amounts or if protein transport could increase the concentration locally. To provide better evidence for the hypothesis that resource sharing improves wound healing, maybe the authors could look at the actomyosin cable in a wounded epithelium (such as in Figure 4E, F), in which all cells express MyoII-GFP. The authors could compare the average intensity of the actomyosin cable at the wound edge in mononucleated cells versus in syncytia. If resource sharing is indeed beneficial, it might be that the actomyosin cable is stronger/brighter in syncytia or it forms quicker.

The biggest limitation of this study is that the authors don't address how the formation of these syncytia is regulated. While the manuscript in its current form provides some valuable new insights into syncytial-driven wound closure, it would be much more informative if it also provided some mechanistic details. The authors could test if some of the mechanisms shown to regulate syncytial formation in other types of syncytia-driven wound healing are also involved here. E.g. Yorkie was shown to negatively regulate cell fusion in adult syncytial-driven wound closure (Losick et al 2013). The authors could test for the effect of Yorkie-RNAi in the epithelium on wound closure and syncytia formation. Expression of the dominant negative RacN17 also blocked cell fusion in adult syncytial-driven wound closure (Losick et al 2013).

Moreover, JNK activation was shown to be needed in larval syncytial-driven wound closure (Galko and Krasnow 2004). The authors could test JNK pathway reporters to assess pathway activation or test if the JNK pathway is needed for syncytial-driven wound closure by expressing a dominant-negative form of Basket JNK in the epithelium.

Or could syncytia formation be regulated by changes in Integrin-mediated adhesion as shown by the Galko lab in Wang et al 2015? They show that wounding provoked a striking relocalization of PINCH and ILK, indicating the disassembly of functional FA complexes concomitant with syncytium formation. Maybe the authors could investigate some of these.

Another general question that the authors raise but don't address enough is whether syncytia-driven wound closure in proliferation-competent epithelia is any different from the one in post-mitotic, polyploid epithelia. Since the mechanism regulating the former is not known, this remains unclear.

Finally, it is not clear, whether syncytia in these proliferation-competent epithelia get resolved after wound healing. Do they get removed and replaced by mononucleated proliferation-competent cells or do the syncytia stay in the epithelium like a scar? The authors should provide some images of wound areas a few hours after wound closure is complete and comment on this.

Minor points:

Figure 3: It would be better to have the microcopy images alongside the quantifications.

Figure 4A: The syncytium at the wound edge here doesn't look straight but wavy. Does it not form an actomyosin cable that straightens the front? Or are there lamellipodia/filopodia?

248: The authors suggest an interesting hypothesis that mitochondria or ER could be pooled in fused cells. It would be nice to see some evidence: e.g. by labeling mitochondria and assessing where they are in syncytia versus mononucleated cells and whether they are concentrated around the wound edge.

141-145 (Figure 4B and C) This example is not completely convincing. First, it is hard to see where the wound edge is. Second, it would be good to include an even later time point when the cell is clearly no longer at the wound edge.

Reviewer #3 (Public Review):

Summary:

White et al. described laser-induced wound healing of the Drosophila pupal notum. They found that the epithelial monolayer is dynamically induced to form syncytia by cell-cell fusion as an important part of repair. They reveal two processes: cell shrinking and border breakage that occur as part of syncytia formation. Expression of GFP in the cytoplasms of some epithelial cells reveals that cytoplasmic contents mix following injury and the GFP rapidly diffuses between cells. Using live imaging they observe that syncytia expand towards the wound, maintain their positions close to the leading edge, and apparently displace smaller cells. They propose that syncytia redistribute cellular components towards the wound facilitating repair and show that labelled actin becomes concentrated at the leading edge.

Strengths:

The manuscript is interesting and on an important and emerging topic of wound healing in a genetically tractable organism. The manuscript is very well written.

Weaknesses:

There are three major issues that the authors must address:

(1) Is cell-cell fusion sufficient to enhance/facilitate wound healing?

(2) Characterization of "border breakdown"; Is this phenomenon disassembly of apical junctions following membrane fusion?

(3) Are cells really shrinking or is it only the apical domains that "shrink" as the cells join the syncytium?

Reviewer #1 (Public Review):

Summary:

This is an original manuscript submission by Tatekoshi et al entitled, "Human induced pluripotent stem cell-derived cardiomyocytes to study inflammation-induced diastolic dysfunction." Based on the premise that treated HIV individuals commonly have heart failure with preserved ejection fraction, yet robust animal models have not been established, the team developed iPS-CM models to study HFpEF with this angle in mind. The group established iPS-CMs using standard methods and studied TNFa and IFNy effects on calcium transients. They observed that both cytokines increased calcium transient decay and downstroke times, which could be reversed by mitoTempo treatment in the case of TNFa. To determine how mitochondrial dysfunction may impact the cytokine-induced calcium transient changes, the team measured OCR treatment changes. They observed that NAC and TNFa co-treated cells demonstrated reduced OCR. The team went on to test the effects of antiretroviral therapies including tenofovir, relategravir, elvitegravir, and darunavir at 3-10 uM levels in iPS-CMs. The team noted that ART treatments reversed the diastolic dysfunction associated with TNFa treatment suggesting that ART therapies may improve diastolic dysfunction that is associated with TNFa signaling directly in cardiomyocytes. Following up on this treatment effect, the team screened several other candidates across drug classes and identified that dapagliflozin (SGLT2i) reversed diastolic dysfunction induced by TNFa. Finally, the team collected human serum from patients with HIV+ patients from two hospitals - Northwestern with diastolic dysfunction by cMRI, and UCSF with normal diastolic function by echo. Both cohort serum samples did not change calcium transients in iPS-CMs. However, due to numerous and significant major methodological concerns, and the potential low impact of the study results, this manuscript is expected to be of very low impact to the field in its current form.

Strengths:

1) From a significance standpoint, understanding the mechanisms of HFpEF, particularly in conditions such as HIV would be very impactful.

2) Collecting HIV patient serum and identifying a plasma factor that impacts cardiac function could be very significant if successful.

Weaknesses:

(1) I am not convinced how this study relates to HIV individual HFpEF, and the study design does not seem to be well thought out.

(2) The connectivity of the study experiments is loose, and data analysis and conclusions are broadly overstated and misinterpreted.

(3) For example the study lacks any measure of diastolic contractile function, and even if performed, the relevance of TNFa treatments to cells in vitro in these immature cell contexts would remain unclear. There is surprisingly no reported molecular analyses of potential mechanisms of the calcium transient changes. The study falls short in molecular detail and instead relies on drug treatments and responses that are hard to interpret with dosages that are not well justified and treatments that are numerous. Unclear what changes in calcium transients mean functionally without a comprehensive assessment of CM biomechanical contraction and relaxation measurements, and this would also require parallel molecular investigations of potential targets of any phenotypes observed.

(4) Calcium transient data need to be better illustrated such as with representative peak tracings. The data overall is with too few samples, particularly given the inherent heterogeneity of iPS-CM studies. The iPS-CM system as a model for diastolic dysfunction remains unestablished.

(5) There are unclear dose choices for the various ART drugs tested, as well as the other drugs tested such as SGLT2i. Besides the observation that SLC5A2 (SGLT2 target) is not established to be expressed in adult mammalian cardiomyocytes.

(6) HIV plasma samples were not tested for cytokine levels, but this could be done to assess the validity of the final experiments. It is unclear what is being tested with these experiments.

(7) The choice of serum controls from a second institution (UCSF) opens up concerns over batch effects unrelated to differences in diastolic dysfunction. However, there were no differences with the Northwestern samples. It is unclear why this data is included as it does not add to the impact of the study.

(8) There are concerns about the quality of the iPS-CMs since there is no cell imaging or molecular analyses. Figure 5 Supplement 1 images are of low quality and low resolution to assess cell quality. Overall the iPS-CM QC data is extremely sparse

Reviewer #2 (Public Review):

The authors investigated the role of inflammatory molecules in diastolic dysfunction and screened antiviral and cardioprotective pharmacological agents for their potential to reverse inflammation-mediated diastolic dysfunction. This study focuses on heart failure with preserved ejection fraction (HFpEF) in people living with HIV (PLWH), a condition often challenging to study due to the lack of suitable animal models. Using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), researchers simulated HFpEF in vitro. They observed that inflammatory cytokines impaired cardiomyocyte relaxation, mimicking HFpEF, while SGLT2 inhibitors and mitochondrial antioxidants reversed this effect. Exposure to serum from HIV patients did not induce dysfunction in hiPSC-CMs. These findings suggest hiPSC-CMs as a promising model for understanding HFpEF mechanisms and testing potential treatments.

Comments to improve the study:

The manuscript is well-written, and the results are well-illustrated. However, there are some topics that are not well-connected, and the rationale and hypothesis are not clearly defined beforehand, such as mitochondrial membrane potential, mitochondrial ROS, and angiogenic potential.

As the hiPSC cardiomyocytes are treated with various reagents to measure diastolic dysfunction, it is important to confirm whether the treatment time and dose used were sufficient to exert a functional effect. Dose and time-dependent experiments are essential, or at least sufficient citations should be provided for selecting the dose for IFN and TNF.

After IFN and TNF treatment, determining the expression levels of molecular markers of DD/HFpEF is crucial. Again, if sufficient evidence is available, it can be cited.

The Methods section describes TMRE colocalization and immunofluorescence, but no images are provided.

The concentration of TNF and IFN in patients is critical, which was acknowledged and discussed as a limitation of the study by the authors. Authors should consider this aspect, and if not feasible, clinical reports should be cited to provide a rough estimation of their concentration.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Weng et al. detect a neuron-specific transcriptome that regulates aging. The authors first profile neuron-specific responses during aging at a time point where a loss in memory function is present. They discover signatures unique to neurons which validate their pipeline and reveal the loss of neuron identity with age. For example, old neurons reduce the expression of genes related to synaptic function and neuropeptide signaling and increase the expression of chromatin regulators, insulin peptides, and glycoproteins. The authors discover the detrimental effect of selected upregulated genes (utx-1, ins-19, and nmgp-1) by knocking them down in the whole body and detecting improvement of short memory functions. They then use their pipeline to test neuronal profiles of long-lived insulin/IGF mutants. They discover that genes related to stress response pathways are upregulated upon longevity (e.g. dod-24, F08H9.4) and that they are required for improved neuron function in long-lived individuals.

Strengths:

Overall, the manuscript is well-written, and the experiments are well-described. The authors take great care to explain their reasoning for performing experiments in a specific way and guide the reader through the interpretation of the results, which makes this manuscript an enjoyable and interesting read. Using neuron-specific transcriptomic analysis in aged animals the authors discover novel regulators of learning and memory, which underlines the importance of cell-specific deep sequencing. The time points of the transcriptomic profiling are elegantly chosen, as they coincide with the loss of memory and can be used to specifically reveal gene expression profiles related to neuron function. The authors showcase on the dod-24 example how powerful this approach is. In long-lived insulin/IGF-1 receptor mutants body-wide dod-24 expression differs from neuron-specific profiles. Importantly, the depletion of dod-24 has an opposing effect on lifespan and learning memory. The dataset will provide a useful resource for the C. elegans and aging community.

Weaknesses:

While this study nicely describes the neuron-specific profiles, the authors do not test the relevance in a tissue-specific way. It remains unclear if modifying the responses only in neurons has implications for either memory or potentially for lifespan. The authors point to this in the text and refer to tissue-specific datasets. However, it is possible that the tissue-specific profile changes with age. The authors should consider mining publicly available cell-specific aging datasets and performing neuron-specific RNAi to test the functional relevance of the neuron-specific response. This would strengthen the importance of cell-specific profiling.

Reviewer #1 (Public Review):

The authors perform RNA-seq on FACS-isolated neurons from adult worms at days 1 and 8 of adulthood to profile the gene expression changes that occur with cognitive decline. Supporting data are included indicating that by day 7 of adulthood, learning and memory are reduced, indicating that this time point or after represents cognitively aged worms. Neuronal identity genes are reduced in expression within cognitively aged worms, whereas genes involved in proteostasis, transcription/chromatin, and stress response are elevated. A number of specific examples are provided, representing markers of specific neuronal subtypes, and correlating expression changes to the erosion of particular functions (e.g. motor neurons, chemosensory neurons, aversive learning neurons, etc).

To investigate whether the upregulation of genes in neurons with age is compensatory or deleterious, the authors reduced the expression of a set of three significantly upregulated genes and performed behavioral assays in young adults. In each case, reduction of expression improved memory, consistent with a model in which age-associated increases impair neuronal function. This claim would be bolstered by an experiment elevating the expression of these genes in young neurons, which should reduce the learning index if the hypothesis is correct.

The authors then characterize learning and memory in wild-type, daf-2, and daf-2/daf-16 worms with age and find that daf-2 worms have an extended ability to learn for approximately 10 days longer than wild types. This was daf-16 dependent. Memory was extended in daf-2 as well, and strikingly, daf-2;daf-16 had no short-term memory even at day 1. Transcriptomic analysis of FACS-sorted neurons was performed on the three groups at day 8. The authors focus their analysis on daf-2 vs. daf-2;daf-16 and present evidence that daf-2 neurons express a stress-resistance gene program. One question that remains unanswered is how well the N2 and daf-2;daf-16 correlate overall, and are there differences? This may be informative as wild type and daf-2;daf-16 mutants are not phenotypically identical when it comes to memory, and there may be differences that can be detected despite the overlap in the PCA. This analysis could reveal the daf-16 targets involved in memory.

The authors tested eight candidate genes that were more highly expressed in daf-2 neurons vs. daf-2;daf-16 and showed that reduction of 2 and 5 of these genes impaired learning and memory, respectively, in daf-2 worms. This finding implicates specific neuronal transcriptional targets of IIS in maintaining cognitive ability in daf-2 with age, which, importantly, are distinct from those in young wild type worms.

Reviewer #2 (Public Review):

Weng et al. perform a comprehensive study of gene expression changes in young and old animals, in wild-type and daf-2 insulin receptor mutants, in the whole animal, and specifically in the nervous system. Using this data, they identify gene families that are correlated with neuronal ageing, as well as a distinct set of genes that are upregulated in neurons of aged daf-2 mutants. This is particularly interesting as daf-2 mutants show both extended lifespans and healthier neurons in aged animals, reflected by better learning/memory in older animals compared with wild-type controls. Indeed, the knockdown of several of these upregulated genes resulted in poorer learning and memory. In addition, the authors showed that several genes upregulated during ageing in wild-type neurons also contribute to learning and memory; specifically knockdown of these genes in young animals resulted in improved memory. This indicates that (at least in this small number of cases), genes that show increased transcript levels with age in the nervous system somehow suppress memory, potentially by having damaging effects on neuronal health.

Finally, from a resource perspective, the neuronal transcriptome provided here will be very useful for C. elegans researchers as it adds to other existing datasets by providing the transcriptome of older animals (animals at day 8 of adulthood) and demonstrating the benefits of performing tissue-specific RNAseq instead of whole-animal sequencing.

The work presented here is of high quality and the authors present convincing evidence supporting their conclusions. I only have a few comments/suggestions:

(1) Do the genes identified to decrease learning/memory capacity in daf-2 animals (Figure 4d/e) also impact neuronal health? daf-2 mutant worms show delayed onset of age-related changes to neuron structure (Tank et al., 2011, J Neurosci). Does knockdown of the genes shown to affect learning also affect neuron structure during ageing, potentially one mechanism through which they modulate learning/memory?

(2) The learning and memory assay data presented in this study uses the butanone olfactory learning paradigm, which is well established by the same group. Have the authors tried other learning assays when testing for learning/memory changes after the knockdown of candidate genes? Depending on the expression pattern of these genes, they may have more or less of an effect on olfactory learning versus for example gustatory or mechanosensory-based learning.

(3) I have a comment on the 'compensatory vs dysregulatory' model as stated by the authors on page 7. I understand that this model presents the two main options, but perhaps this is slightly too simplistic: the gene expression that rises during ageing may be detrimental for memory (= dysregulatory), but at the same time may also be beneficial for other physiological roles in other tissues (=compensatory).

Reviewer #1 (Public Review):

Summary:

The manuscript by Relovska and colleagues aims to decipher the importance of sterol homeostasis on male reproduction and, in particular, the impact of altered sterol homeostasis in sperm cells. To this end, they are generating a global line of Dhcr24 transgenic mice by mating Dhcr24fl/fl mice (overexpressing the construct in the Rosa269c gene locus) with EIla 100 CRE mice (expressing Cre recombinase in the early mouse embryo).

The data provided are robust, using a range of approaches from sperm analysis (structure, function) to lipid analysis. Results show that overexpression of DHCR24 (TG) leads to altered sterol homeostasis in spermatozoa. Sperm from TG mice have abnormal mitochondria and sperm tails. TG spermatozoa have reduced efficiency in undergoing the acrosomal reaction. Furthermore, the data suggest that TG spermatozoa have an altered metabolism with increased oxygen consumption. These data highlight that desmosterol depletion and/or altered sterol homeostasis impact sperm morphology, number, motility, and metabolism, resulting in reduced male fertility.

Strengths:

The manuscript is clear and well-written, and the results are presented in high-quality figures.

Weaknesses:

The main concern is the clear analysis of the rodent model. Indeed, the use of this particular Cre leads to whole-body overexpression, the remaining question is whether the observed effects are directly mediated by the testicular impacts of Dhcr24 overexpression. Even if it is a testicular effect, we can't conclude where it comes from. Is it at the level of spermatogenesis, as the authors speculate? Furthermore, the authors mention that normally, Dhcr24c is mainly expressed in spermatogonia, so it's not clear why they focus only on spermatozoa, which in WT males do not normally express dhcr24 according to the authors. It is worth clarifying the testicular phenotype in more detail.

The lower level of TG in aged mice could suggest an extinction of the transgene at least in sperm during aging, which could be difficult to reconcile with the observed phenotype. With this in mind, it would be interesting to define the penetrance of the phenotype during aging, to define variability between mice, and to clearly define potential correlations between sterol levels and fertility disorders, or altered sperm parameters.

Reviewer #2 (Public Review):

Summary:

Sterols, including desmosterol and cholesterol, play critical roles in male fertility including membrane rearrangements associated with sperm capacitation, steroidogenesis, and germ cell development. Relovska, Sona, et al. investigated the effects of global overexpression of classic cholesterol biosynthesis enzyme DHCR24 in a mouse model, focusing on the impacts on sperm function and male fertility. While mice were viable and did not exhibit altered plasma cholesterol levels or obesity, the authors demonstrated that concentrations of relevant sterols in sperm from transgenic mice were altered compared to WT mouse sperm, including the expected depletion of desmosterol. The transgenic males exhibited several indicators of reduced sperm function and fertility. Mitochondrial dysfunction was indicated by a noted depletion of localization in the distal middle-piece of up to approximately 20-25% of transgenic sperm flagella, and alterations in mitochondrial membrane potential and oxygen consumption rates in transgenic sperm were noted.

Strengths:

The authors demonstrate that DHCR24 overexpression was achieved and that sperm sterol levels are altered. The conclusions that global DHCR24 overexpression impacts mitochondrial localization and male fertility parameters are supported by the number of different supporting assessments utilized to reach these conclusions and this is a strength. Overall, the authors achieve their aim of demonstrating DHCR24 overexpression impacts on indicators of sperm function and fertility including reduced sperm counts and sperm motility, reduced fertility in mating trials with aged males, and reduced IVF success when sperm were capacitated in conditions of higher sperm concentrations in vitro. The authors further investigate sperm mitochondrial localization and function. While a mitochondrial sheath can form in sperm from transgenic mice, 25% of the sperm exhibit a shortened mitochondrial sheath where a distal portion of the middle piece of the sperm flagella lacks mitochondria and instead exhibits exposed outer dense fibers.

Weaknesses:

In the current study, the authors conclude that desmosterol may not act as an LXR activator in testicular cells based on assessment of relevant mRNA levels in whole testis that indicated the relevant transcripts were not altered in transgenic testes. However, caution should be taken in utilizing whole testis transcriptomics to rule out a role in specific cell populations within the testis with minor relative representation, such as macrophages or undifferentiated spermatogonia. This is an important distinction for a few reasons. The authors reveal through single-cell assessments of DHCR24 expression in WT testis that it is most highly expressed in undifferentiated spermatogonia. Further, the authors previously reported that DHCR24 over-expression in myeloid/macrophage populations did impact LXR activation impacting atherosclerosis. Taken together with emerging evidence that testis macrophages may impact spermatogonial fate decisions, the potential for DHCR24 to impact these minor testicular cell populations should not yet be ruled out. The significance of individual observations needs to be clarified through improved reporting of methodologies, specific biological and technical replicates, and statistical significance for each individual assessment. The lack of these details obfuscates the ability of the reader to interpret or replicate several reported observations which is a weakness.

(1) The fertility trials indicate a reduced number of pups/litter in aged but not younger transgenic males. However, the data for the aged males includes three data points of 0 pups, which brings to question if the data points each represent the average pups/litter for individual males or individual litters with multiple litters separately included for fertile males. Clarification could help in interpreting whether litter sizes were reduced, or if litter frequency and/or fertility of individual males was reduced. In the latter case, behavioral infertility would not be excluded from consideration.

(2) The statistical significance is not clear for altered acrosome reaction data, hyperactivated motility data, waveform analysis, mitochondrial membrane potential, and some of the sperm morphology assessments. In many assessments, the biological and technical replicates assessed need to be clarified.

(3) Methods utilized for image assessment of waveform analysis and mitochondrial membrane potential are lacking detail sufficient for replication of the assessments or for reader interpretation of how conclusions were reached.

Summary of impact:

Overall, the novel observations in this study are consistent with a role for controlled sterol concentrations being important for male fertility and indicate that this model will be useful to further investigate sterol biosynthesis contributions to testis function including steroidogenesis, spermatogenesis, and sperm function including capacitation.

Reviewer #3 (Public Review):

Summary:

The authors have created DHCR24 knockin mice and noted changes in the sperm sterol composition. Concurrently, alterations in the quantity, motility, and function of the sperm in DHCR24 knockin mice were identified.

Strengths:

The manuscript offers an intriguing perspective on how disruptions in sperm sterol composition can lead to sperm abnormalities.

Weaknesses:

From the current data, several issues remain to be clarified, including the fertility test results, which merit a more detailed presentation to ascertain whether differences stem from individual variability or overall changes. The authors suggest an increase in ROS in the sperm of DHCR24 knockin mice, leading to sperm damage, which also requires further confirmation. Moreover, the quality of some data requires verification or improvement, such as the morphological analysis of testicular sections and the OCR experiments.

Reviewer #3 (Public Review):

The author presents a novel theory and computational model suggesting that grid cells do not encode space, but rather encode non-spatial attributes. Place cells in turn encode memories of where those specific attributes occurred. The theory accounts for many experimental results and generates useful predictions for future studies. The model's simplicity and potential explanatory power will interest others in the field, though there are a number of concerns that should first be addressed.

A crucial assumption of the model is that the content of experience must be constant in space. It's difficult to imagine a real-world example that satisfies this assumption. Odors and sounds are used as examples. While they are often more spatially diffuse than an objects on the ground, odors and sounds have sources that are readily detectable. Animals can easily navigate to a food source or to a vocalizing conspecific. This assumption is especially problematic because it predicts that all grid cells should become silent when their preferred non-spatial attribute (e.g. a specific odor) is missing. I'm not aware of any experimental data showing that grid cells become silent. On the contrary, grid cells are known to remain active across all contexts that have been tested, including across sleep/wake states. Unlike place cells, grid cells do not seem to turn off. Since grid cells are active in all contexts, their preferred attribute must also be present in all contexts, and therefore they would not convey any information about the specific content of an experience.

The proposed novelty of this theory is that other models all assume that grid cells encode space. This isn't quite true of models based on continuous attractor networks, the discussion of which is notably absent. More specifically, these models focus on the importance of intrinsic dynamics within the entorhinal cortex in generating the grid pattern. While this firing pattern is aligned to space during navigation and therefore can be used as a representation of that space, the neural dynamics are preserved even during sleep. Similarly, it is because the grid pattern does not strictly encode physical space that grid-like signals are also observed in relation to other two-dimensional continuous variables.

The use of border cells or boundary vector cells as the main (or only) source of spatial information in the hippocampus is not well supported by experimental data. Border cells in the entorhinal cortex are not active in the center of an environment. Boundary-vector cells can fire farther away from the walls but are not found in the entorhinal cortex. They are located in the subiculum, a major output of the hippocampus. While the entorhinal-hippocampal circuit is a loop, the route from boundary-vector cells to place cells is much less clear than from grid cells. Moreover, both border cells and boundary-vector cells (which are conflated in this paper) comprise a small population of neurons compared to grid cells.

Reviewer #1 (Public Review):

Huber proposes a theory where the role of the medial temporal lobe (MTL) is memory, where properties of spatial cells in the MTL can be explained through memory function rather than spatial processing or navigation. Instantiating the theory through a computational model, the author shows that many empirical phenomena of spatial cells can be captured, and may be better accounted through a memory theory. It is an impressive computational account of MTL cells with a lot of theoretical reasoning and aims to tightly relate to various spatial cell data.

In general, the paper is well written, but likely due to the complexity, there are various aspects of the paper that are difficult to understand. One point is that it is not entirely clear to me that it is a convincing demonstration of purely memory rather than navigation, but rather an account of the findings through the lens of memory. Below, I raise several big-picture theoretical questions. I also have some clarification questions about the model (where I also have some theoretical question marks - due to not achieving a full understanding).

(1) Although the theory is based on memory, it also is based on spatially-selective cells. Not all cells in the hippocampus fulfill the criteria of place/HD/border/grid cells, and place a role in memory. E.g., Tonegawa, Buszaki labs' work does not focus on only those cells, and there are certainly a lot of non-pure spatial cells in monkeys (Martinez-Trujillo) and humans (iEEG). Does the author mainly focus on saying that "spatial cells" are memory, but do not account for non-spatial memory cells? This seems to be an incomplete account of memory - which is fine, but the way the model is set up suggests that *all* memory is, place (what/where), and non-spatial attributes ("grid") - but cells that don't fulfil these criteria in MTL (Diehl et al., 2017, Neuron; non-grid cells; Schaeffer et al., 2022, ICML; Luo et al., 2024, bioRxiv) certainly contribute to memory, and even navigation. This is also related to the question of whether these cell definitions matter at all (Luo et al., 2024).

The authors note "However, this memory conjunction view of the MTL must be reconciled with the rodent electrophysiology finding that most cells in MTL appear to have receptive fields related to some aspect of spatial navigation (Boccara et al., 2010; Grieves & Jeffery, 2017). The paucity of non-spatial cells in MTL could be explained if grid cells have been mischaracterized as spatial." Is the author mainly talking about rodent work?

(2) Related to the last point, how about non-grid multi-field mEC cells? In theory, these also should be the same; but the author only presents perfect-look grid cells. In empirical work, clearly, this is not the case, and many mEC cells are multi-field non-grid cells (Diehl et al., 2017). Does the model find these cells? Do they play a different role?

As noted by the author "Because the non-spatial attributes are constant throughout the two-dimensional surface, this results in an array of discrete memory locations that are approximately hexagonal (as explained in the Model Methods, an "online" memory consolidation process employing pattern separation rapidly turns an approximately hexagonal array into one that is precisely hexagonal). "

If they are indeed all precisely hexagonal, does that mean the model doesn't have non-grid spatial cells?

(3) Theoretical reasons for why the model is put together this way, and why grid cells must be coding a non-spatial attribute: Is this account more data-driven (fits the data so formulated this way), or is it theoretical - there is a reason why place, border, grid cells are formulated to be like this. For example, is it an efficient way to code these variables? It can be both, like how the BVC model makes theoretical sense that you can use boundaries to determine a specific location (and so place cell), but also works (creates realistic place cells).

But in this case, the purpose of grid cell coding a non-spatial attribute, and having some kind of system where it doesn't fire at all locations seems a little arbitrary. If it's not encoding a spatial attribute, it doesn't have to have a spatial field. For example, it could fire in the whole arena - which some cells do (and don't pass the criteria of spatial cells as they are not spatially "selective" to another location, related to above).

(4) Why are grid cells given such a large role for encoding non-spatial attributes? If anything, shouldn't it be lateral EC or perirhinal cortex? Of course, they both could, but there is less reason to think this, at least for rodent mEC.

(5) Clarification: why do place cells and grid cells differ in terms of stability in the model? Place cells are not stable initially but grid cells come out immediately. They seem directly connected so a bit unclear why; especially if place cell feedback leads to grid cell fields. There is an explanation in the text - based on grid cells coding the on-average memories, but these should be based on place cell inputs as well. So how is it that place fields are unstable then grid fields do not move at all? I wonder if a set of images or videos (gifs) showing the differences in spatial learning would be nice and clarify this point.

(6) Other predictions. Clearly, the model makes many interesting (and quite specific!) predictions. But does it make some known simple predictions?<br /> • More place cells at rewarded (or more visited) locations. Some empirical researchers seem to think this is not as obvious as it seems (e.g., Duvellle et al., 2019; JoN; Nyberg et al., 2021, Neuron Review).<br /> • Grid cell field moves toward reward (Butler et al., 2019; Boccera et al., 2019).<br /> • Grid cells deform in trapezoid (Krupic et al., 2015) and change in environments like mazes (Derikman et al., 2014).

Reviewer #2 (Public Review):

The manuscript describes a new framework for thinking about the place and grid cell system in the hippocampus and entorhinal cortex in which these cells are fundamentally involved in supporting non-spatial information coding. If this framework were shown to be correct, it could have high impact because it would suggest a completely new way of thinking about the mammalian memory system in which this system is non-spatial. Although this idea is intriguing and thought-provoking, a very significant caveat is that the paper does not provide evidence that specifically supports its framework and rules out the alternate interpretations. Thus, although the work provides interesting new ideas, it leaves the reader with more questions than answers because it does not rule out any earlier ideas.

Basically, the strongest claim in the paper, that grid cells are inherently non-spatial, cannot be specifically evaluated versus existing frameworks on the basis of the evidence that is shown here. If, for example, the author had provided behavioral experiments showing that human memory encoding/retrieval performance shifts in relation to the predictions of the model following changes in the environment, it would have been potentially exciting because it could potentially support the author's reconceptualization of this system. But in its current form, the paper merely shows that a new type of model is capable of explaining the existing findings. There is not adequate data or results to show that the new model is a significantly better fit to the data compared to earlier models, which limits the impact of the work. In fact, there are some key data points in which the earlier models seem to better fit the data.

Overall, I would be more convinced that the findings from the paper are impactful if the author showed specific animal memory behavioral results that were only supported by their memory model but not by a purely spatial model. Perhaps the author could run new experiments to show that there are specific patterns of human or animal behavior that are only explained by their memory model and not by earlier models. But in its current form, I cannot rule out the existing frameworks and I believe some of the claims in this regard are overstated.

In addition to the broader concerns noted above regarding the absence of any specific behavioral data that are explained by their model and not by existing spatial models, I am additionally concerned that this manuscript does not explain a number of important key empirical results in the rodent grid cell literature.

* The paper does not fully take into account all the findings regarding grid cells, some of which very clearly show spatial processing in this system. For example, findings on grid-by-direction cells (e.g., Sargolini et al. 2006) would seem to suggest that the entorhinal grid system is very specifically spatial and related to path integration. Why would grid-by-direction cells be present and intertwined with grid cells in the author's memory-related reconceptualization? It seems to me that the existence of grid-by-direction cells is strong evidence that at least part of this network is specifically spatial.

* I am also concerned that the paper does not do enough to address findings regarding how the elliptical shape of grid fields shifts when boundaries of an environment compress in one direction or change shape/angles (Lever et al., & Krupic et al). Those studies show compression in grid fields based on boundary position, and I don't see how the authors' model would explain these findings.

* Are findings regarding speed modulation of grid cells problematic for the paper's memory results?

* A further issue is that the paper does not seem to adequately address developmental findings related to the timecourses of the emergence of different cell types. In their simulation, researchers demonstrate the immediate emergence of grid fields in a novel environment, while noting that the stabilization of place cell positions takes time. However, these simulation findings contradict previous empirical developmental studies (Langston et al., 2010). Those studies showed that head direction cells show the earliest development of spatial response, followed by the appearance of place cells at a similar developmental stage. In contrast, grid cells emerge later in this developmental sequence. The gradual improvement in spatial stability in firing patterns likely plays a crucial role in the developmental trajectory of grid cells. Contrary to the model simulation, grid cells emerge later than place cells and head direction cells, yet they also hold significance in spatial mapping.

* The model simulations suggest that certain grid patterns are acquired more gradually than others. For instance, egocentric grid cells require the stabilization of place cell memories amidst ongoing consolidation, while allocentric grid cells tend to reflect average place field positions. However, these findings seemingly conflict with empirical studies, particularly those on the conjunctive representation of distance and direction in the earliest grid cells. Previous studies show no significant differences were found in grid cells and grid cells with directional correlates across these age groups, relative to adults (Wills et al., 2012). This indicates that the combined representation of distance and direction in single mEC cells is present from the earliest ages at which grid cells emerge.

Reviewer #1 (Public Review):

Summary:

The goal of this study was to use in vitro cell populations to determine mechanisms that may be important for the propagation of epimutations induced by EDCs in vivo. To do this, authors exposed induced pluripotent stem cells (iPS), somatic cells (Sertoli, granulosa), and primordial germ cell like cells (PGCLCs) to BPS, and conducted epigenomic and transcriptomic analyses on outcomes. The importance of estrogen receptors, and the relationship of epigenomic results to genomic sites expressing EREs, were also determined in the different cell types. Results revealed differential effects of BPS in each cell population on each of these endpoints, and that epimutations were prevalent in enhancer regions with EREs with the exception of PGCLCs (which do not express ERs). The authors speculate that because epimutations also occurred in regions without EREs, especially in PGCLCs, other mechanisms may be in place. Finally, epimutations induced in iPSCs exposed to BPS that were subsequently differentiated into PGCLCs demonstrated that most epimutations were corrected.

Strengths:

A strength of this work is the use of different cell types representing somatic cells that would be the major recipient of EDC exposure; pluripotent cells representing preimplantation embryos; and PGCLCs that model the early germline in which epigenetic reprogramming takes place. Work differentiating the iPSCs from PGCLCs with or without BPS exposure at the iPSC level is also very informative as it suggests that most epimutations are corrected, at least in vitro. The paper is well-written and studies were technically well-executed and validated. Results are novel and likely to be of interest to those interested in transgenerational inheritance of environmentally-induced traits, as well as others more broadly interested in epigenetic mechanisms.

Critique/Weaknesses:

(1) A problem with in vitro work is that homogeneous cell lines/cultures are, by nature, absent from the rest of the microenvironment. The authors need to discuss this.

(2) What are n's/replicates for each study? Were the same or different samples used to generate the data for RNA sequencing, methylation beadchip analysis, and EM-seq? This clarification is important because if the same cultures were used, this would allow comparisons and correlations within samples.

(3) In Figure 1, it is interesting that the 50 uM BPS dose mainly resulted in hypermethylation whereas 100 uM appears to be mainly hypomethylation. (This is based on the subjective appearance of graphs). The authors should discuss and/or present these data more quantitatively. For example, what percentage of changes were hypo/hypermethylation for each treatment? How many DMRs did each dose induce? For the RNA-seq results, again, what were the number of up/down-regulated genes for each dose?

(4) Also in Figure 1, were there DMRs or genes in common across the doses? How did DMRs relate to gene expression results? This would be informative in verifying or refuting expectations that greater methylation is often associated with decreased gene expression.

(5) In Figure 2, was there an overlap in the hypo- and/or hyper-methylated DMCs? Please also add more description of the data in 2b to the legend including what the dot sizes/colors mean, etc. Some readers (including me) may not be familiar with this type of data presentation. Some of this comes up in Figure 4, so perhaps allude to this earlier on, or show these data earlier.

(6) iPSCs were derived from male mice MEFs, and subsequently used to differentiate into PGCLCs. The only cell type from an XX female is the granulosa cells. This might be important, and should be mentioned and its potential significance discussed (briefly).

(7) EREs are only one type of hormone response element. The authors make the point that other mechanisms of BPS action are independent of canonical endocrine signaling. Would authors please briefly speculate on the possibility that other endocrine pathways including those utilizing AREs or other HREs may play a role? In other words, it may not be endocrine signaling independent. The statement that the differences between PGCLCs and other cells are largely due to the absence of ERs is overly simplistic.

(8) Interpretation of data from the GO analysis is similarly overly simplistic. The pathways identified and discussed (e.g. PI3K/AKT and ubiquitin-like protease pathways are involved in numerous functions, both endocrine and non-endocrine. Also, are the data shown in Figure 6a from all 4 cell types? I am confused by the heatmap in 6c, which genes were significantly affected by treatment in which cell types?

(9) In Figure 7, what were the 138 genes? Any commonalities among them?

(10) The Introduction is very long. The last paragraph, beginning line 105, is a long summary of results and interpretations that better fit in a Discussion section.

(11) Provide some details on husbandry: e.g. were they bred on-site? What food was given, and how was water treated? These questions are to get at efforts to minimize exposure to other chemicals.

Reviewer #2 (Public Review):

Summary:

This manuscript uses cell lines representative of germ line cells, somatic cells, and pluripotent cells to address the question of how the endocrine-disrupting compound BPS affects these various cells with respect to gene expression and DNA methylation. They find a relationship between the presence of estrogen receptor gene expression and the number of DNA methylation and gene expression changes. Notably, PGCLCs do not express estrogen receptors and although they do have fewer changes, changes are nevertheless detected, suggesting a nonconical pathway for BPS-induced perturbations. Additionally, there was a significant increase in the occurrence of BPS-induced epimutations near EREs in somatic and pluripotent cell types compared to germ cells. Epimutations in the somatic and pluripotent cell types were predominantly in enhancer regions whereas that in the germ cell type was predominantly in gene promoters.

Strengths:

The strengths of the paper include the use of various cell types to address the sensitivity of the lineages to BPS as well as the observed relationship between the presence of estrogen receptors and changes in gene expression and DNA methylation.

Weaknesses:

The weaknesses include the lack of reporting of replicates, superficial bioinformatic analysis, and the fact that exposures are more complicated in a whole organism than in an isolated cell line.

Reviewer #1 (Public Review):

Wang et al investigated the evolution, expression, and function of the X-linked miR-506 miRNA family. They showed that the miR-506 family underwent rapid evolution. They provided evidence that miR-506 appeared to have originated from the MER91C DNA transposons. Human MER91C transposon produced mature miRNAs when expressed in cultured cells. A series of mouse mutants lacking individual clusters, a combination of clusters, and the entire X-linked cluster (all 22 miRNAs) were generated and characterized. The mutant mice lacking four or more miRNA clusters showed reduced reproductive fitness (litter size reduction). They further showed that the sperm from these mutants were less competitive in polyandrous mating tests. RNA-seq revealed the impact of deletion of miR-506 on the testicular transcriptome. Bioinformatic analysis analyzed the relationship among miR-506 binding, transcriptomic changes, and target sequence conservation. The miR-506-deficient mice did not have apparent effect on sperm production, motility, and morphology. Lack of severe phenotypes is typical for miRNA mutants in other species as well. However, the miR-506-deficient males did exhibit reduced litter size, such an effect would have been quite significant in an evolutionary time scale. The number of mouse mutants and sequencing analysis represent a tour de force.

Strengths:

This study is a comprehensive investigation of the X-linked miR-506 miRNA family. It provides important insights into the evolution and function of the miR-506 family.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors conducted a comprehensive study of the X-linked miR-506 family miRNAs in mice on its origin, evolution, expression, and function. They demonstrate that the X-linked miR-506 family, predominantly expressed in the testis, may be derived from MER91C DNA transposons and further expanded by retrotransposition. By genetic deletion of different combinations of 5 major clusters of this miRNA family in mice, they found these miRNAs are not required for spermatogenesis. However, by further examination, the mutant mice show mild fertility problem and inferior sperm competitiveness. The authors conclude that the X-linked miR-506 miRNAs finetune spermatogenesis to enhance sperm competition.

Strengths:

This is a comprehensive study with extensive computational and genetic dissection of the X-linked miR-506 family providing a holistic view of its evolution and function in mice. The finding that this family miRNAs could enhance sperm competition is interesting and could explain their roles in finetuning germ cell gene expression to regulate reproductive fitness.

Comments on revised version:

The authors have addressed the concerns raised.

Reviewer #1 (Public Review):

The present study conducted by Berger et al. delves into the extent to which memory formation relies on available energy reserves. While aversive memory formation has been extensively studied in this context, the investigation into appetitive memory formation has been comparatively sparse. It has long been recognized that flies can only form appetitive memory under conditions of starvation. However, the authors of this study go beyond this understanding by revealing that not only the duration of starvation matters, but it also dictates the type of memory formed, whether short- or long-term memory. The authors illustrate that internal glycogen stores play a crucial role in this process, facilitated by insulin-like signaling in octopaminergic reward neurons, which integrates internal energy reserves into memory formation. Consequently, the authors propose that octopamine serves as a negative regulator of various forms of memory, shedding light on the enduring question of the octopaminergic neuronal system's involvement in appetitive memory formation, which has been overshadowed by the focus on the dopaminergic system in recent years. Additionally, the findings contribute to the ongoing debate concerning the role of insulin receptors, whether they function within neurons themselves or in glial cells. Moreover, the authors not only convincingly demonstrate that octopamine negatively regulates appetitive memory formation, but they also propose a mechanism whereby the insulin receptor in octopaminergic neurons senses the internal energy status and subsequently modulates the activity of these neurons. The experiments are meticulously designed, employing a variety of behavioral assays, genetic tools for manipulating neuronal activity, and state-of-the-art imaging techniques. The conclusions are well supported by the data and carefully performed controlled experiments, yielding high-quality data.

Reviewer #2 (Public Review):

How organism physiological state modulates establishment and perdurance of memories is a timely question that the authors aimed at addressing by studying the interplay between energy homeostasis and food-related conditioning in Drosophila. Specifically, they studied how starvation modulates the establishment of short-term vs long-term memories and clarified the role of the monoamine Octopamine in food-related conditioning, showing that it is not per se involved in formation of appetitive short-term memories but rather gates memory formation by suppressing LTM when energy levels are high. This work clarifies previously described phenotypes and provides insight about interconnections between energy levels, feeding and formation of short-term and long-term food-related memories.

Strengths<br /> - Previous studies have documented the impact of Octopamine on different aspects of food-related behaviors (regulation of energy homeostasis, feeding, sugar sensing, appetitive memory...), but we currently lack a clear understanding of how these different functions are interconnected. The authors have used a variety of experimental approaches to systematically test the impact of internal energy levels in establishment of different forms of appetitive memory and the role of Octopamine in this process.

- The authors have used a range of approaches, performed carefully controlled experiments and produced high quality data.

Reviewer #3 (Public Review):

In this manuscript, Berger et al. study how internal energy storage influence learning and memory. Since in Drosophila melanogaster, octopamine (OA) is involved in the regulation of energy homeostasis they focus on the roles of OA. To do so they use the tyramine-β-hydroxylase (Tbh) mutant that is lacking the neurotransmitter OA and study short term memory (STM), long-term memory (LTM) and anesthesia-resistant memory (ARM). They show that the duration of starvation affects the magnitude of both short- and long-term memory. In addition, they show that OA has a suppressive effect on learning and memory. In terms of energy storage, they show that internal glycogen storage influences how long sucrose is remembered, and high glycogen suppresses memory. Finally, they show that insulin-like signaling in octopaminergic neurons, which is also related to internal energy storage, suppresses learning and memory.

The revised version of the manuscript is greatly improved, and I thank the authors for taking the comment seriously. This is an important study that extends our knowledge on OA activity in learning and memory and the effects the metabolic state has on learning and memory. The authors nicely use the genetic tools available in flies to try and unravel the complex circuitry of metabolic state level, OA activity and learning and memory. The overall take-home message of the manuscript is clear and supported by the data presented.

Reviewer #2 (Public Review):

Summary:

This paper acknowledges that most development occurs in social contexts, with other social partners. The authors put forth two main frameworks of how development occurs within a social interaction with a caregiver. The first, is that although social interaction with mature partners is somewhat bi-directional, mature social partners exogenously influence infant behaviors and attention through "attentional scaffolding", and that in this case infant attention is reactive to caregiver behavior. The second framework posits that caregivers support and guide infant attention by contingently responding to reorientations in infant behavior, thus caregiver behaviors are reactive to infant behavior. The aim of this paper is to use moment-to-moment analysis techniques to understand the directionality of dyadic interaction.

Strengths:

The question driving this study is interesting and a genuine gap in the literature. Almost all development occurs in the presence of a mature social partner. While it is known that these interactions are critical for development, the directionality of how these interactions unfold in real-time is less known.

The analyses are appropriate for the question at hand, capturing small moment-to-moment dynamics in both infant and child behavior, and their relationships with themselves and each other. Autocorrelations and cross-correlations are powerful tools that can uncover small but meaningful patterns in data that may not be uncovered with other more discretized analyses (i.e. regression).

Weaknesses:

While the authors improved their explanation of why they are using cross-correlations and the resting EEG patterns and what they mean, they did not address this specific piece of feedback: to explain their rationale for only focussing on fronto-temporal channels, rather than averaging channels across the whole brain.

Reviewer #2 (Public Review):

Summary:

Through a set of experiments and model simulations, the authors tested whether the commonly assumed world model of gravity was a faithful replica of the physical world. They found that participants did not model gravity as single, fixed vector for gravity but instead as a distribution of possible vectors. Surprisingly, the width of this distribution was quite large (~20 degrees). While previous accounts had suggested that this uncertainty was due to perceptual noise or an inferred external perturbation, the authors suggest that this uncertainty simply arises from a noisy distribution of the representation of gravity's direction. A reinforcement learning model with an initial uniform distribution for gravity's direction ultimately converged to a precision on the same order as the human participants, which lends support to the authors' conclusion and suggests that this distribution is learned through experience. What's more, further simulations suggest that representing gravity with such a wide distribution may balance speed and accuracy, providing a potentially normative explanation for the world model with gravity as a distribution.

Strengths:

The authors present surprising findings in a relatively straight-forward in a now classic experimental task. They provide a normative explanation based on a resource-rational framework for why people may have a stochastic world model instead of a deterministic world model. While the stochastic world model could be the result of people mentally simulating an external perturbation, the authors include several control experiments to test this possibility.

Weaknesses:

The possibility of inferred external perturbations, as opposed to a stochastic world model, is difficult to rule out. This could stem from how people interpret task instructions and it will likely take many, clever studies, to fully reconcile these two alternative accounts.

Reviewer #1 (Public Review):

Summary:

The study examines the role of release site clearance in synaptic transmission during repetitive activity under physiological conditions in two types of central synapses, calyx of Held and hippocampal CA1 synapses. After acute block of endocytosis by pharmacology, deeper synaptic depression or less facilitation was observed in two types of synapses. Acute block of CDC42 and actin polymerization, which possibly inhibits the activity of Intersectin, affected synaptic depression at the calyx synapse, but not at CA1 synapses. The data suggest an unexpected, fast role of the site clearance in counteracting synaptic depression.

Strengths:

The study uses acute block of the molecular targets with pharmacology together with precise electrophysiology. The experimental results are clear cut and convincing. The study also examines the physiological roles of the site clearance using action potential-evoked transmission at physiological Ca and physiological temperature at mature animals. This condition has not been examined.

Weaknesses:

Pharmacology may have some off-target effects, though acute manipulation should be appreciated and the authors have tried several reagents to verify the overall conclusions.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Mahapatra and Takahashi report on the physiological consequences of pharmacologically blocking either clathrin and dynamin function during compensatory endocytosis or of the cortical actin scaffold both in the calyx of Held synapse and hippocampal boutons in acute slice preparations

Strengths:

Although many aspects of these pharmacological interventions have been studied in detail during the past decades, this is a nice comprehensive and comparative study, which reveals some interesting differences between a fast synapse (Calyx of Held) tuned to reliably transmit at several 100 Hz and a more slow hippocampal CA1 synapse. In particular the authors find that acute disturbance of the synaptic actin network leads to a marked frequency-dependent enhancement of synaptic depression in the Calyx, but not in the hippocampal synapse This striking difference between both preparations is the most interesting and novel finding.

Weaknesses:

Unfortunately, however, these findings concerning the different consequences of actin depolymerization are not sufficiently discussed in comparison to the literature. My only criticism concerns the interpretation of the ML 141 and Lat B data. With respect to the Calyx data, I am missing a detailed discussion of the effects observed here in light of the different RRP subpools SRP and FRP. This is very important since Lee at al. (2012, PNAS 109 (13) E765-E774) showed earlier that disruption of actin inhibits the rapid transition of SRP SVs to the FRP at the AZ. The whole literature on this important concept is missing. Likewise, the role of actin for the replacement pool at a cerebellar synapse (Miki et al., 2016) is only mentioned in half a sentence. There is quite some evidence that actin is important both at the AZ (SRP to FRP transition, activation of replacement pool) and at the peri-active zone for compensatory endocytosis and release site clearance. Both possible underlying mechanisms (SRP to FRP transition or release site clearance) should be better dissected.

Reviewer #3 (Public Review):

The manuscript by Mahapatra and Takahashi addresses the role of presynaptic release site clearance during sustained synaptic activity. The authors characterize the effects of pharmacologically interfering with SV endocytosis (pre-incubation with Dynasore or Pitstop-2) on synaptic short-term plasticity (STP) at two different CNS synapses (calyx of Held synapses and hippocampal SC to CA1 synapses) using patch-clamp recordings in acute slices under experimental conditions designed to closely mimic a physiological situation (37{degree sign}C and 1.3 mM external [Ca2+]). Endocytosis blocker-induced changes in STP and in the recovery from short-term depression (STD) are compared to those seen after pharmacologically inhibiting actin filament assembly (pre-incubation with Latrunculin-B or the selective Cdc42 GTPase inhibitor ML-141). Presynaptic capacitance (Cm) recordings in calyx terminals were used to establish the effects of the pharmacological maneuvers on SV endocytosis.<br /> Latrunculin-B and ML-141 neither affect SV endocytosis (assayed by Cm recordings) nor EPSC recovery following conditioning trains, but strongly enhances STD at calyx synapses. No changes in STP were observed at Latrunculin-B- or ML-141-treated SC to CA1 synapses.

Dynasore and Pitstop-2 slow down endocytosis, limit the total amount of exocytosis in response to long stimuli, enhance STD in response to 100 Hz stimulation, but profoundly accelerate EPSC recovery following conditioning 100 Hz trains at calyx synapses. At SC to CA1 synapses, Dynasore and Pitstop-2 reduce the extend of facilitation and lower relative steady-state EPSCs suggesting a change in the facilitation-depression balance in favor of the latter.

The authors use state-of-the art techniques and their data, which is clearly presented, leads to authors to conclude that endocytosis is universally important for clearance of release sites while the importance of scaffold protein-mediated site clearance is limited to 'fast synapses'.

Unfortunately, and perhaps not completely unexpected in view of the pharmacological tools chosen, there are several observations which remain difficult to understand:

(1) Blocking site clearance affects release sites that have previously been used, i.e. sites at which SV fusion has occurred and which therefore need to be cleared. Calyces use at most 20% of all release sites during a single AP, likely fewer at 1.3 mM external [Ca2+]. Even if all those 20% of release sites become completely unavailable due to a block of release site clearance, the 2nd EPSC in a train should not be reduced by >20% because ~80% of the sites cannot be affected. However, ~50% EPSC reduction was observed (Fig. 2B1, lower right panel) raising the possibility that Dynasore does more than specifically interfering with SVs endocytosis (and possibly Pitstop as well). Non-specific effects are also suggested by the observed two-fold increase in initial EPSC size in SC to CA1 synapses after Dynasore pre-incubation.

(2) More severe depression was observed at calyx synapses after blocking endocytosis which the authors attribute to a presynaptic mechanism affecting pool replenishment. When probing EPSC recovery after conditioning 100 Hz trains, a speed up was observed mediated by an "unknown mechanism" which is "masked in 2 mM [Ca2+]". These two observations, deeper synaptic depression during 100 Hz but faster recovery from depression following 100 Hz, are difficult to align and no attempt was made to find an explanation.

(3) To reconcile previous data reporting a block of Ca2+-dependent recovery (CDR) by Dynasore or Latrunculin (measured at 2 mM external [Ca2+]) with the data presented here (using 1.3 mM external [Ca2+]) reporting no effect or a speed up of recovery from depression, the authors postulate that "CDR may operate only when excessive Ca2+ enters during massive presynaptic activation" (page 10 line 244). While that is possible, such explanation ignores plenty of calyx studies demonstrating fiber stimulation-induced CDR and elucidating molecular pathways mediating fiber stimulation-induced CDR, and it also completely dismisses the strong change in recovery time course after 10 Hz conditioning (single exponential) as compared to 100 Hz conditioning (double exponential with a pronounced fast component).

Strong presynaptic stimuli such as those illustrated in Figs. 1B,C induce massive exocytosis. The illustrated Cm increase of 2 to 2.5 pF represents fusion of 25,000 to 30,000 SVs (assuming a single SV capacitance of 80 aF) corresponding to a 12 to 15% increase in whole terminal membrane surface (assuming a mean terminal capacitance of ~16 pF). Capacitance measurements can only be considered reliable in the absence of marked changes in series and membrane conductance. Documentation of the corresponding conductance traces is therefore advisable for such massive Cm jumps and merely mentioning that the first 450 ms after stimulation were skipped during analysis or referring to previous publications showing conductance traces is insufficient.<br /> All bar graphs in Figures 1 through 6 and Figures S3 through S6 compare three or even four (Fig. 5C) conditions, i.e. one control and at least two treatment data sets. It appears as if repeated t-tests were used to run multiple two-group comparisons (i.e. using the same control data twice for two different comparisons). Either a proper multiple comparison test should be used or a Bonferroni correction or similar multiple-comparison correction needs to be applied.

Finally, the terminology of contrasting "fast-signaling" (calyx synapses) and "slow-plastic" (SC synapses) synapses seems to imply that calyx synapses lack plasticity, as does the wording "conventional bouton-type synapses involved in synaptic plasticity" (page 11, line 251). I assume, the authors primarily refer to the maximum frequencies these two synapse types typically transmit (fast-signaling vs slow-signaling)?

Reviewer #2 (Public Review):

Gillespie et al. introduced a novel neurofeedback (NF) procedure to train rats in enhancing their sharp-wave ripple (SWR) rate within a short duration, a key neural mechanism associated with memory consolidation. The training, embedded within a spatial memory task, spanned 20-30 days and utilized food rewards as positive reinforcement upon SWR detection. Rats were categorized into NF and control groups, with the NF group further divided into NF and delay trials for within-subject control. While single trial differences were elusive due to the variability of SWR occurrence, the study revealed that statistically rats in NF trials exhibited a notably higher SWR rate before receiving rewards compared to delay trials. This difference was even more pronounced when juxtaposed with rats not exposed to NF training (control group). The unique design of blending the NF phase with the memory dependent spatial task enabled the authors to analyze whether the NF training influence the task performance and replay content during SWRs across three different conditions (NF trials, delay trials and control group). Interestingly, despite the NF training, there was no significant improvement or decline in the performance of the spatial memory task, and the replay content remained consistent across all three conditions. Hence, the operant conditioning only amplified the SWR rate before reward in NF trials without altering the task performance and the replay content during SWR. Moreover, considering the post-reward period, the total SWR count was consistent across all conditions as well, meaning the NF training also do not affect the total SWR count. The study concludes with the hypothesis of a potential homeostatic mechanism governing the total SWR production in rats. This research significantly extends previous work by Ishikawa et al. (2014), offering insights into the NF training with external reward on the SWR rate/counts, replay content and task performance.

Strengths:

- Integration of NF task and spatial memory task in a single trial<br /> The integration of NF training within a spatial memory task poses significant challenges. Gillespie and colleagues overcame this by seamlessly blending the NF task and the spatial memory task into a single trial. Each trial involved a rat undergoing three steps: First, initiating a trial. Second, moving to either the NF port or the delay trial port, as indicated by an LED, and then maintaining a nosepoke at one of the center ports. During this step, the rat had to keep its nose (in the NF port) until a sharp-wave ripple (SWR) exceeding a set threshold was detected, which then triggered a reward, or until a variable time elapsed (in the delay port). Third, the rat would choose one of eight arms to explore before starting the next trial. This integration of the two tasks (step two as the NF task and step three as the spatial memory task) facilitated a direct analysis of the impact of NF training on behaviorally relevant replay content during SWRs and the performance in the spatial memory task.

- Clear Group Separation<br /> A robust study design necessitates clear distinctions between experimental conditions to ensure that observed differences can be attributed to the variable under investigation. This study meticulously categorized rats into three distinct conditions: NF trials, delay trials (for within-subject control), and a control group (for across-subject control). Furthermore, for each trial, the times of interest (TOI) were separated into pre-reward and post-reward periods. This clear separation ensures that any observed differences in SWR rates and other outcomes can be confidently attributed to the effects of neurofeedback training during specific time periods, minimizing potential confounding factors.

- Evidence of SWR rate modulation<br /> The study's results offer compelling evidence that rats can be trained to modulate their SWR rates during the pre-reward period. This is evident from the observation that rats in the NF trials consistently displayed a higher SWR rate before receiving rewards compared to those in delay trials or the control group (Fig. 2). Such findings not only validate the efficacy of the NF paradigm but also underscore the potential of operant conditioning in influencing neural mechanisms. The observation that rats were able to produce larger SWR events by modulating their occurrence rate, rather than merely waiting for these events, suggests a learned strategy to generate them more efficiently.

- Evidence of SWR count homeostasis<br /> A notable finding from the study was the observation of a consistent total SWR count during both pre-reward and post-reward periods across all conditions, despite the evident increase in SWR rates during the pre-reward period in NF trials. This points to a potential homeostatic mechanism governing SWR production in rats. This balance suggests that while NF training can modulate the timing and rate of SWRs over a short duration, it doesn't influence the overall count of SWRs over a longer period. Such a mechanism might be essential in ensuring that the brain neither overcompensates nor depletes its capacity for SWRs, maintaining the overall neural balance and functionality. This discovery deepens our understanding of neural mechanisms and highlights potential avenues for future research into the regulatory processes governing neural activity.

In this revision, the paper explores a neurofeedback technique in rats that modulates hippocampal sharp-wave ripple (SWR) rates, crucial for memory replay, without altering the content of those replays. The study demonstrates that neurofeedback can specifically increase SWR rates during a task's pre-reward phase. Revisions address concerns about movement's impact on SWR rates, clarify the statistical approach used, and modify the title for accuracy, now emphasizing the modulation of memory replay rates rather than suggesting alterations to memory content itself. I think all the concerns in the previous version have been addressed.

Reviewer #3 (Public Review):

Summary:

This study implements an innovative neurofeedback procedure in rats, providing food reward upon detection of a sharp wave-ripple event (SWR) in the hippocampus. The elegant experimental design enables a within-animal comparison of the effects of this neurofeedback procedure as compared to a control condition in which equivalent reward is provided in a non-contingent manner. The neurofeedback procedure was found to increase SWR rate, followed by a compensatory reduction in SWR rate. These changes in SWR rate were not accompanied by any changes in memory performance on the memory-guided task.

Strengths:

The scientific premise for the study is outstanding. It addresses an issue of high importance, of developing ways to not merely describe correlations between SWRs (and their content) and memory performance, but to manipulate them. The authors argue clearly and convincingly that even studies that have performed causal manipulations of SWRs have important confounds and limitations, and most importantly for translational purposes, they are all invasive. So, the idea of developing a potentially non-invasive neurofeedback procedure for modulating SWRs is compelling both as an innovative new experimental manipulation in studies of SWRs, and as a potentially impactful therapeutic avenue.

In addition to addressing an important issue with an innovative approach, the study has many other strengths. The data unambiguously show that the method is effective at increasing SWR rate in each individual subject. The experimental design allows within-subject comparison of neurofeedback and control trials, where the subjects wait an equivalent amount of time. The careful analyses of SWR properties and their content establish that neurofeedback SWRs are comparable to control SWRs. The data add further evidence to the notion that SWR rate is subject to homeostatic control. The paper is also exceptionally well written, and was a pleasure to read. So, there is a clear technical advance, in that there is now a method for increasing SWR rate non-invasively, which is rigorously established and characterized.

Weaknesses:

The one overall limitation I find with this study is that it is unclear to what extent the same (or better) results could have been obtained using behavior-feedback instead of neuro-feedback. Because SWR rates are generally higher during states of quiescence compared to active movement or task engagement, it is possible that reinforcing behaviorally detected quiescent states (e.g. low movement) would indirectly increase SWR rates. The authors include an important control analysis showing higher SWR rates in the neurofeedback condition even when movement speed is controlled for by subsetting the data, demonstrating that changes in movement speed cannot be the only explanation of the results. At the same time, the observation that all 4 subjects had lower movement speeds during neurofeedback compared to control trials suggests that neurofeedback is likely reinforcing both overt (behavior) and covert (SWR) processes. Understanding the relative contributions of each to the observed SWR increase would help clarify whether the neurofeedback approach is worth the additional effort and expense compared to behavioral feedback.

Reviewer #1 (Public Review):

The study investigates parafoveal processing during natural reading, combining eye-tracking and MEG techniques, building upon the RIFT paradigm previously introduced by Pan et al. (2021). Overall, the manuscript is well-written with a clear structure, and the data analysis and experimental results are presented in a lucid manner.

The authors have addressed the issues I raised in the previous round of review to my satisfaction. However, I still have two concerns that require the authors' consideration.

Firstly, the similarity between the RIFT analysis process in this study and traditional ERP analysis could lead readers to equate RIFT with components like N400, potentially influencing their interpretation of the results. Although the author's response has somewhat clarified my queries, I seek confirmation: does RIFT itself signify "visual attention" or the "allocation of attentional resources to the flickering target words" (line 208) in this study? While this may not be pivotal, as it primarily serves as an indicator to evaluate whether contextual congruity can indeed modulate the RIFT response rather than indicating early parafoveal semantic integration, I recommend that the authors explicitly address this point in the manuscript, maybe in the discussion section, to enhance reader comprehension of the article's rationale.

Secondly, regarding the study's conclusions, there appears to be an overemphasis in stating that "semantic information ... can also be integrated with the sentence context ..." (line 21-22). As raised by Reviewer 2 (Major Point 1) and acknowledged by the authors in the limitations of the revised manuscript (lines 403-412), the RIFT effect observed likely stems from local congruency. Therefore, adjusting the conclusion to "integrated with previous context" may offer a more precise reflection of the findings.

Reviewer #2 (Public Review):

This MEG study used co-registered eye-tracking and Rapid Invisible Frequency Tagging (RIFT) to track the effects of semantic parafoveal preview during natural sentence reading. Unpredictable target words could either be congruent or incongruent with sentence context. This modulated the RIFT response already while participants were fixating the preceding word. This indicates that the semantic congruency of the upcoming word modulates visual attention demands already in parfoveal preview.<br /> The quest for semantic parafoveal preview in natural reading has attracted a lot of attention in recent years, especially with the development of co-registered eye-tracking and EEG/MEG. Evidence from dynamic neuroimaging methods using innovative paradigms as in this study is important for this debate.

Major points:

(1) The authors frame their study in terms of "congruency with sentence context". However, it is the congruency between adjective-noun pairs that determines congruency (e.g. "blue brother" vs "blue jacket", and examples p. 16 and appendix). This is confirmed by Suppl Figure 1, which shows a significantly larger likelihood of refixations to the pre-target word for incongruent sentences, probably because the pre-target word is most diagnostic for the congruency of the target word. The authors discuss some possibilities why there is variability in parafoveal preview effects in the literature. It is more likely to see effects for this simple and local congruency, rather than congruency that requires and integration and comprehension of the full sentence. Future studies should investigate whether the observed effects depend on sentence context or local congruency.

(2) The authors used MEG and provided a source estimate for the tagging response (Figure 2), which unsurprisingly is in visual cortex. The most important results are presented at the sensor level. This does not add information about the brain sources of the congruency affect, as the RIFT response probably reflects top-down effects on visual attention etc. The RIFT response can test for preview effects on visual brain responses but does not allow the localisation of context processing effects that cause them.

(3) The earliest semantic preview effects occurred around 100ms after fixating the pre-target word (discussed around l. 323). This means that at this stage the brain must have processed the pre-target and the target word and integrated their meanings (at some level). Even in the single-word literature, semantic effects at 100 ms are provocatively early. Future studies should aim at reconciling these different findings.

(4) As in previous EEG/MEG studies, the authors found a neural but no behavioural preview effect. As before, this raises the question whether the observed effect is really "critical" for sentence comprehension. If interpreted in terms of "information" and "attention", then one would expect a positive effect on behaviour, either reading speed or accuracy. The authors provide a correlation analysis with reading speed, but this does not allow causal conclusions: Some people may simply read slowly and therefore pay more attention and get a larger preview response. Some readers may hurry and therefore not pay attention and not get a preview response. In order to address this, one would have to control for reading speed and show an effect of RIFT response on comprehension performance (or vice versa, with a task that is not close to ceiling performance).

Reviewer #1 (Public Review):

Zhu, et al present a genome-wide histone modification analysis comparing patients with schizophrenia (on or off antipsychotics) to non-psychiatric controls. The authors performed analyses across the dorsolateral prefrontal cortex and tested for enrichment of nearby genes and pathways. The authors performed analysis measuring the effect of age on the epigenomic landscape as well. This paper provides a unique resource around SCZ and its epigenetic correlates, and some potentially intriguing findings in the antipsychotic response dataset.

Comments on revised version:

The authors have adequately responded to my review comments.

Reviewer #2 (Public Review):

Sasaki et al. investigated methods to entrain vasomotion in awake wild-type mice across multiple regions of the brain using a horizontally oscillating visual pattern which induces an optokinetic response (HOKR) eye movement. They found that spontaneous vasomotion could be detected in individual vessels of their wild-type mice through either a thinned cranial window or intact skull preparation using a widefield macro-zoom microscope. They showed that low-resolution autofluorescence signals coming from the brain parenchyma could be used to capture vasomotion activity using a macro-zoom microscope or optical fibre, as this signal correlates well with the intensity profile of fluorescently-labelled single vessels. They show that vasomotion can also be entrained across the cortical surface using an oscillating visual stimulus with a range of parameters (with varying temporal frequencies, amplitudes, or spatial cycles), and that the amplitude spectrum of the detected vasomotion frequency increases with repeated training sessions. The authors include some control experiments to rule out fluorescence fluctuations being due to artifacts of eye movement or screen luminance and attempt to demonstrate some functional benefit of vasomotion entraining as HOKR performance improves after repeat training. These data add in an interesting way to the current knowledge base on vasomotion, as the authors demonstrate the ability to entrain vasomotion across multiple brain areas and show some functional significance to vasomotion with regards to information processing as HOKR task performance correlates well with vascular oscillation amplitudes.

Reviewer #3 (Public Review):

Summary:

Here the authors show global synchronization of cerebral blood flow (CBF) induced by oscillating visual stimuli in the mouse brain. The study validates the use of endogenous autofluorescence to quantify the vessel "shadow" to assess the magnitude of frequency-locked cerebral blood flow changes. This approach enables straightforward estimation of artery diameter fluctuations in wild-type mice, employing either low magnification wide-field microscopy or deep-brain fibre photometry. For the visual stimuli, awake mice were exposed to vertically oscillating stripes at a low temporal frequency (0.25 Hz), resulting in oscillatory changes in artery diameter synchronized to the visual stimulation frequency. This phenomenon occurred not only in the primary visual cortex but also across a broad cortical and cerebellar surface. The induced CBF changes adapted to various stimulation parameters, and interestingly, repeated trials led to plastic entrainment. The authors control for different artefacts that may have confounded the measurements such as light contamination and eye movements but found no influence of these variables. The study also tested horizontally oscillating visual stimuli, which induce the horizontal optokinetic response (HOKR). The amplitude of eye movement, known to increase with repeated training sessions, showed a strong correlation with CBF entrainment magnitude in the cerebellar flocculus. The authors suggest that parallel plasticity in CBF and neuronal circuits is occurring. Overall, the study proposes that entrained "vasomotion" contributes to meeting the increased energy demand associated with coordinated neuronal activity and subsequent neuronal circuit reorganization.

Strengths:

-The paper describes a simple and useful method for tracking vasomotion in awake mice through an intact skull.<br /> -The work controls for artefacts in their primary measurements.<br /> -There are some interesting observations, including the nearly brain-wide synchronization of cerebral blood flow oscillations to visual stimuli and that this process only occurs after mice are trained in a visual task.<br /> -This topic is interesting to many in the CBF, functional imaging, and dementia fields.

Reviewer #1 (Public Review):

Summary:

Most studies in sensory neuroscience investigate how individual sensory stimuli are represented in the brain (e.g., the motion or color of a single object). This study starts tackling the more difficult question of how the brain represents multiple stimuli simultaneously and how these representations help to segregate objects from cluttered scenes with overlapping objects.

Strengths

The authors first document the ability of humans to segregate two motion patterns based on differences in speed. Then they show that a monkey's performance is largely similar; thus establishing the monkey as a good model to study the underlying neural representations.

Careful quantification of the neural responses in the middle temporal area during the simultaneous presentation of fast and slow speeds leads to the surprising finding that, at low average speeds, many neurons respond as if the slowest speed is not present, while they show averaged responses at high speeds. This unexpected complexity of the integration of multiple stimuli is key to the model developed in this paper.

One experiment in which attention is drawn away from the receptive field supports the claim that this is not due to the involuntary capture of attention by fast speeds.

A classifier using the neuronal response and trained to distinguish single-speed from bi-speed stimuli shows a similar overall performance and dependence on the mean speed as the monkey. This supports the claim that these neurons may indeed underlie the animal's decision process.

The authors expand the well-established divisive normalization model to capture the responses to bi-speed stimuli. The incremental modeling (eq 9 and 10) clarifies which aspects of the tuning curves are captured by the parameters.

Weaknesses

While the comparison of the overall pattern of behavioral performance between monkeys and humans is important, some of the detailed comparisons are not well supported by the data. For instance, whether the monkey used the apparent coherence simply wasn't tested and a difference between 4 human subjects and a single monkey subject cannot be tested statistically in a meaningful manner. I recommend removing these observations from the manuscript and leaving it at "The difference between the monkey and human results may be due to species differences or individual variability" (and potentially add that there are differences in the task as well; the monkey received feedback on the correctness of their choice, while the humans did not.)

A control experiment aims to show that the "fastest speed takes all" behavior is general by presenting two stimuli that move at fast/slow speeds in orthogonal directions. The claim that these responses also show the "fastest speed takes all" is not well supported by the data. In fact, for directions in which the slow speed leads to the largest response on its own, the population response to the bi-speed stimulus is the average of the response to the components. Only for the directions where the fast speed stimulus is the preferred direction is there a bias towards the faster speed (Figure 7A). The quantification of this effect in Figure 7B seems to suggest otherwise, but I suspect that this is driven by the larger amplitude of Rf in Figure 8, and the constraint that ws and wf are constant across directions. The interpretation of this experiment needs to be reconsidered.

Reviewer #2 (Public Review):

Summary:

This is a paper about the segmentation of visual stimuli based on speed cues. The experimental stimuli are random dot fields in which each dot moves at one of two velocities. By varying the difference between the two speeds, as well as the mean of the two speeds, the authors estimate the capacity of observers (human and non-human primates) to segment overlapping motion stimuli. Consistent with previous work, perceptual segmentation ability depends on the mean of the two speeds. Recordings from area MT in monkeys show that the neuronal population to compound stimuli often shows a bias towards the faster-speed stimuli. This bias can be accounted for with a computational model that modulates single-neuron firing rates by the speed preferences of the population. The authors also test the capacity of a linear classifier to produce the psychophysical results from the MT data.

Strengths:

Overall, this is a thorough treatment of the question of visual segmentation with speed cues. Previous work has mostly focused on other kinds of cues (direction, disparity, color), so the neurophysiological results are novel. The connection between MT activity and perceptual segmentation is potentially interesting, particularly as it relates to existing hypotheses about population coding.

Weaknesses:

Page 10: The relationship between (R-Rs) and (Rf-Rs) is described as "remarkably linear". I don't actually find this surprising, as the same term (Rs) appears on both the x- and y-axes. The R^2 values are a bit misleading for this reason.

Figure 9: I'm confused about the linear classifier section of the paper. The idea makes sense - the goal is to relate the neuronal recordings to the psychophysical data. However the results generally provide a poor quantitative match to the psychophysical data. There is mention of a "different paper" (page 26) involving a separate decoding study, as well as a preprint by Huang et al. (2023) that has better decoding results. But the Huang et al. preprint appears to be identical to the current manuscript, in that neither has a Figure 12, 13, or 14. The text also says (page 26) that the current paper is not really a decoding study, but the linear classifier (Figure 9F) is a decoder, as noted on page 10. It sounds like something got mixed up in the production of two or more papers from the same dataset. In any case, I think that some kind of decoding analysis would really strengthen the current paper by linking the physiology to the psychophysics, but given the limitations of the linear classifier, a more sophisticated approach might be necessary -- see for example Zemel, Dayan, and Pouget, 1998. The authors might also want to check out closely related work by Treue et al. (Nature Neuroscience 2000) and Watamaniuk and Duchon (1992).

What do we learn from the normalization model? Its formulation is mostly a restatement of the results - that the faster and slower speeds differentially affect the combined response. This hypothesis is stated quantitatively in equation 8, which seems to provide a perfectly adequate account of the data. The normalization model in equation 10 is effectively the same hypothesis, with the mean population response interposed - it's not clear how much the actual tuning curve in Figure 10A even matters, since the main effect of the model is to flatten it out by averaging the functions in Figure 10B. Although the fit to the data is reasonable, the model uses 4 parameters to fit 5 data points and is likely underconstrained; the parameters other than alpha should at least be reported, as it would seem that sigma is actually the most important one. And I think it would help to examine how robust the statistical results are to different assumptions about the normalization pool.

Reviewer #3 (Public Review):

Summary:

This study concerns how macaque visual cortical area MT represents stimuli composed of more than one speed of motion.

Strengths:

The study is valuable because little is known about how the visual pathway segments and preserves information about multiple stimuli. The study presents compelling evidence that (on average) MT neurons represent the average of the two speeds, with a bias that accentuates the faster of the two speeds. An additional strength of the study is the inclusion of perceptual reports from both humans and one monkey participant performing a task in which they judged whether the stimuli involved one vs two different speeds. Ultimately, this study raises intriguing questions about how exactly the response patterns in visual cortical area MT might preserve information about each speed, since such information could potentially be lost in an average response as described here, depending on assumptions about how MT activity is evaluated by other visual areas.

Weaknesses:

My main concern is that the authors are missing an opportunity to make clear that the divisive normalization, while commonly used to describe neural response patterns in visual areas (and which fits the data here), fails on the theoretical front as an explanation for how information about multiple stimuli can be preserved. Thus, there is a bit of a disconnect between the goal of the paper - how does MT represent multiple stimuli? - and the results: mostly averaging responses which, while consistent with divisive normalization, would seem to correspond to the perception of a single intermediate speed. This is in contrast to the psychophysical results which show that subjects can at least distinguish one from two speeds. The paper would be strengthened by grappling with this conundrum in a head-on manner.

Reviewer #1 (Public Review):

Summary:

This study compares experimental data recorded from the PFC of monkeys to the activity of recurrent neural networks trained to perform the same `task' as the monkeys, namely, to predict the delivery of reward following the presentation of visual stimuli. The visual information varied along 3 dimensions, color, shape, and width. Shape was always relevant for reward prediction, width was always irrelevant, and color was irrelevant at the beginning of the trial but became relevant later on, once it could be assessed together with shape. The neural data showed systematic changes in the representations of these features and of the expected reward as the learning progressed, and the objective of this study was to try to understand what principles could underlie these changes. The simulations and theoretical calculations indicated that the changes in PFC activity (throughout learning and throughout a trial) can be understood as an attempt by the circuitry to use an efficient representational strategy, i.e., one that uses as few spikes as possible, given that the resulting representation should be accurate enough for task performance.

Strengths:

- The paper is concise and clearly written.

- The paper shows that, in a neural circuit, the information that is decodable and the information that is task-relevant may relate in very different ways. Decodable information may be very relevant or very irrelevant. This fact is critical for interpreting the results of pure decoding studies, which often assume an equivalence. This take-home message is not emphasized by the authors, but I think is quite important.

- The results provide insight as to how neural representations may be transformed as a task is learned, which often results in subtle changes in selectivity and overall activity levels whose impact or reason is not entirely clear just by looking at the data.

Weaknesses:

The match between the real PFC and the model networks is highly qualitative, and as noted by the authors, comparisons only make sense in terms of *changes* between early and late learning. The time scales, activity levels, and decoding accuracies involved are all different between the model and recording data. This is not to disregard what the authors have done, but simply to point out an important limitation.

Reviewer #2 (Public Review):

Summary:

The study investigates the representation of irrelevant stimuli in neural circuits using neural recordings from the primate prefrontal cortex during a passive object association task. They find a significant decrease in the linear decodability of irrelevant stimuli over the course of learning (in the time window in which the stimuli are irrelevant). They then compare these trends to RNNs trained with varying levels of noise and firing rate regularization and find agreement when these levels are at an intermediate value. In a complementary analysis, they found (in both RNNs and PFC) that the magnitude of relevant and irrelevant stimuli increased and decreased, respectively, during learning. These findings were interpreted in terms of a minimization of metabolic cost in the cortex.

To understand how stimuli can be dynamically suppressed at times when they are irrelevant, the authors constructed and analyzed a reduced two-neuron model of the task. They found a mechanism in which firing rate regularization increased the probability of negative weights in the input, pushing the neural activities below the threshold. A similar mechanism was observed in RNNs.

Strengths:

The article is well-written and the figures are easily understood. The analyses are well explained and motivated. The article provides a valuable analysis of the effect of two parameters on representations of irrelevant stimuli in trained RNNs.

Weaknesses:

(1) The mechanism for suppressing dynamically relevant stimuli appears to be incomplete and does not explain clearly enough how representations of 'color' which are suppressed through negative input weights become un-suppressed in the presence of the second variable 'shape'.

(2) Interpretation of results in terms of the effect of metabolic cost on cortical dynamics is not backed up by the presented data/analyses. The change in dynamics of 'color' representations in the prefrontal cortex only qualitatively matches RNN dynamics and may arise from other causes.

Reviewer #3 (Public Review):

Summary:

In order to study the factors and neural dynamics that lead to the suppression of irrelevant information in the brain, the authors trained artificial neural networks in the execution of a task that involved the discrimination of complex stimuli with three main features: color, shape, and width. Specific combinations of color and shape led to a reward, but the temporal structure made color dynamically irrelevant at the beginning of the trial, and then it became relevant once the shape was presented. On the other hand, the width of the stimulus was always irrelevant. Importantly, non-human primates were also trained to execute this task (in a previous study by the authors) and the activity from neural populations from the dorsolateral Prefrontal Cortex (dlPFC) was recorded, allowing to compare the coding of information by the artificial neural network model with what happens in biological neural populations.

The authors changed systematically the amount of noise present in the neural network model, as well as limiting the firing rate of the artificial neurons to simulate the limitations imposed by high metabolic costs in biological neurons. They found that models with medium and low noise, as well as medium and low metabolic cost, developed information encoding patterns that resembled the patterns observed throughout learning in the dlPFC, as follows: early in the learning process, color information was strongly represented during the whole trial, as well as shape and width, whereas the color/shape combination significance (XOR operation) was weakly encoded. Late in learning, color information was initially suppressed (while it was deemed irrelevant) and became more prominent during the shape presentation. Width information coding decreased, and the XOR operation result became more strongly encoded.

Subthreshold activity dynamics were studied by training artificial networks consisting of 2 neurons, with the aim of understanding how dynamically irrelevant information is suppressed and then encoded more strongly at a different time during the trial. Under medium noise and medium metabolic cost, color information is suppressed by the divergence of the activity away from the level that triggers spikes. The authors claim that this subthreshold dynamic explains the suppression of irrelevant information in biological neural networks.

Strengths:

The study leverages the power of computational models to simulate biological networks and do manipulations that are difficult (if not impossible) to perform in vivo. The analyses of the activity of the network model are neat and thorough and provide a clear demonstration of how noise and metabolic costs may affect the information coding in the brain. The mathematical analyses are rigorous and nicely documented.

Weaknesses:

The study does not leverage the fact that they have access to the activity of individual neurons both on a neural network model and in neural recordings. The model/brain comparison results are limited to the decodability of different pieces of information during the execution of the task at different stages of learning. It would have been useful if the authors had shown response profiles of individual neurons, both biological and artificial, to strengthen the claim that the activity patterns are similar. Perhaps showing that the firing rates vary in a similar way in the large models (like they do for the 2-neuron model) would have been informative. For instance, it is possible that suppression is not occurring in the dlPFC, but that the PFC receives input with this information already suppressed. If suppression indeed happens in the PFC, response profiles associated with this process may be observed.

There is no way to say that the 2-neuron models are in any way informative of what happens in brain neurons, or even larger artificial networks since the sources of sensory input, noise, and inhibition will differ between biological and artificial networks. And because the firing patterns are not shown for large networks, it is not clear if some non-coding artificial neurons will become broadly inhibitory but maintain a relatively high firing rate (to mention only one possibility).

Reviewer #1 (Public Review):

Summary:

The authors bring together implanted radiofrequency coils, high-field MRI imaging, awake animal imaging, and sensory stimulation methods in a technological demonstration. The results are very detailed descriptions of the sensory systems under investigation.

Strengths:

- The maps are qualitatively excellent for rodent whole-brain imaging.<br /> - The design of the holder and the coil is pretty clever.

Weaknesses:

- Some unexpected regions appear on the whole brain maps, and the discussion of these regions is succinct.<br /> - The authors do not make the work and effort to train the animals and average the data from several hundred trials apparent enough. This is important for any reader who would like to consider implementing this technology.<br /> - The data is not available. This does not let the readers make their own assessment of the results.

Reviewer #2 (Public Review):

Summary:

The manuscript by Hike et al. entitled 'High-resolution awake mouse fMRI at 14 Tesla' describes the implementation of awake mouse BOLD-fMRI at high field. This work is timely as the field of mouse fMRI is working toward collecting high-quality data from awake animals. Imaging awake subjects offers opportunities to study brain function that are otherwise not possible under the more common anesthetized conditions. Not to mention the confounding effects that anesthesia has on neurovascular coupling. What has made progress in this area slow (relative to other imaging approaches like optical imaging) is the environment within the MRI scanner (high acoustic noise) - as well as the intolerance of head and body motion. This work adds to a relatively small, but quickly growing literature on awake mouse fMRI. The findings in the study include testing of an implanted head-coil (for MRI data reception). Two designs are described and the SNR of these units at 9.4T and 14T are reported. Further, responses to visual as well as whisker stimulation recorded in acclimated awake mice are shown. The most interesting finding, and most novel, is the observation that mice seem to learn to anticipate the presentation of the stimulus - as demonstrated by activations evident ~6 seconds prior to the presentation of the stimulus when stimuli are delivered at regular intervals (but not when stimuli are presented at random intervals). These kinds of studies are very challenging to do. The surgical preparation and length of time invested into training animals are grueling. I also see this work as a step in the right direction and evidence of the foundations for lots of interesting future work. However, I also found a few shortcomings listed below.

Weaknesses:

(1) The surface coil, although offering a great SNR boost at the surface, ultimately comes at a cost of lower SNR in deeper more removed brain regions in comparison to commercially available Bruker coils (at room temperature). This should be quantified. A rough comparison in SNR is drawn between the implanted coils and the Bruker Cryoprobe - this should be a quantitative comparison (if possible) - including any differences in SNR in deeper brain structures. There are drawbacks to the Cryoprobe, which can be discussed, but a more thorough comparison between the implanted coils, and other existing options should be provided (the Cryoprobe has been used previously in awake mouse experiments). Further, the details of how to build the implanted coils should be provided (shared) - this should include a parts list as well as detailed instructions on how to build the units. Also, how expensive are they? And can they be reused?

(2) In the introduction, the authors state that "Awake mouse fMRI has been well investigated". I disagree with this statement and others in the manuscript that give the reader the impression that awake experiments are not a challenging and unresolved approach to fMRI experiments in mice (or rodents). Although there are multiple labs (maybe 15 worldwide) that have conducted awake mouse experiments (with varying degrees of success/thoroughness), we are far from a standardized approach. This is a strength of the current work and should be highlighted as such. I encourage the authors to read the recent systematic review that was published on this topic in Cerebral Cortex by Mandino et al. There are several elements in there that should influence the tone of this piece including awake mouse implementations with the Bruker Cryoprobe, prevalence of surgical preparations, and evaluations of stress.

(3) The authors also comment on implanted coils reducing animal stress - I don't know where this comment is coming from, as this has not been reported in the literature (to my knowledge) and the authors don't appear to have evaluated stress in their mice.

(4) Following on the above point, measures of motion, stress, and more details on the acclimation procedure that was implemented in this study should be included.

(5) It wasn't clear to me at what times the loop versus "Figure 8" coil was being used, nor how many mice (or how much data) were included in each experiment/plot. There is also no mention of biological sex.

(6) Building on the points above, the manuscript overall lacks experimental detail (especially since the format has the results prior to the methods).

(7) An observation is made in the manuscript that there is an appreciable amount of negative BOLD signal. The authors speculate that this may come from astrocyte-mediated BOLD during brain state changes (and cite anesthetized rat and non-human primate experiments). This is very strange to me. First, the negative BOLD signal is not plotted (please do this), further, there are studies in awake mice that measure astrocyte activation eliciting positive BOLD responses (see Takata et al. in Glia, 2017).

Reviewer #1 (Public Review):

Summary:

This paper presents two experiments, both of which use a target detection paradigm to investigate the speed of statistical learning. The first experiment is a replication of Batterink, 2017, in which participants are presented with streams of uniform-length, trisyllabic nonsense words and asked to detect a target syllable. The results replicate previous findings, showing that learning (in the form of response time facilitation to later-occurring syllables within a nonsense word) occurs after a single exposure to a word. In the second experiment, participants are presented with streams of variable-length nonsense words (two trisyllabic words and two disyllabic words) and perform the same task. A similar facilitation effect was observed as in Experiment 1. The authors interpret these findings as evidence that target detection requires mechanisms different from segmentation. They present results of a computational model to simulate results from the target detection task and find that an "anticipation mechanism" can produce facilitation effects, without performing segmentation. The authors conclude that the mechanisms involved in the target detection task are different from those involved in the word segmentation task.

Strengths:

The paper presents multiple experiments that provide internal replication of a key experimental finding, in which response times are facilitated after a single exposure to an embedded pseudoword. Both experimental data and results from a computational model are presented, providing converging approaches for understanding and interpreting the main results. The data are analyzed very thoroughly using mixed effects models with multiple explanatory factors.

Weaknesses:

In my view, the main weaknesses of this study relate to the theoretical interpretation of the results.

(1) The key conclusion from these findings is that the facilitation effect observed in the target detection paradigm is driven by a different mechanism (or mechanisms) than those involved in word segmentation. The argument here I think is somewhat unclear and weak, for several reasons:

First, there appears to be some blurring in what exactly is meant by the term "segmentation" with some confusion between segmentation as a concept and segmentation as a paradigm.<br /> Conceptually, segmentation refers to the segmenting of continuous speech into words. However, this conceptual understanding of segmentation (as a theoretical mechanism) is not necessarily what is directly measured by "traditional" studies of statistical learning, which typically (at least in adults) involve exposure to a continuous speech stream followed by a forced-choice recognition task of words versus recombined foil items (part-words or nonwords). To take the example provided by the authors, a participant presented with the sequence GHIABCDEFABCGHI may endorse ABC as being more familiar than BCG, because ABC is presented more frequently together and the learned association between A and B is stronger than between C and G. However, endorsement of ABC over BCG does not necessarily mean that the participant has "segmented" ABC from the speech stream, just as faster reaction times in responding to syllable C versus A do not necessarily indicate successful segmentation. As the authors argue on page 7, "an encounter to a sequence in which two elements co-occur (say, AB) would theoretically allow the learner to use the predictive relationship during a subsequent encounter (that A predicts B)." By the same logic, encoding the relationship between A and B could also allow for the above-chance endorsement of items that contain AB over items containing a weaker relationship.

Both recognition performance and facilitation through target detection reflect different outcomes of statistical learning. While they may reflect different aspects of the learning process and/or dissociable forms of memory, they may best be viewed as measures of statistical learning, rather than mechanisms in and of themselves.

(2) The key manipulation between experiments 1 and 2 is the length of the words in the syllable sequences, with words either constant in length (experiment 1) or mixed in length (experiment 2). The authors show that similar facilitation levels are observed across this manipulation in the current experiments. By contrast, they argue that previous findings have found that performance is impaired for mixed-length conditions compared to fixed-length conditions. Thus, a central aspect of the theoretical interpretation of the results rests on prior evidence suggesting that statistical learning is impaired in mixed-length conditions. However, it is not clear how strong this prior evidence is. There is only one published paper cited by the authors - the paper by Hoch and colleagues - that supports this conclusion in adults (other mentioned studies are all in infants, which use very different measures of learning). Other papers not cited by the authors do suggest that statistical learning can occur to stimuli of mixed lengths (Thiessen et al., 2005, using infant-directed speech; Frank et al., 2010 in adults). I think this theoretical argument would be much stronger if the dissociation between recognition and facilitation through RTs as a function of word length variability was demonstrated within the same experiment and ideally within the same group of participants.

(3) The authors argue for an "anticipation" mechanism in explaining the facilitation effect observed in the experiments. The term anticipation would generally be understood to imply some kind of active prediction process, related to generating the representation of an upcoming stimulus prior to its occurrence. However, the computational model proposed by the authors (page 24) does not encode anything related to anticipation per se. While it demonstrates facilitation based on prior occurrences of a stimulus, that facilitation does not necessarily depend on active anticipation of the stimulus. It is not clear that it is necessary to invoke the concept of anticipation to explain the results, or indeed that there is any evidence in the current study for anticipation, as opposed to just general facilitation due to associative learning.

In addition, related to the model, given that only bigrams are stored in the model, could the authors clarify how the model is able to account for the additional facilitation at the 3rd position of a trigram compared to the 2nd position?

(4) In the discussion of transitional probabilities (page 31), the authors suggest that "a single exposure does provide information about the transitions within the single exposure, and the probability of B given A can indeed be calculated from a single occurrence of AB." Although this may be technically true in that a calculation for a single exposure is possible from this formula, it is not consistent with the conceptual framework for calculating transitional probabilities, as first introduced by Saffran and colleagues. For example, Saffran et al. (1996, Science) describe that "over a corpus of speech there are measurable statistical regularities that distinguish recurring sound sequences that comprise words from the more accidental sound sequences that occur across word boundaries. Within a language, the transitional probability from one sound to the next will generally be highest when the two sounds follow one another within a word, whereas transitional probabilities spanning a word boundary will be relatively low." This makes it clear that the computation of transitional probabilities (i.e., Y | X) is conceptualized to reflect the frequency of XY / frequency of X, over a given language inventory, not just a single pair. Phrased another way, a single exposure to pair AB would not provide a reliable estimate of the raw frequencies with which A and AB occur across a given sample of language.

(5) In experiment 2, the authors argue that there is robust facilitation for trisyllabic and disyllabic words alike. I am not sure about the strength of the evidence for this claim, as it appears that there are some conflicting results relevant to this conclusion. Notably, in the regression model for disyllabic words, the omnibus interaction between word presentation and syllable position did not reach significance (p= 0.089). At face value, this result indicates that there was no significant facilitation for disyllabic words. The additional pairwise comparisons are thus not justified given the lack of omnibus interaction. The finding that there is no significant interaction between word presentation, word position, and word length is taken to support the idea that there is no difference between the two types of words, but could also be due to a lack of power, especially given the p-value (p = 0.010).

(6) The results plotted in Figure 2 seem to suggest that RTs to the first syllable of a trisyllabic item slow down with additional word presentations, while RTs to the final position speed up. If anything, in this figure, the magnitude of the effect seems to be greater for 1st syllable positions (e.g., the RT difference between presentation 1 and 4 for syllable position 1 seems to be numerically larger than for syllable position 3, Figure 2D). Thus, it was quite surprising to see in the results (p. 16) that RTs for syllable position 1 were not significantly different for presentation 1 vs. the later presentations (but that they were significant for positions 2 and 3 given the same comparison). Is this possibly a power issue? Would there be a significant slowdown to 1st syllables if results from both the exact replication and conceptual replication conditions were combined in the same analysis?

(7) It is difficult to evaluate the description of the PARSER simulation on page 36. Perhaps this simulation should be introduced earlier in the methods and results rather than in the discussion only.

Reviewer #2 (Public Review):

Summary:

This valuable study investigates how statistical learning may facilitate a target detection task and whether the facilitation effect is related to statistical learning of word boundaries. Solid evidence is provided that target detection and word segmentation rely on different statistical learning mechanisms.

Strengths:

The study is well designed, using the contrast between the learning of words of uniform length and words of variable length to dissociate general statistical learning effects and effects related to word segmentation.

Weaknesses:

The study relies on the contrast between word length effects on target detection and word learning. However, the study only tested the target detection condition and did not attempt to replicate the word segmentation effect. It is true that the word segmentation effect has been replicated before but it is still worth reviewing the effect size of previous studies.

The paper seems to distinguish prediction, anticipation, and statistical learning, but it is not entirely clear what each term refers to.

Reviewer #1 (Public Review):

Summary:

The authors introduce two preparations for observing large-scale cortical activity in mice during behavior. Alongside, they present intriguing preliminary findings utilizing these methods. This paper is poised to be an invaluable resource for researchers engaged in extensive cortical recording in behaving mice.

Strengths:

Comprehensive methodological detailing:<br /> The paper excels in providing an exceptionally detailed description of the methods used. This meticulous documentation includes a step-by-step workflow, complemented by thorough workflow, protocols and list of materials in the supplementary materials.

Minimal of movement artifacts:<br /> A notable strength of this study is the remarkably low movement artifacts, with specific strategies outlined to attain this outcome.

Insightful preliminary data and analysis:<br /> The preliminary data unveiled in the study reveal interesting heterogeneity in the relationships between neural activity and detailed behavioral features, particularly notable in the lateral cortex. This aspect of the findings is intriguing and suggests avenues for further exploration.

Weaknesses:

Clarification about the extent of the method in title:<br /> The title of the paper, using the term "pan-cortical", may inadvertently suggest that both the top and lateral view preparations are utilized in the same set of mice, while the authors employ either the dorsal view (which offers limited access to the lateral ventral regions) or the lateral view (which restricts access to the opposite side of the cortex).

Despite the authors not identifying qualitative effects, tilting the mouse's head could potentially influence behavioral outcomes in certain paradigms.

Reviewer #2 (Public Review):

Summary:

The authors present a comprehensive technical overview of the challenging acquisition of large-scale cortical activity, including surgical procedures and custom 3D-printed headbar designs to obtain neural activity from large parts of the dorsal or lateral neocortex. They then describe technical adjustments for stable head fixation, light shielding, and noise insulation in a 2-photon mesoscope and provide a workflow for multisensory mapping and alignment of the obtained large-scale neural data sets in the Allen CCF framework. Lastly, they show different analytical approaches to relate single-cell activity from various cortical areas to spontaneous activity by using visualization and clustering tools, such as Rastermap, PCA-based cell sorting, and B-SOID behavioral motif detection.

The study contains a lot of useful technical information that should be of interest to the field. It tackles a timely problem that an increasing number of labs will be facing as recent technical advances allow the activity measurement of an increasing number of neurons across multiple areas in awake mice. Since the acquisition of cortical data with a large field of view in awake animals poses unique experimental challenges, the provided information could be very helpful to promote standard workflows for data acquisition and analysis and push the field forward.

Strengths:

The proposed methodology is technically sound and the authors provide convincing data to suggest that they successfully solved various challenging problems, such as motion artifacts of large imaging preparations or high-frequency noise emissions, during 2-photon imaging. Overall, the authors achieved their goal of demonstrating a comprehensive approach for imaging neural data across many cortical areas and providing several examples that demonstrate the validity of their methods and recapitulate and further extend some recent findings in the field. A particular focus of the results is to emphasize the need for imaging large population activity across cortical areas to identify cross-area information processing during active behaviors.

Weaknesses:

The manuscript contains a lot of technical details and might be challenging for readers without previous experimental experience. However, the different paragraphs illuminate a large range of technical aspects and challenges of large-scale functional imaging. Therefore, the work should be a valuable source of solutions for a diverse audience.

Reviewer #3 (Public Review):

Summary

In their manuscript, Vickers and McCormick have demonstrated the potential of leveraging mesoscale two-photon calcium imaging data to unravel complex behavioural motifs in mice. Particularly commendable is their dedication in providing detailed surgical preparations and corresponding design files, a contribution that will greatly benefit the broader neuroscience community as a whole. The quality of the data is high and examples are available to the community. More importantly, the authors have acquired activity-clustered neural ensembles at an unprecedented spatial scale to further correlate with high level behaviour motifs identified by B-SOiD. Such an advancement marks a significant contribution to the field. While the manuscript is comprehensive and the analytical strategy proposed is promising, some technical aspects warrant further clarification. Overall, the authors have presented an invaluable and innovative approach, effectively laying a solid foundation for future research in correlating large scale neural ensembles with behavioural. The implementation of a custom sound insulator for the scanner is a great idea and should be something implemented by others.

This is a methods paper, but there is no large diagram (in the main figures) that shows how all the parts are connected, communicating and triggering between each other. This is described in the methods and now supplemental figure, but a visual representation would greatly benefit the readers looking to implement something similar as a main figure but I guess they can find it in the methods. No stats for the results shown in Figure 6e, it would be useful to know which of these neural densities for all areas show a clear statistical significance across all the behaviors. While I understand that this is a methods paper, it seems like the authors are aware of the literature surrounding large neuronal recordings during mouse behavior. Indeed, in line 178-179 the authors mention how a significant portion of the variance in neural activity can be attributed to changes in "arousal or self-directed movement even during spontaneous behavior." Why then did the authors not make an attempt at a simple linear model that tries to predict the activity of their many thousands of neurons by employing the multitude of regressors at their disposal (pupil, saccades, stimuli, movements, facial changes, etc). These models are straightforward to implement, and indeed it would benefit this work if the model extracts information on par with what it's known from the literature. We also realize such a model could be done in the future.

Reviewer #1 (Public Review):

Summary:

The manuscript examines the contribution of the dorsal and intermediate hippocampus to goal-directed navigation in a wide virtual environment where visual cues are provided by the scenery on the periphery of a wide arena. Among a choice of 2 reward zones located near the arena periphery, rats learn to navigate from the center of the arena to the reward zone associated with the highest reward. Navigation performance is largely assessed from the rats' body orientation when they leave the arena center and when they reach the periphery, as well as the angular mismatch between the reward zone and the site rats reach the periphery. Muscimol inactivation of the dorsal and intermediate hippocampus alters rat navigation to the reward zone, but the effect was more pronounced for the inactivation of the intermediate hippocampus, with some rat trajectories ending in the zone associated with the lowest reward. Based on these results, the authors suggest that the intermediate hippocampus is critical, especially for navigating to the highest reward zone.

Strengths:

_ The authors developed an effective approach to study goal-directed navigation in a virtual environment where visual cues are provided by the peripheral scenery.

_ In general, the text is clearly written and the figures are well-designed and relatively straightforward to interpret, even without reading the legends.

_ An intriguing result, which would deserve to be better investigated and/or discussed, was that rats tended to rotate always in the counterclockwise direction. Could this be because of a hardware bias making it easier to turn left, some aspect of the peripheral landscape, or a natural preference of rats to turn left that is observable (or reported) in a real environment?

_ Another interesting observation, which would also deserve to be addressed in the discussion, is the fact that dHP/iHP inactivations produced to some extent consistent shifts in departing and peripheral crossing directions. This is visible from the distributions in Figures 6 and 7, which still show a peak under muscimol inactivation, but this peak is shifted to earlier angles than the correct ones. Such change is not straightforward to interpret, unlike the shortening of the mean vector length.

Maybe rats under muscimol could navigate simply by using the association of reward zone with some visual cues in the peripheral scene, in brain areas other than the hippocampus, and therefore stopped their rotation as soon as they saw the cues, a bit before the correct angle. While with their hippocampus is intact, rats could estimate precisely the spatial relationship between the reward zone and visual cues.

Weaknesses:

_ I am not sure that the differential role of dHP and iHP for navigation to high/low reward locations is supported by the data. The current results could be compatible with iHP inactivation producing a stronger impairment on spatial orientation than dHP inactivation, generating more erratic trajectories that crossed by chance the second reward zone.

To make the point that iHP inactivation affects the disambiguation of high and low reward locations, the authors should show that the fraction of trajectories aiming at the low reward zone is higher than expected by chance. Somehow we would expect to see a significant peak pointing toward the low reward zone in the distribution of Figures 6-7.

Reviewer #2 (Public Review):

Summary:

The aim of this paper was to elucidate the role of the dorsal HP and intermediate HP (dHP and iHP) in value-based spatial navigation through behavioral and pharmacological experiments using a newly developed VR apparatus. The authors inactivated dHP and iHP by muscimol injection and analyzed the differences in behavior. The results showed that dHP was important for spatial navigation, while iHP was critical for both value judgments and spatial navigation. The present study developed a new sophisticated behavioral experimental apparatus and proposed a behavioral paradigm that is useful for studying value-dependent spatial navigation. In addition, the present study provides important results that support previous findings of differential function along the dorsoventral axis of the hippocampus.

Strengths:

The authors developed a VR-based value-based spatial navigation task that allowed separate evaluation of "high-value target selection" and "spatial navigation to the target." They were also able to quantify behavioral parameters, allowing detailed analysis of the rats' behavioral patterns before and after learning or pharmacological inactivation.

Weaknesses:

Although differences in function along the dorsoventral axis of the hippocampus is an important topic that has received considerable attention, differences in value coding have been shown in previous studies, including the work of the authors; the present paper is an important study that supports previous studies, but the novelty of the findings is not that high, as the results are from pharmacological and behavioral experiments only.

Reviewer #3 (Public Review):

Summary:

The authors established a new virtual reality place preference task. On the task, rats, which were body-restrained on top of a moveable Styrofoam ball and could move through a circular virtual environment by moving the Styrofoam ball, learned to navigate reliably to a high-reward location over a low-reward location, using allocentric visual cues arranged around the virtual environment.

The authors also showed that functional inhibition by bilateral microinfusion of the GABA-A receptor agonist muscimol, which targeted the dorsal or intermediate hippocampus, disrupted task performance. The impact of functional inhibition targeting the intermediate hippocampus was more pronounced than that of functional inhibition targeting the dorsal hippocampus.

Moreover, the authors demonstrated that the same manipulations did not significantly disrupt rats' performance on a virtual reality task that required them to navigate to a spherical landmark to obtain reward, although there were numerical impairments in the main performance measure and the absence of statistically significant impairments may partly reflect a small sample size (see comments below).

Overall, the study established a new virtual-reality place preference task for rats and established that performance on this task requires the dorsal to intermediate hippocampus. They also established that task performance is more sensitive to the same muscimol infusion (presumably - doses and volumes used were not clearly defined in the manuscript, see comments below) when the infusion was applied to the intermediate hippocampus, compared to the dorsal hippocampus, although this does not offer strong support for the authors claim that dorsal hippocampus is responsible for accurate spatial navigation and intermediate hippocampus for place-value associations (see comments below).

Strengths:

(1) The authors established a new place preference task for body-restrained rats in a virtual environment and, using temporary pharmacological inhibition by intra-cerebral microinfusion of the GABA-A receptor agonist muscimol, showed that task performance requires dorsal to intermediate hippocampus.

(2) These findings extend our knowledge about place learning tasks that require dorsal to intermediate hippocampus and add to previous evidence that, for some place memory tasks, the intermediate hippocampus may be more important than other parts of the hippocampus, including the dorsal hippocampus, for goal-directed navigation based on allocentric place memory.

(3) The hippocampus-dependent task may be useful for future recording studies examining how hippocampal neurons support behavioral performance based on place information.

Weaknesses:<br /> (1) The new findings do not strongly support the authors' suggestion that the dorsal hippocampus is responsible for accurate spatial navigation and the intermediate hippocampus for place-value associations.

The authors base this claim on the differential effects of the dorsal and intermediate hippocampal muscimol infusions on different performance measures. More specifically, dorsal hippocampal muscimol infusion significantly increased perimeter crossings and perimeter crossing deviations, whereas dorsal infusion did not significantly change other measures of task performance, including departure direction and visits to the high-value location. However, these statistical outcomes offer only limited evidence that dorsal hippocampal infusion specifically affected the perimeter crossing, without affecting the other measures. Numerically the pattern of infusion effects is quite similar across these various measures: intermediate hippocampal infusions markedly impaired these performance measures compared to vehicle infusions, and the values of these measures after dorsal hippocampal muscimol infusion were between the values in the intermediate hippocampal muscimol and the vehicle condition (Figures 5-7). Moreover, I am not so sure that the perimeter crossing measures really reflect distinct aspects of navigational performance compared to departure direction and hit rate, and, even if they did, which aspects this would be. For example, in line 316, the authors suggest that 'departure direction and PCD [perimeter crossing deviation] [are] indices of the effectiveness and accuracy of navigation, respectively'. However, what do the authors mean by 'effectiveness' and 'accuracy'? Accuracy typically refers to whether or not the navigation is 'correct', i.e. how much it deviates from the goal location, which would be indexed by all performance measures.

So, overall, I would recommend toning down the claim that the findings suggest that the dorsal hippocampus is responsible for accurate spatial navigation and the intermediate hippocampus for place-value associations.

(2) The claim that the different effects of intermediate and dorsal hippocampal muscimol infusions reflect different functions of intermediate and dorsal hippocampus rests on the assumption that both manipulations inhibit similar volumes of hippocampal tissue to a similar extent, but at different levels along the dorso-ventral axis of the hippocampus. However, this is not a foregone conclusion (e.g., drug spread may differ depending on the infusion site or drug effects may differ due to differential expression of GABA-A receptors in the dorsal and intermediate hippocampus), and the authors do not provide direct evidence for this assumption. Therefore, a possible alternative account of the weaker effects of dorsal compared to intermediate hippocampal muscimol infusions on place-preference performance is that the dorsal infusions affect less hippocampal volume or less markedly inhibit neurons within the affected volume than the intermediate infusions. I would recommend that the authors briefly consider this issue in the discussion. Moreover, from the Methods, it is not clear which infusion volume and muscimol concentration were used for the different infusions (see below, 4.a.), and this must be clarified.

(3) It is good that the authors included a comparison/control study using a spherical beacon-guided navigation task, to examine the specific psychological mechanisms disrupted by the hippocampal manipulations. However, as outlined below (4.b.), the sample size for the comparison study was lower than for the main study, and the data in Figure 8 suggest that the comparison task may be affected by the hippocampal manipulations similarly to the place-preference task, albeit less markedly. This would raise the question as to which mechanisms that are common to the two tasks may be affected by hippocampal functional inhibition, which should be considered in the discussion.

(4) Several important methodological details require clarification:<br /> a. Drug infusions (from line 673):<br /> - '0.3 to 0.5 μl of either phosphate-buffered saline (PBS) or muscimol (MUS) was infused into each hemisphere'; the authors need to clarify when which infusion volume was used and why different infusion volumes were used.<br /> - I could not find the concentration of the muscimol solution that was used. The authors must clarify this and also should include a justification of the doses used, e.g. based on previous studies.<br /> - Please also clarify if the injectors and dummies were flush with the guides or by which distance they protruded from the guides.<br /> b. Sample sizes: The authors should include sample size justifications, e.g. based on considerations of statistical power, previous studies, practical considerations, or a combination of these factors. Importantly, the smaller sample size in the control study using the spherical beacon-guided navigation task (n=5 rats) limits comparability with the main study using the place-preference task (n=8). Numerically, the findings on the control task (Figure 8) look quite similar to the findings on the place-preference task, with intermediate hippocampal muscimol infusions causing the most pronounced impairment and dorsal hippocampal muscimol infusions causing a weaker impairment. These effects may have reached statistical significance if the same sample size had been used in the place-preference study.<br /> c. Statistical analyses: Why were the data of the intermediate and dorsal hippocampal PBS infusion conditions averaged for some of the analyses (Figure 5; Figure 6B and C; Figure 7B and C; Figure 8B) but not for others (Figure 6A and Figure 7A)?

Reviewer #1 (Public Review):

Summary:

This work describes a simple mechanical model of worm locomotion, using a series of rigid segments connected by damped torsional springs and immersed in a viscous fluid. It uses this model to simulate forward crawling movement, as well as omega turns.

Strengths:

The primary strength is in applying a biomechanical model to omega-turn behaviors. The biomechanics of nematode turning behaviors are relatively less well described and understood than forward crawling, and the increase in power during omega turns is one of the more novel results. The model itself may be a useful implementation to other researchers, particularly owing to its simplicity.

Weaknesses:

The strength of the model presented in this work relative to prior approaches is not well supported, and in general the paper would be improved with a better description of the broader context of existing modeling literature related to undulatory locomotion. This paper claims to improve on previous approaches to taking body shapes as inputs. However, the sole nematode model cited aims to do something different, and arguably more significant, which is to use experimentally derived parameters to model both the neural circuits that induce locomotion as well as the biomechanics and to subsequently compare the model to experimental data. Other modeling approaches do take experimental body kinematics as inputs and use them to produce force fields, however, they are not cited or discussed. Finally, the overall novelty of the approach is questionable. A functionally similar approach was developed in 2012 to describe worm locomotion in lattices (Majmudar, 2012, Roy. Soc. Int.), which is not discussed and would provide an interesting comparison and needed context.

In some sense, because the model takes kinematics as an input and uses previously established techniques to model mechanics, it is unsurprising that it can reproduce experimentally observed kinematics, however, the forces calculated and the variation of parameters could be of interest, but other methods derived from kinematics could provide similar results. It is unclear what the predictive power of the model is.

Relatedly, a justification of why the drag coefficients had to be changed by a factor of 100 should be explored. Plate conditions are difficult to replicate and the rheology of plates likely depends on several factors, but is for example, changes in hydration level likely to produce a 100-fold change in drag? or something more interesting/subtle within the model producing the discrepancy?

Finally, the language used to distinguish different modeling approaches was often unclear. For example, it was unclear in what sense the model presented in Boyle, 2012 was a "kinetic model" and in many situations, it appeared that the term kinematic might have been more appropriate. Other phrases like "frictional forces caused by the tension of its muscles" were unclear at first glance, and might benefit from revision and more canonical usage of terms.

Reviewer #2 (Public Review):

Summary:

Developing a mechanical model of C. elegans is difficult to do from basic principles because it moves at low (but not very small) Reynolds number, is itself visco-elastic, and often is measured moving at a solid/liquid interface. The ElegansBot is a good first step at a kinetic model that reproduces a wide range of C. elegans motility behavior.

Strengths:

The model is general due to its simplicity and likely useful for various undulatory movements. The model reproduces experimental movement data using realistic physical parameters (e.g. drags, forces, etc). The model is predictive (semi?) as shown in the liquid to solid gait transition. The model is straightforward in implementation and so likely is adaptable to modification and addition of control circuits.

Comments on revised version:

This is a revised manuscript. I'm happy with the changes made, including the specific responses to my previous concerns.

Reviewer #3 (Public Review):

A mechanical model of C. elegans, embedded in a resistive force environment, is used to calculate input torque patterns required to generate output curvature patterns and coordinates, corresponding to a number of different locomotion behaviors in C. elegans.

Strengths:

The use of a mechanical model to study a variety of locomotor sequences and the grounding in empirical data are strengths. The matching of speeds (though requiring adjusted drag coefficients) is a strength.

Weaknesses:

The paper lacks evidence of numerical validation or comparison with the results and tools in the literature. E.g. is it surprising that the uniform torque distribution yields maximal speed? What is the relation between input and output data? How does the input-output relation depend on the parameters of the model? What novel model predictions are made?

In particular, if validated, the breakdown of drag forces and torque distributions during forward locomotion and turning behaviors may be interesting to compare to predictions by other tools, and to empirical measurement. One caveat is that the worm touches itself during such turns, and even crosses over itself in delta turns, and so the estimated drag coefficients and the resultant mechanical forces are likely incorrect.

Reviewer #2 (Public Review):

Summary:

Laham et al. investigate how the projection from adult born granule cells into CA2 affects the retrieval of social memories at various developmental points. They use chemogenetic manipulations and electrophysiological recordings to test how this projection affects hippocampal network properties during behavior. The study is of relevant interest for the neuroscience community and the results are important for our understanding of how social memories of different nature (remote or immediate) are encoded and supported by the hippocampal circuitry. The behavioral experiments after abGC projections to CA2 are compelling as they show clearly distinct behavioral readout. While the electrophysiological experiments are difficult to interpret without more single cell responses quantifications, they clearly show that more than one region in the hippocampus is involved in the formation of social memories.

Reviewer #3 (Public Review):

Laham et al. present a manuscript investigating the function of adult-born granule cells (abGCs) projecting to the CA2 region of the hippocampus during social memory. It should be noted that no function for the general DG to CA2 projection has been proposed yet. The authors use targeted ablation, chemogenetic silencing and in vivo ephys to demonstrate that the abGCs to CA2 projection is necessary for the retrieval of a remote social memories such as the memory of one's mother. They also use in vivo ephys to show that abGCs are necessary for differential CA2 network activity, including theta-gamma coupling and sharp wave-ripples, in response to novel versus familiar social stimuli.

The question investigated is important since the function of DG to CA2 projection remained elusive a decade after its discovery. Overall, the results are interesting but focused to the social memory of the mother and their description in the manuscript and figures is too cursory. For example, raw interaction times must be shown before their difference. The assumption that mice exhibit social preference between familiar or novel individuals such as mother and non-mother based on social memory formation, consolidation and retrieval should be better explained throughout the manuscript. Thus, when describing the results, the authors should comment on changes in preference and how this can be interpreted as a change in social memory retrieval. Several critical experimental details such as the total time of presentation to the mother and non-mother stimulus mice are also lacking from the manuscript. The in vivo e-phys results are interesting as well but even more succinct with no proposed mechanism as to how abGCs could regulate SWR and PAC in CA2.

The manuscript is well-written with the appropriate references. The choice of behavioral test is somewhat debatable however. It is surprising the authors chose to use a direct presentation test (presentation of the mother and non-mother in alternance) instead of the classical 3-chamber test which is particularly appropriate to investigate social preference. Since the authors focused exclusively on this preference, the 3-chamber test would have been more adequate in my opinion. It would greatly strengthened the results if the authors could repeat a key experiment from their investigation using such test. In addition, the authors only impaired the mother's memory. An additional experiment showing that disruption of the abGCs to CA2 circuit impairs social memory retrieval in general would allow to generalize the findings to social memories in general. As the manuscript stands, the authors can only conclude as to the importance of this circuit for the memory of the mother. Developmental memory implies the memory of familiar kin as well.

The in vivo ephys section (Figure 3) is interesting but even more minimalistic and it is unclear how abGCs projection to CA2 can contribute to SWR and theta-gamma PAC. In figure 1, the authors suggest that abGCs project preferentially to PV+ neurons in CA2. At minima, the authors should discuss how the abGCs to PV+ neurons to CA2 pyramidal neurons circuit can facilitate SWR and theta-gamma PAC.

Finally, proposing a function for 4-6-week-old abGCs projecting to CA2 begs two questions: What are abGCs doing once they mature further and more generally, what is the function of the DG to CA2 projection? It would be interesting for the authors to comment on these questions in the discussion.

Revision:

The authors have followed my recommendations except for the ones suggesting new experiments. As a result, the clarity of the manuscript and the links between evidence and claims have improved by the message is quite reduced. Many important questions remain open such as: What makes mother's memories so special they require the abGC projection to CA2 unlike other types of social memories? Do abGCs truly connect CA2 PV+ interneurons and how does this connection shape sharp-wave ripples in CA2?

Reviewer #1 (Public Review):

Summary:

In this study, Diana et al. present a Monte Carlo-based method to perform spike inference from calcium imaging data. A particular strength of their approach is that they can estimate not only averages but also uncertainties of the modeled process. The authors then focus on the quantification of spike time uncertainties in simulated data and in data recorded with a high sampling rate in cerebellar slices with GCaMP8f.

Strengths:

- The authors provide a solid groundwork for sequential Monte Carlo-based spike inference, which extends previous work of Pnevmatikakis et al., Greenberg et al., and others.

- The integration of two states (silence vs. burst firing) seems to improve the performance of the model.

- The acquisition of a GCaMP8f dataset in the cerebellum is useful and helps make the point that high spike time inference precision is possible under certain conditions.

Weaknesses:

- The algorithm is designed to predict single spike times. Currently, it is not benchmarked against other algorithms in terms of single spike precision and spike time errors. A benchmarking with the most recent other SMC model and another good model focused on single spike outputs (e.g., MLSpike) would be useful to have.

- Some of the analyses and benchmarks seem too cursory, and the reporting simply consists of a visual impression of results instead of proper analysis and quantification. For example, the authors write "The spike patterns obtained using our method are very similar across trials, showing that PGBAR can reliably detect single-trial action potential-evoked GCaMP8f fluorescence transients." This is a highly qualitative statement, just based on the (subjective) visual impression of a plot. Similarly, the authors write "we could reliably identify the two spikes in each trial", but this claim is not supported by quantification or a figure, as far as I can see. The authors write "but the trade-off between temporal accuracy, SNR and sampling frequency must be considered", but they don't discuss these trade-offs systematically.

- It has been shown several times from experimental data that spike inference with single spike resolution does not work well (Huang et al. eLife, 2021; Rupprecht et al., Nature Neuroscience, 2021) in general. This limitation should be discussed with respect to the applicability of the proposed algorithm for standard population calcium imaging data.

- Several analyses are based on artificial, simulated data with simplifying assumptions. Ever since Theis et al., Neuron, 2016, it has been known that artificially generated ground truth data should not be used as the primary means to evaluate spike inference algorithms. It would have been informative if the authors had used either the CASCADE dataset or their cerebellum dataset for more detailed analyses, in particular of single spike time precision.

- In its current state, the sum of the current weaknesses makes the suggested method, while interesting for experts, rather unattractive for experimentalists who want to perform spike inference on their recorded calcium imaging data.

Other comments:

- One of the key features of the SMC model is the assumption of two states (bursting vs. non-bursting). However, while it seems clear that this approach is helpful, it is not clear where this idea comes from, from an observation of the data or another concept.

- Another SMC algorithm (Greenberg et al., 2018) stated that the fitted parameters showed some degeneracy, resulting in ambiguous fitting parameters. It would be good to know if this problem was avoided by the authors.

Reviewer #2 (Public Review):

Summary:

Methods to infer action potentials from fluorescence-based measurements of intracellular calcium dynamics are important for optical measurements of activity across large populations of neurons. The variety of existing methods can be separated into two broad classes: a) model-independent approaches that are trained on ground truth datasets (e.g., deep networks), and b) approaches based on a model of the processes that link action potentials to calcium signals. Models usually contain parameters describing biophysical variables, such as rate constants of the calcium dynamics and features of the calcium indicator. The method presented here, PGBAR, is model-based and uses a Bayesian approach. A novelty of PGBAR is that static parameters and state variables are jointly estimated using particle Gibbs sampling, a sequential Monte Carlo technique that can efficiently sample the latent embedding space.

Strengths:

A main strength of PGBAR is that it provides probability distributions rather than point estimates of spike times. This is different from most other methods and may be an important feature in cases when estimates of uncertainty are desired. Another important feature of PGBAR is that it estimates not only the state variable representing spiking activity but also other variables such as baseline fluctuations and stationary model variables, in a joint process. PGBAR can therefore provide more information than various other methods. The information in the GitHub repository is well-organized.

Weaknesses:

On the other hand, the accuracy of spike train reconstructions is not higher than that of other model-based approaches, and clearly lower than the accuracy of a model-independent approach based on a deep network. The authors demonstrate convincingly that PGBAR can resolve inter-spike intervals in the range of 5 ms using fluorescence data obtained with a very fast genetically encoded calcium indicator at very high sampling rates (line scans at >= 1 kHz). It would be interesting to more systematically compare the performance of PGBAR to other methods in this regime of high temporal resolution, which has not been explored much.

Reviewer #1 (Public Review):

Short Assessment

In this work the authors propose a new regulatory role for one the most abundant circRNAs, circHIPK3. They demonstrate that circHIPK3 interacts with an RNA binding protein (IGF2BP2), sequestering it away from its target mRNAs. This interaction is shown to regulates the expression of hundreds of genes that share a specific sequence motif (11-mer motif) in their untranslated regions (3'-UTR), identical to one present in circHIPK3 where IGF2BP2 binds. The study further focuses on the specific case of STAT3 gene, whose mRNA product is found to be downregulated upon circHIPK3 depletion. This suggests that circHIPK3 sequesters IGF2BP2, preventing it from binding to and destabilizing STAT3 mRNA. The study presents evidence supporting this mechanism and discusses its potential role in tumor cell progression. These findings contribute to the growing complexity of understanding cancer regulation and highlight the intricate interplay between circRNAs and protein-coding genes in tumorigenesis.

Strengths:<br /> The authors show mechanistic insight into a proposed novel "sponging" function of circHIPK3 which is not mediated by sequestering miRNAs but rather a specific RNA binding protein (IGF2BP2). They address the stoichiometry of the molecules involved in the interaction, which is a critical aspect that is frequently overlooked in this type of studies. They provide both genome-wide analysis and a specific case (STAT3) which is relevant for cancer progression. Overall, the authors have significantly improved their manuscript in their revised version.

Weaknesses:<br /> While the authors have performed northern blots to measure circRNA levels, an estimation of the circRNA overexpression efficiency, namely the circular-to-linear expression ratio, would be desired. The seemingly contradictory effects of circHIPK3 and STAT3 depletion in cancer progression, are now addressed by the authors in their revised manuscript, incorporating potential reasons that might explain such complexity.

Major points about revised manuscript

(1) In Supplementary Figure S5H, the membrane may have been trimmed too closely to the circRNA band, potentially resulting in the absence of the linear RNA band. Could the authors provide a full image of the membrane that includes the loading points? Having access to the complete image would allow for a more comprehensive evaluation of the results, including the presence or absence of expected linear and circular RNA bands.

Reviewer #2 (Public Review):

Summary:

The authors have diligently addressed most of the points raised during the review process (except the important point of "additional in vitro experiments [...] needed to investigate the implication of circHIPK3 in bladder cancer cell phenotype" for which no additional experiments were performed), resulting in an improvement in the study. The data are now described with clarity and conciseness, enhancing the overall quality of the manuscript.

Strengths:

New, well-defined molecular mechanism of circRNAs involvement in bladder cancer.

Weaknesses:

Lack of solid translational significance data.

Reviewer #3 (Public Review):

In Okholm et al., the authors evaluate the functional impact of circHIPK3 in bladder cancer cells. By knocking down circHIPK3 and performing an RNA-seq analysis, the authors found thousands of deregulated genes which look unaffected by miRNAs sponging function and that are, instead, enriched for a 11-mer motif. Further investigations showed that the 11-mer motif is shared with the circHIPK3 and able to bind the IGF2BP2 protein. The authors validated the binding of IGF2BP2 and demonstrated that IGF2BP2 KD antagonizes the effect of circHIPK3 KD and leads to the upregulation of genes containing the 11-mer. Among the genes affected by circHIPK3 KD and IGF2BP2 KD, resulting in downregulation and upregulation respectively, the authors found the STAT3 gene, which also consistently has concomitant upregulation of one of its targets TP53. The authors propose a mechanism of competition between circHIPK3 and IGF2BP2 triggered by IGF2BP2 nucleation, potentially via phase separation.

Strengths:

Although the number of circRNAs continues to grow, this field lacks many instances of detailed molecular investigations. The presented work critically addresses some of the major pitfalls in the field of circRNAs, and there has been a careful analysis of aspects frequently poorly investigated. Experiments involving use of time-point knockdown followed by RNA-seq, investigation of miRNA-sponge function of circHIPK3, identification of 11-mer motif, identification and validation of IGF2BP2, and the analysis of copy number ratio between circHIPK3 and IGF2BP2 in assessing the potential ceRNA mode of action are thorough and convincing.

Weaknesses:

It is unclear why the authors used certain bladder cancer cells versus non-bladder cells in some experiments. The efficacy of certain experiments (specifically rescue experiments) and some control conditions is still questionable. Overall, the presented study adds some further knowledge in describing circHIPK3 function, its capability to regulate some downstream genes, and its interaction and competition for IGF2BP2.

Reviewer #1 (Public Review):

Summary:

Authors were attempting to determine the extent that CIH altered swallowing motor function; specifically, the timing and probability of the activation of the larygneal and submental motor pools. The paper describes a variety of different motor patterns elicited by optogenetic activation of individual neuronal phenotypes within PiCo in a group of mice exposed to CIH. They show that there are a variety of motor patterns that emerge in CIH mice; this is apparently different than the more consistent motor patterns elicited by PiCo activation in normoxic mice (previously published)

Strengths:

The preparation is technically challenging and gives valuable information related to the role of PiCo in the pattern of motor activation involved in swallowing and its timing with phrenic activity. Genetic manipulations allow for the independent activation of the individual neuronal phenotypes of PiCo (glutamatergic, cholinergic) which is a strength.

Weaknesses:

(1) Comparisons made between experimental data acquired currently with those previously published are extremely problematic, with the potential confounding influence of changing environments, genetics and litter effects. For example, were the current mice tested at the same time as those exposed to normoxia? Are they littermates (or at least from the same colony) as those previously examined? If they were tested at the same time and age, then the authors should explicitly state this in the methods. The authors have provided no statistical analyses to determine whether there is an effect of CIH on the motor patterns. In short, how can they be sure that the phenomena they observe with respect to motor patterns is due to CIH?

(2) The data are descriptive in nature, reporting only differences (diversity) of motor patterns in this cohort of animals exposed to CIH. There is limited mechanistic insight into how PiCo manipulation alters the pattern and probability of motor activation. Can they utilize Fos or marker of activation within the nTS or other regions to provide initial insight? Or in another nucleus that contributes as part of the circuit.

(3) The differences between the genotypes (ChaTcre; Vglut2Cre; ChatCre:Vglut2FlpO) with regard to the probability of generating a swallow are not sufficiently discussed, in my view. If, as the authors state, it is "reasonable to suggest that CIH differentially affects" these populations, then what are some viable reasons? What are the known differences in these populations of neurons that could lead to variable responses? Do they project to different places?

(4) The Results section is difficult to follow and interpret. It would be beneficial to have a couple of sentences after each sub-section stating what the data actually mean. As of now it reads like a statistical report of the data with little "basic" interpretation of the data.

(5) I have a hard time understanding the functional significance of calculating and plotting the degree of correlation between shifting/delaying the following inspiratory burst and triggering a swallow.

Reviewer #2 (Public Review):

The manuscript has been revised according to Reviewer's suggestions. Recommendations for the Authors have been almost entirely followed. However, there are some points where the authors state that they have made changes, but the text does not show this. The revised version would have gained in clarity if it was with track changes and numbered rows. In particular, I cannot see the following changes:

Lines 104-105: Did you mean: "We confirmed that optogenetic stimulation of PiCo neurons in ChATcre:Vglut2FlpO:ChR2 mice exposed to CIH triggers swallow and laryngeal activation similar to the control mice exposed to room air (Huff et al., 2023)." Otherwise, the sentence is not clear.<br /> Thank you, this has been changed

Lines 228-232: "PiCo-triggered swallows are characterized by a significant decrease in duration compared to swallows evoked by water in ChATcre:Ai32 mice (265 {plus minus} 132ms vs 144 {plus minus} 101ms; paired t-test: p= 0.0001, t= 5.21, df= 8), Vglut2cre:Ai32 mice (308 {plus minus} 184ms vs 125 {plus minus} 44ms; paired t-test: p= 0.0003, t= 6.46, df= 7), and ChATcre:Vglut2FlpO:ChR2 mice (230 {plus minus} 67ms vs 130 {plus minus} 35ms; paired t-test: p= 0.0005, t= 5.62, df= 8) exposed to CIH (Table S1).".<br /> Thank you, this has been changed

Lines 283-290: "Thus, CIH does not alter PiCo's ability to coordinate the timing for swallowing and breathing. Rather, our data reveals that CIH disrupts the swallow motor sequence likely due to changes in the interaction between PiCo and the SPG, presumably the cNTS.

While it has previously been demonstrated that PiCo is an important region in swallow-breathing coordination (Huff et al., 2023), previous studies did not demonstrate that PiCo is involved in swallow pattern generation itself. Thus, here we show for the first time that CIH resulted in the instability of the swallow motor pattern activated by stimulating PiCo, suggesting PiCo plays a role in its modulation.".<br /> Thank you, this has been changed

Line 437: Mice of the ChATcre:Ai32, Vglut2cre:Ai32 and ChATcre:Vglut2FlpO:ChR2 lines were kept in collective cages with food and water ad libitum placed inside custom-built chambers.<br /> Thank you, this has been changed.

Overall, the manuscript has been improved.

Reviewer #1 (Public Review):

Summary:

In this work, the authors examine the activity and function of D1 and D2 MSNs in dorsomedial striatum (DMS) during an interval timing task. In this task, animals must first nose poke into a cued port on the left or right; if not rewarded after 6 seconds, they must switch to the other port. Critically, this task thus requires animals to estimate if at least 6 seconds have passed after the first nose poke - this is the key aspect of the task focused on here. After verifying that animals reliably estimate the passage of 6 seconds by leaving on average after 9 seconds, the authors examine striatal activity during this interval. They report that D1-MSNs tend to decrease activity, while D2-MSNs increase activity, throughout this interval. They suggest that this activity follows a drift-diffusion model, in which activity increases (or decreases) to a threshold after which a decision (to leave) is made. The authors next report that optogenetically inhibiting D1 or D2 MSNs, or pharmacologically blocking D1 and D2 receptors, increased the average wait time of the animals to 10 seconds on average. This suggests that both D1 and D2 neurons contribute to the estimate of time, with a decrease in their activity corresponding to a decrease in the rate of 'drift' in their drift-diffusion model. Lastly, the authors examine MSN activity while pharmacologically inhibiting D1 or D2 receptors. The authors observe most recorded MSNs neurons decrease their activity over the interval, with the rate decreasing with D1/D2 receptor inhibition.

Major strengths:

The study employs a wide range of techniques - including animal behavioral training, electrophysiology, optogenetic manipulation, pharmacological manipulations, and computational modeling. The behavioral task used by the authors is quite interesting and a nice way to probe interval timing in rodents. The question posed by the authors - how striatal activity contributes to interval timing - is of importance to the field and has been the focus of many studies and labs; thus, this paper can meaningfully contribute to that conversation. The data within the paper is presented very clearly, and the authors have done a nice job presenting the data in a transparent manner (e.g., showing individual cells and animals). Overall, the manuscript is relatively easy to read and clear, with sufficient detail given in most places regarding the experimental paradigm or analyses used.

Major weaknesses:

I perceive two major weaknesses. The first is the impact or contextualization of their results in terms of the results of the field more broadly. More specifically, it was not clear to me how the authors are interpreting the striatal activity in the context of what others have observed during interval timing tasks. In other words - what was the hypothesis going into this experiment? Does observing increasing/decreasing activity in D2 versus D1 support one model of interval timing over another, or does it further support a more specific idea of how DMS contributes to interval timing? Or was the main question that we didn't know if D2 or D1 neurons had differential activity during interval timing?

In the second, I felt that some of the conclusions suggested by the authors don't seem entirely supported by the data they present, or the data presented suggests a slightly more complicated story. Below I provide additional detail on some of these instances.

Regarding the results presented in Figures 2 and 3:

I am not sure the PC analysis adds much to the interpretation, and potentially unnecessarily complicates things. In particular, running PCA on a matrix of noisy data that is smoothed with a Gaussian will often return PCs similar to what is observed by the authors, with the first PC being a line up/down, the 2nd PC being a parabola that is up/down, etc. Thus, I'm not sure that there is much to be interpreted by the specific shape of the PCs here. I think an alternative analysis that might be both easier and more informative is to compute the slope of the activity of each neuron across the 6 seconds. This would allow the authors to quantify how many neurons increase or decrease their activity much like what is shown in Figure 2.

Relatedly, it seems that the data shown in Figure 2D *doesn't* support the authors' main claim regarding D2/D1 MSNs increasing/decreasing their activity, as the trial-by-trial slope is near 0 for both cell types.

Regarding the results in Figure 4:

The authors suggest that their data is consistent with a drift-diffusion model. However, it is unclear how well the output from the model fits the activity from neurons the authors recorded. Relatedly, it is unclear how the parameters were chosen for the D1/D2 versions of this model. I think that an alternate approach that would answer these questions is to fit the model to each cell, and then examine the best-fit parameters, as well as the ability of the model to predict activity on trials held out from the fitting process. This would provide a more rigorous method to identify the best parameters and would directly quantify how well the model captures the data.

Relatedly, looking at the raw data in Figure 2, it seems that many neurons either fire at the beginning or end of the interval, with more neurons firing at the end, and more firing at the beginning, for D2/D1 neurons respectively. Thus, it's not clear to me whether the drift-diffusion model is a good model of activity. Or, perhaps the model is supposed to be related to the aggregate activity of all D1/D2 neurons? (If so, this should be made more explicit. The comment about fitting the model directly to the data also still stands).

Further, it's unclear to me how, or why, the authors changed the specific parameters they used to model the optogenetic manipulation. Were these parameters chosen because they fit the manipulation data? This I don't think is in itself an issue, but perhaps should be clearly stated, because otherwise it sounds a bit odd given the parameter changes are so specific. It is also not clear to me why the noise in the diffusion process would be expected to change with increased inhibition.

Regarding the results in Figure 6:

My comments regarding the interpretation of PCs in Figure 2 apply here as well. In addition, I am not sure that examining PC2 adds much here, given that the authors didn't examine such nonlinear changes earlier in the paper.

A larger concern though that seems potentially at odds with the authors' interpretation is that there seems to be very little change in the firing pattern after D1 or D2 blockade. I see that in Figure 6F the authors suggest that many cells slope down (and thus, presumably, they are recoding more D1 cells), and that this change in slope is decreased, but this effect is not apparent in Figure 6C, and Figure 6B shows an example of a cell that seems to fire in the opposite direction (increase activity). I think it would help to show some (more) individual examples that demonstrate the summary effect shown by the authors, and perhaps the authors can comment on the robustness (or the variability) of this result.

Also, it seems that if the authors want to claim that this manipulation lowers the drift rate. I think to make this claim, they could fit the DDM model and examine whether D is significantly lower.

Regarding the results in Figure 7:

I am overall a bit confused about what the authors are trying to claim here. In Figure 7, they present data suggesting that D1 or D2 blockade disrupts their ability to decode time in the interval of interest (0-6 seconds). However, in the final paragraph of the results, the authors seem to say that by using another technique, they didn't see any significant change in decoding accuracy after D1 or D2 blockade. What do the authors make of this?

Impact:

The task and data presented by the authors are very intriguing, and there are many groups interested in how striatal activity contributes to the neural perception of time. The authors perform a wide variety of experiments and analysis to examine how DMS activity influences time perception during an interval-timing task, allowing for insight into this process. However, the significance of the key finding - that D2/D1 activity increases/ decreases with time - remains somewhat ambiguous to me. This arises from a lack of clarity regarding the initial hypothesis and the implications of this finding for advancing our understanding of striatal functions.

Reviewer #2 (Public Review):

Summary:

In the present study, the authors investigated the neural coding mechanisms for D1- and D2-expressing striatal direct and indirect pathway MSNs in interval timing by using multiple strategies. They concluded that D2-MSNs and D1-MSNs have opposing temporal dynamics yet disrupting either type produced similar effects on behavior, indicating the complementary roles of D1- and D2- MSNs in cognitive processing. However, the data was incomplete to fully support this major finding. One major reason is the heterogenetic responses within the D1-or D2-MSN populations. In addition, there are additional concerns about the statistical methods used. For example, the majority of the statistical tests are based on the number of neurons, but not the number of mice. It appears that the statistical difference was due to the large sample size they used (n=32 D2-MSNs and n=41 D1-MSNs), but different neurons recorded in the same mouse cannot be treated as independent samples; they should use independent mouse-based statistical analysis.

Strengths:

The authors used multiple approaches including awake mice behavior training, optogenetic-assistant cell-type specific recording, optogenetic or pharmacological manipulation, neural computation, and modeling to study neuronal coding for interval timing.

Weaknesses:

(1) More detailed behavior results should be shown, including the rate of the success switches, and how long it takes to wait in the second nose poke to get a reward. For line 512 and the Figure 1 legend, the reviewer is not clear about the reward delivery. The methods appear to state that the mouse had to wait for 18s, then make nose pokes at the second port to get the reward. What happens if the mouse made the second nose poke before 18 seconds, but then exited? Would the mouse still get the reward at 18 seconds? Similarly, what happens if the mice made the third or more nosepokes within 18 seconds? It is important to clarify because, according to the method described, if the mice made a second nose poke before 18 seconds, this already counted as the mouse making the "switch." Lastly, what if the mice exited before 6s in the first nosepoke?

(2) There are a lot of time parameters in this behavior task, the description of those time parameters is mentioned in several parts, in the figure legend, supplementary figure legend, and methods, but was not defined clearly in the main text. It is inconvenient, sometimes, confusing for the readers. The authors should make a schematic diagram to illustrate the major parameters and describe them clearly in the main text.

(3) In Line 508, the reviewer suggests the authors pay attention to those trials without "switch". It would be valuable to compare the MSN activity between those trials with or without a "switch".

(4) The definition of interval is not very clear. It appears that the authors used a 6-second interval in analyzing the data in Figure 2 and Figure 3. But from my understanding, the interval should be the time from time "0" to the "switch", when the mice start to exit from the first nose poke.

(5) For Figure 2 C-F, the authors only recorded 32 D2-MSNs in 4 mice, and 41 D1-MSNs in 5 mice. The sample size is too small compared to the sample size usually used in the field. In addition to the small sample size, the single-cell activity exhibited heterogeneity, which created potential issues. For both D1 and D2 MSNs, the authors tried to make conclusions on the "trend" of increasing in D2-MSNs and decreasing in D1-MSNs populations, respectively, during the interval. However, such a conclusion is not sufficiently supported by the data presented. It looks like the single-cell activity patterns can be separated into groups: one is a decreasing activity group, one is an increasing activity group and a small group for on and off response. Because of the small sample size, the author should pay attention to the variance across different mice (which needs to be clearly presented in the manuscript), instead of pooling data together and analyzing the mean activity.

(6) For Figure 2, from the activity in E and F, it seems that the activity already rose before the trial started, the authors should add some longer baseline data before time zero for clarification and comparison, and show the timing of the actual start of the activity with the corresponding behavior. What behavior states are the mice in when initiating the activity?

(7) The authors were focused on the "switch " behavior in the task, but they used an arbitrary 6s time window to analyze the activity, and tried to correlate the decreasing or increasing activities of MSNs to the neural coding for time. A better way to analyze is to sort the activity according to the "switch" time, from short to long intervals. This way, the authors could see and analyze whether the activity of D1 or D2 MSNs really codes for the different length of interval, instead of finding a correlation between average activity trends and the arbitrary 6s time window.

Reviewer #3 (Public Review):

Summary:

The cognitive striatum, also known as the dorsomedial striatum, receives input from brain regions involved in high-level cognition and plays a crucial role in processing cognitive information. However, despite its importance, the extent to which different projection pathways of the striatum contribute to this information processing remains unclear. In this paper, Bruce et al. conducted a study using a range of causal and correlational techniques to investigate how these pathways collectively contribute to interval timing in mice. Their results were consistent with previous research, showing that the direct and indirect striatal pathways perform opposing roles in processing elapsed time. Based on their findings, the authors proposed a revised computational model in which two separate accumulators track evidence for elapsed time in opposing directions. These results have significant implications for understanding the neural mechanisms underlying cognitive impairment in neurological and psychiatric disorders, as disruptions in the balance between direct and indirect pathway activity are commonly observed in such conditions.

Strengths:

The authors employed a well-established approach to study interval timing and employed optogenetic tagging to observe the behavior of specific cell types in the striatum. Additionally, the authors utilized two complementary techniques to assess the impact of manipulating the activity of these pathways on behavior. Finally, the authors utilized their experimental findings to enhance the theoretical comprehension of interval timing using a computational model.

Weaknesses:

The behavioral task used in this study is best suited for investigating elapsed time perception, rather than interval timing. Timing bisection tasks are often employed to study interval timing in humans and animals. The main results from unit recording (opposing slopes of D1/D2 cell firing rate, as shown in Figure 3D) appear to be very sensitive to a couple of outlier cells, and the predictive power of ensemble recording seems to be only slightly above chance levels. In the optogenetic experiment, the laser was kept on for too long (18 seconds) at high power (12 mW). This has been shown to cause adverse effects on population activity (for example, through heating the tissue) that are not necessarily related to their function during the task epochs. Given the systemic delivery of pharmacological interventions, it is difficult to conclude that the effects are specific to the dorsomedial striatum. Future studies should use the local infusion of drugs into the dorsomedial striatum.

Reviewer #2 (Public Review):

Summary:

In this study, the authors find that the deletion of a sulfate transporter in yeast, Sul1, leads to the extension of replicative lifespan. They investigate mechanisms underlying this extension and claim that the effects on longevity can be separated from sulfate transport, and are instead linked to a previously proposed transceptor function of the Sul1 transporter. Through RNA sequencing analysis, the authors find that Sul1 loss triggers activation of several stress response pathways, and conclude that deletion of two pathways, autophagy or Msn2/4, partially prevents lifespan extension in cells lacking Sul1. Overall, while it is well-appreciated that activation of Msn2/4 or autophagy is beneficial for lifespan extension in yeast, the results of this study would add an important new mechanism by which this could achieved, through perceived sulfate starvation. However, as described below, several of the experiments utilized to support the authors' conclusion are not experimentally sound, and significant additional experimentation is required to support the authors' claims throughout the manuscript.

Strengths:

The major strength of the study is the robust RNA-seq data that identified differentially expressed genes in cells lacking Sul1. This facilitated the authors' focus on two of these pathways, autophagy and the Msn2/4 stress response pathway.

Weaknesses:

Several critical experimental flaws need to be addressed by the authors to more rigorously test their hypothesis.

(1) The lifespan assays throughout the manuscript contain inconsistencies in the mean lifespan of the wild-type strain, BY4741. For example, in Figure 1A, the lifespan of BY4741 is 24.3, and the extended lifespan of the sul1 mutant is 31. However, although all mutants tested in Figure 1B also have lifespans close to 30 cell divisions, the wild-type control is also at 30 divisions in those experiments as well. This is problematic, as it makes it impossible to conclude anything about the lifespan extension of various mutants with inconsistencies in the wild-type lifespan. Additionally, the mutants analyzed in 1B are what the authors use to claim that loss of the transporter does not extend lifespan through sulfate limitation, but instead through a signaling function. Thus, it remains unclear whether loss of sul1 extends lifespan at all, and if it does, whether this is separable from cellular sulfate levels.

(2) While the authors use mutants in Figure 1 that should have differential effects on sulfate levels in cells, the authors need to include experiments to measure sulfate levels in their various mutant cells to draw any conclusions about their data.

3) Similar to point 2, the authors focused their RNA sequencing analysis on the deletion of sul1 and did not include important RNA seq analysis of the specific Sul1 mutation or other mutants in Figure 1B that do not exhibit lifespan extension. The prediction is that they should not see the activation of stress response pathways in these mutants as they do not see lifespan extension, but this needs to be tested.

(4) While the RNA-seq data is robust in Figure 2 as well as the follow-up quantitative PCR and trehalose/glycogen assays in 2A-B, the follow-up imaging assays for Msn2/4 localization in Figure 2 are not robust and are difficult to interpret. The authors need to include more high-resolution imaging or at least a close-up of the cells in Figure 3C.

(5) The autophagy assays utilized in Figure 4 appear to all be done with a C-terminal GFP-tagged Atg8 protein. As C-terminal GFP is removed from Atg8 prior to conjugation to phosphatidylethanolamine, microscopy assays of this reporter cannot be utilized to report on autophagy activity or flux. Instead, the authors need to utilize N-terminally tagged Atg8, which they can monitor for vacuole uptake as an appropriate readout of autophagy levels. As it stands, the authors cannot draw any conclusions about autophagy activity in their studies.

Reviewer #1 (Public Review):

The manuscript by Long et al. focused on SUL1, a gene encoding a sulfate transporter with signaling roles in yeast. The authors claim that the deletion of SUL1, rather than SUL2 (encoding a similar transporter), extended yeast replicative lifespan independent of sulfate transport. They also show that SUL1 loss-of-function mutants display decreased PKA activity, indicated by stress-protective carbohydrate accumulation, relevant transcription factor relocalization (measured during aging in single cells), and changes in gene expression. Finally, they show that loss of SUL1 increases autophagy, which is consistent with the longer lifespan of these cells. Overall, this is an interesting paper, but additional work should strengthen several conclusions, especially for the role of sulfate transport. Specific points include the following:

- What prompted the authors to measure the RLS of sul1 mutants? Prior systematic surveys of RLS in the same strain background (which included the same sul1 deletion strain they used) did not report lifespan extension in sul1 cells (PMID: 26456335).

- Cells carrying a mutant Sul1 (E427Q), which was reported to be disrupted in sulfate transport, did not have a longer lifespan (Figure 1), leading them to conclude that "lifespan extension by SUL1 deletion is not caused by decreased sulfate uptake". They would need to measure sulfate uptake in the mutants they test to draw that conclusion firmly.

- Related to my previous point, another simple experiment would be to repeat the assays in Figure 1 with exogenous sulfur added to see if the lifespan extension is suppressed.

- There needs to be more information in the text or the methods about how they did the enrichment analysis in Figure 2B. P-values are typically insufficient, and adjusted FDR values are reported from standard gene ontology platforms (e.g., PANTHER).

- It is somewhat puzzling that relocalization of Msn2 was not seen in very old cells (past the 17th generation), but it was evident in younger cells. The authors could consider another possibility, that it was early and midlife experiences that made those cells live longer. Past that window, loss of Sul1 may have no impact on longevity. A conditional shutoff system to regulate SUL1 expression would be needed to test the above, albeit this is probably beyond the scope of this report.

- The connections between glucose restriction, autophagy, and sul1 (Figure 4) could be further tested by measuring the RLS of sul1 cells in glucose-restricted cells. If RLS is further extended by glucose restriction, then whatever effects they see should be independent of glucose restriction.

- They made and tested the double (sul1, msn2) mutants, but they should also test the sul1, msn4 combination since Msn4 functions similarly to Msn2.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Long et al. demonstrated that the deletion of SUL1, which encodes a sulfate transporter localized on the plasma membrane, extends the replicative lifespan in S. cerevisiae. The authors further investigated the mechanism underlying this lifespan extension. They found that, unlike sul1∆ mutants, other mutants that have been shown to have a deficiency in sulfate transport cannot extend lifespan, from which they concluded that it is unlikely that SUL1 deletion extends lifespan by impairing sulfate intake. The authors then performed a series of characterizations on sul1∆ mutants and found that consistent with previous studies, PKA activity is downregulated when SUL1 is deleted. The authors demonstrated that SUL1 deletion promotes the nuclear localization of Msn2, as well as autophagy, which are known downstream signals of the PKA pathway. In addition, the authors show that MSN2 and ATG8 are indispensable for the lifespan extension in sul1∆ cells. Altogether, this manuscript suggests that SUL1 deletion extends lifespan by affecting PKA activity.

Strengths:

This study reported an interesting phenotype that the deletion of SUL1, but not SUL2, promotes lifespan extension in budding yeast. The authors performed some characterizations on sul1∆ mutants and epistatic studies to demonstrate that this lifespan extension requires MSN2 and ATG8, which further support the importance of the PKA pathway in regulating lifespan.

Weaknesses:

However, one of the major findings in this paper that SUL1 deletion extends lifespan independently of its role in sulfate uptake was merely based on lifespan measurements on sul2∆, SUL1E427Q, and met3∆ mutants, which cannot exclude the possibility that yeast lifespan is affected by sulfate intake. In addition, the strength of evidence for whether SUL1 deletion extends lifespan through affecting PKA activity is incomplete. It has been shown that Sul1 and Sul2 have redundant functions in both sulfate transport and PKA activation (Kankipati et al. 2015). However, in this manuscript, as shown by the authors, the deletion of SUL2 does not extend the lifespan compared with sul1∆ mutants. Without a further characterization on why deletion of SUL1, but not SUL2, extends lifespan, it is likely that SUL1 deletion extends lifespan independently of either sulfate transport or PKA activation.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors discover that nuclear volume decreases after mitotic exit following cell confinement in a manner that scales with the extent of confinement. This adaptation appears to protect the cells from adverse outcomes of critical confinement such as nuclear blebs and DNA damage. The evidence to support these claims is strong.

The authors also provide a model in which argue that what they call the "apparent nuclear surface area" is modulated by confinement through a mechanism regulated by cPLA2 and myosin II activities. Here there are weaknesses in that the manuscript relies on a single approach, measurements are indirect, and alternative models are not explored. Similarly, additional considerations need to be addressed so that the reader can interpret the data presented - for example whether cell volume is also changing coincident with nuclear volume changes, and whether other aspects of cell physiology such as cytokinesis are altered.

Considerations that could support the manuscript further:

One essential consideration that goes unaddressed is whether the nuclear volume alone is changing under compression (resulting in a higher nuclear to cytoplasmic ratio) or if the cell volume is changing and the nuclear volume is following suit (no change in the N:C ratio). Depending on which of these is the case, the overall model would likely shift. In particular, interpreting the effect of disrupting myosin II activity given its different distribution at the cortex in response to the higher confinement would be influenced by which of these conditions are at play.

A key approach used and interpreted by the investigators is an assessment of the folding of the "inner lamin envelope", which they derive from an image analysis routine of lamin staining that they developed and argue reflects "nuclear envelope tension". I am not convinced of the robustness of this approach or what it mechanistically reveals. It may or may not reflect the contour of the inner nuclear membrane, which (perhaps) is the most relevant to the authors' interpretation of nuclear envelope tension. Given the major contribution of this data to the model, which is based on the "unfolding" of the nuclear envelope, an orthogonal approach (e.g. electron microscopy - which one needs to truly address the high-frequency undulations of the nuclear envelope) is needed to support the larger conclusions.

The authors argue that nuclear tension is lost after mitosis in the confined devices because nuclear volume has decreased. While a smaller nuclear volume might indeed translate to less compressive force from the device on the nucleus, one would imagine that the chromosomes still have to be accommodated and that confining them in a smaller volume could increase the tension. Although arguable, the potential alternative possibilities suggest that actual measurements of nuclear envelope tension are needed to robustly test the model. The authors cite the observation that blebs are less prevalent after mitosis as additional support for this model, but this is expected as nuclear envelope breakdown and reformation will "reset" the nuclear contour while the appearance of blebs at mitotic entry is essential a "memory" of all blebs and ruptures over the entire preceding cell cycle.

Representative images for the pharmacological perturbations other than blebbistatin are notably absent - only the analyzed data are presented in the manuscript or the supplemental material. How these perturbations (e.g. to cPLA2) also affect the cortex is important to interpret the data given the point raised above. Orthogonal approaches would also strengthen the conclusions (for example, the statement that "nuclear adaptation observed during mitosis requires nuclear tension sensing through cPLA2" requires more evidence to be convincing - it is not sufficiently supported by the data presented). Even if this is the case, the authors acknowledge that cPLA2 is likely not the answer to the adaption observed under the lower degrees of confinement. Thus, the mechanisms underlying the adaptive changes to nuclear volume remain enigmatic.

One more consideration that seems to go without comment is that the cells under confinement do not appear to successfully complete cytokinesis (Fig. 5b). At a minimum this seems like a major perturbation to cell physiology and needs to be more fully discussed by the authors as playing a role in the observed changes in nuclear volume.

Reviewer #1 (Public Review):

Summary<br /> In this work, Mouelhi et al investigated how the nucleus responds to long term confinement. They find that short-term confinement does not affect nuclear volume, whereas long-term confinement leads to a decrease in volume. The authors propose this decrease occurs after mitosis and relies on cPLA2 and myosin contractility.

Strengths

The ability to accurately control cell confinement allows authors to determine its effects on cellular function with high resolution. This provides a good addition to the existing collection of tools used for cellular micromanipulation. The results provided are relevant and timely and could help understand how cancer cells adapt to conditions of confinement.

Weaknesses

I have a few concerns which I believe should be addressed:

(1) It is unclear whether the authors took into consideration the contribution of nuclear blebs for nuclear volume measurements. This would be particularly relevant in situations of very strong confinement. Blebs were previously shown to affect volume (Mistriotis et al., JCB 2019). One could argue that the decreased nuclear volume was due to the increased blebbing observed in very strong confinements.

(2) From their experimental setup, it is unclear whether the reduced nuclear volume observed after confined cell division arises from a geometrical constraint or is due to an intrinsic nuclear feature. One could argue that cells exiting mitosis under confinement have clustered chromosomes and, therefore, will have decreased volume. This would imply that the nucleus is not "reset" but rather that a geometrical constraint is forcing nuclei to be smaller. One way to test this would be to follow individual cells under confinement, let them enter mitosis, and then release the confinement. If, under these conditions, the daughter nuclei are smaller, then it supports their model. If daughter nuclei recover to their initial value, then it´s simply due to a geometrical constraint that forces the clustering of chromosomes and the reassembly of the NE in a confined space.

(3) The authors claim that the nucleus adapts to confinement based on evidence that the nucleus no longer shrinks in the second division following the first division. I would argue no further decrease is possible because the DNA is already compacted in the smallest possible volume. If indeed nuclei are in a new homeostatic state as the authors claim, then one would expect nuclei to remain smaller even after confinement is removed. This analysis is missing.

(4) Also, if the authors want to claim that this is a mechanism used for cancer cells to adapt to confined situations as the title says, they need to show that normal, near-diploid cells do not behave in the same way. This analysis is missing.

(5) Authors state that "Loss of nuclear blebs is clearly linked to mitosis, suggesting that nuclear volume and nuclear envelope tension are tightly coupled, and supports the hypothesis that mitosis is a key regulator of nuclear envelope tension". I have a few issues with the way this sentence is written. Firstly, one could say that all nuclear structures (and not only blebs) are lost during mitosis because the nucleus disassembles. Hence, the new homeostatic state could be determined by envelope reassembly after mitosis and not mitosis itself. Secondly, I don´t understand why the loss of nuclear blebs suggests that volume and tension are tightly coupled. Thirdly, how can mitosis be a key regulator of nuclear envelope tension when the nucleus is disassembled during the process? These require clarification.

(6) The authors claim that, unlike previous studies (Lomakin et al), this work shows a "gradual nuclear adaptation". From their results, this is difficult to conclude simply because they do not analyse cPLA2 levels. This is solely based on indirect evidence obtained from cPLA2 inhibition. A gradual adaptation would mean that based on the level of confinement we would expect to have increasingly higher levels of cPLA2 (and therefore nuclear tension).

(7) The authors should refrain from saying that the mechanism behind DNA repair is coupled to the nuclear adaptation they show. There are several points regarding this statement. Firstly, increased DNA damage could be due to nuclear ruptures imposed by confinement at 2h. In fact, the authors show leakage of NLS from the nucleus after confinement (Figure S3A). Secondly, the decrease in DNA damage at 24h could be because these nuclei did not rupture. How can they ensure that cells with low DNA damage at 24h had increased DNA damage at 2h? Finally, one needs to confirm if the nuclei they are analysing at 24h did undergo a round of cell division previously. From the evidence provided, the authors cannot conclude that DNA damage regulation is occurring in confined cells. Moreover, cell cycle arrest is a known effect of DNA damage. Cells with high damage at 2h most likely are arrested or will present with increased mitotic errors (which the authors exclude from their analyses).

Reviewer #2 (Public Review):

Summary:

Extensive previous research has shown that cell confinement, e.g., vertical compression of cells to a height smaller than the height of the unconfined cells, results in the unfolding of nuclear membrane invaginations, calcium and membrane tension mediated recruitment of cPLA2 to the nuclear membrane (which triggers increased cortical myosin accumulation and activity, among other effects), nuclear blebbing, and DNA damage. However, the long-term effects of confinement, and how cells adapt to such confined conditions, have remained largely unexplored.

In this work, the authors use custom-built cell confinement devices that enable precise control of confinement for prolonged periods of time (up to several days), along with live cell and fixed cell imaging to compare short-term (2 hours) and long-term (24+ hours) effects of confinement on nuclear structure. The authors report that while vertical confinement results in a short-term increase in nuclear cross-sectional area, associated with an increase in nuclear surface area due to unfolding of nuclear envelope invaginations while maintaining nuclear volume, long-term confinement results in a decrease in nuclear volume, reduced cross-sectional area, and re-appearance of nuclear envelope invaginations. Using time-lapse imaging, the authors demonstrate that these effects are associated with a reduction in nuclear volume upon completion of the first mitosis under confinement. Pharmacological inhibition experiments indicate a requirement of cPLA2, calcium signaling, and actomyosin contractility in this process. Although it is not surprising that nuclear blebs disappear following mitosis, as the nuclear envelope breaks down at the onset of mitosis and subsequently reforms as the chromatin decondenses, the observed change in nuclear volume upon prolonged confinement is intriguing. Notably, the nuclear adaptation following prolonged confinement was also associated with a reduction in DNA damage when comparing cells at 2h and 24h of confinements, measured by the presence of gamma-H2AX foci in the nucleus. By fitting their experimental data of nuclear surface area measurements, the authors arrive at the conclusion that cells have an intrinsic nuclear envelope tension set-point and that completing mitosis enables cells to reset nuclear envelope tension to this set-point.

Strengths:

The use of an agarose confinement system with precise control over vertical confinement enables the authors to apply long-term confinement without depriving cells of nutrients while performing live cell imaging or immunofluorescence analysis following fixation. The live cell imaging is a powerful tool to assess the effect of confinement not only on nuclear morphology, but also on cell cycle progression (using the FUCCI fluorescent reporter) and to compare nuclear volume between mother and daughter cells. The data presented by the authors to demonstrate changes in nuclear volume and surface area are convincing and supported by several independent measurements. The model comparing total and apparent nuclear surface area nicely complements the experimental measurements and helps to make the point that cells have a nuclear envelope tension set-point, even though the authors were unable to directly measure nuclear envelope tension. The inhibitor experiments targeting cPLA2 (using AACOCF3), intracellular calcium (using BAPTA-Amand 2APB), and myosin contractility (using blebbistatin) identify key players in the underlying cellular mechanism.

Weaknesses:

Although the findings by the authors will be of interest to a broad community, several weaknesses limit the mechanistic insights gained from this study. One major limitation is that all experiments are performed in a single cell line, H-29 human colorectal cancer cells, which has an unusual nuclear envelope composition as it has no lamin B2, low lamin B1 levels, and contains a p53 mutation. Because lamins B1 and B2 play important functions in protecting the nuclear envelope from blebs and confinement-induced rupture, and p53 is crucial in the cellular DNA damage response, it remains unclear whether other cell lines exhibit similar adaptation behavior.

Furthermore, although the time-lapse experiments suggest that reduction in nuclear volume occurs primarily during mitosis, the authors do not address whether prolonged confinement, even in the absence of apoptosis, could also result in cells adjusting their nuclear volume, or alternatively normalizing nuclear envelope tension by recruiting additional membrane from the endoplasmic reticulum, which is continuous with the nuclear membranes.

Additionally, the molecular mechanisms underlying the observed loss in nuclear volume and the regulation of this process remain to be identified. The pharmacological studies implicate cPLA2, intracellular calcium, and actomyosin contractility in this process, but do not include validation to confirm the efficiency of the drug treatment or to rule out off-target effects. Regarding the proposed role of cPLA2, previous studies have shown that cPLA2 recruitment to the nuclear membrane, which is essential to mediate its nuclear mechanotransduction function, requires both an increase in nuclear membrane tension and intracellular calcium. However, the current study does not include any data showing the recruitment of cPLA2 to the nuclear membrane upon confinement, or the disappearance of nuclear membrane-associated cPLA2 during prolonged confinement, leaving unclear the precise function and dynamics of cPLA2 in the process.

Lastly, it remains unclear (1) whether the reduction in nuclear volume is caused by a reduction in nuclear water content, by chromatin compaction, e.g. associated with an increase in heterochromatin, or through other mechanisms, (2) whether the change in nuclear volume is reversible, and if so, how quickly, and (3) what functional consequences the substantial reduction in nuclear volume has on nuclear function, as one would expect that this reduction would be associated with a substantial increase in nuclear crowding, affecting numerous nuclear processes.

Reviewer #1 (Public Review):

Summary:

This is well-performed research with solid results and thorough control. The authors did a good job of finding the relationship between the 5-HT1A receptor and megakaryocytopoiesis, which demonstrated the potential of vilazodone in the management of thrombocytopenia. It emphasizes the regulatory mechanism of 5-HT1A receptor signaling on hematopoietic lineages, which could further advance the field of thrombocytopenia for therapeutic purposes.

Strengths:

This is a comprehensive and detailed research using multiple methods and model systems to determine the pharmacological effects and molecular mechanisms of vilazodone. The authors conducted in vitro experiments using HEL and Meg-01 cells and in vivo experiments using Zebrafish and Kunming-irradiated mice. The experiments and bioinformatics analysis have been performed with a high degree of technical proficiency. The authors demonstrated how vilazodone binds to 5-HTR1A and regulates the SRC/MAPK pathway, which is inhibited by particular 5-HTR1A inhibitors. The authors determined this to be the mechanistic underpinning for the effects of vilazodone in promoting megakaryocyte differentiation and thrombopoiesis.

Weaknesses:

(1) Which database are the drug test sets and training sets for the creation of drug screening models obtained from? What criteria are used to grade the results?<br /> (2) What is the base of each group in Figure 3b for the survival screening of zebrafish? The positivity rate of GFP-labeled platelets is too low, as indicated by the quantity of eGFP+ cells. What gating technique was used in Figure 3e?<br /> (3) In Figure 4C, the MPV values of each group of mice did not show significant downregulation or upregulation. Please explain the possible reasons.<br /> (4) The PPI diagram and the KEGG diagram in Figure 6 both provide a possible mechanism pathway for the anti-thrombocytopenia effect of vilazodone. How can the author analyze the differences in their results?<br /> (5) 5-HTR1A protein expression is measured only in the Meg-01 cells assay. Similar quantitation through western blot is not shown in other cell models.

Reviewer #2 (Public Review):

Summary:

The authors tried to understand the mechanism on how a drug candidate, VLZ, works on a receptor, 5-HTR1A, by activating the SRC/MAPK pathway to promote the formation of platelets.

Strengths:

The authors used both computational and experimental methods. This definitely saves time and funds to find a useful drug candidate and its therapeutic marker in the subfield of platelets reduction in cancer patients. The authors achieved the aim to explain the mechanism of VLZ on improving thrombocytopenia by using two cell lines and two animal models.

Weaknesses:

Only two cell lines, HEL and Meg-01 cells, were evaluated in this study. However, using more cell lines is really depending on the work flow and the grant situations of the current research team.

Reviewer #2 (Public Review):

Summary:

Bestry et al. investigated the effects of prenatal alcohol exposure (PAE) and high methyl donor diet (HMD) on offspring DNA methylation and behavioral outcomes using a mouse model that mimics common patterns of alcohol consumption in pregnancy in humans. The researchers employed whole-genome bisulfite sequencing (WGBS) for unbiased assessment of the epigenome in the newborn brain and liver, two organs affected by ethanol, to explore tissue-specific effects and to determine any "tissue-agnostic" effects that may have arisen prior to the germ-layer commitment during early gastrulation. The authors found that PAE induces measurable changes in offspring DNA methylation. DNA methylation changes induced by PAE coincide with non-coding regions, including enhancers and promoters, with the potential to regulate gene expression. Though the majority of the alcohol-sensitive differentially methylated regions (DMRs) were not conserved in humans, the ones that were conserved were associated with clinically relevant traits such as facial morphology, educational attainment, intelligence, autism, and schizophrenia Finally, the study provides evidence that maternal dietary support with methyl donors alleviates the effects of PAE on DNA methylation, suggesting a potential prenatal care option.

Strengths:

The strengths of the study include the use of a mouse model where confounding factors such as genetic background and diet can be well controlled. The study performed whole-genome bisulfite sequencing, which allows a comprehensive analysis of the effects of PAE on DNA methylation.

Weaknesses:

Transcriptome analysis to test if the identified DMRs indeed affect gene expression would help determine the potential function of the identified methylation changes.

Reviewer #1 (Public Review):

Summary:

This manuscript examined the impact of prenatal alcohol exposure on genome-wide DNA methylation in the brain and liver, comparing ethanol-exposed mice to unexposed controls. They also investigated whether a high-methyl diet (HMD) could prevent the DNA methylation alterations caused by alcohol. Using bisulfite sequencing (n=4 per group), they identified 78 alcohol-associated differentially methylated regions (DMRs) in the brain and 759 DMRs in the liver, of which 85% and 84% were mitigated by the HMD group, respectively. The authors further validated 7 DMRs in humans using previously published data from a Canadian cohort of children with FASD.

Overall, the findings from this study provide new insight into the impact of prenatal alcohol exposure, while also showing evidence for methyl-rich diets as an intervention to prevent the effects of alcohol on the epigenome. Some methodological concerns and confounders limit the robustness of these results, and should be addressed in future studies to further strengthen the conclusions of this study and its applicability to broader settings.

Strengths:

- The use of whole genome bisulfite sequencing allowed for the interrogation of the entire DNA methylome and DMR analysis, rather than a subset of CpGs.<br /> - The combination of data from animal models and humans allowed the authors to make stronger inferences regarding their findings<br /> - The authors investigated a potential mechanism (high methyl diet) to buffer against the effects of prenatal alcohol exposure, which increases the relevance and applicability of this research.

Weaknesses:

- The sample size was small for the epigenetic analyses, which limits the robustness of the findings.<br /> - The authors could not account for potential confounders in their analyses, including birthweight, alcohol levels, and sex. This is a particular problem for the high-methyl diet analyses, in which the alcohol-exposed mice consumed less alcohol than their non-diet counterparts.

Reviewer #2 (Public Review):

This work started with transcriptomic profiling of ductal cells to identify the upregulation of calcineurin in the zebrafish after beta-cell ablation. By suppressing calcineurin with its chemical inhibitor cyclosporin A and expressing a constitutively active form of calcineurin ubiquitously or specifically in ductal cells, the authors found that inhibited calcineurin activity promoted beta-cell regeneration transiently while ectopic calcineurin activity hindered beta-cell regeneration in the pancreatic tail. They also showed similar effects in the basal state but only when it was within a particular permissive window of Notch activity. To further investigate the roles of calcineurin in the ductal cells, the authors demonstrated that calcineurin inhibition additionally induced the proliferation of the ductal cells in the regenerative context or under a limited level of Notch activity. Interestingly, the enhanced proliferation was followed by a depletion of ductal cells, suggesting that calcineurin inhibition would exhaust the ductal cells. Based on the data, the authors proposed a very attractive and intriguing model of the role of calcineurin in maintaining the balance of the progenitor proliferation and the endocrine differentiation. However, the conclusions of this paper are only partially supported by the data as some evidence of the lineage between ductal cells and beta cells remains suggestive.

Reviewer #1 (Public Review):

Induction of beta cell regeneration is a promising approach for the treatment of diabetes. In this study, Massoz et.al., identified calcineurin (CaN) as a new potential modulator of beta cell regeneration by using zebrafish as model. They also showed that calcineurin (CaN) works together with Notch signaling to promote the beta cell regeneration. Overall, the paper is well organized, and technically sound. However, some evidences seem weak to get the conclusion.

Reviewer #1 (Public Review):

Summary:

In this manuscript the authors have applied an asymmetric split mNeonGreen2 (mNG2) system to human iPSCs. By integrating a constitutively expressed long fragment of mNG2 at the AAVS1 locus, this allows other proteins to be tagged through the use of available ssODN donors. This removes the need to generate long AAV donors for tagging, thus greatly facilitating high-throughput tagging efforts. The authors then demonstrate the feasibility of the method by successfully tagging 9 markers expressed in iPSC at various, and one expressed upon endoderm differentiation. Several additional differentiation markers were also successfully tagged but not subsequently tested for expression/visibility. As one might expect for high-throughput tagging, a few proteins, while successfully tagged at the genomic level, failed to be visible. Finally, to demonstrate the utility of the tagged cells, the authors isolated clones with genes relevant to cytokinesis tagged, and together with an AI to enhance signal to noise ratios, monitored their localization over cell division.

Strengths

Reviewer Comment: Characterization of the mNG2 tagged parental iPSC line was well and carefully done including validation of a single integration, the presence of markers for continued pluripotency, selected off-target analysis and G-banding-based structural rearrangement detection.<br /> The ability to tag proteins with simple ssODNs in iPSC capable of multi-lineage differentiation will undoubtedly be useful for localization tracking and reporter line generation.<br /> Validation of clone genotypes was carefully performed and highlights the continued need for caution with regards to editing outcomes.

Weaknesses

Reviewer Comment: IF and flow cytometry figures lack quantification and information on replication. How consistent is the brightness and localization of the markers? How representative are the specific images? Stability is mentioned in the text but data on the stability of expression/brightness is not shown.

Author Response: To address this comment, we have quantified the mean fluorescence intensity of the tagged cell populations in Fig. S3B-T. This data correlates well with the expected expression levels of each gene relative to the others (Fig. S3A), apart from CDH1 and RACGAP1, which are described in the discussion.

Reviewer Reply: Great, thanks.

Reviewer Comment: The localization of markers, while consistent with expectations, is not validated by a second technique such as antibody staining, and in many cases not even with Hoechst to show nuclear vs cytoplasmic.

Author Response: We find that the localization of each protein is distinct and consistent with previous studies. To address this comment, we have added an overlay of the green fluorescence images with brightfield images to better show the location of the tagged protein relative to the nuclei and cytoplasm. We have also added references to other studies that showed the same localization patterns for these proteins in iPSCs and other relevant cell lines.

Reviewer Reply: There was no question that the localization fit with expectations, however, this still doesn't show that in the same cell the tag is in the same spot. It would have been fairly simple to do for at least a handful of markers, image, fix and stain to demonstrate unequivocally the tag and protein are co-localized. Of course, this isn't damning by any means, it just would have been nice.

Reviewer Comment: For the multi-germ layer differentiation validation, NCAM is also expressed by ectoderm, so isn't a good solo marker for mesoderm as it was used. Indeed, the kit used for the differentiation suggests Brachyury combined with either NCAM or CXCR4, not NCAM alone.

Author Response: Since Brachyury is the most common mesodermal marker, we first tested differentiation using anti-Brachyury antibodies, but they did not work well for flow cytometry. We then switched to anti-NCAM antibodies. Since we used a kit for directed differentiation of iPSCs into the mesodermal lineage, NCAM staining should still report for successful differentiation. In the context of mixed differentiation experiments (embryoid body formation or teratoma assay), NCAM would not differentiate between ectoderm and mesoderm. The parental cells (201B7) have also been edited at the AAVS1 locus in multiple other studies, with no effect on their differentiation potential.

Reviewer Reply: This is placing a lot of trust in the kit that it only makes what it says it makes. It could have been measured by options other than flow such as qPCR, Western blot, or imaging, but fine.

Reviewer Comment: Only a single female parental line has been generated and characterized. It would have been useful to have several lines and both male and female to allow sex differences to be explored.

Author Response: We agree that it would be interesting (and important) to study differences in protein localization between female and male cell types, and from different individuals with different genetic backgrounds. We see our tool as opening a door for cell biology to move away from randomly collected, transformed, differentiated cell types to more directed comparative studies of distinct normal cell types. Since few studies of cell biological processes have been done in normal cells, a first step is to understand how processes compare in an isogenic background, then future studies can reveal how they compare with other individuals and sexes. We hope that either our group or others will continue to build similar lines so that these studies can be done.

Reviewer Reply: Fair enough.

Reviewer Comment: The AI-based signal to noise enhancement needs more details and testing. Such models can introduce strong assumptions and thus artefacts into the resolved data. Was the model trained on all markers or were multiple models trained on a single marker each? For example, if trained to enhance a single marker (or co-localized group of markers), it could introduce artefacts where it forces signal localization to those areas even for others. What happens if you feed in images with scrambled pixel locations, does it still say the structures are where the training data says they should be? What about markers with different localization from the training set. If you feed those in, does it force them to the location expected by the training data or does it retain their differential true localization and simply enhance the signal?

Author Response: The image restoration neural network was used as in Weigert et al., 2018. The model was trained independently for each marker. Each trained model was used only on the corresponding marker and with the same imaging conditions as the training images. From visual inspection, the fluorescent signal in the restored images was consistent with the signal in the raw images, both for interphase and mitotic cells. We found very few artefacts of the restoration (small bright or dark areas) that were discarded. We did not try to restore scrambled images or images of mismatched markers.

Reviewer Reply: I understand. What I'm saying is that for the restoration technique to be useful you need to know that it won't introduce artefacts if you have an unexpected localization. Think of it this way, if you already know the localization, then there's no point measuring it. If you don't, or there's a possibility that it is somewhere unexpected, then you need to know with confidence that your algorithm will be able to accurately detect that unexpected localization. As such, it would be extremely important to validate that your restoration algorithm will not bias the results to the expected localization if the true localization is unexpected/not seen in the training dataset. It would have been extremely trivial to run this analysis and I do not feel this comment has been in any way adequately addressed.

Reviewer #2 (Public Review):

Summary:

The authors have generated human iPSC cells constitutively expressing the mNG21-10 and tested them by endogenous tagging multiple genes with mNG211 (several tagged iPS cell lines clones were isolated). With this tool they have explored several weakly expressed cytokinesis genes gained insights into how cytokinesis occurs.

Strengths:

(i) Human iPSC cells are used

Weaknesses:

(i) The manuscript is extremely incremental, no improvements are present in the split-Fluorescent (split-FP) protein variant used nor in the approach for endogenous tagging with split-FPs (both of them are already very well established and used in literature as well as in different cell types).

(ii) The fluorescence intensity of the split mNeonGreen appears rather low, for example in Figure 2C the H2BC11, ANLN, SOX2 and TUBB3 signals are very noisy (differences between the structures observed are almost absent). For low expression targets this is an important limitation. This is also stated by the authors but image restoration could not be the best solution since a lot of biologically relevant information will be lost anyway.

(iii) there is no comparison with other existing split-FP variants, methods, or imaging and it is unclear what the advantages of the system are.

Reviewer #3 (Public Review):

The authors report on the engineering of an induced Pluripotent Stem Cell (iPSC) line that harbours a single copy of a split mNeonGreen, mNG2(1-10). This cell line is subsequently used to take endogenous protein with a smaller part of mNeonGreen, mNG2(11), enabling complementation of mNG into a fluorescent protein that is then used to visualize the protein. The parental cell is validated and used to construct several iPSC line with endogenously tagged proteins. These are used to visualize and quantify endogenous protein localisation during mitosis.

I see the advantage of tagging endogenous loci with small fragments, but the complementation strategy has disadvantages that deserve some attention. One potential issue is the level of the mNG2(1-10). In addition, this may probably not work for organelle-resident proteins, where the mNG2(11) tag is localised in a membrane enclosed compartment.

Overall the tools and resources reported in this paper will be valuable for the community that aims to study proteins at endogenous levels.

Reviewer #1 (Public Review):

Summary:

This study offers a comprehensive examination of the early postnatal development of the patch and matrix compartments within the striatum. These are segregated circuits within the striatum circuits with distinct embryonic origins and functional roles in mature brain physiology. Despite the recognized significance of these circuits, a comprehensive understanding of their postnatal maturation remains elusive.

Strengths:

The authors undertake a thorough investigation, characterizing the intrinsic properties of direct pathway spiny projection neurons (dSPNs) and indirect pathway spiny projection neurons (iSPNs) across both matrix and striosome compartments throughout development. The authors identify the regulatory role of M1 receptors in modulating spontaneous activity in SPNs, and demonstrate the impact of chemogenetic inhibition of MOR-positive neurons during development on GABAergic synapses in substantia nigra pars compacta (SNc) dopamine (DA) neurons. These findings significantly advance our understanding of striatal development and function.

Weaknesses:

Certain methodological considerations warrant attention. Notably, the reliance on TdTomato expression for the identification of striosomes raises concerns, particularly regarding the substantial difference in slice thickness between the immunohistochemistry (IHC) images (50um) shown in Figure 2 and those utilized for whole-cell recordings (300um).

Enhanced clarification regarding the identification of cell patches is possible in the electrophysiology rig conditions. Using a widefield microscope rather than a confocal would strengthen the reliability of this methodology.

In the Ca2+ imaging experiments of Figure 2, striosomes were defined as the regions of brighter GCaMP fluorescence. This presents a potential limitation because it presupposes higher activity levels within patch cells, which is what the experiment is designed to test. Based on this criteria, neurons of this region will necessarily have more activity than in others.

There is also no information on how Ca2+ imaging traces were analyzed. In the examples provided, putative matrix neurons seem to exhibit different Ca2+ dynamics compared to striosome neurons. The plateau responses might reflect even higher activity than the transient signals observed in striosome neurons. It'll be important to know how the data was quantified. For example, calculations of F0 based on rolling functions tend to underestimate dF/F in traces like this. Calculations of the area under the curve can also provide valuable information in these cases.

There is no description of the 8mM KCl treatment in the methods. Was this only used for the Ca2+ imaging experiments? The percentage of active cells in Figures 2C-D is similar to or lower than that described in Figure 2B, which is confusing. Were recordings always performed in 8mM KCl?

Lastly, while the findings of Figure 6 suggest a deficit in striosomal inputs to SNc DA neurons, they do not conclusively demonstrate this point (DA neurons receive many sources of inhibition, and local interneurons in SNc are highly plastic). Given the availability of Opmr1-Cre mice and the utilization of multiple viruses in Figure 6 experiments, the inclusion of experiments employing ChR2 to directly assess striatal/striosome inputs would substantially strengthen this claim. This is the main claim stated in the manuscript title, so it is important to provide evidence of specific striatonigral deficits.

Reviewer #2 (Public Review):

Summary:

The manuscript by Kokinovic et al. presents evidence that a significant portion of striatal projection neurons (SPNs) are spontaneously active early in development. This spontaneous activity (as measured in ex vivo brain slices) is due to intrinsic mechanisms, and subsides over the course of the first few postnatal weeks in a cell-type specific way: striosome direct and indirect pathway SPNs (dSPNs and iSPNs, respectively) remain spontaneously active until postnatal days 10-14, by which time matrix dSPNs and iSPNs have become entirely silent. The authors suggest that this early spontaneous activity may be in part due to M1 muscarinic receptor signaling. Through chemogenetic inhibition of striosome SPNs (of which dSPNs target dopaminergic neurons of the SNc), the authors present evidence that critical postnatal windows of SPN activity shape the strength of GABAergic innervation of the SNc (measured in adults). This study provides a useful and solid characterization of the functional, postnatal compartmental development of the striatum. However, some weaknesses in the experimental design should be addressed before definitively concluding that postnatal striosome SPN activity determines its functional innervation of dopaminergic SNc neurons.

Specific Comments:

(1) While certainly interesting and possibly true, evidence for the necessity of early striosome dSPN activity in shaping their functional innervation of dopaminergic SNc neurons is not entirely convincing. The functional measure of GABAergic innervation of dopamine neurons is inferred from mIPSCs. As the authors state, dopaminergic neurons have numerous other sources of GABAergic inputs in addition to striosome dSPNs. So while manipulating striosome activity may ultimately alter the overall GABAergic innervation of SNc dopamine neurons, the specificity of this to striosome dSPN inputs is not known. Optogenetic stimulation of striosome->SNc neurons after chemogenetic silencing would help support the authors' interpretation. Related to this point, while striatonigral projections form embryonically, is there evidence that striosome->SNc synapses are indeed functional by P6-14 when CNO is delivered?

(2) One big caveat that needs to be addressed is that all measures of early postnatal spontaneous SPN activity were performed in ex vivo slices. Are SPNs active (in pathway/compartmental specific ways) in vivo during this time? If it is unknown, is there other evidence (e.g. immediate early gene expression, etc...) that may suggest this is indeed the case in vivo?

(3) It appears that 8mM KCl (external) was only used while measuring spontaneous calcium oscillations, not spontaneous spiking (Figure 2). Was there any evidence of spontaneous calcium activity in the lower KCl concentration (3mM?) used for cell-attached recordings? One caveat is that experiments demonstrating that SPNs fire spontaneously in the presence of AMPA receptor blockers (Figure S1) were presumably performed in 3mM KCl. Does elevated KCl increases spontaneous EPSPs during the ages examined? If so, are the calcium oscillations shown in Figure 2 synaptically driven or intrinsically generated? Somewhat related, speculation on why M1 receptor blockade reduces calcium oscillations but not spontaneous spikes in striosome dSPNs would be useful.

(4) Several statements in the introduction could use references.

Reviewer #3 (Public Review):

Summary:

Kokinovic et al. presents an interesting paper that addresses an important gap in knowledge about the differences in the development of direct and indirect pathway striatal neurons in the striosome and matrix compartments. The division of the striatum into 4 distinct populations, striosome-dSPNs, striosome-iSPNs, matrix-dSPNs, and matrix-iSPNs is important, but rarely done. This study records all four populations across early development and shows differences in action potential characteristics and intrinsic properties. They also suppress striosome activity during postnatal development and evaluate the characteristics of adult dopaminergic neurons in control and previously striosome-quieted conditions.

Strengths:

The striatal electrophysiology is beautifully and carefully done and shows important developmental differences between neural subtypes.

The idea to test the striatonigral connection is a good idea.

Weaknesses:

The authors didn't actually test the striatonigral connection. The experiments they do instead don't convincingly show that the striosomal or even striatal connection to the dopaminergic neurons is altered after postnatal striosome suppression.

Major concerns:

(1) mIPSCs are measured and are reduced after chemogenetic suppression of striosomal neurons during development. This is an interesting finding, but these mIPSCs could be coming from any inhibitory input onto the SNc neurons. It is unlikely that most of the mIPSCs are coming from the striosomal inputs. The GPe is much more likely to be the source of these mIPSCs than the striatum because the GPe inputs form synapses nearer the soma and have a higher probability of release (Evans et al., 2020). dSPNs inhibit GPe neurons through a non-canonical pathway (Cui et al., 2021; Spix et al., 2021) and striosomes also inhibit the SNr (McGregor et al., 2019). The striatum has the potential to disinhibit SNc neurons through both the SNr or the GPe (Evans, 2022), and modification of the striosome-SNr or striosome-GPe connections during development could be what is causing the mIPSC changes. To claim that the striosome-SNc connection is altered, a direct test of this connection is necessary.

(2) The dopaminergic neurons recorded seem to be randomly selected, but the striosomes do not inhibit all SNc dopamine neurons. They selectively inhibit the ventral tier SNc neurons (Evans et al., 2020). In the present manuscript, it is impossible to know which subpopulation of SNc neurons was recorded, so it is impossible to tell whether the dopaminergic neurons recorded are the ones expected to receive striosomal input.

(3) Very similarly, the striosomes selectively wrap around the "SNr dendrite" of SNc neurons that participate in striosome-dendron bouquets (Crittenden et al., 2016). However, not all SNc neurons have prominent SNr dendrites (Henny et al., 2012). In the morphological images of Supplemental Figure 3, it looks like the recorded cells sometimes have an SNr dendrite and sometimes don't (but it is hard to tell because the medial-lateral rostral-caudal axis is not labeled in the images). The presence or absence of the "SNr dendrite" is a strong determinant of whether an individual dopaminergic neuron receives striosomal inhibition or not (Evans et al., 2020). As above, not knowing whether the neurons recorded have SNr dendrites makes it impossible to know whether they should be receiving striosomal input at all.

(4) It's quite interesting that the dendron-bouquet structure is intact even after striosomal activity suppression, as cannabinoid receptor knockout greatly disrupts the structural integrity of bouquets (Crittenden et al., 2022). However, going along with point 3, the gephyrin puncta analysis only at the somas is very limiting. The striosome-SNc relevant puncta would be primarily on the SNr dendrite. Gephyrin density on the SNr dendrites or in bouquets would be much more informative than density on the soma.

(5) The authors claim that "CNO didn't affect the shape of the DA neuron dendritic tree", but more information about the morphological analysis should be added. It is not clear how the sholl analysis was conducted or whether a full 3D reconstruction was made. This claim seems to be based on only one dendritic measurement (sholl analysis), but many other dendritic or morphological features could be altered.

Crittenden, J.R., Tillberg, P.W., Riad, M.H., Shima, Y., Gerfen, C.R., Curry, J., Housman, D.E., Nelson, S.B., Boyden, E.S., & Graybiel, A.M. (2016) Striosome-dendron bouquets highlight a unique striatonigral circuit targeting dopamine-containing neurons. Proc. Natl. Acad. Sci. U.S.A., 113, 11318-11323.<br /> Crittenden, J.R., Yoshida, T., Venu, S., Mahar, A., & Graybiel, A.M. (2022) Cannabinoid Receptor 1 Is Required for Neurodevelopment of Striosome-Dendron Bouquets. eNeuro, 9, ENEURO.0318-21.2022.<br /> Cui, Q., Du, X., Chang, I.Y.M., Pamukcu, A., Lilascharoen, V., Berceau, B.L., García, D., Hong, D., Chon, U., Narayanan, A., Kim, Y., Lim, B.K., & Chan, C.S. (2021) Striatal Direct Pathway Targets Npas1+ Pallidal Neurons. J Neurosci, 41, 3966-3987.<br /> Evans, R.C. (2022) Dendritic involvement in inhibition and disinhibition of vulnerable dopaminergic neurons in healthy and pathological conditions. Neurobiol Dis, 172, 105815.<br /> Evans, R.C., Twedell, E.L., Zhu, M., Ascencio, J., Zhang, R., & Khaliq, Z.M. (2020) Functional Dissection of Basal Ganglia Inhibitory Inputs onto Substantia Nigra Dopaminergic Neurons. Cell Rep, 32, 108156.<br /> Henny, P., Brown, M.T.C., Northrop, A., Faunes, M., Ungless, M.A., Magill, P.J., & Bolam, J.P. (2012) Structural correlates of heterogeneous in vivo activity of midbrain dopaminergic neurons. Nat. Neurosci., 15, 613-619.<br /> McGregor, M.M., McKinsey, G.L., Girasole, A.E., Bair-Marshall, C.J., Rubenstein, J.L.R., & Nelson, A.B. (2019) Functionally Distinct Connectivity of Developmentally Targeted Striosome Neurons. Cell Rep, 29, 1419-1428.e5.<br /> Spix, T.A., Nanivadekar, S., Toong, N., Kaplow, I.M., Isett, B.R., Goksen, Y., Pfenning, A.R., & Gittis, A.H. (2021) Population-specific neuromodulation prolongs therapeutic benefits of deep brain stimulation. Science, 374, 201-206.

Reviewer #1 (Public Review):

Summary:

The authors seek to elucidate the structural role of N-glycosylation at the N343 position of the SARS-CoV-2 Spike protein's Receptor Binding Domain (RBD) and its evolution across different variants of concern (VoCs). Specifically, they aim to understand the impact of this glycosylation on the RBD's stability and function, which could have implications for the virus's infectivity and, eventually, the effectiveness of vaccines.

Strengths:

The major strength of the study stems from the molecular-level picture emerging from the use of over 45 μs of cumulative molecular dynamics (MD) simulations, including both conventional and enhanced sampling schemes, which provide detailed insights into the structural role of N343 glycosylation. The combination of these simulations with experimental assays, such as electron-spray ionization mass spectrometry (ESI-MS) for affinity measurements, bolsters the reliability of the findings. At the same time, one potential weakness is the inherent limitation of the current computational models to fully capture the complexities of in vivo systems. While the authors acknowledge the difficulty in completely gauging the N343 glycosylation's impact on RBD folding due to the dynamic nature of glycan structures, their computational/experimental approach lends support to their claims.

Weaknesses:

One potential weakness is the inherent limitation of computational models to fully capture the complexities of in vivo systems. While the authors acknowledge the difficulty in completely gauging the N343 glycosylation's impact on RBD folding due to the dynamic nature of glycan structures, their multi-faceted approach lends solid support to their claims.

Other Comments:

The study shows that N343 glycosylation plays a structural role in stabilizing the RBD across various SARS-CoV-2 strains. The removal of this glycan led to conformational changes that could affect the virus's infectivity. The results correlate with a reported reduction in viral infectivity upon deletion of glycosylation sites, supporting the authors' conclusion that N343 glycosylation is functionally essential for viral infection.

By providing molecular insights into the spike protein's architectural changes, the work could influence the design of more effective vaccines and therapeutic agents. The data and methods used could serve as a valuable resource for researchers looking into viral evolution, protein-glycan interactions, and the development of glycan-based interventions.

Reviewer #2 (Public Review):

The authors sought to establish the role played by N343 glycosylation on the SARS-CoV-2 S receptor binding domain structure and binding affinity to the human host receptor ACE2 across several variants of concern. The work includes both computational analysis in the form of molecular dynamics simulations and experimental binding assays between the RBD and ganglioside receptors.

The work extensively samples the conformational space of the RBD beginning with atomic coordinates representing both the bound and unbound states and computes molecular dynamics trajectories until equilibrium is achieved with and without removing N343 glycosylation. Through comparison of these simulated structures, the authors are able to demonstrate that N343 glycosylation stabilizes the RBD. Prior work had demonstrated that glycosylation at this site plays an important role in shielding the RBD core and in this work, the authors demonstrate that removal of this glycan can trigger a conformational change to reduce water access to the core without it. This response is variant-dependent and variants containing interface substitutions that increase RBD stability, including Delta substitution L452R, do not experience the same conformational change when the glycan is removed. The authors also explore structures corresponding to Alpha and Beta in which no structure-reinforcing substitutions were identified and two Omicron variants in which other substitutions with an analogous effect to L452R are present.

The authors experimentally assessed these inferred structural changes by measuring the binding affinity of the RBD for the oligosaccharides of the mono-sialylated gangliosides GM1os and GM2os with and without the glycan at N343. While GM1os and GM2os binding is influenced by additional factors in the Beta and Omicron variants, the comparison between Delta and Wuhan-hu-1 is clear: removal of the glycan abrogated binding for Wuhan-hu-1 and minimally affected Delta as predicted by structural simulations.

In summary, these findings suggest, in the words of the authors, that SARS-CoV-2 has evolved to render the N-glycosylation site at N343 "structurally dispensable". This study emphasizes how glycosylation impacts both viral immune evasion and structural stability which may in turn impact receptor binding affinity and infectivity. Mutations that stabilize the antigen may relax the structural constraints on glycosylation opening up avenues for subsequent mutations that remove glycans and improve immune evasion. This interplay between immune evasion and receptor stability may support complex epistatic interactions which may in turn substantially expand the predicted mutational repertoire of the virus relative to expectations that do not take into account glycosylation.

Reviewer #3 (Public Review):

Summary:

The receptor binding domain of SARS-Cov-2 spike protein contains two N-glycans which have been conserved by the variants observed in these last 4 years. Through the use of extensive molecular dynamics, the authors demonstrate that even if glycosylation is conserved, the stabilization role of glycans at N343 differs among the strains. They also investigate the effect of this glycosylation on the binding of RBD towards sialylated gangliosides, as a function of evolution.

Strengths:

The molecular dynamics characterization is well performed and demonstrates differences in the effect of glycosylation as a factor of evolution. The binding of different strains to human gangliosides shows variations of strong interest. Analyzing the structure function of glycans on SARS-Cov-2 surface as a function of evolution is important for the surveillance of novel variants since it can influence their virulence.

Weaknesses:

The article is difficult to read, with no sufficient efforts of clarification for non-glycobiology audiences. The presentation of previous knowledge about RBD glycosylation and its effect on structure is very difficult to follow and should be reorganized. The choice of the nature of the biantennary glycan at N343 is not rationalized. A major weakness is the absence of data supporting the proposed binding site for ganglioside.

Reviewer #1 (Public Review):

Summary:

This is an interesting and potentially important paper, which however has some deficiencies.

Strengths:

A significant amount of potentially useful data.

Weaknesses:

One issue is a confusion of thermal stability with solubility. While thermal stability of a protein is a thermodynamic parameter that can be described by the Gibbs-Helmholtz equation, which relates the free energy difference between the folded and unfolded states as a function of temperature, as well as the entropy of unfolding. What is actually measured in PISA is a change in protein solubility, which is an empirical parameter affected by a great many variables, including the presence and concentration of other ambient proteins and other molecules. One might possibly argue that in TPP, where one measures the melting temperature change ∆Tm, thermal stability plays a decisive or at least an important role, but no such assertion can be made in PISA analysis that measures the solubility shift.

Another important issue is that the authors claim to have discovered for the first time a number of effects well described in prior literature, sometimes a decade ago. For instance, they marvel at the differences between the solubility changes observed in lysate versus intact cells, while this difference has been investigated in a number of prior studies. No reference to these studies is given during the relevant discussion.

The validity of statistical analysis raises concern. In fact, no calculation of statistical power is provided. As only two replicates were used in most cases, the statistical power must have been pretty limited. Also, there seems to be an absence of the multiple-hypothesis correction.

Also, the authors forgot that whatever results PISA produces, even at high statistical significance, represent just a prediction that needs to be validated by orthogonal means. In the absolute majority of cases such validation is missing.

Finally, to be a community-useful resource the paper needs to provide the dataset with a user interface so that the users can data-mine on their own.

Reviewer #2 (Public Review):

Summary:

Using K562 (Leukemia) cells as an experimental model, Van Vracken et. al. use Thermal Proteome Profiling (TPP) to investigate changes in protein stability after exposing either live cells or crude cell lysates to a library of anti-cancer drugs. This was a large-scale and highly ambitious study, involving thousands of hours of mass spectrometry instrument time. The authors used an innovative combination of TPP together with Proteome Integral Solubility Alternation (PISA) assays to reduce the amount of instrument time needed, without compromising on the amount of data obtained.

The paper is very well written, the relevance of this work is immediately apparent, and the results are well-explained and easy to follow even for a non-expert. The figures are well-presented. The methods appear to be explained in sufficient detail to allow others to reproduce the work.

Strengths:

Using CDK4/6 inhibitors, the authors observe strong changes in protein stability upon exposure to the drug. This is expected and shows their methodology is robust. Further, it adds confidence when the authors report changes in protein stability for drugs whose targets are not well-known. Many of the drugs used in this study - even those whose protein targets are already known - display numerous off-target effects. Although many of these are not rigorously followed up in this current study, the authors rightly highlight this point as a focus for future work.

Weaknesses:

While the off-target effects of several drugs could've been more rigorously investigated, it is clear the authors have already put a tremendous amount of time and effort into this study. The authors have made their entire dataset available to the scientific community - this will be a valuable resource to others working in the fields of cancer biology/drug discovery.

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 the 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 that 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 the 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 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 the 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 data for PIK3CB and p38α inhibitors (Figures 2B-C). They have thus likely missed many small, but biologically 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 the 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 likely have low nM IC50s, this concentration will often be multiple 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.

The authors claim that combining cell-based and lysate-based assays increases coverage (Figure 3F) is not supported by their data. The '% targets' presented in Figure 3F have a different denominator for each bar. As it stands, all 49 targets quantified in both assays which have a significant change in thermal stability may be significant in the cell-based assay. If so, the apparent increase in % targets when combining reflects only the subsetting of the data. To alleviate this lack of clarity, the authors could update Figure 3F so that all three bars present the % targets figure for just the 60 compounds present in both assays.

Aims achieved, impact and utility:

The authors have achieved their main aim of presenting a workflow that 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.

Joint Public Review:

Summary:

Brauns et al. work to decipher the respective contribution of active versus passive contributions to cell shape changes during germ band elongation. Using a novel quantification tool of local tension, their results suggest that epithelial convergent extension results from internal forces.

Strengths:

The approach developed here, tension isogonal decomposition, is original and the authors made the demonstration that we can extract comprehensive data on tissue mechanics from this type of analysis.

They present an elegant diagram that quantifies how active and passive forces interact to drive cell intercalations.

The model qualitatively recapitulates the features of passive and active intercalation for a T1 event.

Regions of high isogonal strains are consistent with the proximity of known active regions.

They define a parameter (the LTC parameter) which encompasses the geometry of the tension triangles and allows the authors to define a criterium for T1s to occur.

The data are clearly presented, going from cellular scale to tissue scale, and integrating modeling approach to complement the thoughtful description of tension patterns.

Weaknesses:

The modeling is interesting, with the integration of tension through tension triangulation around vertices and thus integrating force inference directly in the vertex model. However, the authors are not using it to test their hypothesis and support their analysis at the tissue level. Thus, although interesting, the analysis at the tissue level stays mainly descriptive.

Major points:

(1) The authors mention that from their analysis, they can predict what is the tension threshold required for intercalations in different conditions and predict that in Snail and Twist mutants the T1 tension threshold would be around √2. Since movies of these mutants are most probably available, it would be nice to confirm these predictions.

(2) While the formalism is very elegant and convincing, and also convincingly allows making sense of the data presented in the paper, it is not all that clear whether the claims are compatible with previous experimental observations. In particular, it has been reported in different papers (including Collinet et al NCB 2015, Clement et al Curr Biol 2017) that affecting the initial Myosin polarity or the rate of T1s does not affect tissue-scale convergent extension. Analysis/discussion of the Tor phenotype (no extension with myosin anisotropy) and the Eve/Runt phenotype (extension without Myosin anisotropy), which seem in contradiction with an extension mostly driven by myosin anisotropy.

Reviewer #1 (Public Review):

This is an interesting study investigating the mechanisms underlying membrane targeting of the NLRP3 inflammasome and reporting a key role for the palmitoylation-depalmitoylation cycle of cys130 in NRLP3. The authors identify ZDHHC3 and APT2 as the specific ZDHHC and APT/ABHD enzymes that are responsible for the s-acylation and de-acylation of NLRP3, respectively. They show that the levels of ZDHHC3 and APT2, both localized at the Golgi, control the level of palmitoylation of NLRP3. The S-acylation-mediated membrane targeting of NLRP3 cooperates with polybasic domain (PBD)-mediated PI4P-binding to target NLRP3 to the TGN under steady-state conditions and to the disassembled TGN induced by the NLRP3 activator nigericin.

However, the study has several weaknesses in its current form as outlined below.

(1) The novelty of the findings concerning cys130 palmitoylation in NLRP3 is unfortunately compromised by recent reports on the acylation of different cysteines in NLRP3 (PMID: 38092000), including palmitoylation of the very same cys130 in NLRP3 (Yu et al https://doi.org/10.1101/2023.11.07.566005), which was shown to be relevant for NLRP3 activation in cell and animal models. What remains novel and intriguing is the finding that NLRP3 activators induce an imbalance in the acylation-deacylation cycle by segregating NLRP3 in late Golgi/endosomes from de-acylating enzymes confined in the Golgi. The interesting hypothesis put forward by the authors is that the increased palmitoylation of cys130 would finally contribute to the activation of NLRP3. However, the authors should clarify the trafficking pathway of acylated-NLRP3. This pathway should, in principle, coincide with that of TGN46 which constitutively recycles from the TGN to the plasma membrane and is trapped in endosomes upon treatment with nigericin.

(2) To affect the S-acylation, the authors used 16 hrs treatment with 2-bromopalmitate (2-BP). In Figure 1f, it is quite clear that NLRP3 in 2-BP treated cells completely redistributed in spots dispersed throughout the cells upon nigericin treatment. What is the Golgi like in those cells? In other words, does 2-BP alter/affect Golgi morphology? What about PI4P levels after 2-BP treatment? These are important missing pieces of data since both the localization of many proteins and the activity of one key PI4K in the Golgi (i.e. PI4KIIalpha) are regulated by palmitoylation.

(3) The authors argue that the spots observed with NLRP-GFP result from non-specific effects mediated by the addition of the GFP tag to the NLRP3 protein. However, puncta are visible upon nigericin treatment, as a hallmark of endosomal activation. How do the authors reconcile these data? Along the same lines, the NLRP3-C130S mutant behaves similarly to wt NLRP3 upon 2-BP treatment (Figure 1h). Are those NLRP3-C130S puncta positive for endosomal markers? Are they still positive for TGN46? Are they positive for PI4P?

(4) The authors expressed the minimal NLRP3 region to identify the domain required for NLRP3 Golgi localization. These experiments were performed in control cells. It might be informative to perform the same experiments upon nigericin treatment to investigate the ability of NLRP3 to recognize activating signals. It has been reported that PI4P increases on Golgi and endosomes upon NG treatment. Hence, all the differences between the domains may be lost or preserved. In parallel, also the timing of such recruitment upon nigericin treatment (early or late event) may be informative for the dynamics of the process and of the contribution of the single protein domains.

(5) As noted above for the chemical inhibitors (1) the authors should check the impact of altering the balance between acyl transferase and de-acylases on the Golgi organization and PI4P levels. What is the effect of overexpressing PATs on Golgi functions?

Reviewer #2 (Public Review):

Summary:

This paper examines the recruitment of the inflammasome seeding pattern recognition receptor NLRP3 to the Golgi. Previously, electrostatic interactions between the polybasic region of NLRP3 and negatively charged lipids were implicated in membrane association. The current study reports that reversible S-acylation of the conserved Cys-130 residue, in conjunction with upstream hydrophobic residues plus the polybasic region, act together to promote Golgi localization of NLRP3, although additional parts of the protein are needed for full Golgi localization. Treatment with the bacterial ionophore nigericin inhibits membrane traffic and prevents Golgi-associated thioesterases from removing the acyl chain, causing NLRP3 to become immobilized at the Golgi. This mechanism is put forth as an explanation for how NLRP3 is activated in response to nigericin.

Strengths:

The experiments are generally well presented. It seems likely that Cys-130 does indeed play a previously unappreciated role in the membrane association of NLRP3.

Weaknesses:

The interpretations about the effects of nigericin are less convincing. Specific comments follow.

(1) The experiments of Figure 4 bring into question whether Cys-130 is S-acylated. For Cys-130, S-acylation was seen only upon expression of a severely truncated piece of the protein in conjunction with overexpression of ZDHHC3. How do the authors reconcile this result with the rest of the story?

(2) Nigericin seems to cause fragmentation and vesiculation of the Golgi. That effect complicates the interpretations. For example, the FRAP experiment of Figure 5 is problematic because the authors neglected to show that the FRAP recovery kinetics of non-acylated resident Golgi proteins are unaffected by nigericin. Similarly, the colocalization analysis in Figure 6 is less than persuasive when considering that nigericin significantly alters Golgi structure and could indirectly affect colocalization.

Reviewer #1 (Public Review):

Summary:

The authors aim to address a critical challenge in the field of bioinformatics: the accurate and efficient identification of protein binding sites from sequences. Their work seeks to overcome the limitations of current methods, which largely depend on multiple sequence alignments or experimental protein structures, by introducing GPSite, a multi-task network designed to predict binding residues of various molecules on proteins using ESMFold.

Strengths:

(1) Benchmarking. The authors provide a comprehensive benchmark against multiple methods, showcasing the performances of a large number of methods in various scenarios.

(2) Accessibility and Ease of Use. GPSite is highlighted as a freely accessible tool with user-friendly features on their website, enhancing its potential for widespread adoption in the research community.

Weaknesses:

(1) Lack of significant insights. The paper reproduces results and analyses already presented in previous literature, without providing significant novel analysis or interpretation. However, they show a novel method with an original approach.

The work is useful for the field, especially in disease mechanism elucidation and novel drug design. The availability of genome-scale binding residue annotations GPSite offers is a significant advancement.

Reviewer #2 (Public Review):

Summary:

This work provides a new framework, "GPsite" to predict DNA, RNA, peptide, protein, ATP, HEM, and metal ions binding sites on proteins. This framework comes with a webserver and a database of annotations. The core of the model is a Geometric featurizer neural network that predicts the binding sites of a protein. One major contribution of the authors is the fact that they feed this neural network with predicted structure from ESMFold for training and prediction (instead of native structure in similar works) and a high-quality protein Language Model representation. The other major contribution is that it provides the public with a new light framework to predict protein-ligand interactions for a broad range of ligands. It is a convincing outcome of previous efforts to Geometric Deep Learning approaches to model protein-ligand interactions. The authors have demonstrated the interest of their framework with comprehensive ablation studies and benchmarks.

Strengths:

- The performance of this framework as well as the provided dataset and web server make it useful to conduct studies.<br /> - The ablations of some core elements of the method, such as the protein Language Model part, the use of multiple ligands in the same model, the input structure, or the use of predicted structure to complement native structure are very insightful. They can help convince the reader that every part of the framework is necessary. This could also guide further developments in the field. As such, the presentation of this part of the work holds a critical place in this work.

Weaknesses:

- The authors made an important effort to compare their work to other similar frameworks. Yet, the lack of homogeneity of training methods and data from one work to the other makes the comparison slightly unconvincing, as the authors pointed out. Ablations performed by the authors were able to compensate for this general weakness, as well as the focus on several example structures.

Reviewer #3 (Public Review):

Summary

The authors of this work aim to address the challenge of accurately and efficiently identifying protein binding sites from sequences. They recognize that the limitations of current methods, including reliance on multiple sequence alignments or experimental protein structure, and the under-explored geometry of the structure, which limit the performance and genome-scale applications. The authors have developed a multi-task network, GPSite, that predicts binding residues for a range of biologically relevant molecules, including DNA, RNA, peptides, proteins, ATP, HEM, and metal ions, using sequence embeddings from protein language models and ESMFold-predicted structures. The reported results showed to be superior to current sequence-based and structure-based methods in terms of accuracy and efficiency.

Strengths<br /> (1) The GPSite model's ability to predict binding sites for a wide variety of molecules, including DNA, RNA, peptides, and various metal ions.<br /> (2) Based on the presented results, GPSite outperforms state-of-the-art methods in several benchmark datasets in terms of accuracy and efficiency.<br /> (3) GPSite adopts predicted structure instead of native structures as input, enabling the model to be applied to a wider range of scenarios where native structures are rare.<br /> (4) The low computational cost of GPSite is beneficial, which enables rapid genome-scale binding residue annotations, indicating the model's potential for large-scale downstream applications and discoveries.

Weaknesses

There are no major weaknesses after the revision.

Joint Public Review:

In this manuscript, Xue and colleagues investigate the fundamental aspects of cellular fate decisions and differentiation, focusing on the dynamic behaviour of gene regulatory networks. It explores the debate between static (noise-driven) and dynamic (signal-driven) perspectives within Waddington's epigenetic landscape, highlighting the essential role of gene regulatory networks in this process. The authors propose an integrated analysis of fate-decision modes and gene regulatory networks, using the Cross-Inhibition with Self-activation (CIS) network as a model. Through mathematical modelling, they differentiate two logic modes and their effect on cell fate decisions: requires both the presence of an activator and absence of a repressor (AA configuration) with one where transcription occurs as long the repressor is not the only species on the promoter (OO configuration).

The authors establish a relationship between noise profiles, logic-motifs, and fate-decision modes, showing that defining any two of these properties allows the inference of the third. They also identify, under the signal-driven mode, two fundamental patterns of cell fate decisions: either prioritising progression or accuracy in the differentiation process. The authors apply this analysis to available high-throughput datasets of cell fate decisions in hematopoiesis and embryogenesis, proposing the underlying driving force in each case and utilising the observed noise patterns to nominate key regulators.

The paper significantly advances our understanding of gene regulatory networks through a well-described computational study, where the authors rigorously evaluate assumptions in modelling. Particularly commendable is their introduction of the concept of combinatorial logic, exemplified by the double 'and' and double 'or' (AA/OO) logic motifs, which they successfully map to previously described cell fate decision processes. This theoretical and computational exploration sheds light on the dynamic landscape of epigenetic cell fate decisions, emphasising the role of combinatorial logic in coordinating noise and signal-driven processes. The thorough comparison of two model configurations underscores the importance of integration logic, contributing to a clearer understanding of gene regulatory network dynamics. Importantly, the results of the simulations are presented clearly, enhancing accessibility and intuitive understanding. The paper's strength also lies in its predictive power, as the authors use simulations to make insightful predictions about the regulatory organisation of stem cell differentiation systems. While the exploration is restricted to specific scenarios, these limitations serve to highlight areas for future research rather than detract from the paper's strengths.

While the paper presents an intriguing framework for understanding gene regulatory networks and cell fate decisions, there are some weaknesses that warrant attention. Firstly, the framework would benefit from validation with more experimental data and application to diverse systems beyond those explored in the study, such as de-differentiation in adult tissues and regeneration processes. Additionally, while the authors successfully make predictions about the regulatory organisation of stem cell differentiation systems, there is a lack of discussion regarding how perturbations in the regulatory network could affect cell fate decisions. Furthermore, the paper could be strengthened by addressing the effects of mutations and other perturbations that may significantly influence cell fate decision-making processes, thus enhancing the robustness of the findings. Finally, there are instances where the clarity of the writing could be improved to enhance understanding and accessibility for readers.

Reviewer #1 (Public Review):

Summary:

The research study under review investigated the relationship between the gut and identified potential biomarkers derived from the nasopharyngeal and gut microbiota-based that could aid in predicting COVID-19 severity. The study reported significant changes in the richness and Shannon diversity index in nasopharyngeal microbiome associated with severe symptoms. The study showed a high abundance of Bacillota and Pesudomonadota in patients exhibiting severe symptomatology. Positive correlations were also found between Corynebacterium, Acinetobacter, Staphylococcus, and Veillonella, with the severity of SARS-CoV-2 infection.

Strengths:

The study successfully identified differences in the microbiome diversity that could indicate or predict disease severity. Furthermore, the authors demonstrated a link between individual nasopharyngeal organisms and the severity of SARS-CoV-2 infection. The density of the nasopharyngeal organism was shown to be a potential predictor of the severity of COVID-19.

Weaknesses:

The authors claimed an association between nasopharyngeal organisms and severity of SARS-CoV-2 infection but omitted essential data on the statistical significance of these associations between groups. The authors frequently referred to a p-value < 0.05 without presenting the actual p-values and percentages to show the significance of their results. The discussion is hard to understand (lacked clarity), as it contained an extensive literature review without discussing the study findings. A more focused discussion and results section on the main findings could have improved the overall readability of the paper. The role of potential confounders, such as HIV infection, and ethnicity which impacts the nasopharyngeal microbiome composition, was not included in the paper. Addressing the potential confounders would contribute to a more comprehensive understanding of the study's implications, specifically the role of the nasopharyngeal microbiome as a predictor of COVID-19 severity.

Reviewer #2 (Public Review):

The study conducted by Benita et al studied the gut and nasopharyngeal microbiome in covid-19 severity. There are a lot of studies on this topic, and this study therefore cannot stand out from a pool of such similar studies. Beyond that, I have a number of major concerns:

(1) The sample size is limited. There were 3 cohorts, but only ~100 subjects in total. This indicates that there were only a small number of subjects in each cohort (the authors did not list this information), and beyond that, there was a lack of healthy individuals as controls. A cohort-specific effect should usually exist, I believe with such a small number of patients (they were further divided into 3 groups), the authors cannot find reproducible data between cohorts.

(2) The study did not meet the study goal. The authors say "Many factors have been described to be correlated with its severity but no specific determinants of infection outcome have been identified yet". However, numerous studies have shown the relationship between microbiome and covid. The present study only again showed a correlation between microbiome and covid severity and did not provide further insights, nor did they find specific determinants.

(3) This study only studied 16s-seq for microbiome profiling, which made this study lack depth and resolution. Many peer papers have used metagenomics sequencing for in-depth interrogation.

(4) Since there are fecal and nasopharyngeal microbiome data, the authors only listed their respective associations with covid severity yet did not provide further insights into whether and how these two microbiome types are linked to covid, or into whether there is a microbiome priority, resistance or transmission.

(5) The abstract is amiss where each sentence lacks a key message - I don't understand each of the sentences or the underlying meanings. One example of an unclear expression is "this ratio" - what ratio?

(6) The figures are all unclear and need significant improvement

Reviewer #3 (Public Review):

Summary:

How the microbial composition of the human body is influenced by and influences disease progression is an important topic. For people with COVID-19, symptomatic progression and deterioration can be difficult to predict. This manuscript attempts to associate the nasal and fecal microbiomes of COVID-19 patients with the severity of disease symptoms, with the goal of identifying microbial markers that can predict disease outcomes. However, the value of this work is held back by unclear methods and data presentation.

Strengths:

Analysis of microbiomes from two distinct anatomical locations and across three distinct patient groups is a substantial undertaking. How these microbiomes influence and are influenced by COVID-19 disease progression is an important question. In particular, the putative biomarker identified here could be of clinical value with additional research.

Weaknesses:

The methods and statistics used for several figures and comparisons are unclear or used in non-standard ways. For instance: the description of the Bray-Curtis test for Figure 1 is inaccurate and conflicts between the text and figure legend; the method used to compare the relative abundance of genera in Figure 2 is not clear; and it is not stated how the "total amount" of detected bacteria is inferred from the data presented in Figures 2C and 2D.

The description of results for Figure 1 is overstated or unclear for both the alpha diversity among disease groups and the overlap for nasal samples.

The most abundant phyla from nasal samples cumulatively account for less than 1% of abundance and it is unclear why this would be expected or how it compares to other work. Relatedly, the potential biological relevance of the very small proportional changes among phyla in the nasal samples is also not clear.

There is no real discussion of how the identified biomarkers might work in practice. While some microbes are detected in one condition but not others, it is unclear whether these organisms are expected to already exist below the detection threshold and then increase in abundance along with disease severity, or if they are picked up from the environment. For instance, would the presence of these 'severe' - associated microbes in patients with mild or moderate disease justify additional treatment to prevent disease progression?

The authors use the term "nasopharyngeal-faecal axis", but there is no substantial discussion of how these two microbiomes interact to influence disease progression, or how they are jointly affected to yield useful biomarkers. With one exception, correlation values between nasal and fecal microbes range from negligible to modest. It is unclear, then, how much parallel influence disease has on these microbiomes.

Joint Public Review:

This study investigates the role of Ikaros, a zinc finger family transcription factor related to Helios and Eos, in T-regulatory (Treg) cell functionality in mice. Through genome-wide association studies and chromatin accessibility studies, the authors find that Ikaros shares similar binding sites to Foxp3. Ikaros cooperates with Foxp3 to establish a major portion of the Treg epigenome and transcriptome. Ikaros-deficient Treg exhibits Th1-like gene expression with abnormal expression of IL-2, IFNg, TNFa, and factors involved in Wnt and Notch signalling. Further, two models of inflammatory/ autoimmune diseases - Inflammatory Bowel Disease (IBD) and organ transplantation - are employed to examine the functional role of Ikaros in Treg-mediated immune suppression. The authors provide a detailed analysis of the epigenome and transcriptome of Ikaros-deficient Treg cells.

These studies establish Ikaros as a factor required in Treg for tolerance and the control of inflammatory immune responses. The data are of high quality. Overall, the study is well organized, and reports new data consolidating mechanistic aspects of Foxp3 mediated gene expression program in Treg cells.

Strengths:

The authors have performed biochemical studies focusing on mechanistic aspects of molecular functions of the Foxp3-mediated gene expression program and complemented these with functional experiments using two models of autoimmune diseases, thereby strengthening the study. The studies are comprehensive at both the cellular and molecular levels. The manuscript is well organized and presents a plethora of data regarding the transcriptomic landscape of these cells.

Weakness:

The findings of markedly increased percentages of activated conventional T cells (CD44hi), major increases in TFH cells, and elevated serum Ig levels indicate disrupted immune homeostasis even in the absence of overt autoimmune manifestations seen in histopathology. Thus, some of the observed genetic changes observed by the authors are likely Treg cell extrinsic. Further, clear conclusions from the genome-wide studies are lacking.

Reviewer #1 (Public Review):

The manuscript describes the development of a mouse model that co-expresses a fluorescent protein ZsGreen) marker in gene fusion with the FSHR gene.

The authors are correct in that there is a lack of reliable antibodies against many of the GPCR family members. The approach is novel and interesting, with the potential to help understand the expression pattern of gonadotropin receptors. There has been a very long debate about the expression of gonadotropin receptors in other tissues other than gonads. While their expression of the FSHR in some of those tissues has been detected by a variety of methods, their physiological, or pathophysiological, function(s) remain elusive.

The authors in this manuscript assume that the expression of ZsGren and the FSHR are equal. While this is correct genetically (transcription->translation) it does not go hand in hand with other posttranslational processes.

(1) One of the shocking observations in this manuscript is the expression of FSHR in Leydig cells. Other observations are in the osteoblasts and endothelial cells as well as epithelial cells in different organs. The expression of ZsGreen in these tissues seems high and one shall start questioning if there are other mechanisms at play here.

First, the turnover of fluorescent proteins is long, longer than 48h, which means that they accumulate at a different speed than the endogenous FSHR This means that ZsGreen will accumulate in time while the FSHR receptor might be degraded almost immediately. This correlated with mRNA expression (by the authors) but does not with the results of other studies in single-cell sequencing (see below).

The expression of ZsGreen in Leydig cells seems much higher than in Sertoli cells, this is "disturbing" to put it mildly. This is visible in both the ZsGreen expression and the FISH assay (Figure 2 B-D).

(2) The expression in WAT and BAT is also questionable as the expression of ZsGreen is high everywhere. That makes it difficult to believe that the images are truly informative. For example, the stainings of aorta show the ZsGreen expression where elastin and collagen fibres are - these are not "cells" and therefore are not expressing ZsGreen.

(3) FISH expression (for FSHR) in WT mice is missing.

Also, the tissue sections were stained with the IgG only (neg control) but in practice both the KI and the WT tissues should be stained with the primary and secondary antibodies. The only control that I could think of to truly get a sense of this would be a tagged receptor (N-terminal) that could then be analysed by immunohistochemistry.

(4) The authors also claim:<br /> To functionally prove the presence of FSHR in osteoblasts/osteocytes, we also deleted FSHR in osteocytes using an inducible model. The conditional knockout of FSHR triggered a much more profound increase in bone mass and decrease in fat mass than blockade by FSHR antibodies (unpublished data).

This would be a good control for all their images. I think it is necessary to make the large claim of extragonadal expression, as well as intragonadal such as Leydig cells.

(5) Claiming that the under-developed Leydig cells in FSHR KO animals are due to a direct effect of the FSHR, and not via a cross-talk between Sertoli and Leydig cells, is too much of a claim. It might be speculated to some degree but as written at the moment it suggests this is "proven".

(6) We also do not know if this FSHR expressed is a spliced form that would also result in the expression of ZsGreen but in a non-functional FSHR, or whether the FSHR is immediately degraded after expression. The insertion of the ZsGreen might have disturbed the epigenetics, transcription, or biosynthesis of the mRNA regulation.

(7) The authors should go through single-cell data of WT mice to show the existence of the FSHR transcript(s).<br /> For example here:<br /> https://www.nature.com/articles/sdata2018192

Reviewer #2 (Public Review):

The authors developed an original knock-in reporter mice line expressing ZSGreen under the control of endogenous FSHR promoter. The existence of FSHR in various extra-gonadal tissues and the physio-pathological consequences indeed remains a debated question and could potentially have an important impact on many high-incidence diseases occurring in menopausal women. Unfortunately, the provided data set lacks crucial controls and therefore does not provide a robust/convincing answer to the above-mentioned question.

Summary:<br /> The authors investigated the expression pattern of the FSHR in the gonads, where its expression has been demonstrated for decades, but also in many extra-gonadal tissues. The question is important since the expression of FSHR outside of the gonads has been increasingly reported and associated with the dramatic increase of circulating FSH after menopause, and has been suggested to play an important role in the advent of multiple diseases occurring with high incidence in post-menopausal women. However, the reality of such extra-gonadal expression of FSHR remains debated, mainly because this receptor is expressed at a low level and because the specificity/affinity of the available anti-FSHR antibodies is questionable.

Strengths:<br /> The development of reporter mice expressing ZsGreen fluorescent protein under the control of endogenous FSHR promoter is an original and potentially powerful approach to tackle the problem.

Weaknesses:<br /> The data provided are provocative since the FSHR seems to be expressed in all tested tissues. In the testis, for instance, the authors report very high levels of FSHR in interstitial cells and germ cells. In the ovary, there seems to be no difference in FSHR expression between granulosa cells and the other cell types. These findings alone contradict all the knowledge on FSH expression patterns in the gonads that have been accumulated over decades by many independent labs. In view of such results, the validity of the reporter mice line should be questioned thoroughly:

(1) Is the FSHR expression pattern affected by the knockin mice (no side-by-side comparison between wt and GSGreen mice, using in situ hybridization and ddRTPCR, at least in the gonads, is provided)?

(2) Is the splicing pattern of the FSHR affected in the knockin compared to wt mice, at least in the gonads?

(3) Are there any additional off-target insertions of GSGreen in these mice?

(4) Are similar results observed in separate founder mice?

(5) How long is GSGreen half-life? Could a very long half-life be a major reason for the extremely large expression pattern observed?

In the absence of answers to these questions, the data produced in extra-gonadal tissues using the same reporter mice, are not convincing and do not support the authors' claims.

Reviewer #1 (Public Review):

As a pathogen, S. aureus has evolved strategies to evade the host's immune system. It effectively remains 'under the radar' in the host until it reaches high population densities, at which point it triggers virulence mechanisms, enabling it to spread within the host. The agr quorum sensing system is central to this process, as it coordinates the pathogen's virulence in response to its cell density.

In this study, Podkowik and colleagues suggest that cells activating agr signaling also benefit from protection against H2O2 stress, whereas inactivation of agr increases cell death. The underlying cause of this lack of protection is tied to an ATP deficit in the agr mutant, leading to increased glucose consumption and NADH production, ultimately resulting in a redox imbalance. In response to this imbalance, the agr mutant increases respiration, resulting in the endogenous production of ROS which synergizes with H2O2 to mediate killing of the agr mutant. Suppressing respiration in the agr mutant restored protection against H2O2 stress.

Additionally, the authors establish that agr-dependent protection against oxidative stress is also linked to RNAIII activation, and the subsequent block of Rot translation. However, the specific protective genes regulated by Rot remain unidentified. Thus, according to the evidence provided, agr triggers intrinsic mechanisms that not only decrease harmful ROS production within the cell but also alleviate its detrimental effects.

Interestingly, these protective mechanisms are long-lived, and guard the cells against external oxidative stressors such as H2O2, even after the agr system has been 'turned off' in the population.

Reviewer #2 (Public Review):

In their study, Podkowik et al. elucidate the protective role of the accessory gene regulator (agr) system in Staphylococcus aureus against hydrogen peroxide (H2O2) stress. Their findings demonstrate that agr safeguards the bacterium by controlling the accumulation of reactive oxygen species (ROS), independent of agr activation kinetics. This protection is facilitated through a regulatory interaction between RNAIII and Rot, impacting virulence factor production and metabolism, thereby influencing ROS levels. Notably, the study highlights the remarkable adaptive capabilities of S. aureus conferred by agr. The protective effects of agr extend beyond the peak of agr transcription at high cell density, persisting even during the early log-phase. This indicates the significance of agr-mediated protection throughout the infection process. The absence of agr has profound consequences, as observed by the upregulation of respiration and fermentation genes, leading to increased ROS generation and subsequent cellular demise. Interestingly, the study also reveals divergent effects of agr deficiency on susceptibility to hydrogen peroxide compared to ciprofloxacin. While agr deficiency heightens vulnerability to H2O2, it also upregulates the expression of bsaA, countering the endogenous ROS induced by ciprofloxacin. These findings underscore the complex and context-dependent nature of agr-mediated protection. Furthermore, in vivo investigations using murine models provide valuable insights into the importance of agr in promoting S. aureus fitness, particularly in the context of neutrophil-mediated clearance, with notable emphasis on the pulmonary milieu. Overall, this study significantly advances our understanding of agr-mediated protection in S. aureus and sheds light on the sophisticated adaptive mechanisms employed by the bacterium to fortify itself against oxidative stress encountered during infection.

The conclusions drawn in this paper are generally well-supported by the data.

Reviewer #1 (Public Review):

Summary:

Del Rosario et al characterized the extent and cell types of sibling chimerism in marmosets. To do so, they took advantage of the thousands of SNPs that are transcribed in single-nucleus RNA-seq (snRNA-seq) data to identify the sibling genotype of origin for all sequenced cells across 4 tissues (blood, liver, kidney, and brain) from many marmosets. They found that chimerism is prevalent and widespread across tissues in marmosets, which has previously been shown. However, their snRNA-seq approach allowed them to identify precisely which cells were of sibling origin, and which were not. In doing so they definitively show that sibling chimerism across tissues is limited to cells of myeloid and lymphoid lineages. The authors then focus on a large sample of microglia sequenced across many brain regions to quantify: (1) variation in chimerism across brain regions in the same individual, and (2) the relative importance of genetic vs. environmental context on microglia function/identity.

(1) Much like across different tissues in the same individual, they found that the proportion of chimeric microglia varies across brain regions collected from the same individuals (as well as differing from the proportion of sibling cells found in the blood of the same animals), suggesting that cells from different genetic backgrounds may differ in their recruitment and/or proliferation across regions and local tissue contexts, or that this may be linked to stochastic bottleneck effects during brain development.

(2) Their (admittedly smaller sample size) analyses of host-sibling gene expression showed that the local environment dominates genotype.

All told, this thoughtful and thorough manuscript accomplishes two important goals. First, it all but closes a previously open question on the extent and cell origins of sibling chimerism. Second, it sets the stage for using this unique model system to examine, in a natural context, how genetic variation in microglia may impact brain development, function, and disease.

The conclusions of this paper are well supported by the data, and the authors exert appropriate care when extrapolating their results that come from smaller samples. However, there are a few concerns that should be addressed.

The "modest correlation" mentioned in lines 170-172 does not take into account the uncertainty in estimates of each chimeric cell proportion (although the plot shows those estimates nicely). This is particularly important for the macrophages, which are far less abundant. Perhaps a more appropriate way to model this would be in a binomial framework (with a random effect for individuals of origin). Here, you could model the sibling identity of each macrophage as a function of the proportion of sibling-origin microglia and then directly estimate the percent variance explained.

A similar (albeit more complicated because of the number of regions being compared) approach could be applied to more rigorously quantify the variation in chimerism across brain regions (L198-215; Figure 4). This would also help to answer the question of whether specific brain regions are more "amenable" to microglia chimerism than others.

While the sample size is small, it would be exciting to see if any microglia eQTL are driven by sibling chimerism across the marmosets.

L290-292: The authors should propose ways in which they could test the two different explanations proposed in this paragraph. For instance, a simulation-based modeling approach could potentially differentiate more stochastic bottleneck effects from recruitment-like effects.

While intriguing, the gene expression comparison (Figure 5) is extremely underpowered. It would be helpful to clarify this and note the statistical thresholds used for identifying DEGs (the black points in the figure).

Reviewer #2 (Public Review):

Summary:

This manuscript reports a novel and quite important study of chimerism among common marmosets. As the authors discuss, it has been known for years that marmosets display chimerism across a number of tissues. However, as the authors also recognize, the scope and details of this chimerism have been controversial. Some prior publications have suggested that the chimerism only involves cells derived from hematopoietic stem cells, while other publications have suggested more cell types can also be chimeric, including a wide range of cell types present in multiple organs. The present authors address this question and several other important issues by using snRNA-seq to track the expression of host and sibling-derived mRNAs across multiple tissues and cell types. The results are clear and provide strong evidence that all chimeric cells are derived from hematopoietic cell lineages.

This work will have an impact on studies using marmosets to investigate various biological questions but will have the biggest impact on neuroscience and studies of cellular function within the brain. The demonstration that microglia and macrophages from different siblings from a single pregnancy, with different genomes expressing different transcriptomes, are commonly present within specific brain structures of a single individual opens a number of new opportunities to study microglia and macrophage function as well as interactions between microglia, macrophages, and other cell types.

Strengths:

The paper has a number of important strengths. This analysis employs the first unambiguous approach providing a clear answer to the question of whether sibling-derived chimeric cells arise only from hematopoietic lineages or from a wider array of embryonic sources. That is a long-standing open question and these snRNA-seq data seem to provide a clear answer, at least for the brain, liver, and kidney. In addition, the present authors investigate quantitative variation in chimeric cell proportions across several dimensions, comparing the proportion of chimeric cells across individual marmosets, across organs within an individual, and across brain regions within an individual. All these are significant questions, and the answers have important implications for multiple research areas. Marmosets are increasingly being used for a range of neuroscience studies, and a better understanding of the process that leads to the chimerism of microglia and macrophages in the marmoset brain is a valuable and timely contribution. But this work also has implications for other lines of study. Third, the snRNA-seq data will be made available through the Brain Initiative NeMO portal and the software used to quantify host vs. sibling cell proportions in different biosamples will be available through GitHub.

Weaknesses:

I find no major weaknesses, but several minor ones. First, the main text of the manuscript provides no information about the specific animals used in this study, other than sex. Some basic information about the sources of animals and their ages at the time of study would be useful within the main paper, even though more information will be available in the supplementary material. Second, it is not clear why only 14 pairs of animals were used for estimating the correlation of chimerism levels in microglia and macrophages. Is this lower than the total number of pairwise comparisons possible in order to avoid using non-independent samples? Some explanation would be helpful. Finally, I think more analysis of the consistency and variability of gene expression in microglia across different regions of the brain would be valuable. Are there genetic pathways expressed similarly in host and sibling microglia, regardless of region of the brain? Are there pathways that are consistently expressed differently in host vs sibling microglia regardless of brain region?

Reviewer #1 (Public Review):

Summary:<br /> The study presented by Atsumi et al. is about using smartphone-driven, community-sourced data to enhance biodiversity monitoring. The idea is to leverage the widespread use of smartphones to gather data from the community quickly, contributing to a more comprehensive understanding of biodiversity. The authors discuss the importance of ecosystem services linked to biodiversity and the threats posed by human activities. It emphasizes the need for comprehensive biodiversity data to implement the Kunming-Montreal Global Biodiversity Framework. The 'Biome' mobile app, launched in Japan, uses species identification algorithms and gamification to gather over 6 million observations since 2019. While community-sourced data may have biases, incorporating it into Species Distribution Models (SDMs) improves accuracy, especially for endangered species. The app covers urban-natural gradients uniformly, enhancing traditional survey data biased towards natural areas. Combining these sources provides valuable insights into species distributions for conservation, protected area designation, and ecosystem service assessment.

Strengths:

The use of a smartphone app ('Biome') for community-driven species occurrence data collection represents an innovative and inclusive approach to biodiversity monitoring, leveraging the widespread use of smartphones. The app has successfully accumulated a large volume of species occurrence data since its launch in 2019, showcasing its effectiveness in rapidly gathering information from diverse locations. Despite challenges with certain taxa, the study highlights high species identification accuracy, especially for birds, reptiles, mammals, and amphibians, making the 'Biome' app a reliable tool for species observation. The integration of community-sourced data into Species Distribution Models (SDMs) improves the accuracy of predicting species distributions. This has implications for conservation planning, including the designation of protected areas and assessment of ecosystem services. The rapid accumulation of data and advancements in machine learning methods open up opportunities for conducting time-series analyses, contributing to the understanding of ecosystem stability and interaction strength over time. The study emphasizes the collaborative nature of the platform, fostering collaboration among diverse stakeholders, including local communities, private companies, and government agencies. This inclusive approach is essential for effective biodiversity assessment and decision-making. The platform's engagement with various stakeholders, including local communities, supports biodiversity assessment, management planning, and informed decision-making. Additionally, the app's role in fostering nature-positive awareness in society is highlighted as a significant contribution to creating a sustainable society.

Weaknesses:

While the studies make significant contributions to biodiversity monitoring, they also have some weaknesses. Firstly, relying on smartphone-driven, community-sourced data may introduce spatial and taxonomic biases. The 'Biome' app, for example, showed lower accuracy for certain taxa like seed plants, molluscs, and fishes, potentially impacting the reliability of the gathered data. Furthermore, the effectiveness of Species Distribution Models (SDMs) relies on the assumption that biases in community-sourced data can be adequately accounted for. The unique distribution patterns of the 'Biome' data, covering urban-natural gradients uniformly, might not fully represent the diversity of certain ecosystems, potentially leading to inaccuracies in the models. Moreover, the divergence in data distribution patterns along environmental gradients between 'Biome' data and traditional survey data raises concerns. The app data shows a more uniform distribution across natural-urban gradients, while traditional data is biased towards natural areas. This discrepancy may impact the representation of certain ecosystems and influence the accuracy of Species Distribution Models (SDMs). While the integration of 'Biome' data into SDMs improves accuracy, the study notes that controlling the sampling efforts is crucial. Spatially-biased sampling efforts in community-sourced data need careful consideration, and efforts to control biases are essential for reliable predictions.

Reviewer #3 (Public Review):

This study explores sensory prediction errors in the sensory cortex. It focuses on the question of how these signals are shaped by non-hierarchical interactions, specifically multimodal signals arising from same-level cortical areas. The authors used 2-photon imaging of mouse auditory cortex in head-fixed mice that were presented with sounds and/or visual stimuli while moving on a ball. First, responses to pure tones, visual stimuli, and movement onset were characterized. Then, the authors made the running speed of the mouse predictive of sound intensity and/or visual flow. Mismatches were created through the interruption of sound and/or visual flow for 1 second while the animal moved, disrupting the expected sensory signal given the speed of movement. As a control, the same sensory stimuli triggered by the animal's movement were presented to the animal decoupled from its movement. The authors suggest that auditory responses to the unpredicted silence reflect mismatch responses. That these mismatch responses were enhanced when the visual flow was congruently interrupted, indicates the cross-modal influence of prediction error signals.

This study's strengths are the relevance of the question and the design of the experiment. The authors are experts in the techniques used. The analysis explores neither the full power of the experimental design nor the population activity recorded with 2-photon, leaving open the question of to what extent what the authors call mismatch responses are not sensory responses to sound interruption. The auditory system is sensitive to transitions and indeed responses to the interruption of the sound are similar in quality, if not quantity, in the predictive and the control situation.

Reviewer #2 (Public Review):

In this study, Solyga and Keller use multimodal closed-loop paradigms in conjunction with multiphoton imaging of cortical responses to assess whether and how sensorimotor prediction errors in one modality influence the computation of prediction errors in another modality. Their work addresses an important open question pertaining to the relevance of non-hierarchical (lateral cortico-cortical) interactions in predictive processing within the neocortex.

Specifically, they monitor GCaMP6f responses of layer 2/3 neurons in the auditory cortex of head-fixed mice engaged in VR paradigms where running is coupled to auditory, visual, or audio-visual sensory feedback. The authors find strong auditory and motor responses in the auditory cortex, as well as weak responses to visual stimuli. Further, in agreement with previous work, they find that the auditory cortex responds to audiomotor mismatches in a manner similar to that observed in visual cortex for visuomotor mismatches. Most importantly, while visuomotor mismatches by themselves do not trigger significant responses in the auditory cortex, simultaneous coupling of audio-visual inputs to movement non-linearly enhances mismatch responses in the auditory cortex.

Their results thus suggest that prediction errors within a given sensory modality are non-trivially influenced by prediction errors from another modality. These findings are novel, interesting, and important, especially in the context of understanding the role of lateral cortico-cortical interactions and in outlining predictive processing as a general theory of cortical function.

In its current form, the manuscript lacks sufficient description of methodological details pertaining to the closed-loop training and the overall experimental design. In several scenarios, while the results per se are convincing and interesting, their exact interpretation is challenging given the uncertainty about the actual experimental protocols (more on this below). Second, the authors are laser-focused on sensorimotor errors (mismatch responses) and focus almost exclusively on what happens when stimuli deviate from the animal's expectations.

While the authors consistently report strong running-onset responses (during open-loop) in the auditory cortex in both auditory and visual versions of the task, they do not discuss their interpretation in the different task settings (see below), nor do they analyze how these responses change during closed-loop i.e. when predictions align with sensory evidence.

However, I believe all my concerns can be easily addressed by additional analyses and incorporation of methodological details in the text.

Major concerns:

(1) Insufficient analysis of audiomotor mismatches in the auditory cortex:

Lack of analysis of the dependence of audiomotor mismatches on the running speed: it would be helpful if the authors could clarify whether the observed audiomotor mismatch responses are just binary or scale with the degree of mismatch (i.e. running speed). Along the same lines, how should one interpret the lack of dependence of the playback halt responses on the running speed? Shouldn't we expect that during playback, the responses of mismatch neurons scale with the running speed?

Slow temporal dynamics of audiomotor mismatches: despite the transient nature of the mismatches (1s), auditory mismatch responses last for several seconds. They appear significantly slower than previous reports for analogous visuomotor mismatches in V1 (by the same group, using the same methods) and even in comparison to the multimodal mismatches within this study (Figure 4C). What might explain this sustained activity? Is it due to a sustained change in the animal's running in response to the auditory mismatch?

(2) Insufficient analysis and discussion of running onset responses during audiomotor sessions: The authors report strong running-onset responses during open-loop in identified mismatch neurons. They also highlight that these responses are in agreement with their model of subtractive prediction error, which relies on subtracting the bottom-up sensory evidence from top-down motor-related predictions. I agree, and, thus, assume that running-onset responses during the open loop in identified 'mismatch' neurons reflect the motor-related predictions of sensory input that the animal has learned to expect. If this is true, one would expect that such running-onset responses should dampen during closed-loop, when sensory evidence matches expectations and therefore cancels out this prediction. It would be nice if the authors test this explicitly by analyzing the running-related activity of the same neurons during closed-loop sessions.

(3) Ambiguity in the interpretation of responses in visuomotor sessions.

Unlike for auditory stimuli, the authors show that there are no obvious responses to visuomotor mismatches or playback halts in the auditory cortex. However, the interpretation of these results is somewhat complicated by the uncertainty related to the training history of these mice. Were these mice exclusively trained on the visuomotor version of the task or also on the auditory version? I could not find this info in the Methods. From the legend for Figure 4D, it appears that the same mice were trained on all versions of the task. Is this the case? If yes, what was the training sequence? Were the mice first trained on the auditory and then the visual version?

The training history of the animals is important to outline the nature of the predictions and mismatch responses that one should expect to observe in the auditory cortex during visuomotor sessions. Depending on whether the mice in Figure 3 were trained on visual only or both visual and auditory tasks, the open-loop running onset responses may have different interpretations.

a) If the mice were trained only on the visual task, how should one interpret the strong running onset responses in the auditory cortex? Are these sensorimotor predictions (presumably of visual stimuli) that are conveyed to the auditory cortex? If so, what may be their role?

b) If the mice were also trained on the auditory version, then a potential explanation of the running-onset responses is that they are audiomotor predictions lingering from the previously learned sensorimotor coupling. In this case, one should expect that in the visual version of the task, these audiomotor predictions (within the auditory cortex) would not get canceled out even during the closed-loop periods. In other words, mismatch neurons should constantly be in an error state (more active) in the closed-loop visuomotor task. Is this the case?

If so, how should one then interpret the lack of a 'visuomotor mismatch' aligned to the visual halts, over and above this background of continuous errors?<br /> As such, the manuscript would benefit from clearly stating in the main text the experimental conditions such as training history, and from discussing the relevant possible interpretations of the responses.

(4) Ambiguity in the interpretation of responses in multimodal versus unimodal sessions.

The authors show that multimodal (auditory + visual) mismatches trigger stronger responses than unimodal mismatches presented in isolation (auditory only or visual only). Further, they find that even though visual mismatches by themselves do not evoke a significant response, co-presentation of visual and auditory stimuli non-linearly augments the mismatch responses suggesting the presence of non-hierarchical interactions between various predictive processing streams.

In my opinion, this is an important result, but its interpretation is nuanced given insufficient details about the experimental design. It appears that responses to unimodal mismatches are obtained from sessions in which only one stimulus is presented (unimodal closed-loop sessions). Is this actually the case? An alternative and perhaps cleaner experimental design would be to create unimodal mismatches within a multimodal closed-loop session while keeping the other stimulus still coupled to the movement.

Given the current experiment design (if my assumption is correct), it is unclear if the multimodal potentiation of mismatch responses is a consequence of nonlinear interactions between prediction/error signals exchanged across visual and auditory modalities. Alternatively, could this result from providing visual stimuli (coupled or uncoupled to movement) on top of the auditory stimuli? If it is the latter, would the observed results still be evidence of non-hierarchical interactions between various predictive processing streams?

Along the same lines, it would be interesting to analyze how the coupling of visual as well as auditory stimuli to movement influences responses in the auditory cortex in close-loop in comparison to auditory-only sessions. Also, do running onset responses change in open-loop in multimodal vs. unimodal playback sessions?

Minor concerns and comments:

(1) Rapid learning of audiomotor mismatches: It is interesting that auditory mismatches are present even on day 1 and do not appear to get stronger with learning (same on day 2). The authors comment that this could be because the coupling is learned rapidly (line 110). How does this compare to the rate at which visuomotor coupling is learned? Is this rapid learning also observable in the animal's behavior i.e. is there a change in running speed in response to the mismatch?

(2) The authors should clarify whether the sound and running onset responses of the auditory mismatch neurons in Figure 2E were acquired during open-loop. This is most likely the case, but explicitly stating it would be helpful.

(3) In lines 87-88, the authors state 'Visual responses also appeared overall similar but with a small increase in strength during running ...'. This statement would benefit from clarification. From Figure S1 it appears that when the animal is sitting there are no visual responses in the auditory cortex. But when the animal is moving, small positive responses are present. Are these actually 'visual' responses - perhaps a visual prediction sent from the visual cortex to the auditory cortex that is gated by movement? If so, are they modulated by features of visual stimuli eg. contrast, intensity? Or, do these responses simply reflect motor-related activity (running)? Would they be present to the same extent in the same neurons even in the dark?

(4) The authors comment in the text (lines 106-107) about cessation of sound amplitude during audiomotor mismatches as being analogous to halting of visual flow in visuomotor mismatches. However, sound amplitude versus visual flow are quite different in nature. In the visuomotor paradigm, the amount of visual stimulation (photons per unit time) does not necessarily change systematically with running speed. Whereas, in the audiomotor paradigm, the SNR of the stimulus itself changes with running speed which may impact the accuracy of predictions. On a broader note, under natural settings, while the visual flow is coupled to movement, sound amplitude may vary more idiosyncratically with movement.

Perhaps such differences might explain why unlike in the case of visual cortex experiments, running speed does not affect the strength of playback responses in the auditory cortex.

Reviewer #1 (Public Review):

Summary:

The manuscript presents a short report investigating mismatch responses in the auditory cortex, following previous studies focused on the visual cortex. By correlating the mouse locomotion speed with acoustic feedback levels, the authors demonstrate excitatory responses in a subset of neurons to halts in expected acoustic feedback. They show a lack of responses to mismatch in the visual modality. A subset of neurons show enhanced mismatch responses when both auditory and visual modalities are coupled to the animal's locomotion.

While the study is well-designed and addresses a timely question, several concerns exist regarding the quantification of animal behavior, potential alternative explanations for recorded signals, correlation between excitatory responses and animal velocity, discrepancies in reported values, and clarity regarding the identity of certain neurons.

Strengths:

(1) Well-designed study addressing a timely question in the field.

(2) Successful transition from previous work focused on the visual cortex to the auditory cortex, demonstrating generic principles in mismatch responses.

(3) The correlation between mouse locomotion speed and acoustic feedback levels provides evidence for a prediction signal in the auditory cortex.

(4) Coupling of visual and auditory feedback shows putative multimodal integration in the auditory cortex.

Weaknesses:

(1) Lack of quantification of animal behavior upon mismatches, potentially leading to alternative interpretations of recorded signals.

(2) Unclear correlation between excitatory responses and animal velocity during halts, particularly in closed-loop versus playback conditions.

(3) Discrepancies in reported values in a few figure panels raise questions about data consistency and interpretation.

(4) Ambiguity regarding the identity of the [AM+VM] MM neurons.

Reviewer #3 (Public Review):

Summary:

In this article, Hermannova et al catalog the changes in ribosome association with mRNAs when the eukaryotic translation initiation factor 3 is disrupted by knocking down subunits of the multisubunit protein. They find that RNAs relying on TOP motifs for translation, such as ribosomal protein RNAs, and RNAs encoding proteins that modify other proteins in the ER or components of the lysosome are upregulated. In contrast, proteins encoding components of MAP kinase cascades are downregulated when subunits of eIF3 are knocked down.

Strengths:

The authors use ribosome profiling of well-characterized mutants lacking subunits of eIF3 and assess the changes in translation that take place. They supplement the ribosome association studies with western blotting to determine protein level changes of affected transcripts. They analyze what is being encoded by the transcripts undergoing translation changes, which is important for understanding more broadly how translation initiation factor levels affect cancer cell translatomes.

Weaknesses:

(1) The data are presented as a catalog of effects, and the paper would be strengthened if there were a clear model tying the various effects together or linking individual subunit knockdown to cancerous phenotypes. It is unclear what the hypothesis is for cells having more MAPK activity with less of the MAPK proteins being translated, so the main findings of the paper become observational without context.

(2) The conclusions drawn are presented as very generalized other than in the last paragraph, but the experiments were only done in Hela cells. Since conclusions are being made about how translation changes affect MAP kinase signaling and there is mention in the abstract that dysregulation of these subunits is observed in cancer, at least one other cell line would need to be analyzed to provide evidence that the effects of subunit knockdown aren't cell-line specific.

(3) It is also unclear how replicates were performed and how many replicates were performed for several experiments. Biological replicates are mentioned, but what the authors did for biological replicates isn't defined and the description of the collection of cells for polysome/ribosome footprint/RNA seq samples makes it unclear whether the "biological replicates" are samples from separate transfections (true biological replicates) or different aliquots or wells from a single transfection (technical replicates) being run over a separate gradient. If using technical replicates, the data comparing the effects of knocking down D vs E vs H subunits are substantially weakened because subunit-specific differences could be the result of non-specific events that occurred in a transfection. It's also notable that while the pooled siRNAs will increase the potency of knockdown, it is possible that one or more of the siRNAs could have off-target effects, and analyzing individual siRNAs would be better for ensuring effects are specific.

(4) Many of the changes in protein levels reported by Western are subtle. Data from all western blots making claims of quantitative differences should really be quantified relative to nontreated over-loading control or total protein quantified from the gel, and presented with a degree of error from biological replicates to make conclusions about differences in protein levels between samples.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Herrmannova et al explore changes in translation upon individual depletion of three subunits of the eIF3 complex (d, e, and f) in mammalian cells. The authors provide a detailed analysis of regulated transcripts, followed by validation by RT-qPCR and/or Western blot of targets of interest, as well as GO and KKEG pathway analysis. The authors confirm prior observations that eIF3, despite being a general translation initiation factor, functions in mRNA-specific regulation, and that eIF3 is important for translation re-initiation. They show that the global effects of eIF3e and eIF3d depletion on translation and cell growth are concordant. Their results support and extend previous reports suggesting that both factors control the translation of 5'TOP mRNAs. Interestingly, they identify MAPK pathway components as a group of targets coordinately regulated by eIF3 d/e. The authors also discuss discrepancies with other reports analyzing eIF3e function.

Strengths:

Altogether, a solid analysis of eIF3 d/e/h-mediated translation regulation of specific transcripts. The data will be useful for scientists working in the Translation field.

Weaknesses:

The authors could have explored in more detail some of their novel observations, as well as their impact on cell behavior.

Reviewer #2 (Public Review):

Summary:

mRNA translation regulation permits cells to rapidly adapt to diverse stimuli by fine-tuning gene expression. Specifically, the 13-subunit eukaryotic initiation factor 3 (eIF3) complex is critical for translation initiation as it aids in 48S PIC assembly to allow for ribosome scanning. In addition, eIF3 has been shown to drive transcript-specific translation by binding mRNA 5' cap structures through the eIF3d subunit. Dysregulation of eIF3 has been implicated in oncogenesis, however the precise eIF3 subunit contributions are unclear. Here, Herrmannová et al. aim to investigate how eIF3 subcomplexes, generated by knockdown (KD) of either eIF3e, eIF3d, or eIF3h, affect the global translatome. Using Ribo-seq and RNA-seq, the authors identified a large number of genes that exhibit altered translation efficiency upon eIF3d/e KD, while translation defects upon eIF3h KD were mild. eIF3d/e KD share multiple dysregulated transcripts, perhaps due to both subcomplexes lacking eIF3d. Both eIF3d/e KD increase the translation efficiency (TE) of transcripts encoding lysosomal, ER, and ribosomal proteins. This suggests a role of eIF3 in ribosome biogenesis and protein quality control. Many transcripts encoding ribosomal proteins harbor a TOP motif, and eIF3d KD and eIF3e KD cells exhibit a striking induction of these TOP-modified transcripts. On the other hand, eIF3d KD and eIF3e KD lead to a reduction of MAPK/ERK pathway proteins. Despite this downregulation, eIF3d KD and eIF3e KD activate MAPK/ERK signaling as ERK1/2 and c-Jun phosphorylation were induced. Finally, in all three knockdowns, MDM2 and ATF4 protein levels are reduced. This is notable because MDM2 and ATF4 both contain short uORFs upstream of the start codon, and further support a role of eIF3 in reinitiation. Altogether, Herrmannová et al. have gained key insights into precise eIF3-mediated translational control as it relates to key signaling pathways implicated in cancer.

Strengths:

The authors have provided a comprehensive set of data to analyze RNA and ribosome footprinting upon perturbation of eIF3d, eIF3e, and eIF3h. As described above in the summary, these data present many interesting starting points for understanding additional roles of the eIF3 complex and specific subunits in translational control.

Weaknesses:

- The differences between eIF3e and eIF3d knockdown are difficult to reconcile, especially since eIF3e knockdown leads to a reduction in eIF3d levels.

- The paper would be strengthened by experiments directly testing what RNA determinants allow for transcript-specific translation regulation by the eIF3 complex. This would allow the paper to be less descriptive.

- The paper would have more biological relevance if eIF3 subunits were perturbed to mimic naturally occurring situations where eIF3 is dysregulated. For example, eIF3e is aberrantly upregulated in certain cancers, and therefore an overexpression and profiling experiment would have been more relevant than a knockdown experiment.

Reviewer #3 (Public Review):

These studies reveal an S-phase requirement for the PARG dePARylation enzyme in removing ADP-ribosylation from PAR-modified proteins whose PARylation is promoted by the presence of unligated Okazaki fragments. The excessive protein ADP-ribosylation observed in S-phase of PARG-depleted human cells leads to trapping of the PARP1 ADP-ribosylation enzyme on chromatin. The findings would be strengthened by identification of the relevant ADP-ribosylation substrates of PARG whose dePARylation is needed for progression through S-phase.

Comments on revised version:

In the revised version the authors have addressed some of the reviewers' concerns, but, despite the new explanatory paragraph on page 16, the paper remains confusing because as shown in Figure 7 at the end of the Results the PARG KO 293A cells that were analyzed at the beginning of the Results are not true PARG knockouts. The authors stated that they did not rewrite the Results because they wanted to describe the experiments in the order in which they were carried out, but there is no imperative for the experiments to be described in the order in which they were done, and it would be much easier for the uninitiated reader to appreciate the significance of these studies if the true PARG KO cell data were presented at the beginning, as all three of the original reviewers proposed.

While the authors have to some extent clarified the nature of the PARG KO alleles, they have not been able to identify the source of the residual PARG activity in the PARG KO cells, in part because different commercial PARG antibodies give different and conflicting immunoblotting results. Additional sequence characterization of PARG mRNAs expressed in the PARG cKO cells, and also in-depth proteomic analysis of the different PARG bands could provide further insight into the origins and molecular identities of the various PARG proteins expressed from the different KO PARG alleles, and determine which of them might retain catalytic activity.

The authors have made no progress in identifying which are the key PARG substrates required for S phase progression, although they suggest that PARP1 itself may be an important target.

Reviewer #2 (Public Review):

Summary:

In this manuscript Nie et al investigate the effect of PARG KO and PARG inhibition (PARGi) on pADPR, DNA damage, cell viability and synthetic lethal interactions in HEK293A and Hela cells. Surprisingly, the authors report that PARG KO cells are sensitive to PARGi and show higher pADPR levels than PARG KO cells, which is abrogated upon deletion or inhibition of PARP1/PARP2. The authors explain the sensitivity of PARG KO to PARGi through incomplete PARG depletion and demonstrate complete loss of PARG activity when incomplete PARG KO cells are transfected with additional gRNAs in the presence of PARPi. Furthermore, the authors show that the sensitivity of PARG KO cells to PARGi is not caused by NAD depletion but by S-phase accumulation of pADPR on chromatin coming from unligated Okazaki fragments, which are recognized and bound by PARP1. Consistently, PARG KO or PARG inhibition show synthetic lethality with Pol beta, which is required for Okazaki fragment maturation. PARG expression levels in ovarian cancer cell lines correlate negatively with their sensitivity to PARGi.

Reviewer #2 (Public Review):

The authors aimed to understand how epistasis influences the genetic architecture of the DNA-binding domain (DBD) of steroid hormone receptor. An ordinal regression model was developed in this study to analyze a published deep mutational scanning dataset that consists of all combinatorial amino acid variants across four positions (i.e. 160,000 variants). This published dataset measured the binding of each variant to the estrogen receptor response element (ERE, sequence: AGGTCA) as well as the steroid receptor response element (SRE, sequence: AGAACA). This model has major strengths of being reference free and able to account for global nonlinearity in the genotype-phenotype relationship. Thorough analyses of the modelling results have performed, which provided convincing results to support the importance of epistasis in promoting evolution of protein functions. This conclusion is impactful because many previous studies have shown that epistasis constrains evolution. The novelty this study will likely stimulate new ideas in the field. The model will also likely be utilized by other groups in the community.

Reviewer #1 (Public Review):

Metzger et al develop a rigorous method filling an important unmet need in protein evolution - analysis of protein genetic architecture and evolution using data from combinatorially complete 20^N variant libraries. Addressing this need has become increasingly valuable, as experimental methods for generating these datasets expand in scope and scale. Their method integrates two key features - (1) it reports the effects of mutations relative to the average across all variants, rather than a particular genotype, making it useful for examining global genetic architecture, and (2) it does this for all possible 20 states at each site, in contrast to the binary analyses in prior work. These features are not individually novel but integrating them into a single analysis framework is novel and will be valuable to the protein evolution community. Using a previously published dataset generated by two of the authors, they conclude that (1) changes in function are largely attributable to pairwise but not higher-order interactions, and (2) epistasis potentiates, rather than constrains, evolutionary paths. These findings are well-supported by the data. Overall, this work has important implications for predicting the relationship between genotype and phenotype, which is of considerable interest to protein biochemistry, evolutionary biology, and numerous other fields.

Reviewer #1 (Public Review):

Summary:

The authors were trying to understand the relation between the development of large trunks and longirrostrine mandibles in bunodont proboscideans of Miocene, and how it reflects the variation in diet patterns.

Strengths:

The study is very well supported, written, and illustrated, with plenty Supplementary materials. The authors included all Asian bunodont proboscideans with long mandibles and I suggest that they should use the expression "bunodont proboscideans" instead of gomphotheres.

Weaknesses:

I believe that the only weakness is the lack of discussion comparing their results with the development of gigantism and long limbs in proboscideans from the same epoch.

The authors reviewed the manuscript according to my suggestions and responded well to all my comments.

Reviewer #3 (Public Review):

This study investigates subtelomeric repetitive sequences in the budding yeast Saccharomyces cerevisiae, known as Y' and X-elements. Taking advantage of yeast strain SY12 that contains only 3 chromosomes and six telomeres (normal yeast strains contain 32 telomeres) the authors are able to generate a strain completely devoid of Y'- and X-elements.

Strengths:

They demonstrate that the SY12 delta XY strain displays normal growth, with stable telomeres of normal length that were transcriptionally silenced, a key finding with wide implications for telomere biology. Inactivation of telomerase in the SY12 and SY12 delta XY strains frequently resulted in survivors that had circularized all three chromosomes, hence bypassing the need for telomeres altogether. They show that survivors with fused chromosomes and so-called atypical survivors arise independently of the central recombination protein Rad52. The SY12 and SY12 delta XY yeast strains can become a useful tool for future studies of telomere biology. The conclusions of this manuscript are well supported by the data and are valuable for researchers studying telomeres.

Weaknesses:

A weakness of the manuscript is the analysis of telomere transcriptional silencing. They state: "The results demonstrated a significant increase in the expression of the MPH3 and HSP32 upon Sir2 deletion, indicating that telomere silencing remains effective in the absence of X and Y'-elements". However, for the SY12 strain, their analyses indicate that the difference between the WT and sir2 strains is nonsignificant. In addition, a striking observation is that the SY12 strain (with only three chromosomes) express much less of both MPH3 and HSP32 than the parental strain BY4742 (16 chromosomes), both in the presence and absence of Sir2.

Reviewer #1 (Public Review):

The authors have generated a set of yeast S. cerevisiae strains containing different numbers of chromosomes.<br /> Elimination of telomerase activates homologous recombination (HR) to maintain telomeres in cells containing the original 16 chromosomes. However, elimination of telomerase leads to circularization of cells containing a single or two chromosomes. The authors examined whether the subtelomeric sequences X and Y' promote HR-mediated telomere maintenance using the strain SY12 carrying three chromosomes. They found that the subtelomeric sequences X and Y' are dispensable for cell proliferation and HR-mediated telomere maintenance in telomerase-minus SY12 cells. They conclude that subtelomeric X and Y' sequences do not play essential roles in both telomerase-proficient and telomerase-null cells and propose that these sequences represent remnants of genome evolution.

Interestingly, telomerase-minus SY12 generates survivors that are different from well-established Type I or Type II survivors. The authors uncover atypical telomere formation which does not depend on the Rad52 homologous recombination pathway.

Strengths:

The authors examined whether the subtelomeric sequences X and Y' promote HR-mediated telomere maintenance using the strain SY12 carrying three chromosomes. They show that subtelomeres do not have essential roles in telomere maintenance and cell proliferation.

Weaknesses:

It is not fully addressed how atypical survivors are generated independently of Rad52-mediated homologous recombination.<br /> It remains possible that X and Y elements influence homologous recombination, type 1 and type 2 (type X), at telomeres. In particular, the presence of X and Y elements appears to be important for promoting type 1 recombination, although the authors conclude "Elimination of subtelomeric repeat sequences exerts little effect on telomere functions".

Reviewer #2 (Public Review):

Summary:

In this work, Hu and colleagues investigate telomerase-independent survival in Saccharomyces cerevisiae strains engineered to have different chromosome numbers. The authors describe the molecular patterns of survival that change with fewer chromosomes and that differ from the well-described canonical Type I and Type II, including chromosome circularization and other atypical outcomes. They then take advantage of the strain with 3 chromosomes to examine the effect of deleting all the subtelomeric elements, called X and Y'. For most of the tested phenotypes, they find no significant effect of the absence of X- and Y'-element, and show that they are not essential for survivor formation. They speculate that X- and Y'-elements are remnants of ancient telomere maintenance mechanisms.

Strengths:

This work advances our understanding of the telomerase-independent strategies available to the cell by altering the structure of the genome and of the subtelomeres, a feat that was enabled by the set of strains they engineered previously. By using strains with non-standard genome structures, several alternative survival mechanisms are uncovered, revealing the diversity and plasticity of telomere maintenance mechanisms. Overall, the conclusions are well supported by the data, with adequate sample sizes for investigating survivors. The assessment of the genetic requirements for survivors in strains with different chromosome numbers greatly improved the quality of this work. The molecular analyses based on Southern blots are also very well-conducted.

Weaknesses:

The authors discovered alternative telomerase-independent survival strategies beyond the well-described type I and II (including circularization, type X and atypical, as they called them) at play in the context of reduced number of chromosomes. Their work provides a molecular and a partial genetic characterization of these survival pathways. A more thorough analysis of the frequency of each type of survivors and their genetic requirements would have advanced our understanding or the diversity of survival strategies in the absence of telomerase. However, as noted by the authors, the quantification of the rate of emergence of survivors (and their subtypes) is very difficult to achieve. This comment is therefore not meant as a criticism but rather as a perspective on exciting future research avenues.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors revealed that genetic deficiencies of ACK1 and BRK are associated with human SLE. First, the authors found that compound heterozygous deleterious variants in the kinase domains of the non-receptor tyrosine kinases (NRTK) TNK2/ACK1 in one multiplex family and PTK6/BRK in another family. Then, by an experimental blockade of ACK1 or BRK in a mouse SLE model, they found an increase in glomerular IgG deposits and circulating autoantibodies. Furthermore, they reported that ACK and BRK variants from the SLE patients impaired the MERTK-mediated anti-inflammatory response to apoptotic cells in human induced pluripotent stem cells (hiPSC)-derived macrophages. This work identified new SLE-associated ACK and BRK variants and a role for the NRTK TNK2/ACK1 and PTK6/BRK in efferocytosis, providing a new molecular and cellular mechanism of SLE pathogenesis.

Strengths:

This work identified new SLE-associated ACK and BRK variants and a role for the NRTK TNK2/ACK1 and PTK6/BRK in efferocytosis, providing a new molecular and cellular mechanism of SLE pathogenesis.

Weaknesses:

Although the manuscript is well-organized and clearly stated, there are some points below that should be considered:

* In this study, the authors used forward genetic analyses to identify novel gene mutations that may cause SLE, combined with GWAS studies of SLE. To further explore the importance of these variants, haplotype analysis of two candidate genes could be performed, to observe the evolution and selection relationship of candidate genes in the population (UK 1000 biobank, for example).

* Although the authors focused on SLE and macrophage efferocytosis in their studies, direct evidence of how macrophage efferocytosis significantly affects SLE is lacking. This point should at least be explicitly introduced and discussed by citing appropriate literature.

* It is still not clear how the target molecules identified in this paper may influence macrophage efferocytosis. More direct evidence should be established.

* For some transcriptional repressors mentioned in their studies, the authors should check whether there is clear experimental evidence. If not, it is recommended to supplement the experimental verifications for clarity.

* In Figures 4C and 4D, it is seen that the usage of inhibitors causes cytoskeletal changes, however this reviewer would not have expected such large change. Did the authors check whether the cells die after heavy treatment by the inhibitors?

Reviewer #1 (Public Review):

Summary:

The authors report compound heterozygous deleterious variants in the kinase domains of the non-receptor tyrosine kinases (NRTK) TNK2/ACK1 in familial SLE. They suggest that ACK1 and BRK deficiencies are associated with human SLE and impair efferocytosis.

Strengths:

The identification of similar mutations in non-receptor tyrosine kinases (NRTKs) in two different families with familial SLE is a significant finding in human disease. Furthermore, the paper provides a detailed analysis of the molecular mechanisms behind the impairment of efferocytosis caused by mutations in ACK1 and BRK.

Weaknesses:

A critical point in this paper is whether the loss of function of ACK1 or BRK contributes to the onset of familial SLE. The authors emphasize that inhibitors of ACK1/BRK worsened IgG deposition in the kidneys in a pristane-induced SLE model, which contributes not to the onset but to the exacerbation of SLE, thus only partially supporting their claim.

Reviewer #1 (Public Review):

Summary:

This manuscript investigates the regulation of chlorophyll biosynthesis in rice embryos, focusing on the role of OsNF-YB7. The rigorous experimental approach, combining genetic, biochemical, and molecular analyses, provides a robust foundation for these findings. The research achieves its objectives, offering new insights into chlorophyll biosynthesis regulation, with the results convincingly supporting the authors' conclusions.

Strengths:

The major strengths include the detailed experimental design and the findings regarding OsNF-YB7's inhibitory role.

Weaknesses:

However, the manuscript's discussion on the practical implications for agriculture and the evolutionary analysis of regulatory mechanisms could be expanded.

Reviewer #2 (Public Review):

Summary:

The authors set out to establish the role of the rice LEC1 homolog OsNF-YB7 in embryo development, especially as it pertains to the development of photosynthetic capacity, with chlorophyll production as a primary focus.

Strengths:

The results are well-supported and each approach used complements each other. There are no major questions left unanswered and the central hypothesis is addressed in every figure.

Weaknesses:

There are a handful of sections that could use clarifying for readers, but overall this is a solidly composed manuscript.

The authors clearly achieved their aims; the results compellingly establish a disparity between how this system operates in rice and Arabidopsis. Conclusions are thoroughly supported by the provided data and interpretations. This work will force a reconsideration of the value of Arabidopsis as a model organism for embryo chlorophyll biosynthesis and possibly photosynthesis during embryo maturation more broadly, as rice is a major crop organism and it very clearly does not follow the Arabidopsis model. It will thus be useful to carry out similar tests in other organisms rather than relying on Arabidopsis and attempting to more fully establish the regulatory mechanism in rice.

Reviewer #3 (Public Review):

Summary:

In this study, the authors set out to understand the mechanisms behind chlorophyll biosynthesis in rice, focusing in particular on the role of OsNF-YB7, an ortholog of Arabidopsis LEC1, which is a positive regulator of chlorophyll (Chl) biosynthesis in Arabidopsis. They showed that OsNF-YB7 loss-of-function mutants in rice have chlorophyll-rich embryos, in contrast to Arabidopsis LEC1 loss-of-function mutants. This contrasting phenotype led the authors to carry out extensive molecular studies on OsNF-YB7, including in vitro and in vivo protein interaction studies, gene expression profiling, and protein-DNA interaction assays. The evidence provided well supported the core arguments of the authors, emphasising that OsNF-YB7 is a negative regulator of Chl biosynthesis in rice embryos by mediating the expression of OsGLK1, a transcription factor that regulates downstream Chl biosynthesis genes. In addition, they showed that OsNF-YB7 interacts with OsGLK1 to negatively regulate the expression of OsGLK1, demonstrating the broad involvement of OsNF-YB7 in rice Chl biosynthetic pathways.

Strengths:

This study clearly demonstrated how OsNF-YB7 regulates its downstream pathways using several in vitro and in vivo approaches. For example, gene expression analysis of OsNF-YB7 loss-of-function and gain-of-function mutants revealed the expression of selected downstream chl biosynthetic genes. This was further validated by EMSA on the gel. The authors also confirmed this using luciferase assays in rice protoplasts. These approaches were used again to show how the interaction of OsNF-YB7 and OsGLK1 regulates downstream genes. The main idea of this study is very well supported by the results and data.

Weaknesses:

From an evolutionary perspective, it is interesting to see how two similar genes have come to play opposite roles in Arabidopsis and rice. It would have been more interesting if the authors had carried out a cross-species analysis of AtLEC1 and OsNF-YB7. For example, overexpressing AtLEC1 in an osnf-yb7 mutant to see if the phenotype is restored or enhanced. Such an approach would help us understand how two similar proteins can play opposite roles in the same mechanism within their respective plant species.

Reviewer #1 (Public Review):

The authors observed a decline in autophagy and proteasome activity in the context of Milton knockdown. Through proteomic analysis, they identified an increase in the protein levels of eIF2β, subsequently pinpointing a novel interaction within eIF subunits where eIF2β contributes to the reduction of eIF2α phosphorylation levels. Furthermore, they demonstrated that overexpression of eIF2β suppresses autophagy and leads to diminished motor function. It was also shown that in a heterozygous mutant background of eIF2β, Milton knockdown could be rescued. This work represents a novel and significant contribution to the field, revealing for the first time that the loss of mitochondria from axons can lead to impaired autophagy function via eIF2β, potentially influencing the acceleration of aging. To further support the authors' claims, several improvements are necessary, particularly in the methods of quantification and the points that should be demonstrated quantitatively. It is crucial to investigate the correlation between aging and the proteins eIF2β and eIF2α.

Reviewer #2 (Public Review):

In the manuscript, the authors aimed to elucidate the molecular mechanism that explains neurodegeneration caused by the depletion of axonal mitochondria. In Drosophila, starting with siRNA depletion of Milton and Miro, the authors attempted to demonstrate that the depletion of axonal mitochondria induces the defect in autophagy. From proteome analyses, the authors hypothesized that autophagy is impacted by the abundance of eIF2β and the phosphorylation of eIF2α. The authors followed up the proteome analyses by testing the effects of eIF2β overexpression and depletion on autophagy. With the results from those experiments, the authors proposed a novel role of eIF2β in proteostasis that underlies neurodegeneration derived from the depletion of axonal mitochondria.

The manuscript has several weaknesses. The reader should take extra care while reading this manuscript and when acknowledging the findings and the model in this manuscript.

The defect in autophagy by the depletion of axonal mitochondria is one of the main claims in the paper. The authors should work more on describing their results of LC3-II/LC3-I ratio, as there are multiple ways to interpret the LC3 blotting for the autophagy assessment. Lysosomal defects result in the accumulation of LC3-II thus the LC3-II/LC3-I ratio gets higher. On the other hand, the defect in the early steps of autophagosome formation could result in a lower LC3-II/LC3-I ratio. From the results of the actual blotting, the LC3-I abundance is the source of the major difference for all conditions (Milton RNAi and eIF2β overexpression and depletion). In the text, the authors simply state the observation of their LC3 blotting. The manuscript lacks an explanation of how to evaluate the LC3-II/LC3-I ratio. Also, the manuscript lacks an elaboration on what the results of the LC3 blotting indicate about the state of autophagy by the depletion of axonal mitochondria.

Another main point of the paper is the up-regulation of eIF2β by depleting the axonal mitochondria leads to the proteostasis crisis. This claim is formed by the findings from the proteome analyses. The authors should have presented their proteomic data with much thorough presentation and explanation. As in the experiment scheme shown in Figure 4A, the author did two proteome analyses: one from the 7-day-old sample and the other from the 21-day-old sample. The manuscript only shows a plot of the result from the 7-day-old sample, but that of the result from the 21-day-old sample. For the 21-day-old sample, the authors only provided data in the supplemental table, in which the abundance ratio of eIF2β from the 21-day-old sample is 0.753, meaning eIF2β is depleted in the 21-day-old sample. The authors should have explained the impact of the eIF2β depletion in the 21-day-old sample, so the reader could fully understand the authors' interpretation of the role of eIF2β on proteostasis.

The manuscript consists of several weaknesses in its data and explanation regarding translation.

(1) The authors are likely misunderstanding the effect of phosphorylation of eIF2α on translation. The P-eIF2α is inhibitory for translation initiation. However, the authors seem to be mistaken that the down-regulation of P-eIF2α inhibits translation.

(2) The result of polysome profiling in Figure 4H is implausible. By 10%-25% sucrose density gradient, polysomes are not expected to be observed. The authors should have used a gradient with much denser sucrose, such as 10-50%.

(3) Also on the polysome profiling, as in the method section, the authors seemed to fractionate ultra-centrifuged samples from top to bottom and then measured A260 by a plate reader. In that case, the authors should have provided a line plot with individual data points, not the smoothly connected ones in the manuscript.

(4) For both the results from polysome profiling and puromycin incorporation (Figure 4H and I), the difference between control siRNA and Milton siRNA are subtle, if not nonexistent. This might arise from the lack of spatial resolution in their experiment as the authors used head lysate for these data but the ratio of Phospho-eIF2α/eIF2α only changes in the axons, based on their results in Figure 4E-G. The authors could have attempted to capture the spatial resolution for the axonal translation to see the difference between control siRNA and Milton siRNA.

Reviewer #1 (Public Review):

Here the authors discuss mechanisms of ligand binding and conformational changes in GlnBP (a small E Coli periplasmic binding protein, which binds and carries L-glutamine to the inner membrane ATP-binding cassette (ABC) transporter). The authors have distinguished records in this area and have published seminal works. They include experimentalists and computational scientists. Accordingly, they provide comprehensive, high-quality, experimental and computational work.

They observe that apo- and holo- GlnBP does not generate detectable exchange between open and (semi-) closed conformations on timescales between 100 ns and 10 ms. Especially, the ligand binding and conformational changes in GlnBP that they observe are highly correlated. Their analysis of the results indicates a dominant induced-fit mechanism, where the ligand binds GlnBP prior to conformational rearrangements. They then suggest that an approach resembling the one they undertook can be applied to other protein systems where the coupling mechanism of conformational changes and ligand binding.

They argue that the intuitive model where ligand binding triggers a functionally relevant conformational change was challenged by structural experiments and MD simulations revealing the existence of unliganded closed or semi-closed states and their dynamic exchange with open unbound conformations, discuss alternative mechanisms that were proposed, their merits and difficulties, concluding that the findings were controversial, which, they suggest is due to insufficient availability of experimental evidence to distinguish them. As to further specific conclusions they draw from their results, they determine that a conformational selection mechanism is incompatible with their results, but induced fit is. They thus propose induced fit as the dominant pathway for GlnBP, further supported by the notion that the open conformation is much more likely to bind substrate than the closed one based on steric arguments.

Considering the landscape of substrate-free states, in my view, the closed state is likely to be the most stable and, thus most highly populated. As the authors note and I agree that state can be sterically infeasible for a deep-pocketed substrate. As indeed they also underscore, there is likely to be a range of open states. If the populations of certain states are extremely low, they may not be detected by the experimental (or computational) methods. The free energy landscape of the protein can populate all possible states, with the populations determined by their relative energies. In principle, the protein can visit all states. Whether a particular state is observed depends on the time the protein spends in that state. The frequencies, or propensities, of the visits can determine the protein function. As to a specific order of events, in my view, there isn't any. It is a matter of probabilities which depend on the populations (energies) of the states. The open conformation that is likely to bind is the most favorable, permitting substrate access, followed by minor, induced fit conformational changes. However, a key factor is the ligand concentration. Ligand binding requires overcoming barriers to sustain the equilibrium of the unliganded ensemble, thus time. If the population of the state is low, and ligand concentration is high (often the case in in vitro experiments, and high drug dosage scenarios) binding is likely to take place across a range of available states.

This is however a personal interpretation of the data. The paper here, which clearly embodies massive careful, and high-quality work, is extensive, making use of a range of experimental approaches, including isothermal titration calorimetry, single-molecule Förster resonance energy transfer, and surface-plasmon resonance spectroscopy. The problem the authors undertake is of fundamental importance.

Reviewer #2 (Public Review):

Summary:

The manuscript by Han et al and Cordes is a tour-de-force effort to distinguish between induced fit and conformational selection in glutamine binding protein (GlnBP). It is important to say that I don't agree that a decision needs to be made between these two limiting possibilities in the sense that whether a minor population can be observed depends on the experiment and the energy difference between the states. That said, the authors make an important distinction which is that it is not sufficient to observe both states in the ligand-free solution because it is likely that the ligand will not bind to the already closed state. The ligand binds to the open state and the question then is whether the ligand sufficiently changes the energy of the open state to effectively cause it to close. The authors point out that this question requires both a kinetic and a thermodynamic answer. Their "method" combines isothermal titration calorimetry, single-molecule FRET including key results from multi-parameter photon-by-photon hidden Markov modelling (mpH2MM), and SPR. The authors present this "method" of combination of experiments as an approach to definitively differentiate between induced fit and conformational selection. I applaud the rigor with which they perform all of the experiments and agree that others who want to understand the exact mechanism of protein conformational changes connected to ligand binding need to do such a multitude of different experiments to fully characterize the process. However, the situation of GlnBP is somewhat unique in the high affinity of the Gln (slow off-rate) as compared to many small molecule binding situations such as enzyme-substrate complexes. It is therefore not surprising that the kinetics result in an induced fit situation. In the case of the E-S complexes I am familiar with, the dissociation is much more rapid because the substrate binding affinity is in the micromolar range and therefore the re-equilibration of the apo state is much faster. In this case, the rate of closing and opening doesn't change much whether ligand is present or not. Here, of course, once the ligand is bound the re-equilibration is slow. Therefore, I am not sure if the conclusions based on this single protein are transferrable to most other protein-small molecule systems. I am also not sure if they are transferrable to protein-protein systems where both molecules the ligand and the receptor are expected to have multiscale dynamics that change upon binding.

Strengths:

The authors provide beautiful ITC data and smFRET data to explore the conformational changes that occur upon Gln binding. Figure 3D and Figure 4 (mpH2MM data) provide the really critical data. The multi-parameter photon-by-photon hidden Markov modelling (mpH2MM) data. In the presence of glutamine concentrations near the Kd, two FRET-active sub-populations are identified that appear to interconvert on timescales slower than 10 ms. They then do a whole bunch of control experiments to look for faster dynamics (Figure 5). They also do TIRF smFRET to try to compare their results to those of previous publications. Here, they find several artifacts are occurring including inactivation of ~50% of the proteins. They also perform SPR experiments to measure the association rate of Gln and obtain expectedly rapid association rates on the order of 10^8 M-1s-1.

Weaknesses:

Looking at the traces presented in the supplementary figures, one can see that several of the traces have more than one molecule present. The authors should make sure that they use only traces with a single photobleaching event for each fluorophore. One can see steps in some of the green traces that indicate two green fluorophors (likely from 2 different molecules) in the traces. This is one of the frequent problems with TIRF smFRET with proteins, that only some of the spots represent single molecules and the rest need to be filtered out of the analysis.

The NMR experiments that the authors cite are not in disagreement with the work presented here. NMR is capable of detecting "invisible states" that occur in 1-5% of the population. SmFRET is not capable of detecting these very minor states. I am quite sure that if NMR spectroscopists could add very high concentrations of Gln they would also see a conversion to the closed population.

Reviewer #1 (Public Review):

Summary:

The paper measures the prevalence and mortality of stroke and its comorbidities across geographic regions in order to find differences in risks that may lead to more effective guidance for these subpopulations. It also does a genetic analysis to look for variants that may drive these phenotypic variations.

Strengths:

The data provided here will provide a foundation for a lot of future research into the causes of the observed correlations as well as whether the observed differences in comorbidities across regions have clinically relevant effects on risk management.

Weaknesses:

As with any cross-national analysis of rates, the data is vulnerable to differences in classification and reporting across jurisdictions. Furthermore, given the increased death rate from COVID-19 associated with many of these comorbid conditions and the long-term effects of COVID-19 infection on vascular health, it is expected that many of the correlations observed in this dataset will shift along with the shifting health of the underlying populations.

Reviewer #2 (Public Review):

Summary:

The authors have analyzed ethnogeographic differences in the comorbidity factors, such as diabetes and heart disease, for the incidences of stroke and whether it leads to mortality.

Strengths:<br /> The idea is interesting and the data are compelling. The results are technically solid.

The authors identify specific genetic loci that increase the risk of a stroke and how they differ by region.

Weaknesses:

The presentation is not focused. It would be better to include p-values and focus presentation on the main effects of the dataset analysis.

Reviewer #1 (Public Review):

Summary:

The manuscript by Duilio M. Potenza et al. explores the role of Arginase II in cardiac aging, majorly using whole-body arg-ii knock-out mice. In this work, the authors have found that Arg-II exerts non-cell-autonomous effects on aging cardiomyocytes, fibroblasts, and endothelial cells mediated by IL-1b from aging macrophages. The authors have used arg II KO mice and an in vitro culture system to study the role of Arg II. The authors have also reported the cell-autonomous effect of Arg-II through mitochondrial ROS in fibroblasts that contribute to cardiac aging. These findings are sufficiently novel in cardiac aging and provide interesting insights. While the phenotypic data seems strong, the mechanistic details are unclear. How Arg II regulates the IL-1b and modulates cardiac aging is still being determined. The authors still need to determine whether Arg II in fibroblasts and endothelial contributes to cardiac fibrosis and cell death. This study also lacks a comprehensive understanding of the pathways modulated by Arg II to regulate cardiac aging.

Strengths:

This study provides interesting information on the role of Arg II in cardiac aging.

The phenotypic data in the arg II KO mice is convincing, and the authors have assessed most of the aging-related changes.

The data is supported by an in vitro cell culture system.

Weaknesses:

The manuscript needs more mechanistic details on how Arg II regulates IL-1b and modulates cardiac aging.

The authors used whole-body KO mice, and the role of macrophages in cardiac aging is not studied in this model. A macrophage-specific arg II Ko would be a better model.

Experiments need to validate the deficiency of Arg II in cardiomyocytes.

The authors have never investigated the possibility of NO involvement in this mice model.

A co-culture system would be appropriate to understand the non-cell-autonomous functions of macrophages.

The Myocardial infarction data shown in the mice model may not be directly linked to cardiac aging.

Reviewer #2 (Public Review):

Summary:

The results from this study demonstrated a cell-specific role of mitochondrial enzyme arginase-II (Arg-II) in heart aging and revealed a non-cell-autonomous effect of Arg-II on cardiomyocytes, fibroblasts, and endothelial cells through the crosstalk with macrophages via inflammatory factors, such as by IL-1, as well as a cell-autonomous effect of Arg-II through mtROS in fibroblasts contributing to cardiac aging phenotype. These findings highlight the significance of non-cardiomyocytes in the heart and bring new insights into the understanding of pathologies of cardiac aging. It also provides new evidence for the development of therapeutic strategies, such as targeting the ArgII activation in macrophages.

Strengths:

This study targets an important clinical challenge, and the results are interesting and innovative. The experimental design is rigorous, the results are solid, and the representation is clear. The conclusion is logical and justified.

Weaknesses:

The discussion could be extended a little bit to improve the realm of the knowledge related to this study.

Reviewer #1 (Public Review):

Summary:

Semenova et al. have studied a large cross-sectional cohort of people living with HIV on suppressive ART, N=115, and performed high dimensional flow cytometry to then search for associations between immunological and clinical parameters and intact/total HIV DNA levels.

A number of interesting data science/ML approaches were explored on the data and the project seems a serious undertaking. However, like many other studies that have looked for these kinds of associations, there was not a very strong signal. Of course, the goal of unsupervised learning is to find new hypotheses that aren't obvious to human eyes, but I felt in that context, there were (1) results slightly oversold, (2) some questions about methodology in terms mostly of reservoir levels, and (3) results were not sufficiently translated back into meaning in terms of clinical outcomes.

Strengths:

The study is evidently a large and impressive undertaking and combines many cutting-edge statistical techniques with a comprehensive experimental cohort of people living with HIV, notably inclusive of populations underrepresented in HIV science. A number of intriguing hypotheses are put forward that could be explored further. Sharing the data could create a useful repository for more specific analyses.

Weaknesses:

Despite the detailed experiments and methods, there was not a very strong signal for the variable(s) predicting HIV reservoir size. The Spearman coefficients are ~0.3, (somewhat weak, and acknowledged as such) and predictive models reach 70-80% prediction levels, though sometimes categorical variables are challenging to interpret.

There are some questions about methodology, as well as some conclusions that are not completely supported by results, or at minimum not sufficiently contextualized in terms of clinical significance.

On associations: the false discovery rate correction was set at 5%, but data appear underdetermined with fewer observations than variables (144vars > 115ppts), and it isn't always clear if/when variables are related (e.g inverses of one another, for instance, %CD4 and %CD8).

The modeling of reservoir size was unusual, typically intact and defective HIV DNA are analyzed on a log10 scale (both for decays and predicting rebound). Also sometimes in this analysis levels are normalized (presumably to max/min?, e.g. S5), and given the large within-host variation of level we see in other works, it is not trivial to predict any downstream impact of normalization across population vs within-person.

Also, the qualitative characterization of low/high reservoir is not standard and naturally will split by early/later ART if done as above/below median. Given the continuous nature of these data, it seems throughout that predicting above/below median is a little hard to translate into clinical meaning.

Lastly, the work is comprehensive and appears solid, but the code was not shared to see how calculations were performed.

Reviewer #2 (Public Review):

Summary:

Semenova et. al., performed a cross-sectional analysis of host immunophenotypes (using flow cytometry) and the peripheral CD4+ T cell HIV reservoir size (using the Intact Proviral DNA Assay, IPDA) from 115 people with HIV (PWH) on ART. The study mostly highlights the machine learning methods applied to these host and viral reservoir datasets but fails to interpret these complex analyses into (clinically, biologically) interpretable findings. For these reasons, the direct translational take-home message from this work is lost amidst a large list of findings (shown as clusters of associated markers) and sentences such as "this study highlights the utility of machine learning approaches to identify otherwise imperceptible global patterns" - lead to overinterpretation of their data.

Strengths:

Measurement of host immunophenotyping measures (multiparameter flow cytometry) and peripheral HIV reservoir size (IPDA) from 115 PWH on ART.

Major Weaknesses:

(1) Overall, there is little to no interpretability of their machine learning analyses; findings appear as a "laundry list" of parameters with no interpretation of the estimated effect size and directionality of the observed associations. For example, Figure 2 might actually give an interpretation of each X increase in immunophenotyping parameter, we saw a Y increase/decrease in HIV reservoir measure.

(2) The correlations all appear to be relatively weak, with most Spearman R in the 0.30 range or so.

(3) The Discussion needs further work to help guide the reader. The sentence: "The correlative results from this present study corroborate many of these studies, and provide additional insights" is broad. The authors should spend some time here to clearly describe the prior literature (e.g., describe the strength and direction of the association observed in prior work linking PD-1 and HIV reservoir size, as well as specify which type of HIV reservoir measures were analyzed in these earlier studies, etc.) and how the current findings add to or are in contrast to those prior findings.

(4) The most interesting finding is buried on page 12 in the Discussion: "Uniquely, however, CD127 expression on CD4 T cells was significantly inversely associated with intact reservoir frequency." The authors should highlight this in the abstract, and title, and move this up in the Discussion. The paper describes a very high dimensional analysis and the key takeaways are not clear; the more the author can point the reader to the take-home points, the better their findings can have translatability to future follow-up mechanistic and/or validation studies.

(5) The authors should avoid overinterpretation of these results. For example in the Discussion on page 13 "The existence of two distinct clusters of PWH with different immune features and reservoir characteristics could have important implications for HIV cure strategies - these two groups may respond differently to a given approach, and cluster membership may need to be considered to optimize a given strategy." It is highly unlikely that future studies will be performing the breadth of parameters resulting here and then use these directly for optimizing therapy.

(6) There are only TWO limitations listed here: cross-sectional study design and the use of peripheral blood samples. (The subsequent paragraph notes an additional weakness which is misclassification of intact sequences by IPDA). This is a very limited discussion and highlights the need to more critically evaluate their study for potential weaknesses.

(7) A major clinical predictor of HIV reservoir size and decay is the timing of ART initiation. The authors should include these (as well as other clinical covariate data - see #12 below) in their analyses and/or describe as limitations of their study.

Reviewer #3 (Public Review):

Summary:

This valuable study by Semenova and colleagues describes a large cross-sectional cohort of 115 individuals on ART. Participants contributed a single blood sample which underwent IPDA, and 25-color flow with various markers (pre and post-stimulation). The authors then used clustering, decision tree analyses, and machine learning to look for correlations between these immunophenotypic markers and several measures of HIV reservoir volume. They identified two distinct clusters that can be somewhat differentiated based on total HIV DNA level, intact HIV DNA level, and multiple T cell cellular markers of activation and exhaustion.

The conclusions of the paper are supported by the data but the relationships between independent and dependent variables in the models are correlative with no mechanistic work to determine causality. It is unclear in most cases whether confounding variables could explain these correlations. If there is causality, then the data is not sufficient to infer directionality (ie does the immune environment impact the HIV reservoir or vice versa or both?). In addition, even with sophisticated and appropriate machine learning approaches, the models are not terribly predictive or highly correlated. For these reasons, the study is very much hypothesis-generating and will not impact cure strategies or HIV reservoir measurement strategies in the short term.

Strengths:

The study cohort is large and diverse in terms of key input variables such as age, gender, and duration of ART. Selection of immune assays is appropriate. The authors used a wide array of bioinformatic approaches to examine correlations in the data. The paper was generally well-written and appropriately referenced.

Weaknesses:

(1) The major limitation of this work is that it is highly exploratory and not hypothesis-driven. While some interesting correlations are identified, these are clearly hypothesis-generating based on the observational study design.

(2) The study's cross-sectional nature limits the ability to make mechanistic inferences about reservoir persistence. For instance, it would be very interesting to know whether the reservoir cluster is a feature of an individual throughout ART, or whether this outcome is dynamic over time.

(3) A fundamental issue is that I am concerned that binarizing the 3 reservoir metrics in a 50/50 fashion is for statistical convenience. First, by converting a continuous outcome into a simple binary outcome, the authors lose significant amounts of quantitative information. Second, the low and high reservoir outcomes are not actually demonstrated to be clinically meaningful: I presume that both contain many (?all) data points above levels where rebound would be expected soon after interruption of ART. Reservoir levels would also have no apparent outcome on the selection of cure approaches. Overall, dividing at the median seems biologically arbitrary to me.

(4) The two reservoir clusters are of potential interest as high total and intact with low % intact are discriminated somewhat by immune activation and exhaustion. This was the most interesting finding to me, but it is difficult to know whether this clustering is due to age, time on ART, other co-morbidity, ART adherence, or other possible unmeasured confounding variables.

(5) At the individual level, there is substantial overlap between clusters according to total, intact, and % intact between the clusters. Therefore, the claim in the discussion that these 2 cluster phenotypes may require different therapeutic approaches seems rather speculative. That said, the discussion is very thoughtful about how these 2 clusters may develop with consideration of the initial insult of untreated infection and / or differences in immune recovery.

(6) The authors state that the machine learning algorithms allow for reasonable prediction of reservoir volume. It is subjective, but to me, 70% accuracy is very low. This is not a disappointing finding per se. The authors did their best with the available data. It is informative that the machine learning algorithms cannot reliably discriminate reservoir volume despite substantial amounts of input data. This implies that either key explanatory variables were not included in the models (such as viral genotype, host immune phenotype, and comorbidities) or that the outcome for testing the models is not meaningful (which may be possible with an arbitrary 50/50 split in the data relative to median HIV DNA volumes: see above).

(7) The decision tree is innovative and a useful addition, but does not provide enough discriminatory information to imply causality, mechanism, or directionality in terms of whether the immune phenotype is impacting the reservoir or vice versa or both. Tree accuracy of 80% is marginal for a decision tool.

(8) Figure 2: this is not a weakness of the analysis but I have a question about interpretation. If total HIV DNA is more predictive of immune phenotype than intact HIV DNA, does this potentially implicate a prior high burden of viral replication (high viral load &/or more prolonged time off ART) rather than ongoing reservoir stimulation as a contributor to immune phenotype? A similar thought could be applied to the fact that clustering could only be detected when applied to total HIV DNA-associated features. Many investigators do not consider defective HIV DNA to be "part of the reservoir" so it is interesting to speculate why these defective viruses appear to have more correlation with immunophenotype than intact viruses.

(9) Overall, the authors need to do an even more careful job of emphasizing that these are all just correlations. For instance, HIV DNA cannot be proven to have a causal effect on the immunophenotype of the host with this study design. Similarly, immunophenotype may be affecting HIV DNA or the correlations between the two variables could be entirely due to a separate confounding variable.

(10) In general, in the intro, when the authors refer to the immune system, they do not consistently differentiate whether they are referring to the anti-HIV immune response, the reservoir itself, or both. More specifically, the sentence in the introduction listing various causes of immune activation should have citations. (To my knowledge, there is no study to date that definitively links proviral expression from reservoir cells in vivo to immune activation as it is next to impossible to remove the confounding possible imprint of previous HIV replication.) Similarly, it is worth mentioning that the depletion of intact proviruses is quite slow such that provial expression can only be stimulating the immune system at a low level. Similarly, the statement "Viral protein expression during therapy likely maintains antigen-specific cells of the adaptive immune system" seems hard to dissociate from the persistence of immune cells that were reactive to viremia.

(11) Given the many limitations of the study design and the inability of the models to discriminate reservoir volume and phenotype, the limitations section of the discussion seems rather brief.

Reviewer #1 (Public Review):

Summary:

The current study aims to quantify associations between the regular use of proton-pump inhibitors (PPI) - defined as using PPI most days of the week during the last 4 weeks at one cross-section in time - with several respiratory outcomes up to several years later in time. There are 6 respiratory outcomes included: risk of influenza, pneumonia, COVID-19, other respiratory tract infections, as well as COVID-19 severity and mortality).

Strengths:

Several sensitivity analyses were performed, including i) estimation of the e-value to assess how strong unmeasured confounders should be to explain observed effects, ii) comparison with another drug with a similar indication to potentially reduce (but not eliminate) confounding by indication.

Weaknesses:

(1) The main exposure of interest seems to be only measured at one time-point in time (at study enrollment) while patients are considered many years at risk afterwards without knowing their exposure status at the time of experiencing the outcome. As indicated by the authors, PPI are sometimes used for only short amounts of time. It seems biologically implausible that an infection was caused by using PPI for a few weeks many years ago.

(2) Previous studies have shown that by focusing on prevalent users of drugs, one often induces several biases such as collider stratification bias, selection bias through depletion of susceptible, etc.

(3) It seems Kaplan Meier curves are not adjusted for confounding through e.g. inverse probability weighting. As such the KM curves are currently not informative (or the authors need to make clearer that curves are actually adjusted for measured confounding).

(4) Throughout the manuscript the authors seem to misuse the term multivariate (using one model with e.g. correlated error terms to assess multiple outcomes at once) when they seem to mean multivariable.

(5) Given multiple outcomes are assessed there is a clear argument for accounting for multiple testing, which following the logic of the authors used in terms of claiming there is no association when results are not significant may change their conclusions. More high-level, the authors should avoid the pitfall of stating there is evidence of absence if there is only an absence of evidence in a better way (no statistically significant association doesn't mean no relationship exists).

(6) While the authors claim that the quantitative bias analysis does show results are robust to unmeasured confounding, I would disagree with this. The e-values are around 2 and it is clearly not implausible that there are one or more unmeasured risk factors that together or alone would have such an effect size. Furthermore, if one would use the same (significance) criteria as used by the authors for determining whether an association exists, the required effect size for an unmeasured confounder to render effects 'statistically non-significant' would be even smaller.

(7) Some patients are excluded due to the absence of follow-up, but it is unclear how that is determined. Is there potentially some selection bias underlying this where those who are less healthy stop participating in the UK biobank?

(8) Given that the exposure is based on self-report how certain can we be that patients e.g. do know that their branded over-the-counter drugs are PPI (e.g. guardium tablets)? Some discussion around this potential issue is lacking.

(9) Details about the deprivation index are needed in the main text as this is a UK-specific variable that will be unfamiliar to most readers.

(10) It is unclear how variables were coded/incorporated from the main text. More details are required, e.g. was age included as a continuous variable and if so was non-linearity considered and how?

(11) The authors state that Schoenfeld residuals were tested, but don't report the test statistics. Could they please provide these, e.g. it would already be informative if they report that all p-values are above a certain value.

(12) The authors would ideally extend their discussion around unmeasured confounding, e.g. using the DAGs provided in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832226/, in particular (but not limited to) around severity and not just presence/absence of comorbidities.

(13) The UK biobank is known to be highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. The potential problems this might create in terms of collider stratification bias - as highlighted here for example: https://www.nature.com/articles/s41467-020-19478-2 - should be discussed in greater detail and also appreciated more when providing conclusions.

Reviewer #2 (Public Review):

Summary:

Zeng et al investigate in an observational population-based cohort study whether the use of proton pump inhibitors (PPIs) is associated with an increased risk of several respiratory infections among which are influenza, pneumonia, and COVID-19. They conclude that compared to non-users, people regularly taking PPIs have increased susceptibility to influenza, pneumonia, as well as COVID-19 severity and mortality. By performing several different statistical analyses, they try to reduce bias as much as possible, to end up with robust estimates of the association.

Strengths:

The study comprehensively adjusts for a variety of critical covariates and by using different statistical analyses, including propensity-score-matched analyses and quantitative bias analysis, the estimates of the associations can be considered robust.

Weaknesses:

As it is an observational cohort study there still might be bias. Information on the dose or duration of acid suppressant use was not available, but might be of influence on the results. The outcome of interest was obtained from primary care data, suggesting that only infections as diagnosed by a physician are taken into account. Due to the self-limiting nature of the outcome, differences in health-seeking behavior might affect the results.

Reviewer #1 (Public Review):

The manuscript, "A versatile high-throughput assay based on 3D ring-shaped cardiac tissues generated from human induced pluripotent stem cell-derived cardiomyocytes," developed a unique culture platform with PEG hydrogel that facilitates the in-situ measurement of contractile dynamics of the engineered cardiac rings. The authors optimized the tissue seeding conditions, demonstrated tissue morphology with expressions of cardiac and fibroblast markers, mathematically modeled the equation to derive contractile forces and other parameters based on imaging analysis, and concluded by testing several compounds with known cardiac responses.

The authors answered my questions with appropriate experiments and explanation.

(1) This paper presents an intriguing platform that creates miniature cardiac rings with merely thousands of cardiomyocytes per tissue in a 96-well plate format. The shape of the ring and the squeezing motion can recapitulate the contraction of the cardiac chamber to a certain degree. However, Thavandiran et al. (PNAS 2013) created a larger version of the cardiac ring and found that electrical propagation revealed spontaneous infinite loop-like cycles of activation propagation traversing the ring. This model was used to mimic a reentrant wave during arrhythmia. Therefore, there are concerns about whether a large number of cardiac tissues experience arrhythmia due to geometry-induced re-entry current and cannot be used as a healthy tissue model.

In the new experiment, the authors demonstrated with voltage-sensitive dye that these miniaturized tissues do not experience any arrhythmia, potentially due to their small size.

(2) The platform can produce 21 cardiac rings per well in 96-well plates, with the throughput being the highest among competing platforms. The resulting tissues exhibit good sarcomere striation due to the strain from the pillars. However, emerging questions pertain to culture longevity and reproducibility among tissues. According to Figure 1E, uneven ring formation around the pillar leads to tissue thinning and breakage. Only 50% survival is observed after 20 days of culture in the optimized seeding group. Are there any strategies to improve this survival rate? Additionally, do the cardiac rings detach from the glass slides and roll up, given the two compartments with cardiac and fibroblast-rich regions where fibroblasts maintain attachment to the glass slides? Moreover, the standard deviation of force measurement is a quarter of the value, which is suboptimal given the high replicate number. As the platform utilizes imaging analysis to derive contractile dynamics, calibration based on the angle and distance of the camera lens to individual tissues should be conducted to reduce error. On the other hand, how reproducible are the pillars? It is highly recommended to mechanically evaluate the consistency of the hydrogel-based pillars across different wells and within wells to understand the variance.

The authors stated that the platform has been tested and improved with multiple cell lines to enhance tissue survival rates. The methodology of image capture and calculation of contractile dynamics were explained in detail to address concerns. Moreover, the reproducibility of the pillars was demonstrated by consistent results of Young's Modulus (AFM) from each pillar, showing low standard deviations.

(3) Does the platform allow the observation of non-synchronized beating when testing with compounds? This can be extremely important as the intended applications of this platform are drug testing and cardiac disease modeling. The author should elaborate on the method in the manuscript and explain the obtained results in detail.

Referring to Question #1, the platform does not present arrythmia potentially due to the small size of the tissue.

(4) The results of drug testing are interesting. Isoperenoral is typically causing positive chronotropic and positive inotropic responses, where inotropic responses are difficult to obtain due to low tissue maturity. It is inconsistent with other reported results that cardiac rings do not exhibit increased beating frequency, but slightly increased forces only.

The authors repeated the experiment with the same results and hypothesized that the results would be line-dependent, since the maturation of iPSC-CM is not consistent. The additional dose curves provided more information on the tissue behaviors against well-known compounds.

Overall, the manuscript is well-written, and the designed platform presents unique advantages for high-throughput cardiac tissue culture. The paper has adequate data to demonstrate the proof-of-concept study of the platform. The throughput, consistency of the tissue, and the potential integration of high-throughput automation would be the highlights of this platform.

Reviewer #1 (Public Review):

Thermogenic adipocyte activity associate with cardiometabolic health in humans, but decline with age. Identifying the underlying mechanisms of this decline is therefore highly important.

To address this task, Holman and co-authors present compelling data from their investigations of the effects of two major determinants of thermogenic activity: cold, which induce thermogenic de novo differentiation as well as conversion of dormant thermogenic inguinal adipocytes: and aging, which strongly reduce thermogenic activity. The authors study young and middle-aged mice at thermoneutrality and following cold exposure.

Using linage tracing, the authors conclude that the older group produce less thermogenic adipocytes from progenitor differentiation. However, they found no differences between thermogenic differentiation capacity between the age groups when progenitors are isolated and differentiated in vitro. This finding is consistent with previous findings in humans, demonstrating that progenitor cells derived from dormant perirenal brown fat of humans differentiate into thermogenic adipocytes in vitro. Taken together, this underscores that age-related changes in the microenvironment rather than autonomous alterations in the ASPCs explain the age related decline in thermogenic capacity, This is an important finding in terms of identifying new approaches to switch dormant adipocytes into an active thermogenic phenotype.

To gain insight into the age-related changes, the authors use single cell and single nuclei RNA sequencing mapping of their two age groups, comparing thermoneutral and cold conditions between the two groups. Interestingly, where the literature previously demonstrated that de novo lipogenesis (DNL) occurs in relation to thermogenic activation, the authors show that DNL in fact is activated in a white adipocyte cell type, whereas the beige thermogenic adipocytes form a separate cluster.

Considering recent findings, that adipose tissue contains several subtypes of ASPCs and adipocytes, mapping the changes at single cell resolution following cold intervention provides an important contribution to the field, in particular as an older group with limited thermogenic adaptation is analyzed in parallel with a younger, more responsive group. This model also allowed for detection of microenvironment as a determining factor of thermogenic response.

The use of only two time points (young and middle-aged) along the aging continuum limits the conclusions that can be made on aging as the only driver of the observed differences between the groups. Furthermore, as the authors also discuss, aging is a complex phenotype, and in this case the older mice were heavier and had larger fat depots, which should be taken into consideration when interpreting the data.

In conclusion, this study provides an important resource for further studies, which should investigate how the findings can be translated into humans for reactivation of dormant thermogenic fat and a potential improvement of metabolic health.

Reviewer #2 (Public Review):

This manuscript focused on why aging leads to decreased beiging of white adipose tissue. The authors used an inducible lineage tracing system and provided in vivo evidence that de novo beige adipogenesis from Pdgfra+ adipocyte progenitor cells is blocked during early aging in subcutaneous fat. Single-cell RNA sequencing of adipocyte progenitor cells and in vitro assays showed that these cells have similar beige adipogenic capacities in vitro. Single-cell nucleus RNA sequencing of mature adipocytes indicated that aged mice have more Npr3 high-expressing adipocytes in the subcutaneous fat from aged mice. Meanwhile, adipocytes from aged mice have significantly lower expression of genes involved in de novo lipogenesis, which may contribute to the declined beige adipogenesis.

The mechanism that leads to age-related impairment of white adipose tissue beiging is not very clear. The finding that Pdgfra+ adipocyte progenitor cells contribute to beige adipogenesis is novel and interesting. It is more intriguing that the aging process represses Pdgfra+ adipocyte progenitor cells from differentiating into beige adipocytes during cold stimulation. Mature adipocytes that have high de novo lipogenesis activity may support beige adipogenesis is also novel and worth further pursuing. The study was carried out with a nice experimental design, and the authors provided sufficient data to support the major conclusions. I only have a few comments that could potentially improve the manuscript.

(1) It is interesting that after three days of cold exposure, aged mice also have much fewer beige adipocytes. Is de novo adipogenesis involved at this early stage? Or does the previous beige adipocyte that acquired white morphology have a better "reactivation" in young mice? It would be nice if the author could discuss the possibilities.

(2) Is the absolute number of Pdgfra+ cells decreased in aged mice? It would be nice to include quantifications of the percentage of tomato+ beige adipocytes in total tomato+ cells to reflect the adipogenic rate.