Reviewer #1 (Public Review):<br /> <br /> Summary:

This paper provides a methodology for normative trajectory modeling, using cross-sectional data to set the "norms," and then applying these norms to longitudinal brain observations. An example of schizophrenia trajectories (two time points) is provided. The method assumes a Bayesian mixed effects model, which included some hyperparameters that need to be tuned. The longitudinal assumption is essentially a random intercept model, assuming that the age-based quantiles do not shift, and if they do that is a sign of disease-like trajectories.

Strengths:

Normative modeling of brain feature trajectories is an important topic. Bayesian models are a promising alternative to modeling these. Leveraging large-scale data to provide norms is also potentially useful.

Weaknesses:

The models described are not fundamentally novel, essentially a random intercept model (with a warping function), and some flexible covariate effects using splines (i.e., additive models). The assumption of constant quantiles is very strong, and limits the utility of the model to very short term data. The schizophrenia example leads to a counter-intuitive normalization of trajectories, which leads to suspicions that this is driven by some artifact of the data modeling/imaging pipelines. The method also assumes that the cross-sectional data is from a "healthy population" without describing what this population is (there is certainly every chance of ascertainment bias in large scale studies as well as small scale studies). This issue is completely elided over in the manuscript.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors provide a method aiming to accurately reflect the individual deviation of longitudinal/temporal change compared to the normal temporal change characterized based on pre-trained population normative model (i.e., a Bayesian linear regression normative model), which was built based on cross-sectional data. This manuscript aims to solve a recently identified problem of using normative models based on cross-sectional data to make inferences about longitudinal change.

Although the proposed method was implemented with real data and shown to be more sensitive in capturing the differences confirmed by previous studies than conventional methods, there is still a lack of simulation studies to formally evaluate the performance of the proposed method in making accurate estimations and inferences about the longitudinal changes.

Strengths:

The efforts of this work make a good contribution to addressing an important question of normative modeling. With the greater availability of cross-sectional studies for normative modeling than longitudinal studies, and the inappropriateness of making inferences about longitudinal subject-specific changes using these cross-sectional data-based normative models, it's meaningful to try to address this gap from the perspective of methodological development.

Weaknesses:

• The organization and clarity of this manuscript need enhancement for better comprehension and flow. For example, in the first few paragraphs of the introduction, the wording is quite vague. A lot of information was scattered and repeated in the latter part of the introduction, and the actual challenges/motivation of this work were not introduced until the 5th paragraph.

• There are no simulation studies to evaluate whether the adjustment of the cross-sectional normative model to longitudinal data can make accurate estimations and inferences regarding the longitudinal changes. Also, there are some assumptions involved in the modeling procedure, for example, the deviation of a healthy control from the population over time is purely caused by noise and constant variability of error/noise across x_n, and these seem to be quite strong assumptions. The presentation of this work's method development would be strengthened if the authors can conduct a formal simulation study to evaluate the method's performance when such assumptions are violated, and, ideally, propose some methods to check these assumptions before performing the analyses.

• The proposed "z-diff score" still falls in the common form of z-score to describe the individual deviation from the population/reference level, but now is just specifically used to quantify the deviation of individual temporal change from the population level. The authors need to further highlight the difference between the "z-score" and "z-diff score", ideally at its first mention, in case readers get confused (I was confused at first until I reached the latter part of the manuscript). The z-score can also be called a measure of "standardized difference" which kind of collides with what "z-diff" implies by its name.

• Explaining that one component of the variance is related to the estimation of the model and the other is due to prediction would be helpful for non-statistical readers.

• It would be easier for the non-statistical reader if the authors consistently used precision or variance for all variance parameters. Probably variance would be more accessible.

• The functions psi were never explicitly described. This would be helpful to have in the supplement with a reference to that in the paper.

• What is the goal of equations (13) and (14)? The authors should clarify what the point of writing these equations is prior to showing the math. It seems like it is to obtain an estimate of \sigma_{\ksi}^2, which the reader only learns at the end.

• What is the definition of "adaption" as used to describe equation (15)? In this equation, I think norm on subsample was not defined.

• "(the sandwich part with A)" - maybe call this an inner product so that it is not confused with a sandwich variance estimator. This is a bit unclear. Equation (8) does have the inner product involving A and \beta^{-1} does include variability of \eta. It seems like you mean that equation (8) incorrectly includes variability of \eta and does not have the right term vector component of the inner product involving A, but this needs clarifying.

• One challenge with the z-diff score is that it does not account for whether a person sits above or below zero at the first time point. It might make it difficult to interpret the results, as the results for a particular pathology could change depending on what stage of the lifespan a person is in. I am not sure how the authors would address those challenges.

Reviewer #1 (Public Review):

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

Given that this is one of the first studies to report the mapping of longitudinal intactness of proviral genomes in the globally dominant subtype C, the manuscript would benefit from placing these findings in the context of what has been reported in other populations, for example, how decay rates of intact and defective genomes compare with that of other subtypes where known. While not a primary outcome of the study, the comparisons of peak viremia in the hyperacute and chronic-treated groups may be confounded by the fact that peak viremia may have been pre-empted by early treatment i.e., the true peak was not reached in early-treated individuals. Indeed, in the abstract, the authors indicate that treatment was initiated before the peak. The use of the term 'peak' viremia in the hyperacute-treated group could perhaps be replaced with 'highest recorded viral load'. The statistical comparison of this measure in the two groups is perhaps more relevant with regards to viral burden over time or area under the curve viral load as these are previously reported as correlates of reservoir size. The analysis of clonal expansion of proviral genomes may be limited by higher sequence homogeneity in hyperacute infection i.e., cells with different proviral integration sites may have a higher likelihood of containing identical genomes than chronic infection.

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

Reviewer #2 (Public Review):

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

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

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

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

Reviewer #3 (Public Review):

Summary:

This paper assesses the size and clearance kinetics of proviral HIV DNA (intact and total) in women in South Africa with clade C virus. who started ART at different time points of infection (very early vs late).

Strengths:

The cohort is excellent. The paper is easy to read. The methodology is appropriate. Some conclusions, particularly the differing kinetics of total HIV DNA despite a similar amount of virus in early vs late treated women are novel and thought-provoking. I really enjoyed reading this paper!

Weaknesses:

There are several areas in the paper that could be explicated a bit more accurately with more detailed references to past work.

(1) The word reservoir should not be used to describe proviral DNA soon after ART initiation. It is generally agreed upon that there is still HIV DNA from actively infected cells (phase 1 & 2 decay of RNA) during the first 6-12 months of ART. Only after a full year of uninterrupted ART is it really safe to label intact proviral HIV DNA as an approximation of the reservoir. This should be amended throughout.

(2) All raw, individualized data should be made available for modelers and statisticians. It would be very nice to see the RNA and DNA data presented in a supplementary figure by an individual to get a better grasp of intra-host kinetics.

(3) The legend of Supplementary Figure 2 should list when samples were taken.

Reviewer #1 (Public Review):

In this manuscript, the authors described a computational method catELMo for embedding TCR CDR3 sequences into numeric vectors using a deep-learning-based approach, ELMo. The authors applied catELMo to two applications: supervised TCR-epitope binding affinity prediction and unsupervised epitope-specific TCR clustering. In both applications, the authors showed that catELMo generated significantly better binding prediction and clustering performance than other established TCR embedding methods.

The authors have addressed all of my concerns except for one as following:

5. GIANA's result is like

## TIME:2020-12-14 14:45:14|cmd: GIANA4.py|COVID_test/rawData/hc10s10.txt|IsometricDistance_Thr=7.0|thr_v=3.7|thr_s=3.3|exact=True|Vgene=True|ST=3

## Column Info: CDR3 aa sequence, cluster id, other information in the input file<br /> CAISDGTAASSTDTQYF 1 TRBV10-3*01 6.00384245917387e-05 0.930103216755186 COVID19:BS-EQ-0002-T1-replacement_TCRB.tsv<br /> CAISDGTAASSTDTQYF 1 TRBV10-3*01 4.34559031223066e-05 0.918135389545364 COVID19:BS-EQ-0002-T2-replacement_TCRB.tsv<br /> CANATLLQVLSTDTQYF 2 TRBV21-1*01 3.00192122958694e-05 0.878695260046097 COVID19:BS-EQ-0002-T1-replacement_TCRB.tsv<br /> CANATLLQVLSTDTQYF 2 TRBV21-1*01 1.44853010407689e-05 0.768125375525736 COVID19:BS-EQ-0002-T2-replacement_TCRB.ts<br /> ...

as in its example file at: https://raw.githubusercontent.com/s175573/GIANA/master/data/hc10s10--RotationEncodingBL62.txt

The results directly give the clustering results in the second column, and there is no direct distance metric for hierarchical clustering. Therefore, it is still not clear how the authors conducted the hierarchical clustering on GIANA's results. Did the hierarchical clustering apply to each of the original clusters on the CDR3 distances within the same original cluster?

Reviewer #2 (Public Review):

In the manuscript, the authors highlighted the importance of T-cell receptor (TCR) analysis and the lack of amino acid embedding methods specific to this domain. The authors proposed a novel bi-directional context-aware amino acid embedding method, catELMo, adapted from ELMo (Embeddings from Language Models), specifically designed for TCR analysis. The model is trained on TCR sequences from seven projects in the ImmunoSEQ database, instead of the generic protein sequences. They assessed the effectiveness of the proposed method in both TCR-epitope binding affinity prediction, a supervised task, and the unsupervised TCR clustering task. The results demonstrate significant performance improvements compared to existing embedding models. The authors also aimed to provide and discuss their observations on embedding model design for TCR analysis: 1) Models specifically trained on TCR sequences have better performance than models trained on general protein sequences for the TCR-related tasks; and 2) The proposed ELMo-based method outperforms TCR embedding models with BERT-based architecture. The authors also provided a comprehensive introduction and investigation of existing amino acid embedding methods. Overall, the paper is well-written and well-organized.

The work has originality and has potential prospects for immune response analysis and immunotherapy exploration. TCR-epitope pair binding plays a significant role in T cell regulation. Accurate prediction and analysis of TCR sequences are crucial for comprehending the biological foundations of binding mechanisms and advancing immunotherapy approaches. The proposed embedding method presents an efficient context-aware mathematical representation for TCR sequences, enabling the capture and analysis of their structural and functional characteristics. This method serves as a valuable tool for various downstream analyses and is essential for a wide range of applications.

Reviewer #3 (Public Review):

In this study, Zhang and colleagues proposed an ELMo-based embedding model (catELMo) for TCRβ CDR3 amino acid sequences. They showed the effectiveness of catELMo in both supervised TCR binding prediction and unsupervised clustering, surpassing existing methods in accuracy and reducing annotation costs. The study provides insights on the effect of model architectures to TCR specificity prediction and clustering tasks.

The authors have addressed our prior critiques of the manuscript.

Reviewer #2 (Public Review):

Summary

In this work, Bartolome and colleagues develop a new approach to identify proteasome interacting proteins and substrates. The approach is based on fusing proteasome subunits with a biotin ligase that will label proteins that come in close physical distance of the ligase. These biotin-labeled proteins (or their resulting tryptic peptides) can be affinity purified using streptavidin and identified by mass spectrometry.

This elegant solution was able to identify a large proportion of known proteasome interactors, as well as multiple potential new interactors. Combining this approach with a proteasome inhibitor allowed also for the enrichment of substrates, due to increased contact time between substrates and the proteasome. Again, the authors were able to identify novel substrates. Finally, the authors implemented this strategy in vivo, providing the hints for potential tissue-specific proteasome interactors.<br /> This novel strategy provides an additional approach to identify new proteasome substrates, which can be particularly powerful for low abundant proteins, e.g., transcription factors. The possibility to implement it in vivo in specific cell types opens the possibility for identifying proteasome interactors in small cell subpopulations or in subpopulations involved in disease.

Strengths

The authors carefully characterized their genetically engineered proteasome-biotin ligase fusions to ensure that proteasome structure and activity was not altered. This is key to ensure that the proteins identified to interact with the proteasome reflect interactions that occur under physiological conditions.

The authors implemented an algorithm that controls the false positive rate of the identified interactors of the proteasome. This is an important aspect to avoid spending time on the characterization of potential interactors that are just an artifact of the experimental setup.

The addition of a proteasome inhibitor allowed the authors to identify substrates of the proteasome. Although there are other strategies to do this (e.g., affinity purification of Gly-Gly modified peptides, which is a marker for ubiquitination), this additional approach can highlight currently unknown substrates. One example are low abundance proteins, such as transcription factors.

The overall strategy developed by the authors can be implemented in vivo, which opens for the possibility of determining cell type-specific proteasome interactors (and perhaps substrates).

Weaknesses

There is a proportion (approximately 38%) of the PSMA4-biotin ligase fusion that remains unassembled (i.e., not part of the functional proteasome) and that can contribute to a small proportion of false positive interactions.

Reviewer #3 (Public Review):

Summary:

Bartolome et al. present ProteasomeID, a novel method to identify components, interactors, and (potentially) substrates of the proteasome in cell lines and mouse models. As a major protein degradation machine that is highly conserved across eukaryotes, the proteasome has historically been assumed to be relatively homogeneous across biological scales (with few notable exceptions, e.g., immunoproteasomes and thymoproteasomes). However, a growing body of evidence suggests that there is some degree of heterogeneity in the composition of proteasomes across cell tissues, and can be highly dynamic in response to physiologic and pathologic stimuli. This work provides a methodological framework for investigating such sources of variation. The authors start by adapting the increasingly popular biotin ligation strategy for labelling proteins coming into close proximity with one of three different subunits of the proteasome, before proceeding with PSMA4 for further development and analysis based on their preliminary labelling data. In a series of well-constructed and convincing validation experiments, the authors go on to show that the tagged PSMA4 construct can be incorporated into functional proteasomes, and is able to label a broad set of known proteasome components and interacting proteins in HEK293T cells. They also attempt to identify novel proteasomal degradation substrates with ProteasomeID; while this was convincing for known substrates with particularly short half-lives, the results for substrates with longer half-lives were less clear. One of the most compelling results was from a similar experiment to confirm proteasomal degradation induced by a BRD-targeting PROTAC, which I think is likely to be of keen interest to the targeted degradation community. Finally, the authors establish a ProteasomeID mouse model, and demonstrate its utility across several tissues.

Strengths:

(1) ProteasomeID itself is an important step forward for researchers with an interest in protein turnover across biological scales (e.g., in sub-cellular compartments, in cells, in tissues, and whole organisms). I especially see interest from two communities: those studying fundamental proteostasis in physiological and pathologic processes (e.g., ageing; tissue-specific protein aggregation diseases), and those developing targeted protein degradation modalities (e.g., PROTACs; molecular glues). All the datasets generated and deposited here are likely to provide a rich resource to both. The HEK293T cell line data are a valuable proof-of-concept to allow expansion into more biologically-relevant cell culture settings; however, I envision the greatest innovation here to be the mouse model. For example, in the targeted protein degradation space, two major hurdles in early-stage pre-clinical development are (i) evaluation of degradation efficacy across disease-relevant tissues, and (ii) toxicity and safety implications caused by off-target degradation, e.g., of newly-identified molecular glues and/or in particularly-sensitive tissues. The ProteasomeID mouse allows early in vivo assessment of both these questions. The results of the BRD PROTAC experiment in 293T cells provides an excellent in vitro proof-of-concept for this approach.

(2) The mass-spectrometry-based proteomics workflows used and presented throughout the manuscript are robust, rigorous, and convincing. For example, the algorithm the authors use for defining enrichment score cut-offs are logical and based on rational models, rather than on arbitrary cut-offs that are common for similar proteomics studies. The construction (and subsequent validation) of both BirA*- and miniTurbo- tagged PSMA4 variants also increases the utility of the method, allowing researchers to choose the variant with the labelling time-scale required for their particular research question.

(3) The optimised BioID and TurboID protocol the authors develop (summarised in Fig. S2A) and validate (Fig. S2B-D) is likely to be of broad interest to cell and molecular biologists beyond the protein degradation field, given that proximity labelling is a current gold-standard in global protein:protein interaction profiling.

Limitations:

I think the authors do an excellent job in highlighting the limitations of ProteasomeID throughout the Results and Discussion. I do have some specific comments that might provide additional context for the reader.

(1) The authors do a good job in showing that a substantial proportion of PSMA4-BirA* is incorporated into functional proteasome particles; however, it is not immediately clear to me how much background (false-positive IDs) might be contributed by the ~40 % of PSMA4-BirA* that is not incorporated into the mature core particle (based on the BirA* SEC-MS traces in Fig. 2b and S3b, i.e., the large peak ~ fraction 20). Are there any bands lower down in the native gel shown in Fig. 2c, i.e., corresponding to lower molecular weight complexes or monomeric PSMA4-BirA*? The enrichment of proteasome assembly factors in all the ProteasomeID experiments might suggest the presence of assembly intermediates, which might themselves become substrates for proteasomal degradation (as has been shown for other incompletely-assembled protein complexes, e.g., the ribosome, TRiC/CCT).

(2) Although the authors attempt to show that BirA* tagging of PSMA4 does not interfere with proteasome activity (Fig. 2e-f), I think the experimental evidence for this is incomplete. They show that the overall chymotrypsin-like activity (attributable to PSMB5) in cells expressing PSMA4-BirA* is not markedly reduced compared with control BirA*-expressing cells. However, they do not show that the activity of the specific proteasome sub-population that contains PSMA4-BirA* is unaffected (e.g., by purifying this sub-population via the Flag tag). The proteasome activity of the sub-population of wild-type proteasome complexes that do not contain the PSMA4-BirA* (~50%, based on the earlier immunoblots) could account for the entire chymotrypsin-like activity-especially in the context of HEK293T cells, where steady-state proteasome levels are unlikely to be limiting. It would also be useful to assess any changes in tryspin- and caspase- like activities, especially as tagging of PSMA4 could conceivably interfere with the activity of some PSMB subunits, but not others.

(3) I was left slightly unsure as to the general utility of ProteasomeID for identifying novel proteasomal substrates in homeostatic conditions--especially for proteins with longer half-lives. The cycloheximide chases in Fig. 4g/S4j are clear for MYC and TIGD5 (which have short half-lives), but are not so clear for ARMC6 and BRAT1: the reduction in the bands are modest, and might have been clearer with longer "chase" time-points. Furthermore, classifying candidates based on enrichment following proteasome inhibition with MG-132 have the potential to lead to a high number of false positives. ProteasomeID's utility in identifying potential substrates in more targeted settings (e.g., molecular glues, off-target PROTAC substrates) is far more apparent.

Reviewer #1 (Public Review):

Summary:

This paper by Gao et al. describes the effect of capsaicin on the NRF2/KEAP1 pathway. The authors carried out a set of in vitro experiments that addressed the mechanisms of the protective effect of capsaicin on ethanol-induced cytotoxicity. They also conducted in vivo studies in rats focusing on ethanol-induced gastric mucosal oxidative damage. The authors conclude that capsaicin activates NRF2, which leads to the induction of cytoprotective genes, preventing oxidative damage. This effect has already been shown, and it is well established that capsaicin activates NRF2, but what can be novel in the paper is the demonstration that capsaicin may directly bind to KEAP1 and that it is a noncovalent modification of the Kelch domain. The authors also designed new albumin-coated capsaicin nanoparticles, which were tested for the therapeutic effect in vivo. Apart from novelty concerns, the manuscript may be potentially interesting, but in my opinion, it is not fully technically sound, which weakens the strength of the evidence.

Major concerns:

For studies investigating capsaicin binding to KEAP1, the authors used capsaicin concentrations that are toxic to cells (Figures S1D and 4F, G). In vivo studies were performed only in 3 rats per group. The T-test was used for the comparison of more than two groups. Given the well-known issues with the specificity of the NRF2 antibody, the authors should provide appropriate controls, especially for IF and IHC staining.

Reviewer #2 (Public Review):

Summary:

In this paper, the authors wanted to show that capsaicin can disrupt the interaction between Keap1 and Nrf2 by directly binding to Keap1 at an allosteric site. The resulting stabilization of Nrf2 would protect CAP-treated gastric cells from alcohol-induced redox stress and damage as well as inflammation (both in vitro and in vivo).

Strengths:

One major strength of the study is the use of multiple methods (CoIP, SPR, BLI, deuterium exchange MS, CETSA, MS simulations, target gene expression) that consistently show for the first time that capsaicin can disrupt the Nrf2/Keap1 interaction at an allosteric site and lead to stabilization and nuclear translocation of Nrf2.

Weaknesses:

One major weakness of the study is that plausibility is taken as proof for causality. The finding that capsaicin directly binds to Keap1 and releases Nrf2 from its fate of degradation (in vitro) is taken for granted as the sole explanation for the observed improved gastric health upon alcohol exposure (in vivo). There is no consideration or exclusion of any potential unrelated off-target effect of capsaicin, or proteins other than Nrf2 that are also controlled by Keap1.

Another point that hampers full appreciation of the capsaicin effect in cells is that capsaicin is not investigated alone, but mostly in combination with alcohol only.

Bottom Line:

Overall, the authors are convincing that capsaicin (although weakly) binds to Keap1 and releases Nrf2 from degradation. With this, the authors provide a significant finding with marked relevance for the redox/Nrf2 as well as natural products /hit discovery communities. Moreover, the employed toolbox of different complementary methodologies can set the bar for future PPI inhibitor studies. The translation of this novel finding in a biological setting (alcohol-stressed gastric cells) still leaves some open questions and concerns. These concerns mainly arise from lacking control experiments and/or somewhat biased conclusions from the obtained data sets.

Reviewer #3 (Public Review):

Summary:

The paper by Gao et al. describes that capsaicin (CAP) might act as a novel NRF2 agonist capable of suppressing ethanol (EtOH)-induced oxidative damage in the gastric mucosa by disrupting the KEAP1-NRF2 interaction. Initially, the authors established and validated a cell model for EtOH-induced oxidative stress which they used to experiment with different CAP concentrations and to determine changes in a variety of parameters such as cell morphology, ROS production, status of redox balance to mitochondrial function, amongst others.

The proposed mechanism by which CAP activates NRF2 and mitigates oxidative stress is thought to be via non-covalent binding to the Kelch domain of KEAP1. A variety of assays such as BLI, CETSA, Pull-down, Co-IP, and HDX-MS were employed to investigate the KEAP1 binding behavior of CAP both in vitro and in GES1 cells. Consequently, the authors developed in vivo nanoparticles harboring CAP and tested those in a rat model. They found that pretreatment with the CAP-nanoparticles led to significant upregulation of NRF2 and subsequent effects on pro- (suppression of IL-1β, TNF-α, IL-6, and CXCL1) and anti-inflammatory (activation of IL-10) cytokines pointing to a resolved state of inflammation and oxidative stress.

Strengths:

The work comprises a comprehensive approach with a variety of in vitro assays as well as cell culture experiments to investigate CAP binding behaviour to KEAP1. In addition, the authors employ in vivo validation by establishing an ethanol-induced acute gastric mucosal damage rat model and providing evidence of the potential therapeutic effect of CAP.

The study further provides novel insights into the mode of CAP action by elucidating the mechanism by which CAP promotes NRF2 expression and downstream antioxidant target gene activation.

The design of IR-Dye800 modified albumin-coated CAP nanoparticles for enhanced drug solubility and delivery efficiency demonstrates a valuable practical application of the research findings.

In summary, the study's findings suggest that CAP could be a safe and novel NRF2 agonist with implications for the development of lead drugs for oxidative stress-related diseases. Collectively, the data support the significance and potential impact of CAP as a therapeutic agent for oxidative stress-related conditions.

Weaknesses:

While the study provides valuable insights into the molecular mechanisms and in vivo effects of CAP, further clinical studies are needed to validate its efficacy and safety in human subjects. The study primarily focuses on the acute effects of CAP on ethanol-induced gastric mucosa damage. Long-term studies are necessary to assess the sustained therapeutic effects and potential side effects of CAP treatment.

Furthermore, the study primarily focuses on the interaction between CAP and the KEAP1-NRF2 axis in the context of ethanol-induced gastric mucosa damage. It may be beneficial to explore the broader effects of CAP on other pathways or conditions related to oxidative stress. CAP has been known for its interaction with the Transient Receptor Potential Vanilloid type 1 (TRPV1) channel and subsequent NRF2 signaling pathway activation. Those receptors are also expressed within the gastric mucosa and could potentially cross-react with CAP leading to the observed outcome. Including experiments to investigate this route of activation could strengthen the present study.

While the design of CAP nanoparticles is innovative, further research is needed to optimize the nanoparticle formulation for enhanced efficacy and targeted delivery to specific tissues.

Addressing these weaknesses through additional research and clinical trials can strengthen the validity and applicability of CAP as a therapeutic agent for oxidative stress-related conditions.

Reviewer #1 (Public Review):

The authors build on their previous study that showed the midgut microbiome does not oscillate in Drosophila. Here, they focus on metabolites and find that these rhythms are in fact microbiome-dependent. Tests of time-restricted feeding, a clock gene mutant, and diet reveal additional regulatory roles for factors that dictate the timing and rhythmicity of metabolites. The study is well-written and straightforward, adding to a growing body of literature that shows the time of food consumption affects microbial metabolism which in turn could affect the host.

Some additional questions and considerations remain:

(1) The main finding that the microbiome promotes metabolite rhythms is very interesting. Which microbiota are likely to be responsible for these effects? The author's previous work in this area may shed light on this question. Are specific microbiota linked to some of the metabolic pathways investigated in Figure 5?

(2) TF increases the number of rhythmic metabolites in both microbiome-containing and abiotic flies in Figure 1. This is somewhat surprising given that flies typically eat during the daytime rather than at night, very similar to TF conditions. I would have assumed that in a clock-functioning animal, the effect of restricting food availability should not make a huge difference in the time of food consumption, and thus downstream impacts on metabolism and microbiome. Can the authors measure food intake directly to compare the ad-lib vs TF flies to see if there are changes in food intake? Would restricting feeding to other times of day shift the timing of metabolites accordingly?

(3) In Figure 2, Per loss of function reveals a change in the phase of rhythmic metabolites. In addition, the effect of the microbiome on these is very different = The per mutants show increased numbers of rhythmic metabolites when the microbiome is absent, unlike the controls. Is it possible that these changes are due to altered daily feeding rhythms in per mutants? Testing the time and amount of food consumed by the per mutant flies would address this question. Would TF in the per mutants rescue their metabolite rhythms and make them resemble clock-functioning controls?

(4) The calorie content of each diet - normal vs high protein vs high-sugar are different. The possibility of a calorie effect rather than a difference in nutrition (protein/carbohydrate) should be discussed. Another issue worth considering is the effect of high protein/sugar on the microbiome itself. While the microbiome doesn't seem to affect rhythms in the high-protein diet, the high-sugar diet seems highly microbiome-dependent in Supplementary Fig 8C vs D. Does the diet impact the microbiome and thus metabolite rhythmicity downstream?

(5) It would be good if a supplementary table was provided outlining the specific metabolites that are shown in the radial plots. It is not clear if the rhythms shown in the figures refer to the same metabolites peaking at the same time, or rather the overall abundance of completely different metabolites. This information would be useful for future research in this area.

Reviewer #2 (Public Review):

Summary:

The paper addresses several factors that influence daily changes in concentration of metabolites in the Drosophila melanogaster gut. The authors describe metabolomes extracted from fly guts at four time-points during a 24-hour period, comparing profiles of primary metabolites, lipids, and biogenic amines. The study elucidates that the percentage of metabolites that exhibit a circadian cycle, peak phases of their increased appearance, and the cycling amplitude depends on the combination of factors (microbiome status, composition or timing of the diet, circadian clock genotype). Multiple general conclusions based on the data obtained with modern metabolomics techniques are provided in each part of the article. Descriptive analysis of the data supports the finding that microbiome increases the number of metabolites for which concentration oscillates during the day period. Results of the experiments show that timed feeding significantly enhanced metabolite cycling and changed its phase regardless of the presence of a microbiome. The authors suggest that the host circadian rhythm modifies both metabolite cycling period and the number of such metabolites.

Strengths:

The obvious strength of the study is the data on circadian cycling of the detected 843, 4510, and 4330 total primary metabolites, lipids, and biogenic amines respectively in iso31 flies and 623, 2245, and 2791 respective metabolites in per01 mutants. The comparison of the abundance of these metabolites, their cycling phase, and the ratio of cycling/non-cycling metabolites is well described and illustrated. The conditions tested represent significant experimental interest for contemporary chronobiology: with/without microbiota, wild-type/mutant period gene, ad libitum/time-restricted feeding, and high-sugar/high-protein diet. The authors conclude that the complex interaction between these factors exists, and some metabolic implications of combinations of these factors can be perceived as reminiscent of metabolic implications of another combination ("...the microbiome and time-restricted feeding paradigms can compensate for each other, suggesting that different strategies can be leveraged to serve organismal health"). Enrichment analysis of cycling metabolites leads to an interesting suggestion that oscillation of metabolites related to amino acids is promoted by the absence of microbiota, alteration of circadian clock, and time-restricted feeding. In contrast, association with microbiota induces oscillation of alpha-linolenic acid-related metabolites. These results provide the initial step for hypothesising about functional explanations of the uncovered observations.

Weaknesses:

Among the weaknesses of the study, one might point out too generalist interpretations of the results, which propose hypothetical conclusions without their mechanistic proof. The quantitative indices analysed are obviously of particular interest, however are not self-explaining and exhaustive. More specific biological examples would add valuable insights into the results of this study, making conclusions clearer. More specific comments on the weaknesses are listed below:

(1) The criterion of the percentage of cycling metabolites used for comparisons has its own limitations. It is not clear, whether the cycling metabolites are the same in the guts with/without microbiota, or whether there are totally different groups of metabolites that cycle in each condition. GO enrichment analysis gives only a partial assessment, but is still not quantitative enough.

(2) The period of cycling data is based on only 4 time points during 24 hours in 4 replicates (>200 guts per replicate) on the fifth day of the experiment (10-12-day-old adults). It does not convincingly prove that these metabolites cycle the following days or more finely within the day. Moreover, it is not clear how peaks in polar histogram plots were detected in between the timepoints of ZT0, ZT6, ZT12, and ZT18.

(3) Average expression and amplitude are analysed for groups of many metabolites, whereas the data on distinct metabolites is hidden behind these general comparisons. This kind of loss of information can be misleading, making interpretation of the mentioned parameters quite complicated for authors and their readers. Probably more particular datasets can be extracted to be discussed more thoroughly, rather than those general descriptions.

(4) The metabolites' preservation is crucial for this type of analysis, and both proper sampling plus normalisation require more attention. More details about measures taken to avoid different degradation rates, different sizes of intestines, and different amounts of microbes inside them will be beneficial for data interpretation.

(5) The data in the article describes formal phenomena, not directly connected with organism physiology. The parameters discussed obviously depend on the behaviour of flies. Food consumption, sleep, and locomotor activity could be additionally taken into account.

(6) Division of metabolites into three classes limits functional discussion of found differences. Since the enrichment analysis provided insights into groups of metabolites of particular interest (for example, amino acid metabolism), a comparison of their cycling characteristics can be shown separately and discussed.

Reviewer #3 (Public Review):

Summary:

The authors. sought to quantify the influence of the gut microbiome on metabolite cycling in a Drosophila model with extensive metabolomic profiling over a 24-hour period. The major strength of the work is the production of a large dataset of metabolites that can be the basis for hypothesis generation for more specific experiments. There are several weaknesses that make the conclusions difficult to evaluate. Additional experiments to quantify food intake over time will be required to determine the direct role of the microbiome in metabolite cycling.

Strengths:

An extensive metabolomic dataset was collected with treatments designed to determine the influence of the gut microbiome on metabolite circadian cycling.

Weaknesses:

(1) The major strength of this study is the extensive metabolomic data, but as far as I can tell, the raw data is not made publicly available to the community. The presentation of highly processed data in the figures further underscores the need to provide the raw data (see comment 3).

(2) Feeding times heavily influence the metabolome. The authors use timed feeding to constrain when flies can eat, but there is no measurement of how much they ate and when. That needs to be addressed.

Since food is the major source of metabolites, the timing of feeding needs to be measured for each of the treatment groups. In the previous paper (Zhang et al 2023 PNAS), the feeding activity of groups of 4 male flies was measured for the wildtype flies. That is not sufficient to determine to what extent feeding controls the metabolic profile of the flies. Additionally, timed feeding opportunities do not equate to the precise time of feeding. They may also result in dietary restriction, leading to the loss of stress resistance in the TF flies. The authors need to measure food consumption over time in the exact conditions under which transcriptomic and metabolomic cycling are measured. I suggest using the EX-Q assay as it is much less effort than the CAFE assay and can be more easily adapted to the rearing conditions of the experiments.

(3) The data on the cycling of metabolites is presented in a heavily analyzed form, making it difficult to evaluate the validity of the findings, particularly when a lack of cycling is detected. The normalization to calculate the change in cycling due to particular treatments is particularly unclear and makes me question whether it is affecting the conclusions. More presentation of the raw data to show when cycling is occurring versus not would help address this concern, as would a more thorough explanation of how the normalization is calculated - the brief description in the methods is not sufficient.

For instance, the authors state that "timed feeding had less effect on flies containing a microbiome relative to sterile flies." One alternative interpretation of that result is that both treatments are cycling but that the normalization of one treatment to the other removes the apparent effect. This concern should be straightforward to address by showing the raw data for individual metabolites rather than the group.

Reviewer #3 (Public Review):

This study was focused on the conserved mechanisms across the Transmembrane Channel/Scramblase superfamily, which includes members of the TMEM16, TMEM63/OSCA, and TMC families. The authors show that the introduction of lysine residues at the TM4-TM6 interface can disrupt gating and confer scramblase activity to non-scramblase proteins. Specifically, they show this to be true for conserved TM4 residues across TMEM16F, TMEM16A, OSCA1.2, and TMEM63A proteins. This breadth of data is a major strength of the paper and provides strong evidence for an underlying linked mechanism for ion conduction and phospholipid transport. Overall, the confocal imaging experiments, patch clamping experiments, and data analysis are performed well.

However, there are several concerns regarding the scope of experiments supporting some claims in the paper. Although the authors propose that the TM4/TM6 interface is critical to ion conduction and phospholipid scramblase activity, in each case, there is very narrow evidence of support consisting of 1-3 lysine substitutions at specific residues on TM4. Given that the authors postulate that the introduction of a positive charge via the lysine side chain is essential to the constitutive activity of these proteins, additional mutation controls for side chain size (e.g. glutamine/methionine) or negative charge (e.g. glutamic acid), or a different positive charge (i.e. arginine) would have strengthened their argument. To more comprehensively understand the TM4/TM6 interface, mutations at locations one turn above and one turn below could be studied until there is no phenotype. In addition, the equivalent mutations on the TM6 side should be explored to rule out the effects of conformational changes that arise from mutating TM4 and to increase the strength of evidence for the importance of side-chain interactions at the TM6 interface. The experiments for OSCA1.2 osmolarity effects on gating and scramblase in Figure 4 could be improved by adding different levels of osmolarity in addition to time in the hypotonic solution.

Reviewer #1 (Public Review):

Summary:

TMEM16, OSCA/TMEM63, and TMC belong to a large superfamily of ion channels where TMEM16 members are calcium-activated lipid scramblases and chloride channels, whereas OSCA/TMEM63 and TMCs are mechanically activated ion channels. In the TMEM16 family, TMEM16F is a well-characterized calcium-activated lipid scramblase that plays an important role in processes like blood coagulation, cell death signaling, and phagocytosis. In a previous study, the group demonstrated that lysine mutation in TM4 of TMEM16A can enable the calcium-activated chloride channel to permeate phospholipids too. Based on this they hypothesize that the energy barrier for lipid scramblase in these ion channels is low, and that modification in the hydrophobic gate region by introducing a charged side chain between the TM4/6 interface in TMEM16 and OSCA/TMEM63 family can allow lipid scramblase. In this manuscript, using scramblase activity via Annexin V binding to phosphatidylserine, and electrophysiology, the authors demonstrate that lysine mutation in TM4 of TMEM16F and TMEM16A can cause constitutive lipid scramblase activity. The authors then go on to show that analogous mutations in OSCA1.2 and TMEM63A can lead to scramblase activity.

Strengths:

Overall, the authors introduce an interesting concept that this large superfamily can permeate ions and lipids.

Weaknesses:

The electrophysiology data does not entirely support their claims.

Reviewer #2 (Public Review):

This concise and focused study by Lowry and colleagues identifies a motif in the pores of three families of channel/scramblase proteins that regulate exclusive ion permeation and lipid transport. These three ion channel families, which include the TMEM16s, the plant-expressed and stress-gated cation channel OSCA, and the mammalian homolog and mechanosensitive cation channel, TMEM63 share low sequence similarity between them and have seemingly differing functions, as anion (TMEM16s), or stress-activated cation channels (OSCA/TMEM63). The study finds that in all three families, mutating a single hydrophobic residue in the ion permeation pathway of the channels confers lipid transport through the pores of the channels, indicating that TMEM16 and the related OSCA and TMEM63 channels have a conserved potential for both ion and lipid permeation. The authors interpret the findings as revealing that these channel/scramblase proteins have a relatively low "energetic barrier for scramblase" activity. The experiments themselves seem to be done with a high level of rigor and the paper is well written. A weakness is the limited scope of the experiments which, if fixed, could open up a new line of inquiry.

Reviewer #1 (Public Review):

Summary:

In this work by Wang et al., the authors use single-molecule super-resolution microscopy together with biochemical assays to quantify the organization of Nipah virus fusion protein F (NiV-F) on cell and viral membranes. They find that these proteins form nanoscale clusters which favors membrane fusion activation, and that the physical parameters of these clusters are unaffected by protein expression level and endosomal cleavage. Furthermore, they find that the cluster organization is affected by mutations in the trimer interface on the NiV-F ectodomain and the putative oligomerization motif on the transmembrane domain, and that the clusters are stabilized by interactions among NiV-F, the AP2-complex, and the clathrin coat assembly. This work improves our understanding of the NiV fusion machinery, which may have implications also for our understanding of the function of other viruses.

Strengths:

The conclusions of this paper are well-supported by the presented data. This study sheds light on the activation mechanisms underlying the NiV fusion machinery.

Weaknesses:

The authors provide limited details of the convolutional neural network they developed in this work. Even though custom-codes are made available, a description of the network and specifications of how it was used in this work would aid the readers in assessing its performance and applicability. The same holds for the custom-written OPTICS algorithm. Furthermore, limited details are provided for the imaging setup, oxygen scavenging buffer, and analysis for the single-molecule data, which limits reproducibility in other laboratories. The claim of 10 nm resolution is not backed up by data and seems low given the imaging conditions and fluorophores used. Fourier Ring Correlation analysis would have validated this claim. If the authors refer to localization precision rather than resolution, then this should be specified and appropriate data provided to support this claim.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Wang and co-workets employ single molecule light microscopy (SMLM) to detect Nipah virus Fusion protein (NiV-F) in the surface of cells. They corroborate that these glycoproteins form microclusters (previously seen and characterized together with the NiV-G and Nipah Matrix protein by Liu and co-workers (2018) also with super-resolution light microscopy). Also seen by Liu and coworkers the authors show that the level of expression of NiV-F does not alter the identity of these microclusters nor endosomal cleavage. Moreover, mutations and the transmembrane domain or the hexamer-of-trimer interface seem to have a mild effect on the size of the clusters that the authors quantified. Importantly, it has also been shown that these particles tend to cluster in Nipah VLPs.

Strengths:

The authors have tried to perform SMLM in single VLPs and have shown partially the importance of NiV-F clustering.

Weaknesses:

The labelling strategy for the NiV-F is not sufficiently explained. The use of a FLAG tag in the extracellular domain should be validated and compared with the unlabelled WT NiV-F when expressed in functional pseudoviruses (for example HIV-1 based particles decorated with NiV-F). This experiment should also be carried out for both infection and fusion (including BlaM-Vpr as a readout for fusion). I would also suggest to run a time-of-addition BlaM experiment to understand how this particular labelling strategy affects single virion fusion as compared to the the WT. It would also be very important to compare the FLAG labelling approach with recent advances in the field (for instance incorporating noncanonical amino acids (ncAAs) into NiV-F by amber stop-codon suppression, followed by click chemistry).

The correlation between the existence of microclusters of a particular size and their functionality is missing. Only cell-cell fusion assays are shown in supplementary figures and clearly, single virus entry and fusion cannot be compared with the biophysics of cell-cell fusion. Not only the environment is completely different, membrane curvature and the number of NiV-F drastically varies also. Therefore, specific fusion assays (either single virus tracking and/or time-of-addition BlaM kinetics with functional pseudoviruses) are needed to substantiate this claim.

The authors also claim they could not characterize the number of NiV-F particles per cluster. Another technique such as number and brightness (Digman et al., 2008) could support current SMLM data and identify the number of single molecules per cluster. Also, this technology does not require complex microscopy apparatus. I suggest they perform either confocal fluorescence fluctuation spectroscopy or TIRF-based nandb to validate the clusters and identify how many molecule are present in these clusters. Also, it is not clear how many cells the authors employ for their statistics (at least 30-50 cells should be employed and not consider the number of events blinking events). I hope the authors are not considering only a single cell to run their stats... The differences between the mutants and the NiV-F is minor even if their statistical analyses give a difference (they should average the number and size of the clusters per cell for a total of 30-50 cells with experiments performed at least in three different cells following the same protocol). They should also compare the level of expression (with the number of molecules per cell provided by number and brightness) with the total number of clusters. Overall, it seems that the authors have only evaluated a very low number of cells.

The same applies to the VLP assay. I assume the authors have only taken VLPs expressing both NiV-M and NiV-F (and NiV-G). But even if this is not clearly stated I would urge the authors to show how many viruses were compared per condition (normally I would expect 300 particles per condition coming from three independent experiments). As a negative control to evaluate the cluster effect I would mix the different conditions. Clearly you have clusters with all conditions and the differences in clustering depending on each condition are minimal. Therefore you need to increase the n for all experiments.

Reviewer #3 (Public Review):

Summary:

The manuscript by Wang and colleagues describes single molecule localization microscopy to quantify the distribution and organization of Nipah virus F expressed on cells and on virus-like particles. Notably the crystal structure of F indicated hexameric assemblies of F trimers. The authors propose that F clustering favors membrane fusion.

Strengths:

The manuscript provides solid data on imaging of F clustering with the main findings of:<br /> - F clusters are independent of expression levels<br /> - Proteolytic cleavage does not affect F clustering<br /> - Mutations that have been reported to affect the hexamer interface reduce clustering on cells and its distribution on VLPs<br /> - - F nanoclusters are stabilized by AP

Weaknesses:

The relationship between F clustering and fusion is per se interesting, but looking at F clusters on the plasma membrane does not exclude that F clustering occurs for budding. Many viral glycoproteins cluster at the plasma membrane to generate micro domains for budding. This does not exclude that these clusters include hexamer assemblies or clustering requires hexamer assemblies.<br /> Assuming that the clusters are important for entry, hexameric clusters are not unique to Nipah virus F. Similar hexameric clusters have been described for the HEF on influenza virus C particles (Halldorsson et al 2021) and env organization on Foamy virus particles (Effantin et al 2016), both with specific interactions between trimers. What is the organization of F on Nipah virus particles? If F requires to be hexameric for entry, this should be easily imaged by EM on infectious or inactivated virus particles.<br /> AP stabilization of the F clusters is curious if the clusters are solely required for entry? Virus entry does not recruit the clathrin machinery. Is it possible that F clusters are endocytosed in the absence of budding?

Other points:<br /> Fig. 3: Some of the V108D and L53D clusters look similar in size than wt clusters. It seems that the interaction is important but not absolutely essential? Would a double mutant abrogate clustering completely?<br /> Fig. 4: The distribution of F on VLPs should be confirmed by cryoEM analyses. This would also confirm the symmetry of the clusters.

The manuscript by Chernomordik et al. JBC 2004 showed that influenza HA outside the direct contact zone affects fusion, which could be further elaborated in the context of F clusters and the fusion mechanism.

Reviewer #1 (Public Review):

Summary:

The study "Endogenous oligomer formation underlies DVL2 condensates and promotes Wnt/β-catenin signaling" by Senem Ntourmas et al. contributes to the understanding of phase separation in Dishevelled (DVL) proteins, specifically focusing on DVL2. It builds upon existing research by investigating the endogenous complexes of DVL2 using ultracentrifugation and contrasting them with DVL1 and DVL3 behavior. The study identifies a DVL2-specific region involved in condensate formation and introduces the "two-step" concept of DVL2 condensate formation, enriching the field's knowledge.

Strengths:

A notable strength of this study is the validation of endogenous DVL2 complexes, providing insights into its behavior compared to DVL1 and DVL3. The functional validation of the DVL C-terminus (here termed conserved domain 2 (CD2) and the identification of DVL2-specific regions (here termed LCR4) involved in condensate formation are significant contributions that complement the current knowledge on the importance of DVL DIX domain, DEP domain and intrinsically disordered regions between DIX and PDZ domains. Additionally, the introduction of the concept where oligomerization (step 1) precedes condensate formation (step 2) is an interesting hypothesis, which can be further experimentally challenged in the future.

Weaknesses:

However, the applicability of the findings to full-length DVL2 protein, hence the physiological relevance, is limited. This is mostly due to the fact that the authors almost completely depend on the set of DVL2 mutants, which lack the (i) DEP domain and (ii) nuclear export signal (NES). These variants fail to establish DEP domain-mediated interactions, including those with FZD receptors. Of note, the DEP domain itself represents a dimerization/tetramerization interface, which could affect the protein condensate formation of these mutants. Possibly even more importantly, the used mutants localize into the nucleus, which has different biochemical & biophysical properties than a cytoplasm, where DVL typically reside, which in turn affects the condensate formation. On top, in the nucleus, most of the DVL binding partners, including relevant kinases, which were reported to affect protein condensate formation, are missing.

Second, the use of an overexpression system, while suitable for comparing DVL2 protein condensate features, falls short in functional assays. The study could benefit from employing established "rescue systems" using DVL1/2/3 knockout cells and re-expression of DVL variants for more robust functional assessments.

Furthermore, the discussion and introduction overlook some essential aspects of DVL biology. One such example is the importance of the open/close conformation of DVL and its effects on DVL phase separation and activity. In the context of this study, it is important to say that this conformational plasticity is mediated by DVL C-terminus (CD2 in this study). The second example is the reported roles of DVL1 and DVL3, which can both mediate the Wnt3a signal. How this can be interpreted when DVL1 and DVL3 lack LCR4 and still form condensates?

In order to increase the physiological relevance of the study, I would recommend analyzing several key mutants in the context of the full-length DVL2 protein using the rescue/complementation system. Further, a more thorough discussion and connections with the existing literature on DVL protein condensates/puncta/LLPS can improve the impact of the study.

Reviewer #2 (Public Review):

Summary:

The authors aimed to identify which regions of DVL2 contribute to its endogenous/basal clustering, as well as the relevance of such domains to condensate/phase separation and WNT activation.

Strengths:

A strength of the study is the focus on endogenous DVL2 to set up the research questions, as well as the incorporation of various techniques to tackle it. I found also quite interesting that DVL2-CFR addition to DVL1 increased its MW in density gradients.

Weaknesses:

I think that several of the approaches of the manuscript are subpar to achieve the goals and/or support several of the conclusions. For example:

(1) Although endogenous DVL2 indeed seems to form complexes (Figure 1A), neither the number of proteins involved nor whether those are homo-complexes can be determined with a density gradient. Super-resolution imaging or structural analyses are needed to support these claims.

(2) Follow-up analyses of the relevance of the DVL2 domains solely rely on overexpressed proteins. However, there were previous questions arising from o/e studies that prompted the focus on endogenous, physiologically relevant DVL interactions, clustering, and condensate formation. Although the title, conclusions, and relevance all point to the importance of this study for understanding endogenous complexes, only Figures 1A and B deal with endogenous DVL2.

(3) Mutants lacking activity/complex formation, e.g. DVL2_1-418, may need further validation. For instance, DVL2_1-506 (same mutant but with DEP) seems to form condensates and it is functional in WNT signalling (King et al., 20223). These differences could be caused by the lack of DEP domain in this particular construct and/or folding differences.

(4) The key mutants, DeltaCFR and VV/FF only show mild phenotypes. The authors' results suggest that these regions contribute but are not necessary for 1) complex formation (Density gradient Figures 7A and B), condensate formation (Figures 7C and D), and WNT activity (Figure 7E). Of note Figure 7C shows examples for the mutants with no condensates while the qualification indicates that 50% of the cells do have condensates.

(5) Most of the o/e analyses (including all reporter assays) should be performed in DVL1-3 KO cells in order to explore specifically the behaviour of the investigated mutants.

(6) How comparable are condensates found in the cytoplasm (usually for wt DVL) with those located in the nucleus (DEP mutants)?

Several studies in the last two decades have analysed the relevance of DVL homo - and hetero-clustering by relying on overexpressed proteins. Recent studies also explored the possibility of DVL undergoing liquid-liquid phase separation following similar principles. As highlighted by the authors in the introduction, there is a need to understand DVL dynamics under endogenous/physiological conditions. Recent super-resolution studies aimed at that question by characterising endogenously edited DVL2. The authors seemed to aim in the same direction with their initial findings (Figure 1A) but quickly moved to o/e proteins without going back to the initial question. This reviewer thinks that to support their conclusions and advance in this important question, the authors should introduce the relevant mutations in the endogenous locus (e.g. by Cas9+ donor template encoding the required 3' exons, as done by others before for WNT components, including DVL2) and determine their impact in the above-indicated processes.

Reviewer #1 (Public Review):

Summary:

In this study, a chromosome-level genome of the rose-grain aphid M. dirhodum was assembled with high quality, and A-to-I RNA-editing sites were systematically identified. The authors then demonstrated that: 1) Wing dimorphism induced by crowding in M. dirhodum is regulated by 20E (ecdysone signaling pathway); 2) an A-to-I RNA editing prevents the binding of miR-3036-5p to CYP18A1 (the enzyme required for 20E degradation), thus elevating CYP18A1 expression, decreasing 20E titer, and finally regulating the wing dimorphism of offspring.

Strengths:

The authors present both genome and A-to-I RNA editing data. An interesting finding is that a A-to-I RNA editing site in CYP18A1 ruin the miRNA binding site of miR-3036-5p. And loss of miR-3036-5p regulation lead to less 20E and winged offspring.

Weaknesses:

How crowding represses the miR-3036-5p is still unclear.

Reviewer #2 (Public Review):

Summary:

Environmental influences on development are ubiquitous, affecting many phenotypes in organisms. However molecular genetic and cellular mechanisms transducing environmental signals are still only barely understood. This study examines part of one such intracellular mechanism in a polyphenic (or dimorphic) aphid.

Strengths:

While other published reports have linked phenotypic plasticity to RNA editing before, this study reports such an interaction in insects. The study uses a wide array of molecular tools to identify connections upstream and downstream of the RNA editing to elucidate the regulatory mechanism, which is illuminating.

Weaknesses:

While this system is intriguing, this report does not foster confidence in its conclusions. Many of the analyses seem based on very small sample sizes. It is itself problematic that sample sizes are not obvious in most figures, although based on Methods section covering RNAseq, they seem to be either 3, 6 or 9, depending on whether stages were pooled, but that point is not made clear. With such small sample sizes, statistical tests of any kind are unreliable. Besides the ambiguity on sample sizes, it's unclear what error bars or whiskers show in plots throughout this study. When sample sizes are small estimates of variance are not reliable. Student's t-test is not appropriate for comparisons with such small sample sizes. Presently, it is not possible to replicate the tests shown in Figures 3, 4 and 6. (Besides the HT-seq reads, other data should also be made publicly available, following the journal's recommendations.) Regardless, effect sizes in some comparisons (Fig 3J, 4A-C, 6E,H) are clearly not large, making confidence in conclusions low. The authors should be cautious about over-interpreting these data.

Reviewer #1 (Public Review):

This manuscript presents an extremely exciting and very timely analysis of the role that the nucleosome acidic patch plays in SWR1-catalyzed histone exchange. Intriguingly, SWR1 loses activity almost completely if any of the acidic patches are absent. To my knowledge, this makes SWR1 the first remodeler with such a unique and pronounced requirement for the acidic patch. The authors demonstrate that SWR1 affinity is dramatically reduced if at least one of the acidic patches is absent, pointing to a key role of the acidic patch in SWR1 binding to the nucleosome. The authors also pinpoint a specific subunit - Swc5 - that can bind nucleosomes and engage the acidic patch and obtain a cryo-EM structure of Swc5 bound to a nucleosome. They also identify a conserved arginine-rich motif in this subunit that is critical for nucleosome binding and histone exchange in vitro and for SWR1 function in vivo. The authors provide evidence that suggests a direct interaction between this motif and the acidic patch.

Strengths:

The manuscript is well-written and the experimental data are of outstanding quality and importance for the field. This manuscript significantly expands our understanding of the fundamentally important and complex process of H2A.Z deposition by SWR1 and would be of great interest for a broad readership.

Reviewer #1 (Public Review):

Summary:

Zhao and colleagues employ Drosophila nephrocytes as a model to investigate the effects of a high-fat diet on these podocyte-like cells. Through a highly focused analysis, they initially confirm previous research in their hands demonstrating impaired nephrocyte function and move on to observe the mislocalization of a slit diaphragm-associated protein (pyd). Employing a reporter construct, they identify the activation of the JAK/STAT signaling pathway in nephrocytes. Subsequently, the authors demonstrate the involvement of this pathway in nephrocyte function from multiple angles, using a gain-of-function construct, silencing of an inhibitor, and ectopic overexpression of a ligand. Silencing the effector Stat92E via RNAi or inhibiting JAK/STAT with Methotrexate effectively restored impaired nephrocyte function induced by a high-fat diet, while showing no impact under normal dietary conditions.

Strengths:

The findings establish a link between JAK/STAT activity and the impact of a high-fat diet on nephrocytes. This nicely underscores the importance of organ crosstalk for nephrocytes and supports a potential role for JAK/STAT in diabetic nephropathy, as previously suggested by other models.

Weaknesses:

The analysis is overly reliant on tracer endocytosis and single lines. Immunofluorescence of slit diaphragm proteins would provide a more specific assessment of the phenotypes.

Reviewer #2 (Public Review):

Summary:

In their manuscript, Zhao et al. describe a link between JAK-STAT pathway activation in nephrocytes on a high-fat diet. Nephrocytes are the homologs to mammalian podocytes and it has been previously shown, that metabolic syndrome and obesity are associated with worse outcomes for chronic kidney disease. A study from 2021 (Lubojemska et al.) could already confirm a severe nephrocyte phenotype upon feeding Drosophila a high-fat diet and also linking lipid overflow by expressing adipose triglyceride lipase in the fat body to nephrocyte dysfunction. In this study, the authors identified a second pathway and mechanism, how lipid dysregulation impact on nephrocyte function. In detail, they show activation of JAK-STAT signaling in nephrocytes upon feeding them a high-fat diet, which was induced by Upd2 expression (a leptin-like hormone) in the fat body, and the adipose tissue in Drosophila. Further, they could show genetic and pharmacological interventions can reduce JAK-STAT activation and thereby prevent the nephrocyte phenotype in the high-fat diet model.

Strengths:

The strength of this study is the combination of genetic tools and pharmacological intervention to confirm a mechanistic link between the fat body/adipose tissue and nephrocytes. Inter-organ communication is crucial in the development of several diseases, but the underlying mechanisms are only poorly understood. Using Drosophila, it is possible to investigate several players of one pathway, here JAK-STAT. This was done, by investigating the functional role of Hop, Socs36E, and Stat92E in nephrocytes and has also been combined with feeding a high-fat diet, to assess restoration of nephrocyte function by inhibiting JAK-STAT signaling. Adding a translational approach was done by inhibiting JAK-STAT signaling with methotrexate, which also resulted in attenuated nephrocyte dysfunction. Expression of the leptin-like hormone upd2 in the fat body is a good approach to studying inter-organ communication and the impact of other organs/tissue on nephrocyte function and expands their findings from nephrocyte function towards whole animal physiology.

Weaknesses:

Although the general findings of this study are of great interest, there are some weaknesses in the study, which should be addressed. Overall, the number of flies investigated for the majority of the experiments is very low (6 flies) and it is not clear whether the flies used, are from independent experiments to exclude problems with food/diet. For the analysis, the mean values of flies should be calculated, as one fly can be considered a biological replicate, but not all individual cells. By increasing the number of flies investigated, statistical analysis will become more solid. In addition, the morphological assessment is rather preliminary, by only using a Pyd antibody. Duf or Sns should be visualized as well, also the investigation of the different transgenic fly strains studying the importance of JAK-STAT signaling in nephrocytes needs to include a morphological assessment. Moreover, the expected effect of feeding a high-fat diet on nephrocytes needs to be shown (e.g. by lipid droplet formation) and whether upd2 is actually increased here should also be assessed. The time points of assessment vary between 1, 3, and 7 days and should be consistent throughout the study or the authors should describe why they use different time points.

Reviewer #2 (Public Review):

This work deals with a very difficult physical problem: relating the assembly of building blocks on a molecular scale to the appearance of large, macroscopic assemblies. This problem is particularly difficult to treat, because of the large number of units involved, and of the complex way in which these units-monomers-interact with each other and with the solvent. In order to make the problem treatable, the authors recur to a number of approximations: Among these, there is the assumption that the system is spatially homogeneous, i.e., its features are the same in all regions of space. In particular, the homogeneity assumption may not hold in biologically relevant systems such as cells, where the behavior close to the cell membrane may strongly differ from the one in the bulk. As a result, this hypothesis calls for a cautious consideration and interpretation of the results of this work. Another notable simplification introduced by the authors is the assumption that the system can only follow two possible behaviors: In the first, each monomer interacts equally with the solvent; no matter the size of the cluster of which it is part. In the second case, monomers in the bulk of a cluster and monomers at the assembly boundary interact with the solvent in a different way. These two cases are considered not only because they simplify the problem, but also because they are inspired by biologically relevant proteins.

With these simplifications, the authors trace the phase diagram of the system, characterizing its phases for different fractions of the volume occupied by the monomers and solvent, and for different values of the temperature. The results qualitatively reproduce some features observed in recent experiments, such as an anomalous distribution of cluster sizes below the system saturation threshold, and the gelation of condensed phases above such threshold.

Reviewer #1 (Public Review):

Summary:

The authors present a mean-field model that describes the interplay between (protein) aggregation and phase separation. Different classes of interaction complexity and aggregate dimensionality are considered, both in calculations concerning (equilibrium) phase behavior and kinetics of assembly formation.

Strengths:

The present work is, although purely theoretical, of high interest to understanding biological processes that occur as a result of a coupling between protein aggregation and phase separation. Of course, such processes are abundant, in the living cell as well as in in-vitro experiments. I appreciate the consideration of aggregates with various dimensionality, as well as the categorization into different "interaction classes", together with the mentioning of experimental observations from biology. The model is convincing and underlines the complexity associated with the distribution of proteins across phases and aggregates in the living cell.

Weaknesses:

There are a few minor weaknesses.

Reviewer #3 (Public Review):

Summary:

The authors combine classical theories of phase separation and self-assembly to establish a framework for explaining the coupling between the two phenomena in the context of protein assemblies and condensates. By starting from a mean-field free energy for monomers and assemblies immersed in solvent and imposing conditions of equilibrium, the authors derive phase diagrams indicating how assemblies partition into different condensed phases as temperature and the total volume fraction of proteins are varied. They find that phase separation can promote assembly within the protein-rich phase, providing a potential mechanism for spatial control of assembly. They extend their theory to account for the possibility of gelation. They also create a theory for the kinetics of self-assembly within phase separated systems, predicting how assembly size distributions change with time within the different phases as well as how the volumes of the different phases change with time.

Strengths:

The theoretical framework that the authors present is an interesting marriage of classic theories of phase separation and self-assembly. Its simplicity should make it a powerful general tool for understanding the thermodynamics of assembly coupled to phase separation, and it should provide a useful framework for analyzing experiments on assembly within biomolecular condensates.

The key advance over previous work is that the authors now account for how self-assembly can change the boundaries of the phase diagram.

A second interesting point is the explicit theoretical consideration for the possibility that gelation (i.e. self-assembly into a macroscopic aggregate) could account for widely observed solidification of condensates. While this concept has been broadly discussed, to date I have yet to see a rigorous theoretical analysis of the possibility.

The kinetic theory in sections 5 and 6 is also interesting as it extends on previous work by considering the kinetics of phase separation as well as those of self-assembly.

Weaknesses:

A key point the authors make about their theory is that it allows, as opposed to previous research, to study non-dilute limits. It is true that they consider gelation when the 3D assemblies become macroscopic. However, dilute solution theory assumptions seem to be embedded in many aspects of their theory, and it is not always clear where else the non-dilute limits are considered. Is it in the inter-species interaction \chi_{ij}? Why then do they never explore cases for which \chi_{ij} is nonzero in their analysis?

The connection between this theory and biological systems is described in the introduction but lost along the main text. It would be very helpful to point out, for instance, that the presence of phase separation might induce aggregation of proteins. This point is described formally at the end of Section 3, but a more qualitative connection to biological systems would be very useful here.

Building on the previous point, it would be helpful to give an intuitive sense of where the equations derived in the Appendices and presented in the main text come from and to spell out clear physical interpretations of the results. For example, it would be helpful to point out that Eq. 4 is a form of the law of mass action, familiar from introductory chemistry.

It would be useful to better explain how the current work extends on existing previous work from these authors as well as others. Along these lines, closely related work by W. Jacobs and B. Rogers [O. Hedge et al. 2023, https://arxiv.org/abs/2301.06134; T. Li et al. 2023, https://arxiv.org/abs/2306.13198] should be cited in the introduction.

The results discussed in the first paragraph of Section 3 on assembly size distributions in a homogeneous system are well-known from classic theories of self-assembly. This should be acknowledged and appropriate references should be added; see for instance Rev. Mod. Phys. 93, 025008 and Statistical Thermodynamics Of Surfaces, Interfaces, And Membranes by Sam Safran.

Equation 14 for the kinetic of volume fractions is given with a reference to Bauermann et al 2022, but it should be accompanied by a better intuitive interpretation of its terms in the main text. In particular, how should one understand the third term in this equation? Why does the change in volume impact the change of volume fraction in this way?

The discussion in the last paragraph of Section 6 should be clarified. How can the total amount of protein in both phases decrease? This would necessarily violate either mass or volume conservation. Also, the discussion of why the volume is non-monotonic in time is not clear.

Reviewer #1 (Public Review):

Using a combination of cutting-edge high-resolution approaches (expansion microscopy, SIM, and CLEM) and biochemical approaches (in vitro translocation of actin filaments, cargo uptake assays, and drug treatment), the authors revisit previous results about TbMyo1 and TbACT in the bloodstream form (BSF) of Trypanosoma brucei. They show that a great part of the myosin motor is cytoplasmic but the fraction associated with organelles is in proximity to the endosomal system. In addition, they show that TbMyo1 can move actin filaments in vitro and visualize for the first time this actomyosin system using specific antibodies, a "classical" antibody for TbMyo1, and a chromobody for actin. Finally, using latrunculin A, which sequesters G-actin and prevents F-actin assembly, the authors show the delocalization and eventually the loss of the filamentous actin signal as well as the concomitant loss of the endosomal system integrity. However, they do not assess the localization of TbMyo1 in the same conditions.

Overall the work is well conducted and convincing. The conclusions are not over-interpreted and are supported by the experimental results.

Reviewer #2 (Public Review):

Summary:

The study by Link et al. advances our understanding of the actomyosin system in T. brucei, focusing on the role of TbMyo1, a class I myosin, within the parasite's endosomal system. Using a combination of biochemical fractionation, in vitro motility assays, and advanced imaging techniques such as correlative light and electron microscopy (CLEM), this paper demonstrates that TbMyo1 is dynamically distributed across early and late endosomes, the cytosol, is associated with the cytoskeleton, and a fraction has an unexpected association with glycosomes. Notably, the study shows that TbMyo1 can translocate actin filaments at velocities suggesting an active role in intracellular trafficking, potentially higher than those observed for similar myosins in other cell types. This work not only elucidates the spatial dynamics of TbMyo1 within T. brucei but also suggests its broader involvement in maintaining the complex architecture of the endosomal network, underscoring the critical role of the actomyosin system in a parasite that relies on high rates of endocytosis for immune evasion.

Strengths:

A key strength of the study is its exceptional rigor and successful integration of a wide array of sophisticated techniques, such as in vitro motility assays, and advanced imaging methods, including correlative light and electron microscopy (CLEM) and immuno-electron microscopy. This combination of approaches underscores the study's comprehensive approach to examining the ultrastructural organization of the trypanosome endomembrane system. The application of functional data using inhibitors, such as latrunculin A for actin depolymerization, further strengthens the study by providing insights into the dynamics and regulatory mechanisms of the endomembrane system. This demonstrates how the actomyosin system contributes to cellular morphology and trafficking processes. Furthermore, the discovery of TbMyo1 localization to glycosomes introduces a novel aspect to the potential roles of myosin I proteins within the cell, particularly in the context of organelles analogous to peroxisomes. This observation not only broadens our understanding of myosin I functionality but also opens up new avenues for research into the cellular biology of trypanosomatids, marking a significant contribution to the field.

Weaknesses:

Certain limitations inherent in the study's design and scope render the narrative incomplete and make it challenging to reach definitive conclusions. One significant limitation is the reliance on spatial association data, such as colocalization of TbMyo1 with various cellular components-or the absence thereof-to infer functional relationships. Although these data suggest potential interactions, the authors do not confirm functional or direct physical interactions.

While TbMyo1's localization is informative, the authors do not directly demonstrate its biochemical or mechanical activities in vivo, leaving its precise role in cellular processes speculative. Direct assays that manipulate TbMyo1 levels, activity, and/or function, coupled with observations of the outcomes on cellular processes, would provide more definitive evidence of the protein's specific roles in T. brucei. A multifaceted approach, including genetic manipulations, uptake assays, kinetic trafficking experiments, and imaging, would offer a more robust framework for understanding TbMyo1's roles. This comprehensive approach would elucidate not just the "what" and "where" of TbMyo1's function but also the "how" and "why," thereby deepening our mechanistic insights into T. brucei's biology.

Reviewer #3 (Public Review):

Summary:

In this work, Link and colleagues have investigated the localization and function of the actomyosin system in the parasite Trypanosoma brucei, which represents a highly divergent and streamlined version of this important cytoskeletal pathway. Using a variety of cutting-edge methods, the authors have shown that the T. brucei Myo1 homolog is a dynamic motor that can translocate actin, suggesting that it may not function as a more passive crosslinker. Using expansion microscopy, iEM, and CLEM, the authors show that MyoI localizes to the endosomal pathway, specifically the portion tasked with internalizing and targeting cargo for degradation, not the recycling endosomes. The glycosomes also appear to be associated with MyoI, which was previously not known. An actin chromobody was employed to determine the localization of filamentous actin in cells, which was correlated with the localization of Myo1. Interestingly, the pool of actomyosin was not always closely associated with the flagellar pocket region, suggesting that portions of the endolysomal system may remain at a distance from the sole site of parasite endocytosis. Lastly, the authors used actin-perturbing drugs to show that disrupting actin causes a collapse of the endosomal system in T. brucei, which they have shown recently does not comprise distinct compartments but instead a single continuous membrane system with subdomains containing distinct Rab markers.

Strengths:

Overall, the quality of the work is extremely high. It contains a wide variety of methods, including biochemistry, biophysics, and advanced microscopy that are all well-deployed to answer the central question. The data is also well-quantitated to provide additional rigor to the results. The main premise, that actomyosin is essential for the overall structure of the T. brucei endocytic system, is well supported and is of general interest, considering how uniquely configured this pathway is in this divergent eukaryote and how important it is to the elevated rates of endocytosis that are necessary for this parasite to inhabit its host.

Weaknesses:

(1) Did the authors observe any negative effects on parasite growth or phenotypes like BigEye upon expression of the actin chromobody?

(2) The Garcia-Salcedo EMBO paper cited included the production of anti-actin polyclonal antibodies that appeared to work quite well. The localization pattern produced by the anti-actin polyclonals looks similar to the chromobody, with perhaps a slightly larger labeling profile that could be due to differences in imaging conditions. I feel that the anti-actin antibody labeling should be expressly mentioned in this manuscript, and perhaps could reflect differences in the F-actin vs total actin pool within cells.

(3) The authors showed that disruption of F-actin with LatA leads to disruption of the endomembrane system, which suggests that the unique configuration of this compartment in T. brucei relies on actin dynamics. What happens under conditions where endocytosis and endocyctic traffic is blocked, such as 4 C? Are there changes to the localization of the actomyosin components?

(4) Along these lines, the authors suggest that their LatA treatments were able to disrupt the endosomal pathway without disrupting clathrin-mediated endocytosis at the flagellar pocket. Do they believe that actin is dispensable in this process? That seems like an important point that should be stated clearly or put in greater context.

Reviewer #1 (Public Review):

As outlined in my previous public review, Yeo et al. revised the current neuronal intoxication model, common to all serotypes of botulinum neurotoxins. Using a combination of genetic and imaging approaches, they demonstrate that upon internalization, BoNT/A-containing endosomes undergo retro-axonally trafficking to the neuronal soma. Within the soma, this particular serotype then traffics to the endoplasmic reticulum (ER) via the Golgi apparatus. At the ER, the SEC61 translocon complex facilitates the translocation of BoNT/A's metalloprotease domain (light chain, LC) from the ER lumen into the cytosol, where the thioredoxin reductase/thioredoxin system and HSP complexes release and refold the catalytic LC. Subsequently, the LC diffuses and cleaves SNAP25 first in the soma before reaching neurites and synapses.

Although I still acknowledge the well-executed and thoroughly analyzed genome-wide RNAi screen, I must once again highlight significant pitfalls and weaknesses in the paper due to the lack of essential controls and validations. Consequently, I suggest readers to approach the authors' findings with caution, as they may be limited to the combination of one specific cellular model and genetic engineering tools. During the revision process, authors declined to conduct additional experiments that could have strengthened their main conclusions. These include, but are not limited to:

(1) Investigating weather in the newly generated cell line Red-SNAPR, the GFP fragment produced upon toxin cleavage degrades more rapidly in the soma compared to axon terminals, possibly due to differences in proteasome activity in these two compartments.

(2) Validating toxin cleavage activity in the soma before reaching synapses by conducting an additional and more physiological approach, a time course experiment using native BoNT/A and staining BoNT/A-cleaved SNAP25 with specific antibodies.

(3) Assessing whether the addition of mNG1-11 to the LC affects the translocation process itself and quantifying the mean fluorescence intensity (MFI) per cell, taking into consideration the amount of HA-tagged Cyt-mG1-10, which appears predominantly expressed in the cytosol and less detected in neurites. This raises the question of potential bias toward the cell soma in this assay.

(4) Validating major hits (e.g., VPS34 and Sec61) by performing WB or IF analysis to test the cleavage of endogenous SNAP25.

Additionally, during the revision process, the authors raised concerns about the level of scrutiny applied by this reviewer, particularly in comparison to the seminal study of Lilia K. Koriazova & Mauricio Montal published in Nature Structural Biology (PMID: 12459720). In this 2003 paper, Montal's lab pioneered the use of single-channel recordings and substrate proteolysis analysis to reconstitute the translocation of BoNT/A light chain protease across an artificial lipid bilayer via the channel formed by its heavy chain. The authors highlighted that, when converting the experimental conditions from the aforementioned paper into molarity, it appears that the cis compartment was loaded with 10−8 M BoNT/A, and the reported translocated protease activity (measured by substrate cleavage) is equivalent to 10−17 M. This implies that only about 1 LC molecule in 100 million has crossed the membrane. The calculation performed by authors is indeed accurate. However, readers should be informed about another piece of information present in the same paper that might help them to clarify this important point. Koriazova & Montal, by discussing this experiment, have pointed out that this value (10−17 M) corresponds to ≈3600 LC molecules, a number closed to the maximum number of channels that can be formed under the used experimental conditions. Indeed, from the same paper, quotation: 'This number is in close agreement with the maximum number of channels inserted in the bilayer under the assay condition, ≈2000 (Fig. 3a), as estimated from macroscopic membrane conductance ∼1 × 105 pS and γ = 50 pS measured in 0.1 M KCl'. Another aspect that Yeo et al. forgot to mention in their rebuttal letter is that the system used by Koriazova & Montal lacks any chaperones in the trans compartment. Nowadays, we know that upon translocation, the refolding of the L chain is aided by Hsp90 (Azarnia Tehran et al., Cellular microbiology, 2017). Keeping this in mind, is not unrealistic to hypothesize that the number of LC molecules calculated more than 22 years ago by Koriazova & Montal (in an indirect way by checking SNAP25 cleavage using an ELISA-based assay) might be an underestimation. Indeed, the addition of Hsp90 in their system might aid in the refolding of LC molecules that, even if they have successfully be translocated, might not cleave the substrate due to their unfolded state.

As active scientist, I understand the challenges of peer review and publication, which can often be slow and frustrating involving seemingly endless rounds of review. Therefore, I am in favor of the new eLife publishing model. Indeed, this paper has already been published as Reviewed Preprints and will soon be declared as the final Version of Record, accompanied by this public review. Having said that, I hope that the readers of this journal and future scientists will prove me wrong. I hope they will engage with this paper, providing comments, validations (which are currently missing), and citations as frequently as they did for the seminal works of Koriazova & Montal.

Reviewer #2 (Public Review):

Summary:

The study by Yeo and co-authors addresses a long-lasting issue about botulinum neurotoxin (BoNT) intoxication. The current view is that the toxin binds to its receptors at the axon terminus by its HCc domain and is internalized in recycled neuromediator vesicles just after release of the neuromediators. Then, the HCn domain assists the translocation of the catalytic light chain (LC) of the toxin through the membrane of these endocytic vesicles into the cytosol of the axon terminus. There, the LC cleaves its SNARE substrate and blocks neurosecretion. However, other views involving kinetic aspects of intoxication suggest that the toxin follows the retrograde axonal transport up to the nerve cell body and then back to the nerve terminus before cleaving its substrate.

In the current study, the authors claim that the BoNT/A (isotype A of BoNT) not only progresses to the cell body but once there, follows the retrograde transport trafficking pathway in a retromer-dependent fashion, through the Golgi apparatus, until reaching the endoplasmic reticulum. Next, the LC dissociates from the HC (a process not studied here) and uses the translocon Sec61 machinery to retro-translocate into the cytosol. Only then, the LC traffics back to the nerve terminus following the anterograde axonal transport. Once there, LC cleaves its SNARE substrate (SNAP25 in the case of BoTN/A) and blocks neurosecretion.

To reach their conclusion, Yeo and co-authors use a combination of engineered tools: a cell line able to differentiate into neurons (ReNcell VN), a reporter dual fluorescent protein derived from SNAP25, the substrate of BoNT/A (called SNAPR), the use of either native BoNT/A or a toxin to which three fragment 11 of the reporter fluorescent protein Neon Green (mNG) are fused to the N-terminus of the LC (BoNT/A-mNG11x3), and finally ReNcell VN transfected with mNG1-10 (a protein consisting of the first 10 beta strands of the mNG).

SNAPR is stably expressed all over in the ReNcell VN. SNAPR is yellow (red and green) when intact and becomes red only when cleaved by BoNT/A LC, the green tip being degraded by the cell. When the LC of BoNT/A-mNG11x3 reaches the cytosol in ReNcell VN transfected by mNG1-10, the complete mNG is reconstituted and emits a green fluorescence.

In the first experiment, the authors show that the catalytic activity of the LC appears first in the cell body of neurons where SNAPR is cleaved first. This phenomenon starts 24 h after intoxication and progresses along the axon towards the nerve terminus during an additional 24 h. In a second experiment, the authors intoxicate the ReNcell VN transfected by mNG1-10 using the BoNT/A-mNG11x3. The fluorescence appears also first in the soma of neurons, then diffuses in the neurites in 48 h. The conclusion of these two experiments is that translocation occurs first in the cell body and that the LC diffuses in the cytosol of the axon in an anterograde fashion.

In the second part of the study, the authors perform a siRNA screen to identify regulators of BoNT/A intoxication. Their aim is to identify genes involved in intracellular trafficking of the toxin and translocation of the LC. Interestingly, they found positive and negative regulators of intoxication. Regulators could be regrouped according to the sequential events of intoxication. Genes affecting binding to the cell-surface receptor (SV2) and internalization. Genes involved in intracellular trafficking. Genes involved in translocation such as reduction of the disulfide bond linking the LC to the HC and refolding in the cytosol. Genes involved in signaling such as tyrosine kinases and phosphatases. All these groups of genes may be consistent with the current view of BoNT intoxication within the nerve terminus. However, two sets of genes were particularly significant to reach the main conclusion of the work and definitely constitute an original finding important to the field. One set of genes consists in those of the retromer, the other relates to the Sec61 translocon. This should indicate that once endocytosed, the BoNT traffics from the endosomes to Golgi apparatus, then to the ER. Ultimately, the LC should translocate from the ER lumen to the cytosol using the Sec61 translocon. The authors further control that the SV2 receptor for the BoNT/A traffics along the axon in a retromer-dependent fashion and that BoNT/A-mNG11x3 traverses the Golgi apparatus by fusing the mNG1-10 to a Golgi resident protein.

Strengths:

The findings in this work are convincing. The experiments are carefully done and are properly controlled. In the first part of the study, both the activity of the LC is monitored together with the physical presence of the toxin. In the second part of the work, the most relevant genes that came out of the siRNA screen are checked individually in the ReNcell VN / BoNT/A reporter system to confirm their role in BoNT/A trafficking and retro-translocation.<br /> These findings are important to the fields of toxinology and medical treatment of neuromuscular diseases by BoNTs. They may explain some aspects of intoxication such as slow symptom onset, aggravation and appearance of central effects.

Weaknesses:

The findings antagonize the current view of the intoxication pathway that is sustained by a vast amount of observations. The findings are certainly valid, but their generalization as the sole mechanism of BoNT intoxication should be tempered. These observations are restricted to one particular neuronal model and engineered protein tools. Other models such as isolated nerve/muscle preparations display nerve terminus paralysis within minutes rather than days. Also, the tetanus neurotoxin (TeNT), which mechanism of action involving axonal transport to the posterior ganglia in the spinal cord is well described, takes between 5 and 15 days. It is thus possible that different intoxication mechanisms co-exist for BoNTs or even vary depending on the type of neurons.

Although the siRNA experiments are convincing, it would be nice to reach the same observations with drugs affecting the endocytic to Golgi to ER transport (such as Retro-2, golgicide or brefeldin A) and the Sec61 retrotranslocation (such as mycolactone). Then, it would be nice to check other neuronal systems for the same observations.

Reviewer #3 (Public Review):

Summary:

The manuscript by Yeo et al. investigates the intracellular trafficking of Botulinum neurotoxin A (BoNT/A), a potent toxin used in clinical and cosmetic applications. Contrary to the prevailing understanding of BoNT/A translocation into the cytosol, the study suggests a retrograde migration from the synapse to the soma-localized Golgi in neurons. Using a genome-wide siRNA screen in genetically engineered neurons, the researchers identify over three hundred genes involved in this process. The study employs organelle-specific split-mNG complementation, revealing that BoNT/A traffics through the Golgi in a retromer-dependent manner before moving to the endoplasmic reticulum (ER). The Sec61 complex is implicated in the retro-translocation of BoNT/A from the ER to the cytosol. Overall, the research challenges the conventional model of BoNT/A translocation, uncovering a complex route from synapse to cytosol for efficient intoxication. The findings are based on a comprehensive approach, including the introduction of a fluorescent reporter for BoNT/A catalytic activity and genetic manipulations in neuronal cell lines. The conclusions highlight the importance of retrograde trafficking and the involvement of specific genes and cellular processes in BoNT/A intoxication.

Strengths:

The major part of the experiments are convincing. They are well-controlled and the interpretation of their results is balanced and sensitive.

Weaknesses:

To my opinion, the main weakness of the paper is that all experiments are performed using a single cellular system (RenVM neurons), as stated in the title. It is therefore unclear at the moment to what extent the findings in this paper can be generalized to other neuronal cell models / in vivo situation.

Reviewer #1 (Public Review):

Summary:

The authors profile gene expression, chromatin accessibility, and chromosomal architecture (by Hi-C) in activated CD4 T cells and use this information to link non-coding variants associated with autoimmune diseases with putative target genes. They find over 1000 genes physically linked with autoimmune disease loci in these cells, many of which are upregulated upon T cell activation. Focusing on IL2, they dissect the regulatory architecture of this locus, including the allelic effects of GWAS variants. They also intersect their variant-to-gene lists with data from CRISPR screens for genes involved in CD4 T cell activation and expression of inflammatory genes, finding enrichments for regulators. Finally, they showed that pharmacological inhibition of some of these genes impacts T-cell activation.

This is a solid study that follows a well-established canvas for variant-to-gene prioritisation using 3D genomics, applying it to activated T cells. The authors go some way in validating the lists of candidate genes, as well as exploring the regulatory architecture of a candidate GWAS locus. Jointly with data from previous studies performing variant-to-gene assignment in activated CD4 T cells (and other immune cells), this work provides a useful additional resource for interpreting autoimmune disease-associated genetic variation.

Suggestions for improvement:

Autoimmune disease variants were already linked with genes in CD28-stimulated CD4 T cells using chromosome conformation capture, specifically Promoter CHi-C and the COGS pipeline (Javierre et al., Cell 2016; Burren et al., Genome Biol 2017; Yang et al., Nat Comms 2020). The authors cite these papers and present a comparative analysis of their variant-to-gene assignments (in addition to scRNA-seq eQTL-based assignments). Furthermore, they find that the Burren analysis yields a higher enrichment for gold standard genes.

The obvious question that the authors don't venture into is why the results are quite different. In principle, this could be due to the differences between:<br /> (a) the cell stimulation procedure<br /> (b) the GWAS datasets used<br /> (c) the types of assay (Hi-C vs Capture Hi-C)<br /> (d) approaches for defining gene-linked regions (loops vs neighbourhoods)<br /> (e) how the GWAS signals at gene-linked regions are aggregated (e.g., the flavours of COGS in Javierre and Burren vs the authors' approach).

Re (a), I'm not sure the authors make it explicitly clear in the main text that the Capture Hi-C-based studies also use *stimulated* CD4 T cells, particularly in the section "Comparative predictive power...". So the cells used are pretty much the same, and the differences likely arise from points (b) to (e).

It would be useful for the community to understand more clearly what is driving these differences, ideally with some added data. Could the authors, for example, take the PCHi-C data from Javierre/Burren and use their GWAS data and variant-to-gene assignment algorithms?

In addition, given that the authors use Hi-C, a popular method for V2G prioritisation for this type of data is currently ABC (Nasser et al, Nature 2021). Could the authors provide a comparative analysis with respect to the V2G assignments in the paper and, if they see it appropriate, also run ABC-based GWAS integration on their own Hi-C data?

Reviewer #2 (Public Review):

Summary:

There is significant interest in characterizing the mechanisms by which genetic mutations linked to autoimmunity perturb immune processes. Pahl et al. collect information on dynamic accessible regions, genes, and 3D contacts in primary CD4+ T cell samples that have been stimulated ex vivo. The study includes a variety of analyses characterizing these dynamic changes. With TF footprinting they propose factors linked to active regulatory elements. They compare the performance of their variant mapping pipeline that uses their data versus existing datasets. Most compelling there was a deep dive into additional study of regulatory elements nearby the IL2 gene. Finally, they perform a pharmacological screen targeting several genes they suggest are involved in T cell proliferation.

Strengths:

The work done characterizing elements at the IL2 locus is impressive.

Weaknesses:

- Missing critical context to evaluate claims. There are extensive studies performed on resting and activated immune cell states (CD4+ T cells and other cell types) and some at multiple time points or concentrations of stimuli that collect ATAC-seq and/or RNA-seq that have been ignored by this study. How do conclusions from previous studies compare to what the authors conclude here? It is impossible to evaluate the claims without this additional context. These are a few studies I am familiar with (the authors should perform a more comprehensive search to be sure they're not ignoring existing observations) that would be important to compare/contrast conclusions:<br /> o Alasoo, K. et al. Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response. Nat. Genet. 50, 424-431 (2018).<br /> o Calderon, D., Nguyen, M.L.T., Mezger, A. et al. Landscape of stimulation-responsive chromatin across diverse human immune cells. Nat Genet 51, 1494-1505 (2019).<br /> o Gate, R.E., Cheng, C.S., Aiden, A.P. et al. Genetic determinants of co-accessible chromatin regions in activated T cells across humans. Nat Genet 50, 1140-1150 (2018).<br /> o Glinos, D.A., Soskic, B., Williams, C. et al. Genomic profiling of T-cell activation suggests increased sensitivity of memory T cells to CD28 costimulation. Genes Immun 21, 390-408 (2020).<br /> o Gutierrez-Arcelus, M., Baglaenko, Y., Arora, J. et al. Allele-specific expression changes dynamically during T cell activation in HLA and other autoimmune loci. Nat Genet 52, 247-253 (2020).<br /> o Kim-Hellmuth, S. et al. Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations. Nat. Commun. 8, 266 (2017).<br /> o Ye, C. J. et al. Intersection of population variation and autoimmunity genetics in human T cell activation. Science 345, 1254665 (2014).

- As a general point, I appreciate it when each claim includes a corresponding effect size and p-value, which helps me evaluate the strength of significance of supporting evidence.

Reviewer #3 (Public Review):

Summary:

This paper used RNAseq, ATACseq, and Hi-C to assess gene expression, chromatin accessibility, and chromatin physical associations for native CD4+ T cells as they respond to stimulation through TCR and CD28. With these data in hand, the author identified 423 GWAS signals to their respective target genes, where most of these were not in the proximal promoter, but rather distal enhancers. The IL-2 gene was used as an example to identify new distal cis-regulatory regions required for optimal IL-2 gene transcription. These distal elements interact with the proximal IL2 promoter region. When the distal enhancer contained an autoimmune SNP, it affected IL-2 gene transcription. The authors also identified genetic risk variants that were associated with genes upon activation. Some of these regulate proliferation and cytokine production, but others are novel.

Strengths:

This paper provides a wealth of data related to gene expression after CD4 T cells are activated through the TCR and CD28. An important strength of this paper is that these data were intensively analyzed to uncover autoimmune disease SNPs in cis-acting regions. Many of these could be assigned to likely target genes even though they often are in distal enhancers. These findings help to provide a better understanding concerning the mechanism by which GWAS risk elements impact gene expression.

Another strength of this study was the proof-of-principle studies examining the IL-2 gene. Not only were new cis-acting enhancers discovered, but they were functionally shown to be important in regulating IL-2 expression, including susceptibility to colitis. Their importance was also established with respect to such distal enhancers harboring disease-relevant SNPs, which were shown to affect IL-2 transcription.

The data from this study were also mined against past CRISPR screens that identified genes that control aspects of CD4 T cell activation. From these comparisons, novel genes were identified that function during T cell activation.

Weaknesses:

A weakness of this study is that few individuals were analyzed, i.e., RNAseq and ATACseq (n=3) and HiC (n=2). Thus, the authors may have underestimated potentially relevant risk associations by their chromatin capture-based methodology. This might account for the low overlap of their data with the eQTL-based approach or the HIEI truth set.

Impact:

This study indicates that defining distal chromatin interacting regions helps to identify distal genetic elements, including relevant variants, that contribute to gene activation.

Reviewer #1 (Public Review):

In this study, the authors examined the role of IBTK, a substrate-binding adaptor of the CRL3 ubiquitin ligase complex, in modulating the activity of the eiF4F translation initiation complex. They find that IBTK mediates the non-degradative ubiquitination of eiF4A1, promotes cap-dependent translational initiation, nascent protein synthesis, oncogene expression, and tumor cell growth. Correspondingly, phosphorylation of  IBTK by mTORC1/ S6K1 increases eIF4A1 ubiquitination and sustains oncogenic translation.

Strengths:

This study utilizes multiple biochemical, proteomic, functional and cell biology assays to substantiate their results.  Importantly, the work nominates IBTK as a unique substrate of mTORC1, and further validates eiF4A1 ( a crucial subunit of the ei44F complex) as a promising therapeutic target in cancer. Since IBTK interacts broadly with multiple members of the translational initial complex- it will be interesting to examine its role in eiF2alpha-mediated ER stress as well as eiF3-mediated translation. Additionally, since IBTK exerts pro-survival effects in multiple cell types, it will be of relevance to characterize the role of IBTK in mediating increased mTORC1 mediated translation in other tumor types, thus potentially impacting their treatment with eiF4F inhibitors.

Limitations/Weaknesses:

The findings are mostly well supported by data, but some areas need clarification and could potentially be enhanced with further experiments:

(1) Since eiF4A1 appears to function downstream of IBTK1, can the effects of IBTK1 KO/KD in reducing puromycin incorporation ( in Fig 3A),  cap-dependent luciferase reporter activity (Fig 3G), reduced oncogene expression ( Fig 4A) or 2D growth/ invasion assays (Fig 4) be overcome or bypassed by overexpressing eiF4A1? These could potentially be tested in future studies. <br /> (2) The decrease in nascent protein synthesis in puromycin incorporation assays in Figure 3A suggests that the effects of IBTK KO are comparable to and additive with silvesterol. It would be of interest to examine whether silvesterol decreases nascent protein synthesis or increases stress granules in the IBTK KO cells stably expressing IBTK as well. <br /> (3) The data presented in Figure 5 regarding the role of mTORC1 in IBTK-mediated eiF4A1 ubiquitination needs further clarification on several points:<br /> - It is not clear if the experiments in Figure 5F with Phos-tag gels are using the FLAG-IBTK deletion mutant or the peptide containing the mTOR sites as it is mentioned on line 517, page 19 "To do so, we generated an IBTK deletion mutant (900-1150 aa) spanning the potential mTORC1-regulated phosphorylation sites" This needs further clarification.<br /> -It may be of benefit to repeat the Phos tag experiments with full length FLAG-IBTK and/or endogenous IBTK with molecular weight markers indicating size of migrated bands.<br /> -Additionally, torin or Lambda phosphatase treatment may be used to confirm the specificity of the band in separate experiments.<br /> -Phos-tag gels with the IBTK CRISPR KO line would also help confirm that the non-phosphorylated band is indeed IBTK. <br /> -It is unclear why the lower, phosphorylated bands seem to be increasing ( rather than decreasing) with AA starvation/ Rapa in Fig 5H.

Reviewer #2 (Public Review):

Summary:

This study by Sun et al. identifies a novel role for IBTK in promoting cancer protein translation, through regulation of the translational helicase eIF4A1. Using a multifaceted approach, the authors demonstrate that IBTK interacts with and ubiquitinates eIF4A1 in a non-degradative manner, enhancing its activation downstream of mTORC1/S6K1 signaling. This represents a significant advance in elucidating the complex layers of dysregulated translational control in cancer.

Strengths:

A major strength of this work is the convincing biochemical evidence for a direct regulatory relationship between IBTK and eIF4A1. The authors utilize affinity purification and proximity labeling methods to comprehensively map the IBTK interactome, identifying eIF4A1 as a top hit. Importantly, they validate this interaction and the specificity for eIF4A1 over other eIF4 isoforms by co-immunoprecipitation in multiple cell lines. Building on this, they demonstrate that IBTK catalyzes non-degradative ubiquitination of eIF4A1 both in cells and in vitro through the E3 ligase activity of the CRL3-IBTK complex. Mapping IBTK phosphorylation sites and showing mTORC1/S6K1-dependent regulation provides mechanistic insight. The reduction in global translation and eIF4A1-dependent oncoproteins upon IBTK loss, along with clinical data linking IBTK to poor prognosis, support the functional importance. Finally, the impact of IBTK on eIF4A1 target gene expression in colon and lung cancer cell lines, strengthens these findings.

Weaknesses:

While the effects of IBTK knockout/over-expression on bulk protein synthesis are shown, the expression of several eIF4A1 target oncogenes remains unchanged.

Summary:

Overall, this study significantly advances our understanding of how aberrant mTORC1/S6K1 signaling promotes cancer pathogenic translation via IBTK and eIF4A1. The proteomic, biochemical and phosphorylation mapping approaches established here provide a blueprint for interrogating IBTK function. These data should galvanize future efforts to target the mTORC1/S6K1-IBTK-eIF4A1 axis as an avenue for cancer therapy, particularly in combination with eIF4A inhibitors.

Reviewer #1 (Public Review):

Summary:

The authors used structural and biophysical methods to provide insight into Parkin regulation. The breadth of data supporting their findings was impressive and generally well-orchestrated. Still, the impact of their results builds on recent structural studies and the stated impact is based on these prior works.

Strengths:

(1) After reading through the paper, the major findings are:<br /> - RING2 and pUbl compete for binding to RING0.<br /> - Parkin can dimerize.<br /> - ACT plays an important role in enzyme kinetics.

(2) The use of molecular scissors in their construct represents a creative approach to examining inter-domain interactions.

(3) From my assessment, the experiments are well-conceived and executed.

Weaknesses:

(1) The manuscript, as written, is NOT for a general audience. Admittedly, I am not an expert on Parkin structure and function, but I had to do a lot of homework to try to understand the underlying rationale and impact. This reflects, I think, that the work generally represents an incremental advance on recent structural findings.

(2) To this point, it is hard to understand the impact of this work without more information highlighting the novelty. There are several structures of Parkin in various auto-inhibited states, and it was hard to delineate how this is different.

(3) As noted, I appreciated the use of protease sites in the fusion protein construct. It is unclear how the loop region might affect the protein structure and function. The authors worked to demonstrate that this did not introduce artifacts, but the biological context is missing.

(4) While it is likely that the binding is competitive between the Ubl and RING2 domains, the data is not quantitative. Is it known whether the folding of the distinct domains is independent? Or are there interactions that alter folding? It seems plausible that conformational rearrangements may invoke an orientation of domains that would be incompatible. The biological context for the importance of this interaction was not clear to me.

(5) What is the rationale for mutating Lys211 to Asn? Were other mutations tried? Glu? Ala? Just missing the rationale. I think this may have been identified previously in the field, but not clear what this mutation represents biologically.

(6) I was confused about how the phospho-proteins were generated. After looking through the methods, there appear to be phosphorylation experiments, but it is unclear what the efficiency was for each protein (i.e. what % gets modified). In the text, the authors refer to phospho-Parkin (T270R, C431A), but not clear how these mutations might influence this process. I gather that these are catalytically inactive, but it is unclear to me how this is catalyzing the ubiquitination in the assay.

(7) The authors note that "ACT can be complemented in trans; however, it is more efficient in cis", but it is unclear whether both would be important or if the favored interaction is dominant in a biological context.

(8) The authors repeatedly note that this study could aid in the development of small-molecule regulators against Parkin to treat PD, but this is a long way off. And it is not clear from their manuscript how this would be achieved. As stated, this is conjecture.

Reviewer #2 (Public Review):

This manuscript uses biochemistry and X-ray crystallography to further probe the molecular mechanism of Parkin regulation and activation. Using a construct that incorporates cleavage sites between different Parkin domains to increase the local concentration of specific domains (i.e., molecular scissors), the authors suggest that competitive binding between the p-Ubl and RING2 domains for the RING0 domain regulates Parkin activity. Further, they demonstrate that this competition can occur in trans, with a p-Ubl domain of one Parkin molecule binding the RING0 domain of a second monomer, thus activating the catalytic RING1 domain. In addition, they suggest that the ACT domain can similarly bind and activate Parkin in trans, albeit at a lower efficiency than that observed for p-Ubl. The authors also suggest from crystal structure analysis and some biochemical experiments that the linker region between RING2 and repressor elements interacts with the donor ubiquitin to enhance Parkin activity.

Ultimately this manuscript challenges previous work suggesting that the p-Ubl domain does not bind to the Parkin core in the mechanism of Parkin activation. The use of the 'molecular scissors' approach to probe these effects is an interesting approach to probe this type of competitive binding. However, there are issues with the experimental approach manuscript that detract from the overall quality and potential impact of the work.

The competitive binding between p-Ubl and RING2 domains for the Parkin core could have been better defined using biophysical and biochemical approaches that explicitly define the relative affinities that dictate these interactions. A better understanding of these affinities could provide more insight into the relative bindings of these domains, especially as it relates to the in trans interactions.

I also have concerns about the results of using molecular scissors to 'increase local concentrations' and allow for binding to be observed. These experiments are done primarily using proteolytic cleavage of different domains followed by size exclusion chromatography. ITC experiments suggest that the binding constants for these interactions are in the µM range, although these experiments are problematic as the authors indicate in the text that protein precipitation was observed during these experiments. This type of binding could easily be measured in other assays. My issue relates to the ability of a protein complex (comprising the core and cleaved domains) with a Kd of 1 µM to be maintained in an SEC experiment. The off-rates for these complexes must be exceeding slow, which doesn't really correspond to the low µM binding constants discussed in the text. How do the authors explain this? What is driving the Koff to levels sufficiently slow to prevent dissociation by SEC? Considering that the authors are challenging previous work describing the lack of binding between the p-Ubl domain and the core, these issues should be better resolved in this current manuscript. Further, it's important to have a more detailed understanding of relative affinities when considering the functional implications of this competition in the context of full-length Parkin. Similar comments could be made about the ACT experiments described in the text.

Ultimately, this work does suggest additional insights into the mechanism of Parkin activation that could contribute to the field. There is a lot of information included in this manuscript, giving it breadth, albeit at the cost of depth for the study of specific interactions. Further, I felt that the authors oversold some of their data in the text, and I'd recommend being a bit more careful when claiming an experiment 'confirms' a specific model. In many cases, there are other models that could explain similar results. For example, in Figure 1C, the authors state that their crystal structure 'confirms' that "RING2 is transiently displaced from the RING0 domain and returns to its original position after washing off the p-Ubl linker". However, it isn't clear to me that RING2 ever dissociated when prepared this way. While there are issues with the work that I feel should be further addressed with additional experiments, there are interesting mechanistic details suggested by this work that could improve our understanding of Parkin activation. However, the full impact of this work won't be fully appreciated until there is a more thorough understanding of the regulation and competitive binding between p-Ubl and RIGN2 to RORB both in cis and in trans.

Reviewer #3 (Public Review):

Summary:

In their manuscript "Additional feedforward mechanism of Parkin activation via binding of phospho-UBL and RING0 in trans", Lenka et al present data that could suggest an "in trans" model of Parkin ubiquitination activity. Parkin is an intensely studied E3 ligase implicated in mitophagy, whereby missense mutations to the PARK2 gene are known to cause autosomal recessive juvenile parkinsonism. From a mechanistic point of view, Parkin is extremely complex. Its activity is tightly controlled by several modes of auto-inhibition that must be released by queues of mitochondrial damage. While the general overview of Parkin activation has been mapped out in recent years, several details have remained murky. In particular, whether Parkin dimerizes as part of its feed-forward signaling mechanism, and whether said dimerization can facilitate ligase activation, has remained unclear. Here, Lenka et al. use various truncation mutants of Parkin in an attempt to understand the likelihood of dimerization (in support of an "in trans" model for catalysis).

Strengths:

The results are bolstered by several distinct approaches including analytical SEC with cleavable Parkin constructs, ITC interaction studies, ubiquitination assays, protein crystallography, and cellular localization studies.

Weaknesses:

As presented, however, the storyline is very confusing to follow and several lines of experimentation felt like distractions from the primary message. Furthermore, many experiments could only indirectly support the author's conclusions, and therefore the final picture of what new features can be firmly added to the model of Parkin activation and function is unclear.

Major concerns:

(1) This manuscript solves numerous crystal structures of various Parkin components to help support their idea of in trans transfer. The way these structures are presented more resemble models and it is unclear from the figures that these are new complexes solved in this work, and what new insights can be gleaned from them.

(2) There are no experiments that definitively show the in trans activation of Parkin. The binding experiments and size exclusion chromatography are a good start, but the way these experiments are performed, they'd be better suited as support for a stronger experiment showing Parkin dimerization. In addition, the rationale for an in trans activation model is not convincingly explained until the concept of Parkin isoforms is introduced in the Discussion. The authors should consider expanding this concept into other parts of the manuscript.

2a. For the in trans activation experiment using wt Parkin and pParkin (T270R/C431A) (Figure 3D), there needs to be a large excess of pParkin to stimulate the catalytic activity of wt Parkin. This experiment has low cellular relevance as these point mutations are unlikely to occur together to create this nonfunctional pParkin protein. In the case of pParkin activating wt Parkin (regardless of artificial point mutations inserted to study specifically the in trans activation), if there needs to be much more pParkin around to fully activate wt Parkin, isn't it just more likely that the pParkin would activate in cis?

2ai. Another underlying issue with this experiment is that the authors do not consider the possibility that the increased activity observed is a result of increased "substrate" for auto-ubiquitination, as opposed to any role in catalytic activation. Have the authors considered looking at Miro as a substrate in order to control for this?

2b. The authors mention a "higher net concentration" of the "fused domains" with RING0, and use this to justify artificially cleaving the Ubl or RING2 domains from the Parkin core. This fact should be moot. In cells, it is expected there will only be a 1:1 ratio of the Parkin core with the Ubl or RING2 domains. To date, there is no evidence suggesting multiple pUbls or multiple RING2s can bind the RING0 binding site. In fact, the authors here even show that either the RING2 or pUbl needs to be displaced to permit the binding of the other domain. That being said, there would be no "higher net concentration" because there would always be the same molar equivalents of Ubl, RING2, and the Parkin core.

2c. A larger issue remaining in terms of Parkin activation is the lack of clarity surrounding the role of the linker (77-140); particularly whether its primary role is to tether the Ubl to the cis Parkin molecule versus a role in permitting distal interactions to a trans molecule. The way the authors have conducted the experiments presented in Figure 2 limits the possible interactions that the activated pUbl could have by (a) ablating the binding site in the cis molecule with the K211N mutation; (b) further blocking the binding site in the cis molecule by keeping the RING2 domain intact. These restrictions to the cis parkin molecule effectively force the pUbl to bind in trans. A competition experiment to demonstrate the likelihood of cis or trans activation in direct comparison with each other would provide stronger evidence for trans activation.

(3) A major limitation of this study is that the authors interpret structural flexibility from experiments that do not report directly on flexibility. The analytical SEC experiments report on binding affinity and more specifically off-rates. By removing the interdomain linkages, the accompanying on-rate would be drastically impacted, and thus the observations are disconnected from a native scenario. Likewise, observations from protein crystallography can be consistent with flexibility, but certainly should not be directly interpreted in this manner. Rigorous determination of linker and/or domain flexibility would require alternative methods that measure this directly.

(4) The analysis of the ACT element comes across as incomplete. The authors make a point of a competing interaction with Lys48 of the Ubl domain, but the significance of this is unclear. It is possible that this observation could be an overinterpretation of the crystal structures. Additionally, the rationale for why the ACT element should or shouldn't contribute to in trans activation of different Parkin constructs is not clear. Lastly, the conclusion that this work explains the evolutionary nature of this element in chordates is highly overstated.

(5) The analysis of the REP linker element also seems incomplete. The authors identify contacts to a neighboring pUb molecule in their crystal structure, but the connection between this interface (which could be a crystallization artifact) and their biochemical activity data is not straightforward. The analysis of flexibility within this region using crystallographic and AlphaFold modeling observations is very indirect. The authors also draw parallels with linker regions in other RBR ligases that are involved in recognizing the E2-loaded Ub. Firstly, it is not clear from the text or figures whether the "conserved" hydrophobic within the linker region is involved in these alternative Ub interfaces. And secondly, the authors appear to jump to the conclusion that the Parkin linker region also binds an E2-loaded Ub, even though their original observation from the crystal structure seems inconsistent with this. The entire analysis feels very preliminary and also comes across as tangential to the primary storyline of in trans Parkin activation.

Reviewer #1 (Public Review):

Summary:

In this paper, Bruter and colleagues report the effects of inducible deletion of the genes encoding the two paralogous kinases of the Mediator complex in adult mice. The physiological roles of these two kinases, CDK8 and CDK19, are currently rather poorly understood; although conserved in all eukaryotes, and among the most highly conserved kinases in vertebrates, individual knockouts of genes encoding CDK8 homologues in different species have revealed generally rather mild and specific effects, in contrast to Mediator itself. Here, the authors provide evidence that neither CDK8 nor CDK19 are required for adult homeostasis but they are functionally redundant for maintenance of reproductive tissue morphology and fertility in males.

Strengths:

The morphological data on the atrophy of the male reproductive system and the arrest of spermatocyte meiosis are solid and are reinforced by single-cell transcriptomics data, which is a challenging technique to implement in vivo. The main findings are important and will be of interest to scientists in the fields of transcription and developmental biology.

Weaknesses:

There are several major weaknesses.

The first is that data on the general health of mice with single and double knockouts is not shown, nor is there any data on effects in any other tissues. This gives the impression that the only phenotype is in the male reproductive system, which would be misleading if there were phenotypes in other tissues that are not reported. Furthermore, data for the genitourinary system in single knockouts are very sparse; data are described for fertility in Figure 1H, ploidy, and cell number in Figures 2B and C, plasma testosterone and luteinizing hormone levels in Figures 5C and 5D, and morphology of testis and prostate tissue for single Cdk8 knockout in Supplementary Figure 1C (although in this case the images do not appear very comparable between control and CDK8 KO, thus perhaps wider fields should be shown), but, for example, there is no analysis of different meiotic stages or of gene expression in single knockouts. It is worth mentioning that single knockouts seem to show a corresponding upregulation of the level of the paralogue kinase, indicating that any lack of phenotypes might be due to feedback compensation, which would be an interesting finding if confirmed; this has not been mentioned.

The second major weakness is that the correlation between double knockout and reduced expression of genes involved in steroid hormone biosynthesis is portrayed as a causal mechanism for the phenotypes observed. While this is a possibility, there are no experiments performed to provide evidence that this is the case. Furthermore, there is no evidence showing that CDK8 and/or CDK19 are directly responsible for the transcription of the genes concerned.

Finally, the authors propose that the phenotypes are independent of the kinase activity of CDK8 or CDK19 because treatment of mice for a month with an inhibitor does not recapitulate the effects of the knockout, and nor does expression of two steroidogenic genes change in cultured Leydig cells upon treatment with an inhibitor. However, there are no controls for effective target inhibition shown.

Reviewer #2 (Public Review):

Summary:

The authors tried to test the hypothesis that Cdk8 and Cdk19 stabilize the cytoplasmic CcNC protein, the partner protein of the Mediator complex including CDK8/19 and Mediator protein via a kinase-independent function by generating induced double knockout of Cdk8/19. However, the evidence presented suffers from a lack of focus and rigor and does not support their claims.

Strengths:

This is the first comprehensive report on the effect of a double knockout of CDK8 and CDK19 in mice on male fertility, hormones, and single-cell testicular cellular expression. The inducible knockout mice led to male sterility with severe spermatogenic defects, and the authors attempted to use this animal model to test the kinase-independent function of CDK8/19, previously reported for humans. Single-cell RNA-seq of knockout testis presented a high resolution of molecular defects of all the major cell types in the testes of the inducible double knockout mice. The authors also have several interesting findings such as reentry into cell cycles by Sertoli cells, and loss of Testosterone in induced dko that could be investigated further.

Weaknesses:

The claim of reproductive defects in the induced double knockout of CDK8/19 resulted from the loss of CCNC via a kinase-independent mechanism is interesting but was not supported by the data presented. While the construction and analysis of the systemic induced knockout model of Cdk8 in Cdk19KO mice is not trivial, the analysis and data are weakened by the systemic effect of Cdk8 loss, making it difficult to separate the systemic effect from the local testis effect.

The analysis of male sterile phenotype is also inadequate with poor image quality, especially testis HE sections. The male reproductive tract picture is also small and difficult to evaluate. The mice crossing scheme is unusual as you have three mice to cross to produce genotypes, while we could understand that it is possible to produce pups of desired genotypes with different mating schemes, such a vague crossing scheme is not desirable and of poor genetics practice. Also using TAM-treated wild type as control is ok, but a better control will be TAM-treated ERT2-cre; CDK8f/f or TAM-treated ERT2 Cre CDK19/19 KO, so as to minimize the impact from the well-recognized effect of TAM.

While the authors proposed that the inducible loss of CDK8 in the CDK19 knockout background is responsible for spermatogenic defects, it was not clear in which cells CDK8/19 genes are interested and which cell types might have a major role in spermatogenesis. The authors also put forward the evidence that reduction/loss of Testosterone might be the main cause of spermatogenic defects, which is consistent with the expression change in genes involved in steroigenesis pathway in Leydig cells of inducible double knockout. However it is not clear how the loss of Testosterone contributed to the loss of CcnC protein.

The authors should clarify or present the data on where CDK8 and CDK19 as well as CcnC are expressed so as to help the readers understand which tissues both CDK might be functioning in and cause the loss of CcnC. It should be easier to test the hypothesis of CDK8/19 stabilizing CcnC protein using double knock-out primary cells, instead of the whole testis.

Since CDK8KO and CDK19KO both have significantly reduced fertility in comparison with wildtype, it might be important to measure the sperm quantity and motility among CDK8 KO, CDK19KO, and induced DKO to evaluate spermatogenesis based on their sperm production.

Some data for the inducible knockout efficiency of Cdk8 were presented in Supplemental Figure 1, but there is no legend for the supplemental figures, it was not clear which band represented the deletion band, and which tissues were examined. Tail or testis? It seems that two months after the injection of Tam, all the Cdk8 were completely deleted, indicating extremely efficient deletion of Tam induction by two months post administration. Were the complete deletion of Cdk8 happening even earlier? An examination of time points of induced loss would be useful and instructional as to when is the best time to examine phenotypes.

The authors found that Sertoli cells re-entered the cell cycle in the inducible double knockout but stopped short of careful characterization other than increased expression of cell cycle genes.

Overall this work suffered from a lack of focus and rigor in the analysis and lack of sufficient evidence to support their main conclusions.

Minor:

Dko should be appropriately named iDKO (induced dKO).

"suppress spermatogenesis and male fertility" in the title does not fit the evidence presented.

"DKO males, had an understized and dedifferentiated reproductive system?" what is the evidence for "undifferentiated"?

We performed necropsy ? not the right wording here.

Colchicine-lke apoptotic bodies ? what does this mean? Not clear.

Images throughout the manuscript suffer from poor resolution and are often blurry and hard to evaluate.

To pinpoint the meiotic stage defect of iDKO, it is better to use the meiotic chromosome spread approach.

Reviewer #1 (Public Review):

Summary:

The authors presented here a novel 3D fibroblast culture and transdifferentiation approach for potential meat production with GelMA hydrogel.

Strengths:

(1) Reduced serum concentration for 3D chicken fibroblast culture and transdifferentiation is optimized.<br /> (2) Efficient myogenic transdifferentiation and lipogenesis as well as controlled fat deposition are achieved in the 3D GelMA.

Reviewer #2 (Public Review):

The manuscript by Ma et al. tries to develop a protocol for cell-based meat production using chicken fibroblasts as three-dimensional (3D) muscle tissues with fat accumulation. The authors used genetically modified fibroblasts, which can be forced to differentiate into muscle cells, and formulated 3D tissues with these cells and a biphasic material (hydrogel). The degrees of muscle differentiation and lipid deposition in culture were determined by immunohistochemical, biochemical, and molecular biological evaluations. Notably, the protocol successfully achieved the process of myogenic and lipogenic stimulation in the 3D tissues.

As addressed after the initial review process, the manuscript is clearly written with well-supportive figures. The study design is reasonable with adequate analysis. In the revised manuscript, the authors further discussed the ideas in terms of the approach using genetic modification for cell-based meat production. However, more careful considerations may still be helpful when actually using the technology for cultivated meat production.

Reviewer #1 (Public Review):

Summary:

This paper provides a straightforward mechanism of how mycobacterial cAMP level is increased under stressful conditions and shows that the increase is important for the survival of the bacterium in animal hosts. The cAMP level is increased by decreasing the expression of an enzyme that degrades cAMP.

Strengths:

The paper shows that under different stresses the response regulator PhoP represses a phosphodiesterase (PDE) that degrades cAMP specifically. Identification of PhoP as a regulator of cAMP is significant progress in understanding Mtb pathogenesis, as an increase in cAMP apparently increases bacterial survival upon infection. On the practical side, reduction of cAMP by increasing PDE can be a means to attenuate the growth of the bacilli. The results have wider implications since PhoP is implicated in controlling diverse mycobacterial stress responses and many bacterial pathogens modulate host cell cAMP levels. The results here are straightforward, internally consistent, and of both theoretical and applied interests. The results also open considerable future work, especially how increases in cAMP level help to increase survival of the pathogen.

Weaknesses:

It is not clear whether PhoP-PDE Rv0805 is the only pathway to regulate cAMP level under stress.

Comments on revised submission:

The authors have addressed my comments adequately, actually except for all but one. I have only one comment to do with the last line of the abstract. First, "genetic manipulation" usually means changing DNA. In Mtb pathogenesis I hope there is no DNA modification or change in the bacterial DNA. Also, the authors did not really inactivate the whole PhoP- rv0805-cAMP pathway. It would be best if the last line is made more fact based: Thus, inactivation of PhoP decreases cAMP level, thereby stress tolerance and intracellular survival of the bacillus.

Reviewer #2 (Public Review):

Summary:

In the manuscript, the authors have presented new mechanistic details to show how intracellular cAMP levels are maintained and linked to the phosphodiesterase enzyme which in turn is controlled by PhoP. Later, they showed the physiological relevance linked to altered cAMP concentrations.

Strengths:

Well-thought-out experiments. The authors carefully planned the experiments well to uncover the molecular aspects of it diligently.

Weaknesses:

None. The authors have meticulously responded to all my queries and concerns through multiple rounds of review.

Reviewer #1 (Public Review):

This work presents CTFFIND5, a new version of the software for determination of the Contrast Transfer Function (CTF) that models the distortions introduced by the microscope in cryoEM images. CTFFIND5 can take acquisition geometry and sample thickness into consideration to improve CTF estimation.

To estimate tilt (tilt angle and tilt axis), the input image is split into tiles and correlation coefficients are computed between their power spectra and a local CTF model that includes the defocus variation according to a tilted plane. As a final step, by applying a rescaling factor to the power spectra of the tiles, an average tilt-corrected power spectrum is obtained and used for diagnostic purposes and to estimate the goodness of fit. This global procedure and the rescaling factor resemble those used in Bsoft, Warp, etc, with determination of the tilt parameters being a feature specific of CTFFIND5 (and formerly CTFTILT). The performance of the algorithm is evaluated with tilted 2D crystals and tilt-series, demonstrating accurate tilt estimation in some cases and some limitations in others. Further analysis of CTF determination with tilt-series, particularly showing whether there is accurate or stable estimation at high tilts, might be helpful to show the robustness of CTFFIND5 in cryoET.

CTFFIND5 represents the first CTF determination tool that considers the thickness-related modulation envelope of the CTF firstly described by McMullan et al. (2015) and experimentally confirmed by Tichelaar et al. (2020). To this end, CTFFIND5 uses a new CTF model that takes the sample thickness into account. CTFFIND5 thus provides more accurate CTF estimation and, furthermore, gives an estimation of the sample thickness, which may be a valuable resource to judge the potential for high resolution. To evaluate the accuracy of thickness estimation in CTFFIND5, the authors use the Lambert-Beer law on energy-filtered data and also tomographic data, thus demonstrating that the estimates are reasonable for images with exposure around 30 e/A2. While consideration of sample thickness in CTF determination sounds ideally suited for cryoET, practical application under the standard acquisition protocols in cryoET (exposure of 3-5 e/A2 per image) is still limited. In this regard, the authors are honest in the conclusions and clearly identify the areas where thickness-aware CTF determination will be valuable at present: e.g. in situ single particle analysis and in vitro single particle cryoEM of purified samples at low voltages.

In conclusion, the manuscript introduces novel methods inside CTFFIND5 that improve CTF estimation, namely acquisition geometry and sample thickness. The evaluation demonstrates the performance of the new tool, with fairly accurate estimates of tilt axis, tilt angle and sample thickness and improved CTF estimation. The manuscript critically defines the current range of application of the new methods in cryoEM.

Reviewer #2 (Public Review):

Summary:

This paper describes the latest version of the most popular program for CTF estimation for cryo-EM images: CTFFIND5. New features in CTFFIND5 are the estimation of tilt geometry, including for samples, like FIB-milled lamellae, that are pre-tilted along a different axis than the tilt axis of the tomographic experiment, plus the estimation of sample thickness from the expanded CTF model described by McMullan et al (2015). The results convincingly show the added value of the program for thicker and tilted images, such as are common in modern cryo-ET experiments. The program will therefore have a considerable impact on the field.

I have only minor suggestions for improvement below:

Abstract: "[CTF estimation] has been one of the key aspects of the resolution revolution"-> This is a bit over the top. Not much changed in the actual algorithms for CTF estimation during the resolution revolution.<br /> L34: "These parameters" -> Cs is typically given, only defocus (and if relevant phase shift) are estimated.<br /> L110-116: The text is ambiguous: are rotations defined clockwise or counter-clockwise? It would be good to explicitly state what subsequent rotations, in which directions and around which axes this transformation matrix (and the input/output angles in CTFFIND5) correspond to.<br /> L129-130: As a suggestion: it would be relatively easy, and possibly beneficial to the user, to implement a high-resolution limit that varies with the accumulated dose on the sample. One example of this exists in the tomography pipeline of RELION-5.<br /> Substituting Eq (7) into Eq (6) yields ksi=pi, which cannot be true. If t is the sample thickness, then how can this be a function of the frequency g of the first node of the CTF function? The former is a feature of the sample, the latter is a parameter of the optical system. This needs correction.

Reviewer #3 (Public Review):

In this manuscript, the authors detail improvements in the core CTFFIND (CTFFIND5 as implemented in cisTEM) algorithm that better estimates CTF parameters from titled micrographs and those that exhibit signal attenuation due to ice thickness. These improvements typically yield more accurate CTF values that better represent the data. Although some of the improvements result in slower calculations per micrograph, these can be easily overcome through parallelization.

There are some concerns outlined below that would benefit from further evaluation by the authors.

For the examples shown in Figure 3b, given the small differences in estimated defocus1 and 2, what type of improvements would be expected in the reconstructed tomograms? Do such improvements in estimates manifest in better tilt-series reconstruction?

Similarly, the data shown in Figure 3C shows minimal improvements in the CTF resolution estimate (e.g., 4.3 versus 4.2 Å), but exhibited several hundred Å difference in defocus values. How do such differences impact downstream processing? Is such a difference overcame by per-particle (local) CTF refinements (like the authors mention in the discussion, see below)?

At which point does the thickness of the specimen preclude the ice thickness modulation to be included for "accurate" estimate? 500Å? 1000Å? 2000Å? Based on the data shown in Figure 3B, as high as 969 Å thick specimens benefit moderately (4.6 versus 3.4 Å fit estimate), but perhaps not significantly, from the ice thickness estimation. Considering the increased computational time for ice thickness estimation, such an estimate of when to incorporate for single-particle workflows would be beneficial.

It would seem that this statement could be evaluated herein: "the analysis of images of purified samples recorded at lower acceleration voltages, e.g., 100 keV (McMullan et al., 2023), may also benefit since thickness-dependent CTF modulations will appear at lower resolution with longer electron wavelengths". There are numerous examples of 300kV, 200kV, and 100kV EMPIAR datasets to be compared and recommendations would be welcomed.

Although logical, this statement is not supported by the data presented in this manuscript: "The improvements of CTFFIND5 will provide better starting values for this refinement, yielding better overall CTF estimation and recovery of high-resolution information during 3D reconstruction."

Moreso, the lack of single-particle data evaluation does present a concern. Naively, these improvements would benefit all cryoEM data, regardless of modality.

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

(1) Lack of mechanistic insight into the sex-dependent effects.<br /> (2) Analysis of indirect calorimetry data requires more depth.<br /> (3) A deeper analysis of hypothalamic inflammation and ER stress pathways would strengthen the manuscript.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

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

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

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

Weaknesses:

There were no major weaknesses perceived. Some comments for potential textual additions to the results/discussion are listed in recommendations to authors.

Reviewer #1 (Public Review):

Summary:

This is a follow-up study to the authors' previous eLife report about the roles of an alpha-arrestin called protein thioredoxin interacting protein (Txnip) in cone photoreceptors and in the retinal pigment epithelium. The findings are important because they provide new information about the mechanism of glucose and lactate transport to cone photoreceptors and because they may become the basis for therapies for retinal degenerative diseases.

Strengths:

Overall, the study is carefully done and, although the analysis is fairly comprehensive with many different versions of the protein analyzed, it is clearly enough described to follow. Figure 4 greatly facilitated my ability to follow, understand and interpret the study. The authors have appropriately addressed a few concerns about statistical significance and the relationship between their findings and previous studies of the possible roles of Txnip on GLUT1 expression and localization on the surfaces of RPE cells.

Reviewer #2 (Public Review):

The hard work of the authors is much appreciated. With overexpression of a-arrestin Txnip in RPE, cones and the combined respectively, the authors show a potential gene agnostic treatment that can be applied to retinitis pigmentosa. Furthermore, since Txnip is related to multiple intracellular signaling pathway, this study is of value for research in the mechanism of secondary cone dystrophy as well.

Strengths

- The follow-up study builds on innovative ground by exploring the impact of TxnipC247S and its combination with HSP90AB1 knockdown on cone survival, offering novel therapeutic pathways.<br /> - Testing of different Txnip deletion mutants provides a nuanced understanding of its functional domains, contributing valuable insights into the mechanism of action in RP treatment.<br /> - The findings regarding GLUT1 clearance and the differential effects of Txnip mutants on cone and RPE cells lay the groundwork for targeted gene therapy in RP.

Comments on revised version:

The researchers answered our questions and included additional discussion in the manuscript.

Reviewer #2 (Public Review):

In their manuscript entitled "BEND2 is a crucial player in oogenesis and reproductive aging", the authors present their findings that full-length BEND2 is important for repair of meiotic double strand break repair in spermatocytes, regulation of LINE-1 elements in spermatocytes, and proper oocyte meiosis and folliculogenesis in females. The manuscript utilizes an elegant system to specifically ablate the full-length form of BEND2 which has been historically difficult to study due to its location on the X chromosome and male sterility of global knockout animals.

While the manuscript is an overall excellent addition to the field, it would significantly benefit from a few additional experiments, as well as some additional clarification/elaboration.

The claim that BEND2 is required for ovarian reserve establishment is not supported, as the authors only look at folliculogenesis and oocyte abundance starting at one week of age, after the reserve is formed. Analysis of earlier time points would be much more convincing and would parse the role of BEND2 in the establishment vs. maintenance of this cell population. In spermatocytes, the authors demonstrate a loss of nuclear BEND2 in their mutant but do not comment on the change in localization (which is now cytoplasmic) of the remaining protein in these animals. This may have true biological significance and a discussion of this should be more thoroughly explored.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors investigate the role of BEND2, a novel regulator of meiosis, in both male and female fertility. Huang et al have created a mouse model where the full-length BEND2 transcript is depleted but the truncated BEND2 version remains. This mouse model is fertile, and the authors used it to study the role of BEND2 on both male and female meiosis. Overall, the full-length BEND2 appears dispensable for male meiosis. The more interesting phenotype was observed in females. Females exhibit a lower ovarian reserve suggesting that full-length BEND2 is involved in the establishment of the primordial follicle pool.

Strengths:

The authors generated a mouse model that enabled them to study the role of BEND2 in meiosis. The role of BEND2 in female fertility is novel and enhances our knowledge of genes involved in the establishment of the primordial follicle pool.

Weaknesses:

The manuscript extensively explores the role of BEND2 in male meiosis; however, a more interesting result was obtained from the study of female mice. Only a few experiments were performed using female mice, therefore, more experiments should be performed to complete the story of the role of BEND2 on female fertility. In addition, the title and abstract of the manuscript do not align with the story, as female fertility is only a small portion of the data compared to the male fertility section.

Reviewer #3 (Public Review):

Summary:

Huang et al. investigated the phenotype of Bend2 mutant mice which expressed a truncated isoform. This mutant male showed increasing apoptosis due to unrepaired double-strand breaks. However, this mutant male has fertility, and this enabled them to analyze Bend2 function in females. They revealed that Bend2 mutation in females showed decreasing follicle numbers which leads to loss of ovarian reserve.

Strengths:

Since their Bend2 mutant males were fertile, they were able to analyze the function of Bend2 in females and they revealed that loss of Bend2 causes less follicle formation.

Weaknesses:

Why the phenotype of their mutant male is different from previous work (Ma et al.) is not clear enough although they discuss it.

Reviewer #3 (Public Review):

Summary:

The authors conducted a time-resolved EEG decoding study where they presented sequences of dot locations (4 locations onscreen) or single elements of those sequences, presented at the correct temporal epoch for if they had been presented in the full sequence. They were interested in examining whether presenting single items would activate representations of the anticipated following events that were never presented. Stimuli were presented for 100 ms and separated by 200 ms ISIs. They also had pattern estimation blocks with 600 ms ISIs. They found indeed, that anticipated events could be decoded at their correct moment in time, although future anticipated elements could not.

The decoding of presented dots was fairly confined to the diagonal of the decoding matrix (training time x testing time), suggesting little temporal generalisation. This was in contrast with successor representations which were temporally more diffuse. The subsequent successor could be decoded but not future successors.

Strengths:

I liked this paper. The design was simple and clean and the implications of the findings are clear. The authors achieved their aims with this design, with the results supporting the conclusions. The findings will be of interest to a range of researchers studying learning and perception mechanisms, as well as the more generic role of prediction in the brain.

Weaknesses:

The sample size is fairly low for an EEG study. The authors justify it according to a previous Hogendoorn study, but not according to effect sizes in that study and particular power values.

For understandable reasons, the long ISI blocks were presented before the main test blocks (I would have made the same decision) but there is the risk that participants then come to expect stimuli at larger temporal separations in the main blocks. I do wonder whether this is part of the reason for the greater temporal generalisation for anticipated event representations.

Additional context:

My memory of Ekman et al. 2017 is that single events (presented at position 1) elicited predictive activation of anticipated future events, but that there was a temporal compression. The present study appears to show no temporal compression but that the representations are activated at the correct moment in time. This seems like a potentially interesting difference and one with mechanistic implications for the field.

Reviewer #1 (Public Review):

Summary:

Li and colleagues describe an experiment whereby sequences of dots in different locations were presented to participants while electroencephalography (EEG) was recorded. By presenting fixed sequences of dots in different locations repeatedly to participants, the authors assumed that participants had learned the sequences during the experiment. The authors also trained classifiers using event-related potential (ERP) data recorded from separate experimental blocks of dots presented in a random (i.e., unpredictable) order. Using these trained classifiers, the authors then assessed whether patterns of brain activity could be detected that resembled the neural response to a dot location that was expected, but not presented. They did this by presenting an additional set of sequences whereby only one of the dots in the learned sequence appeared, but not the other dots. They report that, in these sequences with omitted stimuli, patterns of EEG data resembled the visual response evoked by a dot location for stimuli that could be expected, but were not presented. Importantly, this only occurred for an omitted dot stimulus that would be expected to appear immediately after the dot that was presented in these partial sequences.

This exciting finding complements previous demonstrations of the ability to decode expected (but not presented) stimuli in Blom et al. (2020) and Robinson et al. (2020) that are cited in this manuscript. It suggests that the visual system is able to generate patterns of activity that resemble expected sensory events, approximately at times at which an observer would expect them.

Strengths:

The experiment was carefully designed and care was taken to rule out some confounding factors. For example, gaze location was tracked over time, and deviations from fixation were marked, in order to minimise the contributions of saccades to above-chance decoding of dot position. The use of a separate block of dots (with unpredictable locations) to train the classifiers was also useful in isolating visual responses evoked by each dot location independently of any expectations that might be formed during the experiment. A large amount of data was also collected from each participant, which is important when using classifiers to decode stimulus features from EEG data. This careful approach is commendable and draws on best practices from existing work.

Weaknesses:

While there was clear evidence of careful experiment design, there are some aspects of the data analysis and results that significantly limit the inferences that can be drawn from the data. Both issues raised here relate to the use of pre-stimulus baselines and associated problems. As these issues are somewhat technical and may not be familiar to many readers, I will try to unpack each line of reasoning below. Here, it should be noted that these problems are complex, and similar issues often go undetected even by highly experienced EEG researchers.

Relevant to both issues, the authors derived segments of EEG data relative to the time at which each dot was presented in the sequences (or would have appeared when the stimuli were omitted in the partial sequences). Segments were derived that spanned -100ms to 300ms relative to the actual or expected onset of the dot stimulus. The 300ms post-stimulus time period corresponds to the duration of each dot in the sequence (100ms) plus the inter-stimulus interval (ISI) that was 200ms in duration before the next dot appeared (or would be expected to appear in the partial sequences). Importantly, a pre-stimulus baseline was applied to each of these segments of data, meaning that the average amplitude at each electrode between -100ms and 0ms relative to (actual or expected) stimulus onset was subtracted from each segment of data (i.e., each epoch in common EEG terminology). While this type of baseline subtraction procedure is commonplace in EEG studies, in this study design it is likely to cause problematic effects that could plausibly lead to the patterns of results reported in this manuscript.

First of all, the authors compare event-related potentials (ERPs) evoked by dots in the full as compared to partial sequences, to test a hypothesis relating to attentional tuning. They reported ERP amplitude differences across these conditions, for epochs corresponding to when a dot was presented to a participant (i.e., excluding epochs time-locked to omitted dots). However, these ERP comparisons are complicated by the fact that, in the full sequences, dot presentations are preceded by the presentation of other dots in the sequence. This means that ERPs evoked by the preceding dots in the full sequences will overlap in time with the ERPs corresponding to the dots presented at the zero point in the derived epochs. Importantly, this overlap would not occur in the partial sequence conditions, where only one dot was presented in the sequence. This essentially makes any ERP comparisons between full and partial sequences very difficult to interpret, because it is unclear if ERP differences are simply a product of overlapping ERPs from previously presented dots in the full sequence conditions. For example, there are statistically significant differences observed even in the pre-stimulus baseline period for this ERP analysis, which likely reflects the contributions ERPs evoked by the preceding dots in the full sequences, which are absent in the partial sequences.

The problems with interpreting this data are also compounded by the use of pre-stimulus baselines as described above. Importantly, the use of pre-stimulus baselines relies on the assumption that the ERPs in the baseline period (here, the pre-stimulus period) do not systematically differ across the conditions that are compared (here, the full vs. partial sequences). This assumption is violated due to the overlapping ERPs issue described just above. Accordingly, the use of the pre-stimulus baseline subtraction can produce spurious effects in the time period after stimulus onset (for examples see Feuerriegel & Bode, 2022, Neuroimage). This also makes it very difficult to meaningfully compare the ERPs following dot stimulus onset in these analyses.

The second issue relates to the use of pre-stimulus baselines and concerns the key finding reported in the paper: that EEG patterns corresponding to expected but omitted events can be decoded in the partial sequences. In the partial sequences, there are two critical epochs that were derived: One time-locked to the presentation of the dot, and another that was time-locked to 300ms after the dot was presented (i.e. when the next dot would be expected to appear). The latter epoch was used to test for representations of expected, but omitted, stimulus locations.

For the epochs in which the dots were presented, above-chance decoding can be observed spanning a training time range from around 100-300ms and a testing time range of a similar duration (see the plot in Figure 4b). This plot indicates that, during the time window of around 200-300ms following dot stimulus onset, the position of the dot can be decoded not only from trained classifiers using the same time windows spanning 200-300ms, but also using classifiers trained using earlier time windows of around 100-200ms.

This is important because the 200-300ms time period after dot onset in the partial sequences is the window used for pre-stimulus baseline subtraction when deriving epochs corresponding to the first successor representation (i.e., the first stimulus that might be expected to follow from the presented dot, but did not actually appear). In other words, the 200-300ms time window from dot onset corresponds to the -100 to 0 ms time window in the first successor epochs. Accordingly, the pattern that is indicative of the preceding, actually presented dot position would be subtracted from the EEG data used to test for the successor representation. Notably, the first successor condition would always be in another visual field quadrant (90-degree rotated or the opposite quadrant) as stated in the methods. In other words, the omitted stimulus would be expected to appear in the opposite vertical and/or horizontal visual hemifield as compared to the previously presented dot in these partial sequences.

This is relevant because ERPs tend to show reversed polarity across hemifields. For example, a stimulus presented in the right hemifield will have reversed polarity patterns at the same electrode as compared to an equivalent stimulus presented in the left hemifield (e.g., Supplementary Figure 3 in the comparable study of Blom et al., 2020). By subtracting the ERP patterns evoked by the presented dot in the partial sequences during the time period of 200-300ms (corresponding to the -100 to 0ms baseline window), this would be expected to bias patterns of EEG data in the first successor epochs to resemble stimulus positions in opposite hemifields. This could plausibly produce above-chance decoding accuracy in the time windows identified in Figure 5a, where the training time windows broadly correspond to the periods of above-chance decoding during 200-300ms from dot stimulus onset in Figure 4b.

In other words, the above-chance decoding of the first successor representation may plausibly be an artefact of the pre-stimulus baseline subtraction procedure used when deriving the epochs. This casts some doubt as to whether genuine successor representations were actually detected in the study. Additional tests for successor representations using ERP baselines prior to the presented dot in the partial sequences may be able to get around this, but such analyses were not presented, and the code and data were not accessible at the time of this review.

Although the study is designed well and a great amount of care was taken during the analysis stage, these issues with ERP overlap and baseline subtraction raise some doubts regarding the interpretability of the findings in relation to the analyses currently presented.

Reviewer #2 (Public Review):

Summary:

The authors investigated how predicted stimuli are represented in posterior regions of the brain by recording electroencephalography during a visual sequence learning task. After learning the spatial order in which four stimuli were presented within a fixed sequence, participants were shown partial sequences - i.e., sequences in which only one element of the sequence was presented. By examining the decoding accuracy of the omitted stimuli, the authors aimed to investigate whether anticipated stimuli are (pro)actively represented in the expected spatial location at the expected time.

Strengths and Weaknesses:

The study successfully replicated previous findings on omitted stimuli within a predicted sequence (Ekman et al., 2023), while providing novel information regarding the temporal dynamics of predictive representation. Nevertheless, this outcome is not entirely surprising, as similar temporal dynamics were observed in a previous study employing a different task (Kok et al., 2017). The high level of scientific rigor is evident, as demonstrated by the numerous control analyses. Additionally, the results are particularly intriguing in terms of discerning the nature of the prepared representation, spanning from early perceptual to late attentional representations. Unfortunately, this distinction is not investigated in detail, thus allowing for alternative interpretations of the results.

The connection between the findings and the literature on priority maps could benefit from further clarification. There is room for a clearer delineation of how much of the representation can be ascribed to a perceptual prediction mechanism versus an attentional (post-perceptual) spatial cueing process. Although the latter can be readily connected to the concept of a priority map guiding spatial attention, the relationship between the priority map and perceptual prediction remains somewhat ambiguous. Noteworthy, an explanation of the results in terms of spatial cueing does not necessarily require a perceptual predictive mechanism. The significant decoding of the location of the omitted stimulus might be attributed to the preceding stimulus orienting attention towards the following location. While this potential explanation was not explicitly addressed in the study, it presents an intriguing avenue for further investigation.

The study provides valuable insight into how omitted, yet predicted stimuli are represented in the brain and its dynamics. While the research is commendable, addressing the outlined limitations would enhance its impact in the field. Specifically, the spatial location decoding results do not disentangle between perceptual prediction (i.e., the features of the expected stimulus) and attentional processes (i.e., the cueing of the to-be-attended location),

Reviewer #2 (Public Review):

Summary:

In this manuscript, Shah et al. explore the function of an understudied neural circuitry from the dLS -> LHA -> RVM in mediating stress-induced analgesia. They initially establish this neural circuitry through a series of intersectional tracings. Subsequently, they conduct behavioral tests, coupled with optogenetic or chemogenetic manipulations, to confirm the involvement of this pathway in promoting analgesia. Additionally, fiber photometry experiments are employed to investigate the activity of each brain region in response to stress and pain.

Strengths:

Overall, the study is comprehensive, and the findings are compelling.

Weaknesses:

One noteworthy concern arises regarding the overarching hypothesis that restrained-induced stress promotes analgesia. A more direct interpretation suggests that intense struggling, rather than stress per se, activates the dLS -> LHA -> RVM pathway that may drive analgesic responses.

Reviewer #1 (Public Review):

The manuscript entitled "A septo-hypothalamic-medullary circuit directs stress-induced analgesia" by Shah et al., showed that the dLS-to-LHA circuit is sufficient and necessary for stress-induced analgesia (SIA), which is mediated by the rostral ventromedial medulla (RVM) in a opioid-dependent manner. This study is interesting and important and the conclusions are largely supported by the data. I have a few concerns as follows:

(1) The present data show that activation of dLS neurons produces SIA, however, this manipulation is non-specific. It may be better to see the effect of specific manipulation of stress-activated c-Fos positive neurons in the dLS using a combination of the Tet-Off system and chemogenetic/optogenetic tools.

(2) Depending on its duration, and intensity, stress can exert potent and bidirectional modulatory effects on pain, either reducing pain (SIA) or exacerbating it (stress-induced hyperalgesia, SIH). Is the circuit in the manuscript involved in SIH?

(3) It is well-accepted that opioid and cannabinoid receptors participate in the SIA, and the evidence is especially strong for the RVM endocannabinoid system. Given this, why did the authors focus their study on the opioid system?

(4) Does silencing of the dLS neurons affect stress-induced anxiety-like behaviors? Alternatively, what is the relationship between SIA and the level of stress-induced anxiety?

(5) Direct electrophysiological evidence should be provided to confirm the efficacy of the MP-CNO.

(6) Is the LHA a specific downstream target for SIA, and is the LHA involved in stress-induced anxiety-like behaviors?

(7) Do LHA neurons have direct projections to the RVM? If yes, what is its role in the SIA?

Reviewer #2 (Public Review):

To enable robust production of hematopoietic progenitors in-vitro, Petazzi et al examined the role of transcription factors in the arterial hemogenic endothelium. They use IGFBP2 as a candidate gene to increase the directed differentiation of iPSCs into hematopoietic progenitors. They have established a novel induced-CRISPR mediated activation strategy to drive the expression of multiple endogenous transcription factors and show enhanced production of hematopoietic progenitors through expansion of the arterial endothelial cells. Further, upregulation of IGFBP2 in the arterial cells facilitates the metabolic switch from glycolysis to oxidative phosphorylation, inducing hematopoietic differentiation. While the overall study and resources generated are good, assertions in the manuscript are not entirely supported by the experimental data and some claims need further experimental validation.

Reviewer #1 (Public Review):

Summary:

The work from Petazzi et al. aimed at identifying novel factors supporting the differentiation of human hematopoietic progenitors from induced pluripotent stem cells (iPSCs). The authors developed an inducible CRISPR-mediated activation strategy (iCRISPRa) to test the impact of newly identified candidate factors on the generation of hematopoietic progenitors in vitro. They first compared previously published transcriptomic data of iPSC-derived hemato-endothelial populations with cells isolated ex vivo from the aorta-gonad-mesonephros (AGM) region of the human embryo and they identified 9 transcription factors expressed in the aortic hemogenic endothelium that were poorly expressed in the in vitro differentiated cells. They then tested the activation of these candidate factors in an iPSC-based culture system supporting the differentiation of hematopoietic progenitors in vitro. They found that the IGF binding protein 2 (IGFBP2) was the most upregulated gene in arterial endothelium after activation and they demonstrated that IGFBP2 promotes the generation of functional hematopoietic progenitors in vitro.

Strengths:

The authors developed an extremely useful doxycycline-inducible system to activate the expression of specific candidate genes in human iPSC. This approach allows us to simultaneously test the impact of 9 different transcription factors on in vitro differentiation of hematopoietic cells, and the system appears to be very versatile and applicable to a broad variety of studies.

The system was extensively validated for the expression of 1 transcription factor (RUNX1) in both HeLa cells and human iPSC, and a detailed characterization of this test experiment was provided.

The authors exhaustively demonstrated the role of IGFBP2 in promoting the generation of functional hematopoietic progenitors in vitro from iPSCs. Even though the use of IGFBP2-interacting proteins IGF1 and IGF2 have been previously reported in human iPSC-derived hematopoietic differentiation in vitro (Ditadi and Sturgeon, Methods 2016; Ng et al., Nature Biotechnology 2016), and IGFBP-2 itself has been shown to promote adult HSC expansion ex vivo (Zhang et al., Blood 2008), its role on supporting in vitro hematopoiesis was demonstrated here for the first time.

Weaknesses:

Although the authors performed a very thorough characterization of the system in proof-of-principle experiments activating a single transcription factor, the data provided when 9 independent factors were used is not sufficient to fully validate the experimental strategy. Indeed, in the current version of the manuscript, it is not clear whether the results presented in both the scRNAseq analysis and the functional assays are the consequence of the simultaneous activation of all 9 TF or just a subset of them. This is essential to establish whether all the proposed factors play a role during embryonic hematopoiesis, and a more complete analysis of the scRNAseq dataset could help clarify this aspect.

Similarly, the data presented in the manuscript are not sufficient to clarify at what stage of the endothelial-to-hematopoietic transition (EHT) the TF activation has an impact. Indeed, even though the overall increase of functional hematopoietic progenitors is fully demonstrated, the assays proposed in the manuscript do not clarify whether this is due to a specific effect at the endothelial level or to an increased proliferation rate of the generated hematopoietic progenitors. Similar conclusions can be applied to the functional validation of IGFBP2 in vitro.

The overall conclusions are sometimes vague and not always supported by the data. For instance, the authors state that the CRISPR activation strategy resulted in transcriptional remodeling and a steer in cell identity, but they do not specify which cell types are involved and at what level of the EHT process this is happening. In the discussion, the authors also claim that they provided evidence to support that RUNX1T1 could regulate IGFBP2 expression. However, this is exclusively based on the enrichment of RUNX1T1 gRNA in cells expressing higher levels of IGFBP2 and it does not demonstrate any direct or indirect association of the two factors.

Joint Public Review:

In their revised manuscript additional experiments have been conducted competently, and the interpretation of experiments regarding exit from the ER are convincing. They collectively indicate that the phase partitioning behaviour of the TMDs do not have a significant effect on exit from the ER; they all exit the ER very slowly unless they carry a short cytoplasmic domain from LAT which is sufficient to accelerate ER exit. This data is consistent with available literature supporting a role for a ER-exit signal. Along with new experiments in their revision, they have also toned down the assertion that their data rule out a phase partitioning mechanism at the ER.

The authors, however, continue to interpret their experiments regarding Golgi exit of the transmembrane peptides (with luminal and cytoplasmic domains) as conclusive evidence of the role of lipid rafts in exit from the Golgi. This is once again based on correlation of the phase partitioning behaviour of these proteins in GPMVs, phase separated at low temperatures. They argue that this represents very strong evidence that trafficking out of the Golgi is driven by phase separation. The reviewers consider that there are a number of potential issues with the final model that need to be addressed.

We reiterate that:

(1) the phase segregation in the GPMV at low temperatures is dictated by thermodynamics given its composition and the measurement temperature. However at physiological temperatures at which membrane trafficking is taking place these GPMVs will not exhibit phase separation. Hence it is difficult to argue that a sorting mechanism based solely on the partitioning of the synthetic TM constructs into liquid ordered domain detected at low temperatures in GPMVs provide an explanation of the explanation of the differential kinetics of traffic of the LAT TMD and the allL-TMD constructs, although there is a strong correlation with its phase partitioning behaviour.

(2) The fluctuations of lipid composition resembling lo-domains if persisting at higher temperatures and its conversion into a sorting domain will require a cellular mechanism, that may or may not retain similar properties of these lipidic environments. Additionally, TMDs from TfR/VsVG and GPI prefer different domains in the GPMV assays (Table S1) yet they traffic to the cell surface equally rapidly.

(3) The authors fail to discuss the point raised about the relatively high colocalization of TfR with the GPI probe (seen in Fig 5E) in the Golgi. This is inconsistent with their explanation of traffic correlating with partitioning into distinct domains in the Golgi, since TfR and GPI probes show an opposite preference for lo versus ld domains in cooled GPMVs. TMD-allL and the LAT-allL are segregated from TfR in the Golgi, and end up in a different final destination (ie lysosomes). This could represent yet another membrane specialisation in the Golgi for lysosomal traffic. The segregation that the authors report in the Golgi is therefore not a convincing argument for phase preferences in GPMVs dictating the trafficking behaviour of these molecules towards the plasma membrane.

(4) Despite the authors' claim in their rebuttal that 'we feel that GPMVs are a useful tool for quantifying protein preference for ordered (raft) membrane domains and that this preference is a useful proxy for the raft-associated behavior ... biological membrane with a relevant and measurable cellular outcome, specifically inter-organelle trafficking rates." -several caveats for these observations need to be addressed before they constitute strong evidence for the raft model of membrane trafficking proposed. Phase partitioning in GPMVs is just another operational definition and while more refined (ie the data is derived from the membrane of interest, ie, the plasma membrane) it is not very different conceptually from quantitative measurements of detergent-insolubility.

(5) Further work is necessary to establish that ordered domains are formed at the Golgi at physiological temperatures, into which these proteins may partition; subsequently, there must be a mechanism that selectively traffics these proteins towards the cell surface.

(6) The authors continue to conflate thermodynamic phase separation mechanisms with the real possibility of the formation of functional sorting domains by cellular mechanisms that likely involve lipidic interactions, adding to the confusion in the literature.

Reviewer #1 (Public Review):

Summary:

This manuscript describes the identification and isolation of several phage from deep sea isolates of Lentisphaerae strains WC36 and zth2. The authors observe induction of several putative chronic phages with the introduction of additional polysaccharides to the media. The authors suggest that two of the recovered phage genomes encode AMGs associated with polysaccharide use. The authors also suggest that adding the purified phage to cultures of Pseudomonas stutzeri 273 increased the growth of this bacteria due to augmented polysaccharide use genes from the phage.

While the findings were of interest and relevance to the field, it is my opinion that several of the analysis fall short of supporting the key assertions presented.

Strengths:

Interesting isolate pf deep sea Lentisphaerae strains which will undoubtedly further our understanding of deep sea microbial life.

Weaknesses:

Many of the findings are consistent with a phage contamination in the polysaccharide stock solution.

The genes presented as AMGs are largely well known and studied phage genes which play a role in infection cycles.

The evidence that the isolated phage can infect Pseudomonas stutzeri 273 is lacking, putting into question the dependent results.

Reviewer #2 (Public Review):

Summary:

This paper investigates virus-host interactions in deep-sea bacteriophage systems which employ a seemingly mutualistic approach to viral replication in which the virus aids host cell polysaccharide import and utilization via metabolic reprogramming. The hypothesis being tested is supported with solid and convincing evidence and the findings are potentially generalizable with implications for our understanding of polysaccharide-mediated virus-host interactions and carbon cycles in marine ecosystems more broadly.

Strengths:

This paper synthesizes sequencing and phylogenic analyses of two Lentisphaerae bacteria and three phage genomes; electron microscopy imaging of bacterial/phage particles; differential gene expression analyses; differential growth curve analyses, and differential phage proliferation assays to extract insights into whether laminarin and starch can induce both host growth and phage proliferation. The data presented convincingly demonstrate that both host culture density and phage proliferation increase as a result having host, phage, and polysaccharide carbon source together in culture.

Weaknesses (suggestions for improvement):

The article would be strengthened by the following additional experiment: providing the phage proteins hypothesized to be aiding host cell growth (red genes from Figure 5...TonB system energizer ExbB, glycosidases, etc) individually or in combination on plasmids rather than within the context of the actual phage itself to see if such additional genes are necessary and sufficient to realize the boosts in host cell growth/saturation levels observed in the presence of the phages tested.

The paper would also benefit from additional experiments focused on determining how the polysaccharide processing, transport, and metabolism genes are being used by the phages to either directly increase viral infection/replication or else to indirectly do so by supporting the growth of the host in a more mutualistic manner (i.e. by improving their ability to import, degrade, and metabolize polysaccharides).

The introduction would benefit from a discussion of what is known regarding phage and/or viral entry pathways that utilize carbohydrate anchors during host entry. The discussion could also be improved by linking the work presented to the concept of "selfishness" in bacterial systems (see for instance Giljan, G., Brown, S., Lloyd, C.C. et al. Selfish bacteria are active throughout the water column of the ocean. ISME COMMUN. 3, 11 (2023) https://doi.org/10.1038/s43705-023-00219-7). The bacteria under study are gram negative and it was recently demonstrated (https://www.nature.com/articles/ismej201726) that "selfish" bacteria sequester metabolizable polysaccharides in their periplasm to advantage. It is plausible that the phages may be hijacking this "selfishness" mechanism to improve infectivity and ENTRY rather than helping their hosts to grow and profilerate so they can reap the benefits of simply having more hosts to infect. The current work does not clearly distinguish between these two distinct mechanistic possibilities. The paper would be strengthened by at least a more detailed discussion of this possibility as well as the author's rationale for interpreting their data as they do to favor the "mutualistic" interpretation. In the same light, the paper would benefit from a more careful choice of words which can also help to make such a distinction more clear/evident/intentional. As currently written the authors seem to be actively avoiding giving insights wrt this question.

Finally, I would be interested to know if the author's sequencing datasets might be used to inform the question raised above by using bacterial immunity systems such as CRISPR/Cas9. For example, if the phage systems studied are truly beneficial/mutualistic for the bacteria then it's less likely that there would be evidence of targeted immunity against that particular phage that has the beneficial genes that support polysaccharide metabolism.

Reviewer #1 (Public Review):

This manuscript examines the individual and dual effects of CHIP and LOY in MI employing a cohort of ~460 individuals. CHIP is assessed by NGS and LOY is assessed by PCR. The threshold for CHIP is set at 2% (an arbitrary cutoff that is often used) and LOY at 9% (according to the Discussion text - this reviewer may have missed the section that describes why this threshold was employed). The investigation assessed whether LOY could modulate inflammation, atherosclerotic burden, or MI risk associated with CHIP. Neither CHIP nor LOY independently affected hsCRP, atherosclerotic burden, or MI incidence, nor did LOY presence diminish these outcomes in CHIP+ male subjects.

This study represents the first dual analysis of CHIP and LOY on CVD outcomes. The results are largely negative, contradictory to other studies (many with much larger sample sizes). I would attribute the limitation of sample size as a major contributor to the negative data. While the negative data are suspect, the "positive" finding that LOY abolishes the prognostic significance of CHIP on MI is of interest (and consistent with what is understood from mechanistic studies).

Overall, I enjoyed reading the paper, and it is of interest to the research community. However, I disagree with some of the authors' interpretations of the data. Generally, many conclusions on CHIP interpretation are based on the comparison of findings from very large datasets that have been evaluated by shallow NGS DNA sequencing. These studies lack sensitivity and accuracy, but this is counterbalanced by their very large sample sizes. Thus, they draw conclusions from the sickest individuals (ICD codes) with the largest clones (explaining the 10% VAF threshold). Here, the study has a well-phenotyped cohort, but as far as this reviewer can tell, the DNA sequencing is "shallow" NGS. Typically, to assess smaller datasets, investigators employ an error-correction method (DNA barcodes, duplex sequencing, etc.) for the sensitivity and accuracy of calling variants. Thus, the current study appears to suffer from this limitation (small sample sizes combined with NGS).

While the "negative" data from this study are inconclusive, the positive data (i.e. CHIP being prognostic for MI in the absence but not presence of MI) is of interest. Thus, the investigators may want to consider a shorter report that largely focuses on this finding.

Reviewer #2 (Public Review):

Summary:

The preprint by Fawaz et al. presents the findings of a study that aimed to assess the relationship between somatic mutations associated with clonal hematopoiesis (CHIP) and the prevalence of myocardial infarction (MI). The authors conducted targeted DNA sequencing analyses on samples from 149 MI patients and 297 non-MI controls from a separate cohort. Additionally, they investigated the impact of the loss of the Y chromosome (LOY), another somatic mutation frequently observed in clonally expanded blood cells. The results of the study primarily demonstrate no significant associations, as neither CHIP nor LOY were found to be correlated with an increased prevalence of MI. Of note, the null findings regarding CHIP are in conflict with several larger studies in the literature.

Strengths:

Overall, this is a useful research work on an emerging risk factor for cardiovascular disease (CVD). The use of a targeted sequencing approach is a strength, as it offers higher sensitivity than the whole exome sequencing approaches used in many previous studies.

Weaknesses:

Reporting null findings is definitely relevant in an emerging field such as the role of somatic mutations in cardiovascular disease. Nevertheless, the study suffers from severe limitations, which casts doubts on the authors' conclusions, as detailed below:

(1) The small sample size of the study population is a critical limitation, particularly when reporting null findings that conflict (partly) with positive findings in much larger studies, totaling hundreds of thousands of individuals (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024). The authors claim that they have 90% power to detect an effect size of CHIP on MI comparable to that in a previous report (Jaiswal et al, NEJM 2017). However, the methodology used to estimate statistical power is not described. Furthermore, the work by Jaiswal et al (NEJM 2017) showed a hazard ratio of approx. 2.0, but more recent work in much larger populations suggests that the overall effect of CHIP on atherosclerotic CVD is smaller, most likely due to the heterogeneity of effects of different mutated genes (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024). In addition, several analyses in the current manuscript are conducted separately in MI(+) (n= 149) and MI(-) (N=297) individuals, further limiting statistical power. Power is still lower in the investigation of the effects of LOY and its interaction with CHIP, as only men are included in these analyses. Overall, I believe the study is severely underpowered, which calls into question the validity of the reported null findings.

(2) Related to the above, it is widely accepted that the effects of CHIP on CVD are highly heterogeneous, as some mutated genes appear to have a strong impact on atherosclerosis, whereas the effect of others is negligible (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023, among others). TET2 mutations are frequently considered a "positive control", given the multiple lines of evidence suggesting that these mutations confer a higher risk of atherosclerotic disease. However, no association with MI or related variables was found for TET2 mutations in the current work. Reporting the statistical power specifically for assessing the effect of TET2 mutations would enhance the interpretation of these results.

(3) One of the most essential features of CHIP is the tight correlation with age. In this study, the effect of age on CHIP (Supplementary Tables S5, S6) seems substantially milder than in previous studies. Given the relatively weak association with age here, it is not surprising that no association with MI or atherosclerotic disease was found, considering that this association would have a much smaller effect size. In addition, there are previous reports of sex-related differences in the prevalence of CHIP, is there an association between CHIP and age after adjusting for sex?

(4) The mutated genes included in the definition of "CHIP" here are markedly different than those in most previous studies, particularly when considering specifically the studies that demonstrated an association between CHIP and atherosclerotic CVD. For instance, the definition of CHIP in this manuscript includes genes such as ANKRD26, CALR, CCND2, and DDX41... that are not prototypical CHIP genes. This is unlikely to have a major impact on the main results, as the vast majority of mutations detected are indeed in bona fide CHIP genes, but it should be at least acknowledged. Furthermore, the strategy used here for the CHIP variant calling and curation seems substantially different than that used in previous studies, which precludes a direct comparison. This is important because such differences in the definition of CHIP and the curation of variants are the basis of most conflicting findings in the literature regarding the effects of this condition. Ideally, the authors should conduct sensitivity analyses restricted to prototypical CHIP genes, using the criteria that have been previously established in the field (e.g. Vlasschaert et al, Blood 2023).

(5) An important limitation of the current study is the cross-sectional design of most of the analyses. For instance, it is not surprising that no association is found between CHIP and prevalent atherosclerosis burden by ultrasound imaging, considering that many individuals may have developed atherosclerosis years or decades before the expansion of the mutant clones, limiting the possible effect of CHIP on atherosclerosis burden. Similarly, the analysis of the relationship between CHIP and a history of MI may be confounded by the potential effects of MI on the expansion of mutant clones. In this context, it is noteworthy that the only positive results here are found in the analysis of the relationship between CHIP at baseline and incident MI development over follow-up. Increasing the sample size for these longitudinal analyses would provide deeper insights into the relationship between CHIP and MI.

(6) The description of some analyses lacks detail, but it seems that statistical analyses were exclusively adjusted for age or age and sex. The lack of adjustment for conventional cardiovascular risk factors in statistical analyses may confound results, particularly given the marked differences in several variables observed between groups.

(7) The variant allele fraction (VAF) threshold for identifying clinically relevant clonal hematopoiesis is still a subject of debate. The authors state that subjects without any detectable mutation or with mutations with a VAF below 2% were considered non-CHIP carriers. While this approach is frequent in the field, it likely misses many impactful mutations with lower VAFs. Such false negatives could contribute to the null findings reported here. Ideally, the authors should determine the lower detection limit of their sequencing approach (either computationally or through serial dilution experiments) and identify the threshold of VAF that can be detected reliably with their sequencing assay. The association between CHIP and MI should then be evaluated considering all mutations above this VAF threshold, in addition to sensitivity analyses with other thresholds frequent in the literature, such as 1% VAF, 2% VAF, and 10% VAF.

(8) The authors should justify the use of 3D vascular ultrasound imaging exclusively in the supra-aortic trunk. I am not familiar with this technique, but it seems to be most typically used to evaluate atherosclerosis burden in superficial vascular beds such as carotids or femorals. I am concerned about the potential impact of tissue depth on the accurate quantification of atherosclerosis burden in the current study (e.g. https://doi.org/10.1016/j.atherosclerosis.2016.03.002). It is unclear whether the carotids or femorals were imaged in the study population.

(9) The specific criteria used to define LOY need to be justified. LOY is stated to be defined based on a "A cut off of 9% of cells with mLOY defined the detection of a mLOY based on the study of 30 men of less than 40 years who had a normal karyotype as assessed by conventional cytogenetic study." As acknowledged by the authors, this definition of LOY is substantially different than that used in recent studies employing the same technique to detect LOY (Mas-Peiro et al, EHJ 2023). In addition, it seems essential to provide more detailed information on the ddPCR assay used to determine LOY, including the operating range and, more importantly, the lower limit of detection (%LOY) of the assay. A dilution series of a control DNA with no LOY would be helpful in this context.

(10) Our understanding of the relationship between CHIP and CVD is evolving fast, and the manuscript should be considered in the context of recent literature in the field. For instance, the recent work by Zhao et al (JAMA Cardio 2024, doi:10.1001/jamacardio.2023.5095) should be considered, as it used a similar targeted DNA sequencing approach as the one used here, but found a clear association between CHIP and coronary heart disease (in a population of 6181 individuals).

(11) The use of subjective terms like "comprehensive" or "thorough" in the title of the manuscript does not align with the objective nature of scientific reporting.

Reviewer #1 (Public Review):

This study by Porter et al reports on outcomes from a small, open-label, pilot randomized clinical trial comparing dornase-alfa to best available care in patients hospitalized with COVID-19 pneumonia. As the number of randomized participants is small, investigators describe also a contemporary cohort of controls and the study concludes with decrease of inflammation (reflected by CRP levels) after 7 days of treatment but no other statistically significant clinical benefit.

I read with interest this manuscript and I find the idea about treatment of COVID-19 patients with dornase-alfa novel and inspiring. I have some major concerns about the methodology the authors followed in this RCT.

My major concerns are:

(1) The authors have chosen a primary outcome that cannot be at least considered as clinically relevant or interesting. After 3 years of the pandemic with so much research, why investigate if a drug reduces CRP levels as we already have marketed drugs that provide beneficial clinical outcomes such as dexamethasone, anakinra, tocilizumab and baricitinib.

(2) ΙΤΤ analysis is not followed

Reviewer #2 (Public Review):

Interesting work with an original and appealing hypothesis. The authors performed an open-label trial comparing nebulized dornase alfa to best available care in COVID-19, reaching the primary outcome of CRP reduction over the first week of intervention. The main weaknesses of the study are the small sample size, the lack of randomization for the majority of the participants, and the lack of blinding. The authors have sufficiently addressed the issues raised, provided that these weaknesses are highlighted in the limitations section.

Reviewer #1 (Public Review):

I have reviewed, with interest, the manuscript "Psychological stress disturbs bone metabolism via miR-335-3p/Fos signaling in osteoclast". The described findings are relevant and useful for daily practice in periodontology. The paper is concise, professionally written, and easy to read. In this study, Jiayao et al. revealed the role of miR-335-3p in psychological stress-induced osteoporosis. CUMS mice were constructed to observe the femur phenotype, osteoclasts were identified as the primary research object, and miRNA-seq was used to find the key miRNAs linking the brain and peripheral tissues. This study showed that the expression of miR-335-3p was simultaneously reduced in mice's NAC, serum, and bone under psychological stress. The miR-335-3p/Fos/NFATC1 signaling pathway was validated in osteoclasts to reveal the potential mechanism of enhanced osteoclast activity under psychological stress. From a new perspective of miRNAs, this study indicates a possible cause of disturbed bone metabolism due to psychological stress and may suggest a new approach to treating osteoporosis.

Reviewer #2 (Public Review):

Zhang et al. established chronic unpredictable mild stress (CUMS) mouse model, which displayed osteoporosis phenotype, suggesting a potential correlation between psychological stress and bone metabolism. They found that miRNA candidate miR-335-3p is downregulated in the long bone of CUMS mice through microRNA sequencing and qRT-PCR experiments. They further demonstrated that miR-335-3p attenuates osteoclast activity via inhibiting Fos signaling, which can induce NFATC1 expression and regulate osteoclast activity.

Strengths:

The authors established CUMS mouse model and confirmed the osteoporosis phenotype through careful characterization of bone and analysis of osteoclast activity. They performed microRNA sequencing to identify the miRNA candidate regulating the bone loss in the CUMS mouse model. They also validated the expression of miR-335-3p and interfered with the function of miR-335-3p through an in vitro assay. Overall, the findings from this study provide important hints for the correlation between psychological stress and bone metabolism.

Weakness:

The data provided by the authors are preliminary, especially the mechanistic insight, which needs to be enhanced. The authors have shown that miR-335-3p expression was altered in the CUMS mouse model and the change of its expression regulated osteoclast activity. The validation should be conducted in vivo, and the mechanism behind this should be investigated further.

Reviewer #2 (Public Review):

The authors analysed functional MRI recordings of brain activity at rest, using state-of-the-art methods that reveal the diverse ways in which information can be integrated in the brain. In this way, they found brain areas that act as (synergistic) gateways for the 'global workspace', where conscious access to information or cognition would occur, and brain areas that serve as (redundant) broadcasters from the global workspace to the rest of the brain. The results are compelling and are consistent with the already assumed role of several networks and areas within the Global Neuronal Workspace framework. Thus, in a way, this work comes to stress the role of synergy and redundancy as complementary information processing modes, which fulfill different roles in the bigger context of information integration.

In addition, to prove that the identified high-order interactions are relevant to the phenomenon of consciousness, the same analysis was performed in subjects under anesthesia or with disorders of consciousness (DOC), showing that indeed the loss of consciousness is associated with a deficient integration of information within the gateway regions.

Reviewer #3 (Public Review):

The work proposes a model of neural information processing based on a 'synergistic global workspace,' which processes information in three principal steps: a gatekeeping step (information gathering), an information integration step, and finally, a broadcasting step. They provided an interpretation of the reduced human consciousness states in terms of the proposed model of brain information processing, which could be helpful to be implemented in other states of consciousness. The manuscript is well-organized, and the results are important and could be interesting for a broad range of literature, suggesting interesting new ideas for the field to explore.

Reviewer #1 (Public Review):

Existing literature suggests that brain structures implicated in memory such as the hippocampus, and reward/punishment processing such as the striatal regions are also engaged in learning and value-based decision-making. However, how the contributions of these regions to learning and value-based decision-making change over time, particularly in children where these neural systems show protracted maturation was not studied systematically. This is the question the authors are aiming to address in this work in which children 6-to-7-years-old were recruited for a neuroimaging study that involves taking structural scans from this cohort to investigate how they correlate with changes in the way children approach a reinforcement learning task in which they learn to identify the better shape between 2 options through trial-and-error.

Particular strengths of the paper are longitudinally following up a cohort of small children and engaging them in a value-based decision-making task so that the relationship between neural maturation and improvements in reinforcement learning can be studied reliably. Towards this end, the authors make use of well-established computational modelling approaches to extract key parameters such as learning rates (which designate the speed of learning from expected versus actual outcomes) or choice stochasticity (which designate the inherent variation in people's decisions and the tendency to explore between the options) from children's choices so that their structural neural correlates can be established. As a part of this endeavour, the authors rely on methodological choices which do not warrant much criticism. Their data visualization choices are particularly spot-on and highly informative about the details of the raw data.

Also considering the importance of the hippocampal system in human memory, the key contribution of the paper is that the volumetric increases in hippocampus size between 2 assessment points correlated selectively with the delayed, but not immediate, learning score which refers to the learning condition in which the outcome feedback is given to the children after a 5-seconds delay. Although the authors also demonstrate evidence to suggest that changes in the striatal volume are also implicated in learning performance, this was more general as associations were found for both immediate and delayed feedback conditions. Thus, the paper makes an important contribution to the fields of developmental and decision neuroscience. An important question arising from the authors' findings could be that, whether the hippocampus maintains this selective role in value-based learning during the course of neuronal development, for example, whether a similar association would be found in children 8-to-9 years old. A better understanding of how these developmental trajectories map onto changes in learning and decision-making can inform fields outside neuroscience, for example tailoring educational approaches onto neural development pathways to boost learning efficiency in young children.

Reviewer #2 (Public Review):

Summary:

This is an interesting and impressive study that provides a rare opportunity to learn about brain-behaviour links of learning systems at a relatively early stage of development.

The main strengths are that the authors followed a relatively large group of children over 2 years and used a reinforcement learning task aimed at assessing learning that depends on both the striatum and the hippocampus. The authors also included a thorough overview of the computational models and the choices they made. I think this paper would be of considerable interest and contributes to knowledge about how learning and memory systems change with development.

Reviewer #1 (Public Review):

Summary:

The authors goal here was to explore how a non hebbian form of plasticity, heterosynaptic LTP, could shape neuronal responses and learning. They used several conceptually and technically innovative approaches to answer this. First, they identified a behavioral paradigm that was a subthreshold training paradigm (stimulation of thalamic inputs with a footshock), which could be 'converted' to a memory via homosynaptic LTP (HFS of thalamic inputs). They then find that stimulation of 'cortical' inputs could also convert the subthreshold stimulation to a lasting memory, and that this was associated with a change in neuronal response, akin to LTP. Finally, they provide some slice work which demonstrated that stimulation of cortical inputs could stabilize LTP at thalamic inputs.

Strengths:

(1) The approach was innovative and asked an important question in the field.

(2) The studies are, for the most part, quite rigorous, using a novel dual opsin approach to probe multiple inputs in vivo.

(3) The authors explore neural responses both in vivo and ex vivo, as well as leveraging a 'simple' behavior output of freezing.

Reviewer #2 (Public Review):

Summary

Faress et al. address how synaptic plasticity (i.e. potentiation induced by high frequency stimulation, HFS) induced at different time points and pathways relative to those active during initial learning can transform memories. They adopt an experimental design developed by Nabavi et al, 2014 to optogenetically induce a weak fear memory by pairing an optical conditioned stimulus (CS) at thalamo-LA synapses with a footshock unconditioned stimulus (US) in male mice. Homosynaptic HFS delivered in the same pathway before or after conditioning transforms the weak memory into a stronger one. Leveraging a new dual wavelength optogenetic approach in vivo, they also show that heterosynaptic (cortico-LA) HFS directly following the opto-conditioning can transform the thalamo-LA induced fear memory, or create a memory when directly delivered after unpaired conditioning. Lastly, they demonstrate that heterosynaptic potentiation of the thalamo-LA pathway accompanies the strengthening of fear memory in freely moving mice. The authors conclude that a transient experience (i.e. weak memory) can be transformed into a stable one by non-Hebbian forms of plasticity.

Strengths

This study uses well-defined and elegant optogenetic manipulations of distinct neural pathways in awake behaving mice combined with in vivo recordings, which allows to directly manipulate and monitor synaptic strength and memory. It addresses an interesting, timely, and important question.

Weaknesses

A key experiment with in vivo monitoring of LFPs and behavior (Fig. 5a-c) seems a bit underpowered and input-output curves (extended data 5c) not entirely convincing.<br /> Ex vivo slice experiments (Fig. 5d-f) are not well aligned with in vivo experimental conditions. While they provide proof of principle, this is not entirely novel (see Fonseca et al, 2013).

Significance and impact

The conclusions are well supported by the data. The significance of the study lies in showing in vivo, that plasticity induced at different times or synaptic pathways than those engaged during learning can modify a memory and the synaptic strength in the neural pathway related to that memory. While heterosynaptic and timing-dependent effects in synaptic plasticity have been described largely ex vivo on shorter time scales, the discovery of lasting behavioral effects on memory is novel. The study was enabled by a combination of clever approaches: creation of a "synthetic" pathway-specific association and a novel dual opsin approach in vivo to probe the role of plasticity in a converging second pathway at the same time.<br /> This work broadens our understanding of how Hebbian and non-Hebbian forms of plasticity shape neural activity and associative memory and is of broad interest to the neuroscience community.

Reviewer #1 (Public Review):

Summary:

This is a strong paper that sets the foundation for future work that will explore the innervation of the giant fiber, allowing experiments that will link molecular/developmental mechanisms to circuit function at a level of resolution that has not previously been possible. In the course of this work the investigators discover an axon-axon competition that reflects the order of innervation of the target. In addition, a host of reagents are developed that will be of wide use in dissecting this system.

Strengths:

(1) The developmental, functional and connectomic characterization of the wiring pattern to be dissected is impressively thorough and quantitative.<br /> (2) The reagents that the authors establish will be foundational to subsequent effort.<br /> (3) The discovery that axon-axon competition is involved in patterning this system, and might combined with innervation order to give a deterministic outcome is an interesting one (and might be useful to address variation in cell number (see below)!

Weaknesses:

(1) In my opinion, the authors miss an opportunity to leverage their connectomics characterization somewhat more. That is, from characterization of the connectomes of two flies, the authors describe substantial variation in the number of pre-synaptic cells providing inputs (for example, in FAFB, there are 55 LC4 cells, while in the hemibrain, there are 71 - almost 30 percent more), yet the number of total synapses provided by each class of cell types is remarkably stereotyped 2442 synapses versus 2290 synapses). And the ratio of LC4 to LPLC2 synapses is even more stereotyped... As this kind of stereotypy would be consistent with the authors competition model, but inconsistent with a model in which each cell makes a similar number of synapses (which would be the model from the periphery of the visual system), the authors should comment a bit more on what they see. Perhaps the wiring model the authors advocate for compensates for what appears to be quite significant variation in the numbers of LC neurons?

(2) I appreciate how the authors pivoted to interpreting their results using Kir2.1 to reflect the effects of cell ablation. However, I worry that since the mechanism behind Kir2.1 mediated ablation is unknown, there could be other effects associated with this perturbation, creating indirect effects that alter LPLC2 cells somehow. I would therefore ask that the authors repeat these experiments with a more standard cell ablation strategy (such as a light gated caspase, or ricin). More crucially, the author's model that arrival order is functionally important would be greatly strengthened if they did the reciprocal ablation of LPLC2 and asked what happens to LC4. One could easily imagine a model in which these two cell types mutually compete for real estate, after an initial bias is set by arrival order.

Reviewer #2 (Public Review):

Summary:

The authors investigate axonal and synapse development in two distinct visual feature-encoding neurons (VPN), LC4 and LPLC2. They first show that they occupy distinct regions on the GF dendrites, and likely arrive sequentially. Analysis of the VPNs' morphology throughout development, and synaptic gene and protein expression data reveals the temporal order of maturation. Functional analysis then shows that LPLC2 occupancy of the GF dendrites is constrained by LC4 presence.

Strengths:

The authors investigate an interesting and very timely topic, which will help to understand how neurons coordinate their development. The manuscript is very well written, and data are of high quality, that generally support the conclusions drawn (but see some comments for Fig. 2 below). A thorough descriptive analysis of the LC4/LPLC2 to GF connectivity is followed by some functional assessment showing that one neuron's occupancy of the GF dendrite depend on another.<br /> The manuscripts uses versatile methods to look at membrane contact, gene and protein expression (using scRNAseq data and state-of-the art genetic tools) and functional neuronal properties. I find it especially interesting and elegant how the authors combine their findings to highlight the temporal trajectory of development in this system.

Weaknesses:

After reading the summary, I was expecting a more comprehensive analysis of many VPNs, and their developmental relationships. For a better reflection of the data, the summary could state that the authors investigate *two* visual projection neurons (VPNs) and that ablation *of one cell type of VPNs* results in the expansion of the remaining VPN territory.

The manuscript is falling a bit short of putting the results into the context of what is known about synaptic partner choice/competition between different neurons during neuronal or even visual system development. Lots of work has been done in the peripheral the visual system, from the Hiesinger lab and others. Both the introduction and the discussion section should elaborate on this.

The one thing that the manuscript does not unambiguously show is when the connections between LC4 and LPLC2 become functional.

Figure 2:<br /> Figure 2A-C: I found the text related to that figure hard to follow, especially when talking about filopodia. Overall, life imaging would probably clarify at which time point there really are dynamic filopodia. For this study, high magnification images of what the authors define as filopodia would certainly help.<br /> L137ff: This section talks about filopodia between 24-48 hAPF, but only 36h APF is shown in A, where one could see filopodia. The other time points are shown in B and C, but number of filopodia is not quantified.<br /> L143: "filopodia were still present, but visibly shorter": This is hard to see, and again, not quantified.<br /> L144f: "from 72h APF to eclosion, the volume of GF dendrites significantly decreased": this is not actually quantified, comparisons are only done to 24, 36 and 48 h APF.<br /> Furthermore, 72h APF is not shown here, but in Figure 2D, so either show here, or call this figure panel already?

Figure 2D/E: to strengthen the point that LC4 and LPLC2 arrive sequentially, it would help to show all time points analyzed in Figure D/E.

L208: "significant increase ... from 60h APF to 72h APF": according to the figure caption, this comparison is marked by "+" but there is no + in the figure itself.

Figure 3:<br /> A key point of the manuscript is the sequential arrival of different VPN classes. So then why is the scRNAseq analysis in Figure 3 shown pooled across VPNs? Certainly, the reader at this point is interested in temporal differences in gene expression. The class-specific data are somewhat hidden in Supp. Fig. 9, and actually do not show temporal differences. This finding should be presented in the main data.

L438: "silencing LC4 by expressing Kir2.1... reduced the GF response": Is this claim backed by some quantification?

Figure 4K: Do the control data have error bars, which are just too small to see? And what is tested against what? Is blue vs. black quantified as well? What do red, blue, and black asterisks indicate? Please clarify in figure caption.

Optogenetics is mentioned in methods (in "fly rearing", in the genotypes, and there is an extra "Optogenetics" section in methods), but no such data are shown in the manuscripts. (If the authors have those data, it would be great to know when the VPN>GF connections become functional!)

Methods:

Antibody concentrations are not given anywhere and will be useful information for the reader

Could the authors please give more details on the re-analysis of the scRNAseq dataset? How did you identify cell type clusters in there, for example?

L785 and L794: I am curious. Why is it informative to mention what was *not* done?

Custom-written analysis code is mentioned in a few places. Is this code publicly available?

Reviewer #3 (Public Review):

Summary:

In this work, MacFarland et.al. show that difference in the time of contact between axons of LC4 and LPLC2 visual projection neurons (VPNs) in the optic glomeruli and dendrites of large descending neuron, the giant fiber (GF) shapes the differential connectivity between these neurons.

Strengths:

The authors analyzed the development of a well-known circuit between GF dendrites and LC4 andLPLC2 axons using different approaches. Additionally, they developed an ex-vivo patch clamping technique to show, together with correlative RNA-sequencing data, that contact site restriction is not dependent on neuronal activity. Based on this study, the connectivity pattern between GF and the adjacent different sets of VPNs now provides a very interesting model to investigate developmental programs that lead to synaptic specificity.

Weaknesses:

Following are the concerns that significantly impact the veracity of conclusions drawn based on the data provided.

(1) All the data related to the activity of VPNs and GF and how this activity is related to the connectivity and/or maintaining and stabilizing this connectivity is correlative. The expression profiles of synaptic molecules (only at RNA level) over time or the appearance of pre and post synaptic proteins or the spontaneous spike patterns in GF do not show the role of activity in synapse specificity program. Synaptic molecules have been previously shown to be present at presynaptic sites without being involved in activity (Chen et al., 2014, Jin et al., 2018). To show whether activity is indeed not required for connectivity for either of the cell types (LC4 and LPLC2), they should silence each and also both cell types as early as possible (with the LC4 driver that does not ablate them) and then quantify the contacts with GF. In the same vein, the authors should knock down components of the synaptic machinery as early as possible to show directly the effect on 1) contact formation and 2) contact stabilization. For example, authors state in the lines 267-269 "VPN cholinergic machinery arrives too late to contribute to the initial targeting and localization of VPN axons on GF dendrites. Cholinergic activity instead is likely to participate in VPN and GF synapse refinement and stabilization." This statement would only be valid if the authors knock down the cholinergic machinery and find the contact numbers unchanged in the early stages but significantly different in later stages in comparison to the controls. Furthermore, authors only show increase in the VAChT and ChAT in the presynaptic cells but do not show if the cholinergic receptor AChRs are even expressed in GF cells or at what point they are expressed. Without these receptor expression, cholinergic system might not even be involved in the process. Also, there might be other neurotransmitter systems involved. Authors should at least check if other neurotransmitter systems are expressed in these cells, both pre-and post-synaptic.<br /> Line 371-374: "In the later stages of development, the frequency of synaptic events increase as gap junction proteins are downregulated and cholinergic presynaptic machinery is upregulated to enhance and stabilize synapses with intended synaptic partners while refining unintended contacts". The authors did not show the activity they observed in GF is due to the contacts they make with LC4s and LPLC2s. The functionality of these contacts can be shown by silencing the LC4s and LPLC2s and then doing the patch clamping in GF to see a decrease in the activity. Further, the authors did not show that the reduction in contacts are only by refining "unintended" contacts. There is no evidence that can support this statement.

(2) In the LC4 ablation experiments, authors claim that LC4_4 split Gal4 line is expressed around 18APF, prior to GF LC4 initial contact (Line 387). However, authors do not show the time point of first contact between GF dendrites and LC4 cells. In Fig. 2 the first time point shown is at P36, where there is already significant overlap between GF dendrites and LC4 axons. Authors should show the very first time point where they see any, even if minimal, overlap and/or contact between GFs and LC4s. Once the LC4s are ablated, is the increase in the colocalization between GF and LPLC2 due to LPLC2s increasing their contact numbers or due to them not decreasing the maximum contact numbers that the authors observed at P72 (Fig 2G)? In other words, once the LC4s are ablated, what would the new graph for temporal contact numbers for LPLC2 look like and how it would compare to Fig2G?

(3) If the developmental stages for different lines match, that would be more helpful for comparison. Also, as the authors analyzed expression every 12 hours from 0APF, the panel should also contain earlier time points (e.g. P0, P12) for all lines. This is critical to understand at what point the axons of LC4, LPLC2 and LPLC1 reach their position. From the scale bar in Supp Fig.4, it seems LC4 axons have already reached final position at P24 and there is no extension between P24 and P60. Do the authors know at what point LC4 axons start extending and reach the final position? If the LC4 and LPLC2 arbors are already separated medio-laterally even before GF dendrites extend towards them, it would explain why GF dendrites extending from medial region of the brain would encounter LC4 axons first and LPLC2 axons later, just based on their localization in space.<br /> Further to this point, the authors show in the section two of the paper that it is the GF dendrites that extend, elaborate and refine during the phase the authors analyzed and the authors do not show any morphological change in the axons of the VPNs. Therefore, the title of the paper is 'axon arrival times and physical occupancy establish visual projection neuron integration on developing dendrites in the Drosophila optic glomeruli' is slightly misguided.

(4) In the absence of LC4s, does the LPLC1 and GF colocalization increase or do they still stay disconnected?

(5) Does the absence of LC4s have any effect on GF arbor complexity? Does the graph in Fig 2B and C change? Can the increase in colocalization between LPLC2 and GF be at least partially due to the expansion of GF dendritic volume?

(6) Why is there a segregation in the medial-lateral axis but not in the dorso-ventral axis? Wouldn't the same segregation mechanism be in play in both axes? Also, the authors should clarify if this reduction in dorsal-ventral distribution is because dorso-ventral expansion of GF dendrites beyond the LC4 and LPLC2 axons? Theoretically that would seem to make the LC4s move more ventrally and LPLC2 move more dorsally in comparison to the total arbor.

(7) Why the LPLC2 medial connections are regarded as "mistargeting" in the heading of Supplemental Figure 1? Both in EM data and in some of the confocal datasets, these connections are observed. What is the criteria to label a connection "mistargeting" if it is observed, albeit occasionally, both in EM and confocal datasets?

(8) In Line 126-127, authors state that "we sought to determine how the precise VPN localization along GF dendrites arises across development". However, based in EM and microscopic data, there is considerable variability in the contact numbers and distribution. With such variability present, how can the localization be termed "precise"? Authors should clarify.

Reviewer #1 (Public Review):

The manuscript by Poltavski and colleagues describes the discovery of previously unreported enteric neural crest-derived cells (ENCDC) which are marked by Pax2 and originating from the Placodes. By creating multiple conditional mouse mutants, the authors demonstrate these cells are a distinct population from the previously reported ENCDCs which originate from the Vagal neural crest cells and express Wnt1.

These Pax2-positive ENCDCs are affected due to the loss of both Ret and Ednrb highlighting that these cells are also ultimately part of the canonical processes governing ENCDC and enteric nervous system (ENS) development. The authors also make explant cultures from the mouse GI tract to detect how Ednrb signaling is important for Ret signaling pathways in these cells and rediscovers the interactions between these 2 pathways. One important observation the authors make is that CGRP-positive neurons in the adult distal colon seem to be primarily derived from these Pax2-positive ENCDCs, which are significantly reduced in the Ednrb mutants, thus highlighting the role of Ednrb in maintaining this neuronal type.

I appreciate the amount of work the authors have put into generating the mouse models to detect these cells, but there isn't any new insight on either the nature of ENCDC development or the role of Ret and Ednrb. Also, there are sophisticated single-cell genomics methods to detect rare cell type/states these days and the authors should either employ some of those themselves in these mouse models or look at extensively publicly available single-cell datasets of the developing wildtype and mutant mouse and human ENS to map out the global transcriptional profile of these cells. A more detailed analysis of these Pax2-positive cells would be really helpful to both the ENS community as well as researchers studying gut motility disorders.

Reviewer #2 (Public Review):

Summary:

This manuscript by Poltavski and colleagues explores the relative contributions of Pax2- and Wnt1- lineage-derived cells in the enteric nervous system (ENS) and how they are each affected by disruptions in Ret and Endrb signaling. The current understanding of ENS development in mice is that vagal neural crest progenitors derived from a Wnt1+ lineage migrate into and colonize the developing gut. The sacral neural crest was thought to make a small contribution to the hindgut in addition but recent work has questioned that contribution and shown that the ENS is entirely populated by the vagal crest (PMID: 38452824). GDNF-Ret and Endothelin3-Ednrb signaling are both known to be essential for normal ENS development and loss of function mutations are associated with a congenital disorder called Hirschsprung's disease. The transcription factor Pax2 has been studied in CNS and cranial placode development but has not been previously implicated in ENS development. In this work, the authors begin with the unexpected observation that conditional knockout of Ednrb in Pax2-expressing cells causes a similar aganglionosis, growth retardation, and obstructed defecation as conditional knockout of Ednrb in Wnt1-expressing cells. The investigators then use the Pax2 and Wnt1 Cre transgenic lines to lineage-trace ENS derivatives and assess the effects of loss of Ret or Ednrb during embryonic development in these lineages. Finally, they use explants from the corresponding embryos to examine the effects of GDNF on progenitor outgrowth and differentiation.

Strengths:

- The manuscript is overall very well illustrated with high-resolution images and figures. Extensive data are presented.

- The identification of Pax2 expression as a lineage marker that distinguishes a subset of cells in the ENS that may be distinct from cells derived from Wnt1+ progenitors is an interesting new observation that challenges the current understanding of ENS development.

- Pax2 has not been previously implicated in ENS development - this manuscript does not directly test that role but hints at the possibility.

- Interrogation of two distinct signaling pathways involved in ENS development and their relative effects on the two purported lineages.

Weaknesses:

- The major challenge with interpreting this work is the use of two transgenic lines, rather than knock-ins, Wnt1-Cre and Pax2-Cre, which are not well characterized in terms of fidelity to native gene expression and recombination efficiency in the ENS. If 100% of cells that express Wnt1 do not express this transgene or if the Pax2 transgene is expressed in cells that do not normally express Pax2, then these observations would have very different interpretations and not support the conclusions made. The two lineages are never compared in the same embryo, which also makes it difficult to assess relative contributions and renders the evidence more circumstantial than definitive.

- Visualization of the Pax2-Cre and Wnt-1Cre induced recombination in cross-sections at postnatal ages would help with data interpretation. If there is recombination induced in the mesenchyme, this would particularly alter the interpretation of Ednrb mutant experiments, since that pathway has been shown to alter gut mesenchyme and ECM, which could indirectly alter ENS colonization.

- No consideration of glia - are these derived from both lineages?

- No discussion of how these observations may fit in with recent work that suggests a mesenchymal contribution of enteric neurons (PMID: 38108810).

Joint Public Review:

Summary:

This manuscript investigates how energetic demands affect the sleep-wake cycle in Drosophila larvae. L2 stage larvae do not show sleep rhythm and long-term memory (LTM), however, L3 larvae do. The authors manipulate food content to provide insufficient nutrition, which leads to more feeding, no LTM, and no sleep even in older larvae. Similarly, activation of NPF neurons suppresses sleep rhythm. Furthermore, they try to induce a sleep-like state using pharmacology or genetic manipulations in L2 larvae, which can mimic some of the L3 behaviours. A key experimental finding is that activation of DN1a neurons activate the downstream DH44 neurons, as assayed by GCaMP calcium imaging. This occurs only in third instar and not in second instar, in keeping with the development of sleep-wake and feeding separation. The authors also show that glucose metabolic genes are required in Dh44 neurons to develop sleep rhythm and that DH44 neurons respond differently in malnutrition or younger larvae.

Strengths:

Previous studies from the same lab have shown the sleep is required for LTM formation in the larvae, and that this requires DN1a and DH44 neurons. The current work builds upon this observation and addresses in more detail when and how this might develop. The authors can show that low quality food exposure and enhanced feeding during larval stage of Drosophila affects the formation of sleep rhythm and long-term memory. This suggests that the development of sleep and LTM are only possible under well fed and balanced nutrition in fly larvae. Non-sleep larvae were fed in low sugar conditions and indeed, the authors also find glucose metabolic genes to be required for a proper sleep rhythm. The paper presents precise genetic manipulations of individual classes of neurons in fly larvae followed by careful behavioural analysis. The authors also combine thermogenetic or peptide bath application experiments with direct calcium imaging of specific neurons.

Weaknesses:

The authors tried to induce sleep in younger L2 larvae, however the behavioral results suggest that they were not able to induce proper sleep behaviour as in normal L3 larvae. Thus, they cannot show that sleep during L2 stage would be sufficient to form LTM.<br /> The authors suggest that larval Dh44 neurons may integrate "information about the nutritional environment through the direct sensing of glucose levels to modulate sleep-wake rhythm development". They identify glucose metabolism genes (e.g., Glut1) in the downstream DH44 neurons as being required for the organization of the sleep-wake-feeding rhythm, and that CCHa signaling in DN1a signaling to the DH44 cells via the receptor. However, how this is connected is not well explained. Do the authors think that the nutrient sensing is only occurring in the DH44 neurons and not in DN1a or other neurons? Would not knocking down glucose metabolism in any neuron lead to a functional defect? What is the evidence that Dh44 neurons are specific sensors of nutritional state? For example, do the authors think that e.g. the overexpression of Glut1 in Dh44 neurons, a manipulation that can increase transport of glucose into cells, would rescue the effects of low-sugar food?<br /> Some of the genetic controls seem to be inconsistent suggesting some genetic background effects. In Figure 2B, npf-gal4 flies without the UAS show no significant circadian change in sleep duration, whereas UAS-TrpA flies do. The genetic control data in Figure 2D are also inconsistent. Npf-Gal4 seems to have some effect by itself without the UAS. The same is not seen with R76G11-Gal4. Suppl Fig 2: Naïve OCT and AM preference in L3 expressing various combinations of the transgenes show significant differences. npf-Gal4 alone seems to influence preference.<br /> The sleep duration and bout number/length data are highly variable.

Reviewer #1 (Public Review):

Summary:

The manuscript gives a broad overview of how to write NeuroML, and a brief description of how to use it with different simulators and for different purposes - cells to networks, simulation, optimization, and analysis. From this perspective, it can be an extremely useful document to introduce new users to NeuroML.

However, the manuscript itself seems to lose sight of this goal in many places, and instead, the description at times seems to target software developers. For example, there is a long paragraph on the board and user community. The discussion on simulator tools seems more for developers, not users. All the information presented at the level of a developer is likely to be distracting to readers..

Strengths:

The modularity of NeuroML is indeed a great advantage. For example, the ability to specify the channel file allows different channels to be used with different morphologies without redundancy. The hierarchical nature of NeuroML also is commendable, and well illustrated in Figures 2a through c.

The number of tools available to work with NeuroML is impressive.

The abstract, beginning, and end of the manuscript present and discuss incorporating NeuroML into research workflows to support FAIR principles.

Having a Python API and providing examples using this API is fantastic. Exporting to NeuroML from Python is also a great feature.

Weaknesses:

Though modularity is a strength, it is unclear to me why the cell morphology isn't also treated similarly, i.e., specify the morphology of a multi-compartmental model in a separate file, and then allow the cell file to specify not only the files containing channels, but also the file containing the multi-compartmental morphology, and then specify the conductance for different segment groups. Also, after pynml_write_neuroml2_file, you would not have a super long neuroML file for each variation of conductances, since there would be no need to rewrite the multi-compartmental morphology for each conductance variation.

This would be especially important for optimizations, if each trial optimization wrote out the neuroML file, then including the full morphology of a realistic cell would take up excessive disk space, as opposed to just writing out the conductance densities. As long as cell morphology must be included in every cell file, then NeuroML is not sufficiently modular, and the authors should moderate their claim of modularity (line 419) and building blocks (551). In addition, this is very important for downloading NeuroML-compliant reconstructions from NeuroMorpho.org. If the cell morphology cannot be imported, then the user has to edit the file downloaded from NeuroMorpho.org, and provenance can be lost. Also, Figure 2d loses the hierarchical nature by showing ion channels, synapses, and networks as separate main branches of NeuroML.

In Figure 5, the difference between the core and native simulator is unclear. What is involved in helper scripts? I thought neurons could read NeuroML? If so, why do you need the export simulator-specific scripts? In addition, it seems strange to call something the "core" simulation engine, when it cannot support multi-compartmental models. It is unclear why "other simulators" that natively support NeuroML cannot be called the core. It might be more helpful to replace this sort of classification with a user-targeted description. The authors already state which simulators support NeuroML and which ones need code to be exported. In contrast, lines 369-370 mention that not all NeuroML models are supported by each simulator. I recommend expanding this to explain which features are supported in each simulator. Then, the unhelpful separation between core and native could be eliminated.

The body of the manuscript has so much other detail that I lose sight of how NeuroML supports FAIR. It is also unclear who is the intended audience. When I get to lines 336-344, it seems that this description is too much detail for the audience. The paragraph beginning on line 691 is a great example of being unclear about who is the audience. Does someone wanting to develop NeuroML models need to understand XSD schema? If so, the explanation is not clear. XSD schema is not defined and instead explains NeuroML-specific aspects of XSD. Lines 734-735 are another example of explaining to code developers (not model developers).

Reviewer #2 (Public Review):

Summary:

Developing neuronal models that are shareable, reproducible, and interoperable allows the neuroscience community to make better use of published models and to collaborate more effectively. In this manuscript, the authors present a consolidated overview of the NeuroML model description system along with its associated tools and workflows. They describe where different components of this ecosystem lay along the model development pathway and highlight resources, including documentation and tutorials, to help users employ this system.

Strengths:

The manuscript is well-organized and clearly written. It effectively uses the delineated model development life cycle steps, presented in Figure 1, to organize its descriptions of the different components and tools relating to NeuroML. It uses this framework to cover the breadth of the software ecosystem and categorize its various elements. The NeuroML format is clearly described, and the authors outline the different benefits of its particular construction. As primarily a means of describing models, NeuroML also depends on many other software components to be of high utility to computational neuroscientists; these include simulators (ones that both pre-date NeuroML and those developed afterwards), visualization tools, and model databases.

Overall, the rationale for the approach NeuroML has taken is convincing and well-described. The pointers to existing documentation, guides, and the example usages presented within the manuscript are useful starting points for potential new users. This manuscript can also serve to inform potential users of features or aspects of the ecosystem that they may have been unaware of, which could lower obstacles to adoption. While much of what is presented is not new to this manuscript, it still serves as a useful resource for the community looking for information about an established, but perhaps daunting, set of computational tools.

Weaknesses:

The manuscript in large part catalogs the different tools and functionalities that have been produced through the long development cycle of NeuroML. As discussed above, this is quite useful, but it can still be somewhat overwhelming for a potential new user of these tools. There are new user guides (e.g., Table 1) and example code (e.g. Box 1), but it is not clear if those resources employ elements of the ecosystem chosen primarily for their didactic advantages, rather than general-purpose utility. I feel like the manuscript would be strengthened by the addition of clearer recommendations for users (or a range of recommendations for users in different scenarios).

For example, is the intention that most users should primarily use the core NeuroML tools and expand into the wider ecosystem only under particular circumstances? What are the criteria to keep in mind when making that decision to use alternative tools (scale/complexity of model, prior familiarity with other tools, etc.)? The place where it seems most ambiguous is in the choice of simulator (in part because there seem to be the most options there) - are there particular scenarios where the authors may recommend using simulators other than the core jNeuroML software?

The interoperability of NeuroML is a major strength, but it does increase the complexity of choices facing users entering into the ecosystem. Some clearer guidance in this manuscript could enable computational neuroscientists with particular goals in mind to make better strategic decisions about which tools to employ at the outset of their work.

Reviewer #2 (Public Review):

Summary:

While a significant portion of immunotherapy research has focused on the pivotal role of T cells in tumor immunity, their effectiveness may be limited by the suppressive nature of the tumor environment. On the other hand, myeloid cells are commonly found within tumors and can withstand these adverse conditions. However, these cells often adopt an immunosuppressive phenotype when infiltrating tumors. Therefore, manipulating myeloid cells could potentially enhance the anti-tumor potential of immunotherapy.<br /> In this manuscript, Farhat-Younes and colleagues have demonstrated that activating the IgM receptor signaling in myeloid cells induces an oxygen burst, the secretion of Granzyme B, and the lysis of adjacent tumor cells. Furthermore, they have outlined a strategy to utilize these features to generate CAR macrophages. However, they have identified a limitation: the expression of scFv in myeloid cells induces ER stress and the degradation of misfolded proteins. To address this issue, chimeric receptors were designed based on the high-affinity FcγRI for IgG. When macrophages transfected with these receptors were exposed to tumor-binding IgG, extensive tumor cell killing, and the release of reactive oxygen species and Granzyme B were observed.

Strengths:

In general, I consider this work to be significant, and the results are compelling. It emphasizes the specific considerations and requirements for successful manipulation in myeloid cells, which could further advance the field of cellular engineering for the benefit of immunotherapy

Following the revision of the original manuscript, I can clearly state that my concerns have been addressed and the article has been improved.

Reviewer #2 (Public Review):

This preprint by Pokrovsky and coworkers is a descriptive study reporting on non-breeding itinerant behaviour of an intrapalearctic migratory raptor, the rough-legged buzzard, and relating such non-breeding movements to snow cover across the European non-breeding range. The article is based on long-term GPS tracking data from a relatively large (n=43) sample of individuals that were equipped with state-of-the-art tracking devices in the Russian Arctic during 2013-2019. The results show that, upon breeding, buzzards migrated rapidly to southern non-breeding areas, located in open areas north of the Black and Caspian seas, where they perform continuous directional movements at a slower pace, initially moving SW (Oct to Jan) and then progressively moving NE (Feb to Apr) before embarking on rapid spring migration. It is suggested that such itinerant behaviour follows variation (expansion and retreat) of snow cover across the non-breeding range.

The results are potentially useful for researchers investigating the ecological drivers of bird movement patterns. The analytical framework appears solid, although some details on the analyses (requested during the previous review round) are still unclear and have not been modified despite explicit requests. Significant weaknesses in the theoretical framework persist in the revised version, including unwarranted claiming of novelty, overselling of importance of the study, and overinterpretation of the data. Below are key points that the authors did not consider when revising their manuscript.

(1) The authors underemphasize the fact that what they term 'fox-trot' migration is actually a well-known patterns for many other migratory species, both in the Nearctic and in the Afro-Palearctic migration systems. Such behaviour has previously been identified as 'itinerant' or 'non-breeding itinerancy', involving an alternation of stopovers and movements between different short-term non-breeding residency areas, or even slow continuous movements, and it seems that the pattern the authors report for this particular species is perfectly in line with such previous evidence. For instance, this is well-documented among migratory raptors, such as the Montagu's harrier, lesser kestrels or black kites, that exploit Sahelian savannahs, where large spatio-temporal variation in greenness and hence resource availability occurs. And, besides the mentioned cuckoos and nightingales, there are studies of red-backed shrikes suggesting the same, as well as of tree swallows in the Nearctic. Therefore, the authors should avoid claiming novelty for this study and introducing unnecessary and confusing new terms in the literature (i.e. the 'fox-trot' migration patterns) when these are definitely not strictly needed as they have been previously observed and defined otherwise. Sentences such as 'We used the rough-legged buzzard as a model..." are also similarly unwarranted. This is simply a descriptive studies reporting on such behaviour in yet another migratory species. The whole introduction is pervaded by a faulty logic. The authors first introduce a new (unwarranted) term based on previous evidence from other studies (none of which felt any need to introduce and describe it); then they assume, for unclear reasons, that the species they are studying should behave in that way; even more worryingly, based on these assumptions, they make specific predictions on how this species should behave, without any sound biological reason for these predictions. I admit I hardly see any scientific logic in this approach.

(2) The species has a very standard migration for a short-distance migrant, by all means. It moves to non-breeding areas, and once there it slowly moves towards the south in autumn and back again in spring, until it departs for pre-breeding migration. This is no different from other trans-Saharan migratory raptor species that spend the non-breeding period in the Sahel. Whether the species perform any short/medium term stopover (frequenting the same are for some days) during the non-breeding stage (between end of autumn migration and onset of spring migration), as is the case of most species showing non-breeding itinerancy, is not reported. The authors only show a slower pace of movement during the non-breeding period compared to autumn and spring migration, without providing any further details. This hinders comparisons with other previous studies.

(3) The current title is unnecessarily general (it may recall rather a review or meta-analysis) and not adequately describing the content of the manuscript. In order to be informative, the title should more tightly reflect the content of the article. A valid alternative would be 'Itinerant non-breeding behaviour of an intra-Palaearctic migratory raptor', as it would be far more adequate and informative.

(4) The text, particularly the Introduction and the Discussion, would greatly benefit from profound reframing in light of the above comments. Upon reading the first sentence of the introduction, it looks surprising that the authors based their suggestion for 'fox-trot' migration based on a very outdated article on the migration of Montagu's harrier based on sparse ring recovery data which merely suggests the existence of 'movements' within the non-breeding areas (i.e. non-breeding itinerancy), while subsequent large scale satellite tracking studies of this species provided compelling evidence for non-breeding area itinerancy (and again, no mention of 'fox-trot' whatsoever). The discussion is entirely framed around potential issues related to accurate monitoring of population size and trends, which the author surprisingly refer to 'conservation implications'. As I already mentioned in my previous review, the 'conservation implications' of this study are nearly negligible. At best, it suggests that caution should be applied when interpreting population trends of migratory species based on non-breeding area counts only, a pattern that is already well known for decades (consider the long-running IWC coordinated by Wetlands International!). In addition, Christmas Bird Count, a long-term monitoring program of AOS, is mentioned without any accurate reference to what it actually is, assuming that any reader would be familiar with a very peculiar monitoring scheme of the Nearctic region.

The final paragraph epitomizes how authors are overstating the importance of this study, claiming for non-existent novelty and even 'discovery': "Our study has identified and characterized a new pattern of migratory behavior, the 'foxtrot migration', along with the associated concept of 'dynamic range'. This discovery has significant implications for conservation strategies and adequate representation of non-breeding habitats".

Reviewer #1 (Public Review):

Summary:

For many years, there has been extensive electrophysiological research investigating the relationship between local field potential patterns and individual cell spike patterns in the hippocampus. In this study, using state-of-the-art imaging techniques, they examined spike synchrony of hippocampal cells during locomotion and immobility states. In contrast to conventional understanding of the hippocampus, the authors demonstrated that hippocampal place cells exhibit prominent synchronous spikes locked to theta oscillations.

Strengths:

The voltage imaging used in this study is a highly novel method that allows recording not only suprathreshold-level spikes but also subthreshold-level activity. With its high frame rate, it offers time resolution comparable to electrophysiological recordings. Moreover, it enables the visualization of actual cell locations, allowing for the examination of spatial properties (e.g., Figure 4G).

Weaknesses:

There is a notable deviation from several observations obtained through conventional electrophysiological recordings. Particularly, as mentioned below in detail, the considerable differences in baseline firing rates and no observations of ripple-triggered firing patterns raise some concerns about potential artifacts from imaging and analsyis, such as cell toxicity, abnormal excitability, and false detection of spikes. While these findings are intriguing if the validity of these methods is properly proven, accepting the current results as new insights is challenging.

Reviewer #2 (Public Review):

Summary:

This study employed voltage imaging in the CA1 region of the mouse hippocampus during the exploration of a novel environment. The authors report synchronous activity, involving almost half of the imaged neurons, occurred during periods of immobility. These events did not correlate with SWRs, but instead, occurred during theta oscillations and were phased-locked to the trough of theta. Moreover, pairs of neurons with high synchronization tended to display non-overlapping place fields, leading the authors to suggest these events may play a role in binding a distributed representation of the context.

Strengths:

Technically this is an impressive study, using an emerging approach that allows single-cell resolution voltage imaging in animals, that while head-fixed, can move through a real environment. The paper is written clearly and suggests novel observations about population-level activity in CA1.

Weaknesses:

The evidence provided is weak, with the authors making surprising population-level claims based on a very sparse data set (5 data sets, each with less than 20 neurons simultaneously recorded) acquired with exciting, but less tested technology. Further, while the authors link these observations to the novelty of the context, both in the title and text, they do not include data from subsequent visits to support this. Detailed comments are below:

(1) My first question for the authors, which is not addressed in the discussion, is why these events have not been observed in the countless extracellular recording experiments conducted in rodent CA1 during the exploration of novel environments. Those data sets often have 10x the neurons simultaneously recording compared to these present data, thus the highly synchronous firing should be very hard to miss. Ideally, the authors could confirm their claims via the analysis of publicly available electrophysiology data sets. Further, the claim of high extra-SWR synchrony is complicated by the observation that their recorded neurons fail to spike during the limited number of SWRs recorded during behavior- again, not agreeing with much of the previous electrophysiological recordings.

(2) The authors posit that these events are linked to the novelty of the context, both in the text, as well as in the title and abstract. However, they do not include any imaging data from subsequent days to demonstrate the failure to see this synchrony in a familiar environment. If these data are available it would strengthen the proposed link to novelty if they were included.

(3) In the discussion the authors begin by speculating the theta present during these synchronous events may be slower type II or attentional theta. This can be supported by demonstrating a frequency shift in the theta recording during these events/immobility versus the theta recording during movement.

(4) The authors mention in the discussion that they image deep-layer PCs in CA1, however, this is not mentioned in the text or methods. They should include data, such as imaging of a slice of a brain post-recording with immunohistochemistry for a layer-specific gene to support this.

Reviewer #3 (Public Review):

Summary:

In the present manuscript, the authors use a few minutes of voltage imaging of CA1 pyramidal cells in head-fixed mice running on a track while local field potentials (LFPs) are recorded. The authors suggest that synchronous ensembles of neurons are differentially associated with different types of LFP patterns, theta and ripples. The experiments are flawed in that the LFP is not "local" but rather collected in the other side of the brain, and the investigation is flawed due to multiple problems with the point process analyses. The synchrony terminology refers to dozens of milliseconds as opposed to the millisecond timescale referred to in prior work, and the interpretations do not take into account theta phase locking as a simple alternative explanation.

Weaknesses:

The two main messages of the manuscript indicated in the title are not supported by the data. The title gives two messages that relate to CA1 pyramidal neurons in behaving head-fixed mice: (1) synchronous ensembles are associated with theta (2) synchronous ensembles are not associated with ripples.

There are two main methodological problems with the work: (1) experimentally, the theta and ripple signals were recorded using electrophysiology from the opposite hemisphere to the one in which the spiking was monitored. However, both signals exhibit profound differences as a function of location: theta phase changes with the precise location along the proximo-distal and dorso-ventral axes, and importantly, even reverses with depth. And ripples are often a local phenomenon - independent ripples occur within a fraction of a millimeter within the same hemisphere, let alone different hemispheres. Ripples are very sensitive to the precise depth - 100 micrometers up or down, and only a positive deflection/sharp wave is evident. (2) The analysis of the point process data (spike trains) is entirely flawed. There are many technical issues: complex spikes ("bursts") are not accounted for; differences in spike counts between the various conditions ("locomotion" and "immobility") are not accounted for; the pooling of multiple CCGs assumes independence, whereas even conditional independence cannot be assumed; etc.

Beyond those methodological issues, there are two main interpretational problems: (1) the "synchronous ensembles" may be completely consistent with phase locking to the intracellular theta (as even shown by the authors themselves in some of the supplementary figures). (2) The definition of "synchrony" in the present work is very loose and refers to timescales of 20-30 ms. In previous literature that relates to synchrony of point processes, the timescales discussed are 1-2 ms, and longer timescales are referred to as the "baseline" which is actually removed (using smoothing, jittering, etc.).

Reviewer #2 (Public Review):

Summary:

This manuscript describes P. falciparum population structure in Zanzibar and mainland Tanzania. 282 samples were typed using molecular inversion probes. The manuscript is overall well written and shows clear population structure. It follows a similar manuscript published earlier this year, which typed a similar number of samples collected mostly in the same sites around the same time. The current manuscript extends this work by including a large number of samples from coastal Tanzania, and by including clinical samples, allowing for a comparison with asymptomatic samples.

The two studies made overall very similar findings, including strong small-scale population structure, related infections on Zanzibar and the mainland, near-clonal expansion on Pemba, and frequency of markers of drug resistance.

Strengths:

The overall results show a clear pattern of population structure. The finding of highly related infections detected in close proximity shows local transmission and can possibly be leveraged for targeted control.

Comments on revised version:

The authors have addressed my comments.

Reviewer #1 (Public Review):

Summary:

Zanzibar archipelago is close to achieve malaria elimination, but despite the implementation of effective control measures there is still low level seasonal malaria transmission. This could be due to the frequent importation of malaria from the mainland Tanzania and Kenya, reservoir of asymptomatic infections and competent vectors. To investigate population structure and gene flow of P. falciparum in Zanzibar and mainland Tanzania, they used 178 samples from mainland Tanzania and 213 from Zanzibar that were previously sequenced using molecular inversion probes (MIPs) panels targeting single nucleotide polymorphisms (SNPs). They performed Principal Component Analysis (PCA) and identity by descent (IBD) analysis to assess genetic reladness between isolates. Parasites from coastal mainland Tanzania contribute for the genetic diversity in parasite population in Zanzibar. Despite this, there is a pattern of isolation by distance and microstructure within the achipelago, and evidence of local sharing of highly related strains sustaining malaria transmission in Zanzibar that are important targets for interventions such as mass drug administration and vector control, in addition to measures against imported malaria.

Strengths:

This study presents important samples to understand population structure and gene flow between mainland Tanzania and Zanzibar, especially from rural Bagamoyo District, where malaria transmission persists and there is a major port of entry to Zanzibar. In addition, this study includes a larger set of SNPs, providing more robustness for analyzes such as PCA and IBD. Therefore, the conclusions of this paper are well supported by data.

Comments on revised version:

The authors answered all my questions.

Reviewer #1 (Public Review):

Granados-Aparici et al., investigate somatic-germline interactions in female mice. Mammalian oocytes are nurtured in multi-cellular ovarian follicles and communication with surrounding somatic cells is critical for oocyte development. This study focused on transzonal projections (TZP) extending from granulosa cells to the surface of oocytes and document the importance of SMAD4, a TGF- β mediator, in regulating the TZPs. They propose a model in which individual TZPs contact the surface of the oocyte and stably attaches if there is sufficient N-cadherin. In SMAD4-depleted cells, there is insufficient N-cadherin to stabilize the attachment. The TZP continues to elongate but eventually retracts. Their model is well supported by their experimental evidence and the manuscript is both well-formulated and written.

Comments on revised version:

The authors have addressed the issues raised in the original review.

Reviewer #2 (Public Review):

Summary:

This study proposed a new mechanism by which TGF-beta signaling pathway promotes contacts between oocyte and the surrounding somatic cells in mouse, by regulating the numbers of transzonal projections (TZPs).

Strengths:

The conditional Smad4 knockout and three-dimensional observation of transzonal projections are solid and sufficiently support the major conclusions.

Comments on revised version:

The authors have adequately addressed the reviewers' questions and comments.

Reviewer #1 (Public Review):

Recognition of bacterial lipopolysaccharide by Toll-like Receptor 4 is an essential molecular event triggering inflammation and overcoming Recognition of bacterial lipopolysaccharide by Toll-like Receptor 4 is an essential molecular event in triggering inflammation and overcoming infection by gram-negative bacteria. However, TLR4 has recently been found to respond to other endogenously derived ligands. This has implicated TLR4 signaling in the development of disease pathology, for example, Alzheimer's disease, through the recognition of amyloid-beta. Intriguingly, the signaling response to these non-bacterial-derived ligands differs from that of bacterial-derived LPS, suggesting mechanistic differences between endogenous and bacterial-derived agonists. In this work, the authors set out to characterize these mechanistic differences. TLR4 signals through two large macromolecular complexes that assemble at activated receptors: the Myddosome and Triffosome. One hypothesis the authors aimed to test was that different ligands alter these signaling complexes' kinetics and nano-scale features. The authors focused on testing this hypothesis by examining the formation of the Myddosome in live cells. A significant strength of the paper is that the authors developed technological innovations to address this problem. Using a nanopipette delivery mechanism combined with light sheet microscopy, the authors could observe Myddosome signaling in the whole cell volume of live macrophages. This allowed them to accurately quantify the Myddosome number, size, and kinetics of complex formation and compare cells stimulated with amyloid-beta and LPS. The authors discovered differences in Myddosomes formed under LPS versus amyloid-beta stimulation. In general, amyloid-beta TLR4 stimulation resulted in slower Myddosome formation with altered morphology. One limitation of the work, which the authors point out in the discussion, is that they could not distinguish signaling-competent Myddosomes. Future work will be needed to understand whether these amyloid beta induced Myddosomes assembly have a similar or altered complement of downstream signaling proteins (such as the IRAK4/1 and TRAF6). Secondly, the structural basis for how TLR4 would distinguish between different radically agonists remains speculative, and will need further investigation. Nonetheless, this paper is important for the technological innovation to look at the molecular dynamics of signal transduction, a technology that could be adapted to study other receptor signaling pathways.

It is already known that the subcellular location of intracellular TLRs is important for limiting the recognition of self-derived ligands and maintaining tolerance. This work hints at another possible layer of regulation: that a cell surface TLR (TLR4) generates diverse signaling outcomes to extrinsic or intrinsically derived agonists by changing the dynamic behavior of signaling proteins. If correct (and much further work is required to understand endogenous TLR ligands better), it might suggest that the innate immune system employs the same molecular hardware but with altered kinetics to distinguish between exogenous and endogenous inflammatory signals. Thus, pathological aggregates or markers of sterile inflammation might be recognized and responded to by a specific signaling program that is defined kinetically. It will be an interesting direction for future studies to investigate whether and how diverse pathogen and endogenous inflammatory signals modulate the dynamics of signaling complexes.

Reviewer #1 (Public Review):

Summary:

The paper carries out an impressive and exhaustive non-sense mutagenesis using deep mutational scanning (DMS) of the gonadotropin-releasing hormone receptor for the WT protein and two single point mutations that I) influences TM insertion (V267T) and ii) influences protein stability (W107A) and then measures the effect of these mutants on correct plasma membrane expression (PME).

Overall, most mutations decreased mGnRHR PME levels in all three backgrounds, indicating poor mutational tolerance under these conditions. The W107A variant wasn't really recoverable with low levels of plasma membrane localisation. For the V267T variant, most additional mutations were more deleterious than WT based on correct trafficking, indicating a synergistic effect. As one might expect, there was a higher degree of positive correlation between V267T/W107A mutants and other mutants located in TM regions, confirming that improper trafficking was a likely consequence of membrane protein co-translational folding. Nevertheless, context is important, as positive synergistic mutants in the V27T could be negative in the W107A background and vice versa. Taken together, this important study highlights the complexity of membrane protein folding in dissecting the mechanism-dependent impact of disease-causing mutations related to improper trafficking.

Strengths:

This is a novel and exhaustive approach to dissect how receptor mutations under different mutational backgrounds related to co-translational folding, could influence membrane protein trafficking.

Weaknesses:

The premise for the study requires an in-depth understanding of how the single point mutations analysed effect membrane protein folding in context of DMS, but the single point mutants used could do with further validation. The V267T mutant only reduced MP insertion by 10% and the effect of W107A on protein stability was not assessed. Furthermore, plasma membrane expression has been used as a proxy for incorrect membrane protein folding, but this not necessarily be the case, as even correctly folded membrane proteins may not be trafficked correctly, at least, under heterologous expression conditions. In addition, mutations can effect trafficking and potential post-translational modifications, like glycosylation.

Reviewer #2 (Public Review):

Summary:

In this paper, Chamness and colleagues make a pioneering effort to map epistatic interactions among mutations in a membrane protein. They introduce thousands of mutations to the mouse GnRH Receptor (GnRHR), either under wild-type background or two mutant backgrounds, representing mutations that destabilize GnRHR by distinct mechanisms. The first mutant background is W107A, destabilizing the tertiary fold, and the second, V276T, perturbing the efficiency of cotranslational insertion of TM6 to the membrane, which is essential for proper folding. They then measure surface expression of these three mutant libraries, using it as a proxy for protein stability, since misfolded proteins do not typically make it to the plasma membrane. The resulting dataset is then used to shed light on how diverse mutations interact epistatically with the two genetic background mutations. Their main conclusion is that epistatic interactions vary depending on the degree of destabilization and the mechanism through which they perturb the protein. The mutation V276T forms primarily negative (aggravating) epistatic interactions with many mutations, as is common to destabilizing mutations in soluble proteins. Surprisingly, W107A forms many positive (alleviating) epistatic interactions with other mutations. They further show that the locations of secondary mutations correlate with the types of epistatic interactions they form with the above two mutants.

Strengths:

Such a high throughput study for epistasis in membrane proteins is pioneering, and the results are indeed illuminating. Examples of interesting findings are that: (1) No single mutation can dramatically rescue the destabilization introduced by W107A. (2) Epistasis with a secondary mutation is strongly influenced by the degree of destabilization introduced by the primary mutation. (3) Misfolding caused by mis-insertion tends to be aggravated by further mutations. The discussion of how protein folding energetics affects epistasis (Fig. 7) makes a lot of sense and lays out an interesting biophysical framework for the findings.

Weaknesses:

The major weakness comes from the potential limitations in the measurements of surface expression of severely misfolded mutants. It seems that only about 5% of the W107A makes it to the plasma membrane compared to wild-type. This point is discussed quite fairly in the paper. (Figures 2 and 3). This might be a low starting point from which to accurately measure the effects of secondary mutations. I am concerned about the extent to which surface expression can report on protein stability, especially when it comes to double mutants where each mutation alone severely decreases surface expression. It is possible that in these cases, both the single and double mutants are completely misfolded, beyond repair. The surface-expressed proteins in such mutants may not be stable, folded or active at all, and the authors do not provide any indication that the combined effects of the mutations are derived from effects on folding stability or misfolding. Therefore, the reason for the epistatic effects of these mutations is hard to interpret, leaving a notable gap in our understanding. However, I find that this point is discussed much more fairly in the current manuscript.

With that said, I believe that the results regarding the epistasis of V276T with other mutations are strong and very interesting on their own.

Another concern relates to the measurements of the epistatic effects of mutations in the background of the V107A mutation. I am concerned about their measurement accuracy. Firstly, the authors note that the surface immunostaining measurements of these mutants are on average only 2-fold above background, which is quite a low signal-to-noise regimen. Secondly, I believe that the authors still haven't demonstrated the reproducibility of their surface expression measurements. To showcase the reproducibility, the authors show the correlation of two biological replicates in Figure S3. However, these are shown only for the 251 mutations that passed a reproducibility filter, after the authors "discarded variant scores for which the difference in percentile rank across the two replicates was greater than 25%. " . this means that all mutations that showed irreproducible results were filtered out before the analysis in Figure S3. It is, therefore, no surprise that the remaining mutations are highly reproducible, and such an analysis cannot serve as an indication of the reproducibility. It remains possible that a large fraction of the surface immunostaining scores of the V107A variants are dominated by noise and that their correlation in these two replicates might be random and may not necessarily be reproduced in a third replicate, for example.

Reviewer #1 (Public Review):

This manuscript describes soluble Uric Acid (sUA) as an endogenous inhibitor of CD38, affecting CD38 activity and NAD+ levels both in vitro and in vivo. Importantly, the inhibition constants calculated support the claim that sUA inhibits CD38 under physiological conditions. These findings are of extreme importance to understanding the regulation of an enzyme that has been shown to be the main NAD+/NMN-degrading enzyme in mammals, which impacts several metabolic processes and has major implications for understanding aging diseases. The manuscript is well written, the figures are self-explanatory, and in the experiments presented, the data is very solid. The authors discuss the main limitations of the study, especially in regard to the in vivo results. As a whole, I believe that this is a very interesting manuscript that will be appreciated by the scientific community and that opens a lot of new questions in the field of metabolism and aging. I found some issues that I believe constitute a weakness in the manuscript, and although they do not require new experiments, they may be considered by the authors for discussion in the final version of the manuscript.

The authors acknowledge the existence of several previous papers involving pharmacological inhibition of CD38 and their impact on several models of metabolism and aging. However, they only cite reviews. Given the focus of the manuscript, I believe that the seminal original papers should be cited.

Related to the previous comment, the authors show that they have identified the functional group on sUA that inhibits CD38, 1,3-dihydroimidazol-2-one. How does this group relate with previous structures that were shown to inhibit CD38 and do not have this chemical structure? Is sUA inhibiting CD38 in a different site? A crystallographic structure of CD38-78c is available in PDB that could be used to study or model these interactions.

Although the mouse model used to manipulate sUA levels is not ideal, the authors discuss its limitations, and importantly, they have CD38 KO mice as control. However, all the experiments were performed in very young mice, where CD38 expression is low in most tissues (10.1016/j.cmet.2016.05.006). This point should be mentioned in the discussion and maybe put in the context of variations of sUA levels during aging.

Reviewer #2 (Public Review):

Summary:

This is an interesting work where Wen et al. aimed to shed light on the mechanisms driving the protective role of soluble uric acid (sUA) toward avoiding excessive inflammation. They present biochemical data to support that sUA inhibits the enzymatic activity of CD38 (Figures 1 and 2). In a mouse model of acute response to sUA and using mice deficient in CD38, they find evidence that sUA increases the plasma levels of nicotinamide nucleotides (NAD+ and NMN) (Figure 3) and that sUA reduces the plasma levels of inflammasome-driven cytokines IL-1b and IL-18 in response to endotoxin, both dependent on CD38 (Figure 4). Their work is an important advance in the understanding of the physiological role of sUA, with mechanistic insight that can have important clinical implications.

Strengths:

The authors present evidence from different approaches to support that sUA inhibits CD38, impacts NAD+ levels, and regulates inflammatory responses through CD38.

Weaknesses:

The authors investigate macrophages as the cells impacted by sUA to promote immunoregulation, proposing that inflammasome inhibition occurs through NAD+ accumulation and sirtuin activity due to sUA inhibition of CD38. Unfortunately, the study still lacks data to support this model, as they could not replicate their in vivo findings using murine bone marrow-derived macrophages, a standard model to assess inflammasome activation. Without an alternative approach, the study lacks data to establish in vitro that sUA inhibition of CD38 reduces inflammasome activation in macrophages - consequently, they cannot determine yet if both NAD+ accumulation and sirtuin activity in macrophages is a mechanism leading to sUA role in vivo.

Reviewer #3 (Public Review):

Summary:

In the present manuscript, the authors propose that soluble Uric acid (sUA) is an enzymatic inhibitor of the NADase CD38 and that it controls levels of NAD modulating inflammatory response. Although interesting the studies are at this stage preliminary and validation is needed.

Strengths:

The study characterizes the potential relevance of sUA in NAD metabolism.

Weaknesses:

(1) A full characterization of the effect of sUA in other NAD-consuming and synthesizing enzymes is needed to validate the statement that the mechanism of regulation of NAD by sUA is mediated by CD38, The CD38 KO may not serve as the ideal control since it may saturate NAD levels already. Analysis of multiple tissues is needed.

(2) The physiological role of sUA as an endogenous inhibitor of CD38 needs stronger validation (sUA deficient model?).

(3) Flux studies would also be necessary to make the conclusion stronger.

Reviewer #1 (Public Review):

Summary:

In "1 Exploring the Spatial Distribution of Persistent SARS-CoV-2 Mutations -Leveraging mobility data for targeted sampling" Spott et al. combine SARS-CoV-2 genomic data alongside granular mobility data to retrospectively evaluate the spread of SARS-CoV-2 alpha lineages throughout Germany and specifically Thuringia. They further prospectively identified districts with strong mobility links to the first district in which BQ.1.1 was observed to direct additional surveillance efforts to these districts. The additional surveillance effort resulted in the earlier identification of BQ.1.1 in districts with strong links to the district in which BQ.1.1 was first observed.

Strengths:

There are two important strengths of this work. The first is the scale and detail in the data that has been generated and analyzed as part of this study. Specifically, the authors use 6,500 SARS-CoV-2 sequences and district-level mobility data within Thuringia. I applaud the authors for making a subset of their analyses public e.g. on the associated micro react page.

Further, the main focus of the article is on the potential utility of mobility-directed surveillance sequences. While I may certainly be mistaken, I have not seen this proposed elsewhere, at least in the context of SARS-CoV-2. The authors were further able to test this concept in a real-world setting during the emergence of BQ.1.1. This is a unique real-world evaluation of a novel surveillance sequencing strategy and there is considerable value in publishing this analysis.

Weaknesses:

The article is quite strong and I find the analyses to generally be rigorous. However, there are places where I believe the text should be modified to slightly weaken the conclusions drawn from the presented analyses. Specific examples include:

- It seems the mobility-guided increased surveillance included only districts with significant mobility links to the origin district and did not include any "control" districts (those without strong mobility links). As such, you can only conclude that increasing sampling depth increased the rate of detection for BQ.1.1., not necessarily that doing so in a mobility-guided fashion provided an additional benefit. I absolutely understand the challenges of doing this in a real-world setting and think that the work remains valuable even with this limitation, but I would like the lack of control districts to be more explicitly discussed.

- Line 313: While this work has reliably shown that the spread of Alpha was slower in Thuringia, I don't think there have been sufficient analyses to conclude that this is due to the lack of transportation hubs. My understanding is that only mobility within Thuringia has been evaluated here and not between Thuringia and other parts of Germany.

- Line 333 (and elsewhere): I'm not convinced, based on the results presented in Figure 2, that the authors have reliably identified a sampling bias here. This is only true if you assume (as in line 235) that the variant was in these districts, but that hasn't actually been demonstrated here. While I recognize that for high-prevalence variants there is a strong correlation between inflow and variant prevalence, low-prevalence variants by definition spread less and may genuinely be missing from some districts. To support this conclusion that they identified a bias, I'd like to see some type of statistical model that is based e.g. on the number of sequences, prevalence of a given variant in other districts, etc. Alternatively, the language can be softened ("putative sampling bias").

Reviewer #2 (Public Review):

In the manuscript, the authors combine SARS-CoV-2 sequence data from a state in Germany and mobility data to help in understanding the movement of the virus and the potential to help decide where to focus sequencing. The global expansion in sequencing capability is a key outcome of the public health response. However, there remains uncertainty about how to maximise the insights the sequence data can give. Improved ability to predict the movement of emergent variants would be a useful public health outcome. Also knowing where to focus sequencing to maximising insights is also key. The presented case study from one State in Germany is therefore a useful addition to the literature. Nevertheless, I have a few comments.

One of the key goals of the paper is to explore whether mobile phone data can help predict the spread of lineages. However, it appears unclear whether this was actually addressed in the analyses. To do this, the authors could hold out data from a period of time, and see whether they can predict where the variants end up being found.

The abstract presents the mobility-guided sampling as a success, however, the results provide a much more mixed result. Ultimately, it's unclear what having this strategy really achieved. In a quickly moving pandemic, it is unclear what hunting for extra sequences of a specific, already identified, variant really does. I'm not sure what public health action would result, especially given the variant has already been identified.

Relatedly, it is unclear to me whether simply relying on spatial distance would not be an alternative simpler approach than mobile phone data. From Figure 2, it seems clear that a simple proximity matrix would work well at reconstructing viral flow. The authors could compare the correlation of spatial, spatial proximity, and CDR data.

Reviewer #1 (Public Review):

Summary:

The presented study focuses on the role of formin-like 2 (FMNL2) in oocyte meiosis. The authors assessed FMNL2 expression and localization in different meiotic stages and subsequently, by using siRNA, investigated the role of FMNL2 in spindle migration, polar body extrusion, and distribution of mitochondria and endoplasmic reticulum (ER) in mouse oocytes.

Strengths:

Novelty in assessing the role of formin-like 2 in oocyte meiosis

Weaknesses:

Overstating some of the presented data

Unconvincing analysis of the endoplasmic reticulum and mitochondria distribution

The authors addressed all my comments. The section materials and methods was improved. However, some statements still need to be clarified, as they seem to be overstated. I'm still not convinced about the main findings. For example, the analysis of ER and mitochondria distribution was based on a subjective assessment of clustering in meiosis I oocytes, and it's missing objective parameters and timing of the analysis.

Comments on revised version:

The authors addressed all my comments. The section materials and methods was improved. However, some statements still need to be clarified, as they seem to be overstated.

Reviewer #2 (Public Review):

Summary:

This research involves conducting experiments to determine the role of Fmnl2 during oocyte meiosis I.

Strengths:

Identifying the role of Fmnl2 during oocyte meiosis I is significant.

Weaknesses:

The quantitative analysis and the used approach to perturb FMNL2 function would benefit from more confirmatory approaches and rigorous analysis.

Comments on revised version:

The authors addressed most of my comments. However, some comments were not addressed convincingly.

My concern is still valid. The authors used only one approach to knockdown FMNL2 which is "siRNA-mediated knockdown". Using an additional approach to inhibit FMNL2 (Trim-Away or morpholino,..) would be beneficial to confirm that the effect of siRNA-mediated knockdown of FMNL2 is specific.

Response 1: In the author's response, they mentioned that successful migration was quantified based on the contact between the spindle pole and the oocyte cortex.<br /> After spindle migration, it is very common for the spindle to be close to (but not in contact with) the cortex for a considerable time. The spindle pole comes in contact with the cortex later (just before anaphase onset and polar body extrusion). Fig. 3A shows an example where at 9 h, the spindle is already migrated but did not come in contact with the cortex until 9:30 h. Based on Fig. 3B,C, the authors assessed spindle migration in fixed oocytes, making it impossible to fix all oocytes at the time of spindle contact with the cortex. Also,<br /> the representative images in Fig. 3C do not show spindle staining to assess the contact between the spindle and the cortex.<br /> Overall, I still believe that the distance between the spindle and the cortex is more accurate for quantifying spindle migration.

Response 2: The authors mentioned, "we made appropriate modifications to the relevant descriptions of immunoprecipitation experiments". I can't find these modifications in the manuscript. The authors need to state clearly that the immunoprecipitation results do not necessarily reflect meiotic oocytes specifically because these experiments were done using the whole ovary which contains both somatic cells and oocytes.

Response 5: The authors mentioned that "Based on our observations, during the extrusion of the first polar body in oocytes, there is a temporary occurrence of cellular morphological fragmentation due to cortical reorganization". Unfortunately, this means that the live imaging system in the authors' laboratory is not ideal for oocyte maturation. Several publications show normal oocyte morphology during cytokinesis. Please delete or replace Fig. 2E.

Reviewer #1 (Public Review):

Summary:

HIV associated nephropathy (HIVAN) is a rapidly progressing form of kidney disease that manifests secondary to untreated HIV infection, and is predominantly seen in individuals of African descent. Tg26 mice carrying an HIV transgene lacking gag and pol exhibit high levels of albuminuria and rapid decline in renal function that recapitulates many features of HIVAN in humans. HIVAN is seen predominantly in individuals carrying two copies of missense variants in the APOL1 gene, and the authors have previously shown that APOL1 risk variant mRNA induces activity of the double strand RNA sensor kinase PKR. Because of the tight association between the APOL1 risk genotype and HIVAN, the authors hypothesized that PKR activation may mediate the renal injury in Tg26 mice, and tested this hypothesis by treating mice with a commonly used PKR inhibitory compound called C16. Treatment with C16 substantially attenuated renal damage in the Tg26 model as measured by urinary albumin/creatinine ratio, urinary NGAL/creatinine ratio and improvement in histology. The authors then performed bulk and single-nucleus RNAseq on kidneys from mice from different treatment groups to identify pathways and patterns of cell injury associated with HIV transgene expression as well as to determine the mechanistic basis for the effect of C16 treatment. They show that proximal tubule nuclei from Tg26 mice appear to have more mitochondrial transcripts which was reversed by C16 treatment and suggest that this may provide evidence of mitochondrial dysfunction in this model. They explore this hypothesis by showing there is a decrease in the expression of nuclear encoded genes and proteins involved in oxidative phosphorylation as well as a decrease in respiratory capacity via functional assessment of respiration in tubule and glomerular preparations from these mouse kidneys. All of these changes were reversed by C16 treatment. The authors propose the existence of a novel injured proximal tubule cell-type characterized by the leak of mitochondrial transcripts into the nucleus (PT-Mito). Analysis of HIV transgene expression showed high level expression in podocytes, consistent with the pronounced albuminuria that characterizes this model and HIVAN, but transcripts were also detected in tubular and endothelial cells. Because of the absence of mitochondrial transcripts in the podocytes, the authors speculate that glomerular mitochondrial dysfunction in this model is driven by damage to glomerular endothelial cells.

Strengths:

The strengths of this study include the comprehensive transcriptional analysis of the Tg26 model, including an evaluation of HIV transgene expression, which has not been previously reported. This data highlights that HIV transcripts are expressed in a subset of podocytes, consistent with the highly proteinuric disease seen in mouse and humans. However, transcripts were also seen in other tubular cells, notably intercalated cells, principal cells and injured proximal tubule cells. Though the podocyte expression makes sense, the relevance of the tubular expression to human disease is still an open question.

The data in support of mitochondrial dysfunction are also robust and rely on combined evidence from downregulation of transcripts involved in oxidative phosphorylation, decreases in complex I and II as determined by immunoblot, and assessments of respiratory capacity in tubular and glomerular preparations. These data are largely consistent with other preclinical renal injury model reported in the literature as well as previous, less thorough assessments in the Tg26 model.

Weaknesses:

The key weakness of the study lies in the use of a PKR inhibitor with questionable specificity. C16 has been reported to inhibit numerous other kinases including cyclin CDKs and GSK3α and -β, and this means that the conclusions of this study with respect to the role of PKR are highly questionable. The rationale for the dose used was not provided (and is lower than used in other publications with C16), and in the absence of drug exposure data and assessment of target engagement, it is difficult to ascertain whether substantial inhibition of PKR was achieved.

A second key weakness lies in the identification of the PT-Mito cell cluster. Though the authors provide some rationale for the identification of this specific cell type, it seems equally plausible the cells merely reflect a high background capture of mitochondria in a subset of droplets. The IHC analysis that was provided is not convincing enough to support the claim and more careful high resolution imaging and in situ hybridization (with appropriate quantitation) will be needed to provide substantive support for the presence of a proximal tubule cell type with mitochondrial transcript that are trafficked to the nucleus.

Revision summary:

The authors have revised the manuscript to acknowledge the potential limitations of the C16 tool compound used and have performed some additional analyses that suggest the PT-Mito population can be identified in samples from KPMP. The authors added some control images for the in situ hybridizations, which are helpful, though they don't get to the core issue of limited resolution to determine whether mitochondrial RNA is present in the nuclei of injured PT cells. Some additional work has been done to show that C16 treatment results in a decrease in phospho-PKR, a readout of PKR inhibition. These changes strengthen the manuscript by providing some evidence for the translatability of the PT-mito cluster to humans and some evidence for on-target activity for C16. It would be helpful if the authors could quantify the numbers of cells in IHC with nuclear transcripts as well as pointing out some specific examples in the images provided, as comparator data for the snRNAseq studies in which 3-6% of cortex cells had evidence of nuclear mitochondrial transcripts.

Reviewer #2 (Public Review):

Summary:

Numerous studies by the authors and other groups have demonstrated an important role for HIV gene expression kidney cells in promoting progressive chronic kidney disease, especially HIV associated nephropathy. The authors had previously demonstrated a role for protein kinase R (PKR) in a non-HIV transgenic model of kidney disease (Okamoto, Commun Bio, 2021). In this study, the authors used innovative techniques including bulk and single nuclear RNAseq to demonstrate that mice expressing a replication-incompetent HIV transgene have prominent dysregulation of mitochondrial gene expression and activation of PKR and that treatment of these mice with a small molecule PKR inhibitor ameliorated the kidney disease phenotype in HIV-transgenic mice. They also identified STAT3 as a key upstream regulator of kidney injury in this model, which is consistent with previously published studies. Other important advances include identifying the kidney cell types that express the HIV transgene and have dysregulation of cellular pathways.

Strengths:

Major strengths of the study include the use of a wide variety of state-of-the-art molecular techniques to generate important new data on the pathogenesis of kidney injury in this commonly used model of kidney disease and the identification of PKR as a potential druggable target for the treatment of HIV-induced kidney disease. The authors also identify a potential novel cell type within the kidney characterized by high expression of mitochondrial genes.

Weaknesses:

Though the HIV-transgenic model used in these studies results in a phenotype that is very similar to HIV-associated nephropathy in humans, the model has several limitations that may prevent direct translation to human disease, including the fact that mice lack several genetic factors that are important contributors to HIV and kidney pathogenesis in humans. Additional studies are therefore needed to confirm these findings in human kidney disease.

Reviewer #1 (Public Review):

Summary:

The authors constructed a live-attenuated vaccine candidate, BK2102, combining naturally occurring virulence-attenuating mutations in the key coding regions. They showed that intranasal inoculation with the candidate vaccine-induced humoral and cellular immune responses in Syrian hamsters without apparent tissue damage in the lungs and protected against a wild-type SARS-CoV-2 strain with D614G mutation and the latest Omicron subvariant (BA.5) strain. The neutralizing antibodies induced by BK2102 persisted for the long term (up to 364 days). Furthermore, they confirmed the safety of the proposed vaccine using transgenic (Tg) mice expressing human ACE2 (hACE2).

Strengths:

The authors followed a robust methodology to establish the proposed vaccine's protective effect and safety profile in the hamsters and transgenic mice expressing human ACE2.

Weaknesses:

(1) A comparative safety assessment of the available m-RNA and live attenuated vaccines will be necessary. The comparison should include details of the doses, neutralizing antibody titers with duration of protection, tissue damage in the various organs, and other risks, including virulence reversal.

(2) The vaccine's effect on primates is doubtful. The study fails to explain why only two of four monkeys developed neutralizing antibodies. Information about the vaccine's testing in monkeys is also missing: What was the level of protection and duration of the persistence of neutralizing antibodies in monkeys? Were the tissue damages and other risks assessed?

(3) The vaccine's safety in immunosuppressed individuals or individuals with chronic diseases should be assessed. Authors should make specific comments on this aspect.

(4) The candidate vaccine has been tested with a limited number of SARS-CoV-2 strains. Of note, the latest Omicron variants have lesser virulence than many early variants, such as the alfa, beta, and delta strains.

(5) Limitations of the study have not been discussed.

Reviewer #2 (Public Review):

Summary:

In this manuscript "Immunogenicity and safety of a live-attenuated SARS-CoV-2 vaccine candidate based on multiple attenuation mechanisms" by Suzuki-Okutani et al., the authors evaluate the attenuation, immunogenicity, and protection efficacy of a live-attenuated SARS-CoV-2 vaccine candidate (BK2102) against SARS-CoV-2.

Strengths:

The authors demonstrate that intranasal inoculation of BK2102 is safe and able to induce humoral and cellular immune responses in hamsters, without apparent signs of damage in the lungs, that protects against homologous SARS-CoV-2 and Omicron BA.5 challenge. Safety of BK2102 was further confirmed in a new hACE2 transgenic mouse model generated by the authors.

Weaknesses:

No major weaknesses were identified, however, this reviewer notes the following:

The authors missed the opportunity to include a mRNA vaccine to demonstrate that the immunity and protection efficacy of their live attenuated vaccine BK2102 is better than a mRNA vaccine.

One of the potential advantages of live-attenuated vaccines is their ability to induce mucosal immunity. It would be great if the authors included experiments to assess the mucosal immunity of their live-attenuated vaccine BK2102.

Reviewer #3 (Public Review):

Summary:

Suzuki-Okutani and collogues reported a new live-attenuated SARS-CoV-2 vaccine (BK2102) containing multiple deletion/substitution mutations. They show that the vaccine candidate is highly attenuated and demonstrates a great safety profile in multiple animal models (hamsters and Tg-Mice). Importantly, their data show that single intranasal immunization with BK2102 leads to strong protection of hamsters against D614G and BA.5 challenge in both lungs and URT (nasal wash). Both humoral and cellular responses were induced, and neutralization activity remained for >360 after a single inoculation.

Strengths:

The manuscript describes a comprehensive study that evaluates the safety, immunogenicity, and efficacy of a new live-attenuated vaccine. Strengths of the study include (1) strong protection against immune evasive variant BA.5 in both lungs and NW; (2) durability of immunity for >360 days; (3) confirmation of URT protection through a transmission experiment.

While first-generation COVID-19 vaccines have achieved much success, new vaccines that provide mucosal and durable protection remain needed. Thus, the study is significant.

Weaknesses:

Lack of a more detailed discussion of this new vaccine approach in the context of reported live-attenuated SARS-CoV-2 vaccines in terms of its advantages and/or weaknesses.

Antibody endpoint titers could be presented.

Lack of elaboration on immune mechanisms of protection at the upper respiratory tract (URT) against an immune evasive variant in the absence of detectable neutralizing antibodies.

Reviewer #1 (Public Review):

Overview:

The authors construct a pair of E. coli populations that differ by a single gene duplication in a selectable fluorescent protein. They then evolve the two populations under differing selective regimes to assess whether the end result of the selective process is a "better" phenotype when starting with duplicated copies. Importantly, their starting duplicated population is structured to avoid the duplication-amplification process often seen in bacterial artificial evolution experiments. They find that while duplication increases robustness and speed of adaptation, it does not result in more highly adapted final states, in contrast to Ohno's hypothesis.

Major comments:

This is an excellent study with a very elegant experimental setup that allows a precise examination of the role of duplication in functional evolution, exclusive of other potential mechanisms. My main concern is to clarify some of the arguments relating to Ohno's hypothesis.

I think my main confusion on first reading the manuscript was in the precise definition of Ohno's hypothesis. I think this confusion was mine and not the authors, but it is likely common and could be addressed.

Most evolutionary biologists think of gene duplication as making neofunctionalization "easier" by providing functional redundancy and a larger mutational target, such that the evolutionary process of neofunctionalization is faster (as the authors observed). In this framework, the final evolved state might not differ when selection is applied to duplicated copies or a single-copy gene. Ohno's hypothesis, by contrast, argues that there generally exist adaptive conflicts between the ancestral function and the "desired" novel function, such that strong selection on a single-copy gene cannot produce the evolutionary optima that selection on two copies would. This idea is hinted at in the quotation from Ohno in paragraph 2 of the introduction. However, the sentences that follow I don't think reinforce this concept well enough and lead to some confusion.

With that definition in mind, I agree with the authors' conclusion that these data do not support Ohno's hypothesis. My quibble would be that what is actually shown here is that adaptive conflict in function is not universal: there are cases where a single gene can be optimized for multiple functions just as well as duplicated copies. I do not think the authors have, however, refuted the possibility that such adaptive conflicts are nonetheless a significant barrier to evolutionary innovation in the absence of gene duplication generally. Perhaps just a sentence or two to this effect might be appropriate.

I also think the authors need to clarify their approach to normalizing fluorescence between the two populations to control for the higher relative protein expression of the population with a duplicated gene. Since each population was independently selected with the highest fluorescing 60% (or less) of the cells selected, I think this normalization is appropriate. Of course, if the two populations were to compete against each other, this dosage advantage of the duplicates would itself be a selective benefit. Even as it is, the dosage advantage should be a source of purifying selection on the duplication, and perhaps this should be noted.

Finally, I am slightly curious about the nature of the adaptations that are evolving. The authors primarily discuss a few amino-acid changing mutations that seem to fix early in the experiment. Looking at Figure 3, it however, appears that the populations are still evolving late in the experiment, and so presumably other changes are occurring later on. Do the authors believe that perhaps expression changes to increase protein levels are driving these later changes?

Reviewer #2 (Public Review):

Summary:

Drawing from tools of synthetic biology, Mihajlovic et al. use a cleverly designed experimental system to dissect Ohno's hypothesis, which describes the evolution of functional novelty on the gene-level through the process of duplication & divergence.

Ohno's original idea posits that the redundancy gained from having two copies of the same gene allows one of them to freely evolve a new function. To directly test this, the authors make use of a fluorescent protein with two emission maxima, which allows them to apply different selection regimes (e.g. selection for green AND blue, or, for green NOT blue). To achieve this feat without being distracted by more complex evolutionary dynamics caused by the frequent recombination between duplicates, the authors employ a well-controlled synthetic system to prevent recombination: Duplicates are placed on a plasmid as indirect repeats in a recombination-deficient strain of E.coli. The authors implement their directed evolution approach through in vitro mutagenesis and selection using fluorescent-activated cell sorting. Their in-depth analysis of evolved mutants in single-copy versus double-copy genotypes provides clear evidence for Ohno's postulate that redundant copies experience relaxed purifying selection. In contrast to Ohno's original postulate, however, the authors go on to show that this does not in fact lead to more rapid phenotypic evolution, but rather, the rapid inactivation of one of the copies.

Strengths:

This paper contributes with great experimental detail to an area where the literature predominantly leans on genomics data. Through the use of a carefully designed, well-controlled synthetic system the authors are able to directly determine the phenotype & genotype of all individuals in their evolving populations and compare differences between genotypes with a single or double copy of coGFP. With it they find clear evidence for what critics of Ohno's original model have termed "Ohno's dilemma", the rapid non-functionalization by predominantly deleterious mutations.

Including an expressed but non-functional coGFP in (phenotypically) single copy genotypes provides an especially thoughtful control that allows determining a baseline dN/dS ratio in the absence of selection. All in all the study is an exciting example of how the clever use of synthetic biology can lead to new insights.

Weaknesses:

The major weakness of the study is tied to its biggest strength (as often in experimental biology there is a trade-off between 'resolution' and 'realism').

The paper ignores an important component of the evolutionary process in favour of an in-depth characterization of how two vs one copy evolve. Specifically, by employing a recombination-deficient strain and constructing their duplicates as inverted repeats their experimental design completely abolishes recombination between the two copies.

This is problematic for two reasons:

i) In nature, new duplicates do not arise as inverted, but rather as direct (tandem) repeats and - as the authors correctly point out - these are very unstable, due to the fact that repeated DNA is prone to recA-dependent homologous recombination (which arise orders of magnitude more frequently than point mutations).

ii) This instability often leads to further amplification of the duplicates under dosage selection both in the lab and in the wild (e.g. Andersson & Hughes, Annu. Rev. Genet. 2009), and would presumably also be an outcome under the current experimental set-up if it was not prevented from happening?

So in sum, recombination between duplicate genes is not merely a nuisance in experiments, but occurring at extremely high frequencies in nature (such that the authors needed to devise a clever engineering solution to abolish it), and is often observed in evolving populations, be it in the laboratory or the wild.

The manuscript sells controlling of copy number as a strength. And clearly, without it, the same insights could not be gained. However, if the basis for the very process of what Ohno's model describes is prevented from happening for the process to be studied, then, for reasons of clarity and context this needs pointing out, especially, to readers less familiar with the principles of molecular evolution.

Connected to this, there are several places in the introduction and the discussion where I feel that the existing literature, in particular models put forward since Ohno that invoke dosage selection (such as IAD) end up being slightly misrepresented.

My point is best exemplified in line 1 of Discussion: "To test Ohno's hypothesis and to distinguish its predictions from those of competing hypotheses, it is necessary to maintain a constant and stable copy number of duplicated genes during experimental evolution."

I think this statement is simply not true and might be misleading. To take the exaggerated position of a devil's advocate, the goal of evolutionary biology should be to find out how evolution actually proceeds in nature most of the time, rather than creating laboratory systems that manage to recapitulate influential ideas.

While fixing copy number may be a necessary step to understand how one copy evolves if a second one is present, it seems that if Ohno's hypothesis only works out in recA-deficient bacterial strains and on engineered inverted repeats, that Ohno might have missed one crucial aspect of how paralogs evolve. The mentioned competing hypotheses have been put forward to (a) address Ohno's dilemma (which the present study beautifully demonstrates exists under their experimental conditions) and (b) to reflect a commonly observed evolutionary process in bacteria (dosage gain in response to selection, e.g. a classic way of gaining antibiotic resistance). Fixing the copy number allowed the authors to show which predictions of Ohno's model hold up and which don't (under these specific conditions). But they do so without even preventing the processes described by alternative models from happening, so the experimental system is hardly appropriate to distinguish between Ohno & alternatives. Therefore, I think it could be made clearer that the experimental system is great to look at certain aspects Ohno's hypothesis in detail, but it can only inform us about a universe without recombination.

(1) Citing the works by ref 8, 26, 27 to merely state that "in some copies were gained and some were lost (ref 6, ref 25)" makes it seem as if fixing at 2 copies is some sort of sensible average. Yet ref 6 (Dhar et al.) specifically states that dosage is the most important response. Moreover, in this study gene copies are lost, but plasmid copies are gained instead. In Holloway et al. 2007 (ref 25), the 2 copies resided on different plasmids, so entirely different underlying molecular genetics might be at work (high cost of plasmid maintenance, and competitive binding on both proteins onto the respective (off)-target, where either way selection favored a single copy, so a different situation altogether). In both cited studies, fixing the copy would have prohibited learning something about the process of duplication & divergence.

Hence this statement seems to distract the readers from the main message, which seems that preventing recombination experimentally allows to follow the divergence of each copy and studying a response that does not involve dosage-increase.

(2) "These studies highlighted the importance of gene duplication in providing fast adaptation under changing environmental conditions but they focused on the importance of gene dosage." I think this constructs a false dichotomy. Instead, these studies pointed out that dosage (and with it, selection for dosage) is an important part of the equation that might have been missed by Ohno.

(3) "Such models are also easier to test experimentally, because they do not require precise control of gene copy number. The necessary tests can even benefit from massive gene amplifications8. Although Ohno's hypothesis is more difficult to test experimentally (...)" - again, I feel the wording is slightly misleading. The point is not that IAD is easier to test and Ohno's model is harder to test in laboratory experiments, rather, experiments (and some more limited observations of naturally evolving populations) seem to suggest that in reality evolution proceeds (more often?) according to IAD rather than Ohno's neofunctionalization hypothesis. However, as the authors point out, it will be exciting to see their clever experimental system used to test other genes and conditions to get a more comprehensive understanding of what gene- and selection- parameter values would overcome Ohno's dilemma.

Reviewer #1 (Public Review):

Summary:

The authors collected genomic information from public sources covering 423 eukaryote genomes and around 650 prokaryote genomes. Based on pre-computed CDS annotation, they estimated the frequency of alternative splicing (AS) as a single average measure for each genome and computed correlations with this measure and other genomic properties such as genome size, percentage of coding DNA, gene and intergenic span, etc. They conclude that AS frequency increases with genome complexity in a somewhat directional trend from "lower" organisms to "higher" organisms.

Strengths:

The study covers a wide range of taxonomic groups, both in prokaryotes and eukaryotes.

Weaknesses:

The study is weak both methodologically and conceptually. Current high throughput sequencing technologies, coupled with highly heterogeneous annotation methods, can observe cases of AS with great sensitivity, and one should be extremely cautious of the biases and rates of false positives associated with these methods. These issues are not addressed in the manuscript. Here, AS measures seem to be derived directly from CDS annotations downloaded from public databases, and do not account for differing annotation methods or RNA sequencing depth and tissue sample diversity.

There is no mention of the possibility that AS could be largely caused by random splicing errors, a possibility that could very well fit with the manuscript's data. Instead, the authors adopt early on the view that AS is regulated and functional, generally citing outdated literature.

There is no question that some AS events are functional, as evidenced by strongly supported studies. However, whether all AS events are functional is questionable, and the relative fractions of functional and non-functional AS are unknown. With this in mind, the authors should be more cautious in interpreting their data. The "complexity" of organisms also correlates well (negatively) with effective population size. The power of selection to eliminate (slightly) deleterious mutations or errors decreases with effective population size. The correlation observed by the authors could thus easily be explained by a non-adaptive interpretation based on simple population genetics principles.

The manuscript contains evidence that the authors might benefit from adopting a more modern view of how evolution proceeds. Sentences such as "... suggests that only sophisticated organisms optimize alternative splicing by increasing..." (L113), or "especially in highly evolved groups such as mammals" (L130), or the repeated use of "higher" and "lower" organisms need revising.

Because of the lack of controls mentioned above, and because of the absence of discussion regarding an alternative non-adaptive interpretation, the analyses presented in the manuscript are of very limited use to other researchers in the field. In conclusion, the study does not present solid conclusions.

Reviewer #2 (Public Review):

Summary:

In this contribution, the authors investigate the degree of alternative splicing across the evolutionary tree and identify a trend of increasing alternative splicing as you move from the base of the tree (here, only prokaryotes are considered) towards the tips of the tree. In particular, the authors investigate how the degree of alternative splicing (roughly speaking, the number of different proteins made from a single ORF (open reading frame) via alternative splicing) relates to three genomic variables: the genome size, the gene content (meaning the fraction of the genome composed of ORFs), and finally, the coding percentage of ORFs, meaning the ratio between exons and total DNA in the ORF. When correlating the degree of alternative splicing with these three variables, they find that the different taxonomic groups have a different correlation coefficient, and identify a "progressive pattern" among metazoan groups, namely that the correlation coefficient mostly increases when moving from flowering plants to arthropods, fish, birds, and finally mammals. They conclude that therefore the amount of splicing that is performed by an organismal group could be used as a measure of its complexity.

Weaknesses:

While I find the analysis of alternative splicing interesting, I also find that it is a very imperfect measure of organismal complexity and that the manuscript as a whole is filled with unsupported statements. First, I think it is clear to anyone studying evolution over the tree of life that it is the complexity of gene regulation that is at the origin of much of organismal structural and behavioral complexity. Arguably, creating different isoforms out of a single ORF is just one example of complex gene regulation. However, the complexity of gene regulation is barely mentioned by the authors. Further, it is clear that none of their correlation coefficients actually show a simple trend (see Table 3). According to these coefficients, birds are more complex than mammals for 3 out of 4 measures. It is also not clear why the correlation coefficient between alternative splicing ratio and genome length, gene content, and coding percentage should display such a trend, rather than the absolute value. There are only vague mechanistic arguments.

Much more troubling, however, is the statement that the data supports "lineage-specific trends" (lines 299-300). Either this is just an ambiguous formulation, or the authors claim that you can see trends *within* lineages. The latter is clearly not the case. In fact, within each lineage, there is a tremendous amount of variation, to such an extent that many of the coefficients given in Table 3 are close to meaningless. Note that no error bars or p-values are presented for the values shown in Table 3. Figure 2 shows the actual correlation, and the coefficient for flowering plants there is given as 0.151, with a p-value of 0.193. Table 3 seems to quote r=0.174 instead. It should be clear that a correlation within a lineage or species is not a sign of a trend.

There are several wrong or unsupported statements in the manuscript. Early on, the authors state that the alternative splicing ratio (a number greater or equal to one that can be roughly understood as the number of different isoforms per ORF) "quantifies the number of different isoforms that can be transcribed using the same amount of information" (lines 51-52). But in many cases, this is incorrect, because the same sequence can represent different amounts of information depending on the context. So, if a changed context gives rise to a different alternative splice, it is because the genetic sequence has a different meaning in the changed context: the information has changed. In line 149, the authors state that "the energetic cost of having large genomes is high". No citation is given, and while such a statement seems logical, it does not have very solid support. If there was indeed a strong selective force to reduce genome size, we would not see the stunning diversity of genome sizes even within lineages. This statement is repeated (without support) several times in the manuscript, apparently in support of the idea that mammals had "no choice" to increase complexity via alternative splicing because they can't increase it by having longer genomes. I don't think this reasoning can be supported. Even more problematic is the statement that "the amount of protein-coding DNA seems to be limited to a size of about 10MB" (line 219). There is no evidence whatsoever for this statement. The reference that is cited (Choi et al 2020) suggests that there is a maximum of 150GB in total genome size due to physiological constraints. In lines 257-258, the authors write that "plants are less restricted in terms of storing DNA sequences compared to animals" (without providing evidence or a citation). I believe this statement is made due to the observation that plants tend to have large intergenic regions. But without examining the functionality of these interagency regions (they might host long non-coding RNA stretches that are used to regulate the expression of other genes, for example) it is quite adventurous to use such a simple measure as being evidence that plants "are less restricted in terms of storing DNA sequences", whatever that even means. I do not think the authors mean that plants have better access to -80 freezers. The authors conclude that "plant's primary mechanism of genome evolution is by expanding their genome". This statement itself is empty: we know that plants are prone to whole genome duplication, but this duplication is not, as far as we understand, contributing to complexity. It is not a "primary mechanism of genome evolution". In lines 293-294, the authors claim that "alternative splicing is maximized in mammalian genomes". There is no evidence that this ratio cannot be increased. So, to conclude (on lines 302-303) that alternative splicing ratios are "a potential candidate to quantify organismal complexity" seems, based on this evidence, both far-fetched and weak at the same time.

I am also not very comfortable with the data analysis. The authors, for example, say that they have eliminated from their analysis a number of "outlier species". They mention one: Emmer wheat because it has a genome size of 900 Mb (line 367). Since 900MB does not appear to be extreme, perhaps the authors meant to write 900 Gb. When I consulted the paper that sequenced Triticum dicoccoides, they noted that 14 chromosomes are about 10GB. Even a tetraploid species would then not be near 900Gb. But more importantly, such a study needs to state precisely which species were left out, and what the criteria are for leaving out data, lest they be accused of selecting data to fit their hypothesis.

I understand that Methods are often put at the end of a manuscript, but the measures discussed here are so fundamental to the analysis that a brief description of what the different measures are (in particular, the "alternative splicing ratio") should be in the main text, even when the mathematical definition can remain in the Methods.

Finally, a few words on presentation. I understand that the following comments might read differently after the authors change their presentation. This manuscript was at the border of being comprehensible. In many cases, I could discern the meaning of words and sentences in contexts but sometimes even that failed (as an example above, about "species-specific trends", illustrates). The authors introduced jargon that does not have any meaning in the English language, and they do this over and over again.

Note that I completely agree with all the comments by the other reviewer, who alerted me to problems I did not catch, including the possible correlation with effective population size: a possible non-adaptive explanation for the results.

Reviewer #1 (Public Review):

In their manuscript "Spindle assembly checkpoint-dependent mitotic delay is required for cell division in absence of centrosomes," Farrell and colleagues employ carefully chosen approaches to assay mitotic timeliness in the absence of centrosomes in mammalian culture cells, namely the mechanism behind it and its function. The authors acknowledge prior work well and present their data succinctly, clearly, and with a clear logical flow of experiments. The experiments are thoughtfully designed and presented, with appropriate controls in place.

The authors' model whereby centrosome separation and its early definition of poles mediates timely mitosis without relying on a SAC-dependent delay is compelling, and the authors' data are consistent with it. They show using two different MPS1 inhibitors that acentrosomal cell division fails, supporting their claims that a SAC-dependent delay is required in these instances. Furthermore, they show that reintroducing a time delay is sufficient to restore cell division, but inhibiting a different aspect of SAC function does not restore cell division. Next, the authors rule out polyploidy as a potential confounding factor for requiring a SAC-dependent delay, and instead demonstrate that inhibiting centrosome separation by Eg5 inhibition is sufficient to require this delay for mitotic progression. The authors' findings overall support their proposed model.

Probing what aspects of centrosomes protect against a requirement for SAC-dependent delays would strengthen the work and specifically the conclusion that centrosomes provide "two-ness". For example, the authors could examine division in a population of cells with only one centrosome. Seeing some restoration of mitotic progression in the absence of SAC-dependent delays would suggest that even one centrosome with uninhibited Eg5 is sufficient to negate SAC-dependent delays, and would limit models for what exactly centrosomes contribute. This would help disentangle the roles of actual centrosomes and their biochemical cues, Eg5-driven centrosome separation, and early definition of poles on mitotic progression in the absence of SAC-dependent delays. Making a high fraction of cells with one centrosome could be achieved by using centrinone for a shorter time.

Comments on revised version:

The main point from the initial review does not appear to be addressed in the revised version. As such, the comments on the revised version remain the same.

Reviewer #2 (Public Review):

Centrosomes are an integral part of cell division in most animal cells. There are notable exceptions, however, such as oocytes and plants. In addition, some animal cells can be engineered to lack centrosomes yet they can still manage to complete mitosis. This paper uses a couple of methods (PLK4 inhibition and deletion of SASS6) to remove centrosomes from an immortalized cell line. Indeed, a strength of the paper is that similar results are obtained using both protocols to generate acentrosomal cells. The authors find acentrosomal cells take longer to divide, mostly due to a longer metaphase. The paper is based on the finding that inhibition of MPS1 results in a failure to divide, and the hypothesis that a SAC - dependent delay is required for these acentrosomal cells to divide.

The finding that MPS1 inhibition results in a failure to division is interesting. This is investigated by analyzing cells where AurB, APC or Eg5 (to generate monastral spindles) have been inhibited. My concerns are that the results are not conclusive that the effect of MPS1 is on cell cycle regulation. There is not enough data to make a conclusion as to why inhibition of MPS1 results in cell division failure.

1) An example is how to interpret the effect of Aurora B inhibition, which does not block acentrosomal cell division. If Aurora B is required for SAC activity, it suggests this effect of MPS1 may be a function other than SAC. Given the complexity of the SAC, it would be informative to test other SAC components. Instead, the authors conclude that the mitotic delay caused by MPS is required for acentrosomal cell division. I don't think they have ruled out, or even addressed other functions of MPS1.

2) The authors find that when both the APC and MPS1 are inhibited, the cells eventually divide. These results are intriguing, but hard to interpret. The authors suggest that the failure to divide in MPS1-inhibited cells is because they enter anaphase, and then must back out. This is hard to understand and there is not data supporting some kind of aborted anaphase. Is the division observed with double inhibition some sort of bypass of the block caused by MPS1 inhibition alone? It is not clear why inhibition of APC causes increased cell division when MPS1 is inhibited.

3) The authors characterize MTOC formation in these cells, which is also interesting. MTOCs are established after NEB in acentrosomal cells. Indeed, forming these MTOCs is probably a key mechanism for how these cells complete a division, like mouse oocytes.

Following this, the results with inhibiting Eg5 are interesting. The double inhibition of MPS1 and Eg5 results in division failure, like MPS1 inhibition in acentrosomal cells. Thus, there is a cell division block when the centrioles fail to divide. This result raises the possibility that failure to make a bipolar spindle, or the presence of a monopolar spindle, is the problem. In the absence of a bipolar spindle, a SAC induced delay is required for spindle assembly. This is a possibility but there are multiple interpretations of these results. Primarily, these results do not show the MPS1 effect on acentrosomal cells is SAC related. That a SAC mediated delay is required for acentrosmomal spindle assembly is not the only conclusion.

Comments on revised version:

It appears that very few changes have been made. These are all suggestions in the writing and interpretation.

It's disappointing the most of the readouts are cell division success. There is a lack of data about what happens in the MPS1 knockdowns, such as microtubule attachment to KTs and localization/ activity of checkpoint proteins or downstream factors. More mechanistic insights may be found by testing other checkpoint proteins or assaying more metrics for spindle assembly and cell cycle progression. Or if inducing cell cycle delay suppresses the MPS1 effect. These experiments would implicate cell cycle factors as being required for acentrosomal spindle assembly while ruling out a requirement for MPS1 in spindle assembly.

The paper is well written. But some of the terminology could be improved and some descriptions of the cytology are confusing. Some clear definitions of terms may help. The authors refer to an "extended mitosis" (line 73) and then "exit in the absence of cell division" (line 96) when MPS1 is inhibited. Both are misleading and don't tell the full story. These cells attempt to divide and then fail, resulting in one cell. Use of terms like "spread back out", "rounding up", and "sitting down" seems like jargon and should at least be defined. The term "timely two-ness" (line 23-24) is also not helpful. A brief discussion of data on MPS1 function in mouse and fly acentrosomal meiosis might be appropriate. A comparison would be interesting since loss of MPS1 in acentrosomal oocytes does not have such a drastic block in cell division.

Reviewer #3 (Public Review):

Summary:

Day et al. introduced high-throughput expansion microscopy (HiExM), a method facilitating the simultaneous adaptation of expansion microscopy for cells cultured in a 96-well plate format. The distinctive features of this method include 1) the use of a specialized device for delivering a minimal amount (~230 nL) of gel solution to each well of a conventional 96-well plate, and 2) the application of the photochemical initiator, Irgacure 2959, to successfully form and expand the toroidal gel within each well.

Strengths:

This configuration eliminates the need for transferring gels to other dishes or wells, thereby enhancing the throughput and reproducibility of parallel expansion microscopy. This methodological uniqueness indicates the applicability of HiExM in detecting subtle cellular changes on a large scale.

Weaknesses:

To demonstrate the potential utility of HiExM in cell phenotyping, drug studies, and toxicology investigations, the authors treated hiPS-derived cardiomyocytes with a low dose of doxycycline (dox) and quantitatively assessed changes in nuclear morphology. However, this reviewer is not fully convinced of the validity of this specific application. Furthermore, some data about the effect of expansion require reconsideration.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Day et al. present a high-throughput version of expansion microscopy to increase the throughput of this well-established super-resolution imaging technique. Through technical innovations in liquid handling with custom-fabricated tools and modifications to how the expandable hydrogels are polymerized, the authors show robust ~4-fold expansion of cultured cells in 96-well plates. They go on to show that HiExM can be used for applications such as drug screens by testing the effect of doxorubicin on human cardiomyocytes. Interestingly, the effects of this drug on changing DNA organization were only detectable by ExM, demonstrating the utility of HiExM for such studies.

Overall, this is a very well-written manuscript presenting an important technical advance that overcomes a major limitation of ExM - throughput. As a method, HiExM appears extremely useful, and the data generally support the conclusions.

Strengths:

Hi-ExM overcomes a major limitation of ExM by increasing the throughput and reducing the need for manual handling of gels. The authors do an excellent job of explaining each variation introduced to HiExM to make this work and thoroughly characterize the impressive expansion isotropy. The dox experiments are generally well-controlled and the comparison to an alternative stressor (H2O2) significantly strengthens the conclusions.

Weaknesses:

(1) Based on the exceedingly small volume of solution used to form the hydrogel in the well, there may be many unexpanded cells in the well and possibly underneath the expanded hydrogel at the end of this. How would this affect the image acquisition, analysis, and interpretation of HiExM data?

(2) It is unclear why the expansion factor is so variable between plates (e.g., Figure 2H). This should be discussed in more detail.

(3) The authors claim that CF dyes are more resistant to bleaching than other dyes. However, in Figure. S3, it appears that half of the CF dyes tested still show bleaching, and no data is shown supporting the claim that Alexa dyes bleach. It would be helpful to include data supporting the claim that Alexa dyes bleach more than CF dyes and the claim that CF dyes in general are resistant to bleaching should be modified to more accurately reflect the data shown.

(4) Related to the above point, it appears that Figure S11 may be missing the figure legend. This makes it hard to understand how HiExM can use other photo-inducible polymerization methods and dyes other than CF dyes.

(5) The use of automated high-content imaging is impressive. However, it is unclear to me how the increased search space across the extended planar area and focal depths in expanded samples is overcome. It would be helpful to explain this automated imaging strategy in more detail.

(6) The general method of imaging pre- and post-expansion is not entirely clear to me. For example, on page 5 the authors state that pre-expansion imaging was done at the center of each gel. Is pre-expansion imaging done after the initial gel polymerization? If so, this would assume that the gelation itself has no effect on cell size and shape if these gelled but not yet expanded cells are used as the reference for calculating expansion factor and isotropy.

(7) In the dox experiments, are only 4 expanded nuclei analyzed? It is unclear in the Figure 3 legend what the replicates are because for the unexpanded cells, it says the number of nuclei but for expanded it only says n=4. If only 4 nuclei are analyzed, this does not play to the strengths of HiExM by having high throughput.

(8) I am not sure if the analysis of dox-treated cells is accurate for the overall phenotype because only a single slice at the midplane is analyzed. It would be helpful to show, at least in one or two example cases, that this trend of changing edge intensity occurs across the whole 3D nucleus.

(9) It would be helpful to provide an actual benchmark of imaging speed or throughput to support the claims on page 8 that HiExM can be combined with autonomous imaging to capture thousands of cells a day. What is the highest throughput you have achieved so far?

Reviewer #2 (Public Review):

Summary:

In the present work, the authors present an engineering solution to sample preparation in 96-well plates for high-throughput super-resolution microscopy via Expansion Microscopy. This is not a trivial problem, as the well cannot be filled with the gel, which would prohibit the expansion of the gel. A device was engineered that can spot a small droplet of hydrogel solution and keep it in place as it polymerizes. It occupies only a small portion of space at the center of each well, the gel can expand into all directions, and imaging and staining can proceed by liquid handling robots and an automated microscope.

Strengths:

In contrast to Reference 8, the authors' system is compatible with standard 96 well imaging plates for high-throughput automated microscopy and automated liquid handling for most parts of the protocol. They thus provide a clear path towards high-throughput exM and high-throughout super-resolution microscopy, which is a timely and important goal.

Weaknesses:

The assay they chose to demonstrate what high-throughput ExM could be useful for, is not very convincing. But for this reviewer that is not important.

Reviewer #1 (Public Review):

Summary:

Zanetti et al. use biophysical and cellular assays to investigate the interaction of the birnavirus VP3 protein with the early endosome lipid PI3P. The major novel finding is that the association of the VP3 protein with an anionic lipid (PI3P) appears to be important for viral replication, as evidenced through a cellular assay on FFUs.

Strengths:

Supports previously published claims that VP3 may associate with early endosomes and bind to PI3P-containing membranes. The claim that mutating a single residue (R200) critically affects early endosome binding and that the same mutation also inhibits viral replication suggests a very important role for this binding in the viral life cycle.

Weaknesses:

The manuscript is relatively narrowly focused: one bimolecular interaction between a host cell lipid and one protein of an unusual avian virus (VP3-PI3P). Aspects of this interaction have been described previously. Additional data would strengthen claims about the specificity and some technical issues should be addressed. Many of the core claims would benefit from additional experimental support to improve consistency.

Reviewer #2 (Public Review):

Summary:

Birnavirus replication factories form alongside early endosomes (EEs) in the host cell cytoplasm. Previous work from the Delgui lab has shown that the VP3 protein of the birnavirus strain infectious bursal disease virus (IBDV) interacts with phosphatidylinositol-3-phosphate (PI3P) within the EE membrane (Gimenez et al., 2018, 2020). Here, Zanetti et al. extend this previous work by biochemically mapping the specific determinants within IBDV VP3 that are required for PI3P binding in vitro, and they employ in silico simulations to propose a biophysical model for VP3-PI3P interactions.

Strengths:

The manuscript is generally well-written, and much of the data is rigorous and solid. The results provide deep knowledge into how birnaviruses might nucleate factories in association with EEs. The combination of approaches (biochemical, imaging, and computational) employed to investigate VP3-PI3P interactions is deemed a strength.

Weaknesses:

(1) Concerns about the sources, sizes, and amounts of recombinant proteins used for co-flotation: Figures 1A, 1B, 1G, and 4A show the results of co-flotation experiments in which recombinant proteins (control His-FYVE v. either full length or mutant His VP3) were either found to be associated with membranes (top) or non-associated (bottom). However, in some experiments, the total amounts of protein in the top + bottom fractions do not appear to be consistent in control v. experimental conditions. For instance, the Figure 4A western blot of His-2xFYVE following co-flotation with PI3P+ membranes shows almost no detectable protein in either top or bottom fractions. Reading the paper, it was difficult to understand which source of protein was used for each experiment (i.e., E. coli or baculovirus-expressed), and this information is contradicted in several places (see lines 358-359 v. 383-384). Also, both the control protein and the His-VP3-FL proteins show up as several bands in the western blots, but they don't appear to be consistent with the sizes of the proteins stated on lines 383-384. For example, line 383 states that His-VP3-FL is ~43 kDa, but the blots show triplet bands that are all below the 35 kDa marker (Figures 1B and 1G). Mass spectrometry information is shown in the supplemental data (describing the different bands for His-VP3-FL) but this is not mentioned in the actual manuscript, causing confusion. Finally, the results appear to differ throughout the paper (see Figures 1B v. 1G and 1A v. 4A).

(2) Possible "other" effects of the R200D mutation on the VP3 protein. The authors performed mutagenesis to identify which residues within patch 2 on VP3 are important for association with PI3P. They found that a VP3 mutant with an engineered R200D change (i) did not associate with PI3P membranes in co-floatation assays, and (ii) did not co-localize with EE markers in transfected cells. Moreover, this mutation resulted in the loss of IBDV viability in reverse genetics studies. The authors interpret these results to indicate that this residue is important for "mediating VP3-PI3P interaction" (line 211) and that this interaction is essential for viral replication. However, it seems possible that this mutation abrogated other aspects of VP3 function (e.g., dimerization or other protein/RNA interactions) aside from or in addition to PI3P binding. Such possibilities are not mentioned by the authors.

(3) Interpretations from computational simulations. The authors performed computational simulations on the VP3 structure to infer how the protein might interact with membranes. Such computational approaches are powerful hypothesis-generating tools. However, additional biochemical evidence beyond what is presented would be required to support the authors' claims that they "unveiled a two-stage modular mechanism" for VP3-PI3P interactions (see lines 55-59). Moreover, given the biochemical data presented for R200D VP3, it was surprising that the authors did not perform computational simulations on this mutant. The inclusion of such an experiment would help tie together the in vitro and in silico data and strengthen the manuscript.

Reviewer #3 (Public Review):

Summary:

infectious bursal disease virus (IBDV) is a birnavirus and an important avian pathogen. Interestingly, IBDV appears to be a unique dsRNA virus that uses early endosomes for RNA replication that is more common for +ssRNA viruses such as for example SARS-CoV-2.

This work builds on previous studies showing that IBDV VP3 interacts with PIP3 during virus replication. The authors provide further biophysical evidence for the interaction and map the interacting domain on VP3.

Strengths:

Detailed characterization of the interaction between VP3 and PIP3 identified R200D mutation as critical for the interaction. Cryo-EM data show that VP3 leads to membrane deformation.

Weaknesses:

The work does not directly show that the identified R200 residues are directly involved in VP3-early endosome recruitment during infection. The majority of work is done with transfected VP3 protein (or in vitro) and not in virus-infected cells.

Additional controls such as the use of PIP3 antagonizing drugs in infected cells together with a colocalization study of VP3 with early endosomes would strengthen the study.

In addition, it would be advisable to include a control for cryo-EM using liposomes that do not contain PIP3 but are incubated with HIS-VP3-FL. This would allow ruling out any unspecific binding that might not be detected on WB.

The authors also do not propose how their findings could be translated into drug development that could be applied to protect poultry during an outbreak. The title of the manuscript is broad and would improve with rewording so that it captures what the authors achieved.

Reviewer #1 (Public Review):

Summary:

This is an important work showing that loss of LRRK function causes late-onset dopaminergic neurodegeneration in a cell-autonomous manner. One of the LRRK members, LRRK2, is of significant translational importance as mutations in LRRK2 cause late-onset autosomal dominant Parkinson's disease (PD). While many in the field assume that LRRK2 mutant causes PD via increased LRRK2 activity (i.e., kinase activity), it is not a settled issue as not all disease-causing mutant LRRK2 exhibits increased activity. Further, while LRRK2 inhibitors are under clinical trials for PD, the consequence of chronic, long-term LRRK2 inhibition is unknown. Thus, studies evaluating the long-term impact of LRRK deficit have important translational implications. Moreover, because LRRK proteins, particularly LRRK2, are known to modulate immune response and intracellular membrane trafficking, the study's results and the reagents will be valuable for others interested in LRRK function.

Strengths:

This report describes a mouse model where LRRK1 and LRRK2 genes are conditionally deleted in dopaminergic neurons. Previously, this group showed that while loss of LRRK2 expression does not cause brain phenotype, loss of both LRRK1 and LRRK2 causes a later onset, progressive degeneration of catecholaminergic neurons, dopaminergic (DAergic) neurons in the substantia nigra (SN) and noradrenergic neurons in the Locus Coeruleus (LC). However, because LRRK genes are widely expressed with some peripheral phenotypes, it was unknown if the neurodegeneration in LRRK double Knock Out (DKO) was cell autonomous. To rigorously test this question, the authors generated a double conditional KO allele where both LRRK1 and LRRK2 genes were targeted to contain loxP sites. This was beyond what is usually required as most investigators might just have combined one KO allele with another floxed allele. The authors provide a rigorous validation showing that the Driver (DAT-Cre) is expressed in most DAergic neurons in SN and that LRRK levels are decreased selectively in the ventral midbrain. Using these mice, the authors show that the number of DA neurons is average at 15 but significantly decreased at 20 months of age. Moreover, the authors show that the number of apoptotic neurons is increased by ~2X in aged SN, demonstrating increased ongoing cell death and activated microglia. The degeneration is limited to DA neurons as LC neurons are not lost, and this population does not express DAT. Overall, the mouse genetics and experimental analysis were performed rigorously, and the results were statistically sound and compelling.

Weakness:

I only have a few minor comments. First, in PD and other degenerative conditions, axon and terminal loss occur prior to cell bodies. It might be beneficial to show the status of DAergic markers in the striatum. Second, previous studies indicate that very little, if any, LRRK1 is expressed in SN DAergic neurons. This also the case with the Allen Brain Atlas profile. Thus, the authors should discuss the discrepancy, as they imply significant LRRK1 expression in DA neurons.

Revision:

I appreciate the authors revising the manuscript with additional data that have clarified my prior comments. They now show that TH levels in the striatum decrease with SNpc neurons. Further, while there is some disagreement regarding the expression LRRK1 in SNpc, the authors provide a convincing case that LRRK1 function is important in SNpc DA neurons.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Shen and collaborators described the generation of conditional double knockout (cDKO) mice lacking LRRK1 and LRRK2 selectively in DAT-positive dopaminergic neurons. The Authors asked whether selective deletion of both LRRK isoforms could lead to a Parkinsonian phenotype, as previously reported by the same group in germline double LRRK1 and LRRK2 knockout mice (PMID: 29056298). Indeed, cDKO mice developed a late reduction of TH+ neurons in SNpc that partially correlated with the reduction of NeuN+ cells. This was associated with increased apoptotic cell and microglial cell numbers in SNpc. Unlike the constitutive DKO mice described earlier, cDKO mice did not replicate the dramatic increase in autophagic vacuole numbers. The study supports the authors' hypothesis that loss of function rather than gain of function of LRRK2 leads to Parkinson's Disease.

Strengths:

For the first time, the study described a model in which both the Parkinson's disease-associated gene LRRK2 and its homolog LRRK1 are deleted selectively in dopaminergic neurons. This offers a new tool to understand the physiopathological role of LRRK2 and the compensating role of LRRK1 in modulating dopaminergic cell function.

Weaknesses:

The model has no construct validity since loss of function mutations of LRRK2 are well tolerated in humans and do not lead to Parkinson's disease. The evidence of a Parkinsonian phenotype in these conditional knockout mice is limited and should be considered preliminary.

Reviewer #3 (Public Review):

Kang, Huang, and colleagues have provided new data to address concerns regarding confirmation of LRRK1 and LRRK2 deletion in their mouse model and the functional impact of the modest loss of TH+ neurons observed in the substantia nigra of their double KO mice. In the revised manuscript, the new data around the characterization of the germline-deleted LRRK1 and LRRK2 mice add confidence that LRRK1 and LRRK2 can be deleted using the genetic approach. They have also added new text to the discussion to try and address some of the comments and questions raised regarding how LRRK1/2 loss may impact cell survival and the implications of this work for PD-linked variants in LRRK2 and therapeutic approaches targeting LRRK2. The new data provides additional support for the author's claims.

Reviewer #1 (Public Review):

Summary:

The authors present a detailed study of a nearly complete Entomophthora muscae genome assembly and annotation, along with comparative analyses among related and non-related entomopathogenic fungi. The genome is one of the largest fungal genomes sequenced, and the authors document the proliferation and evolution of transposons and presence/absence of related genetic machinery to explore how this may have occurred. There has also been an expansion in gene number, which appears to contain many "novel" genes unique to E. muscae. Functionally, the authors were interested in CAZymes, proteases, circadian clock related genes (due to entomopathogenicity/ host manipulation), other insect pathogen specific genes, and secondary metabolites. There are many interesting findings including expansions in trahalases, unique insulinase and another peptidase, and some evidence for RIP in Entomophthoralean fungi. The authors performed a separate study examining E. muscae species complex and related strains. Specifically, morphological traits were measured for strains and then compared to the 28S+ITS-based phylogeny, showing little informativeness of these morpho characters with high levels of overlap.

This work represents a big leap forward in genomics of non-Dikarya fungi and large fungal genomes. Most of the gene homologs have been studied in species that diverged hundreds of millions of years ago, and therefore using standard comparative genomic approaches are not trivial and still relatively little is known. This paper provides many new hypotheses and potential avenues of research about fungal genome size expansion, entomopathogenesis in zygomycetes, and cellular functions like RIP and circadian mechanisms.

Strengths:

There are many strengths to this study. It represents a massive amount of work and a very thorough functional analysis of the gene content in these fungi (which are largely unsequenced and definitely understudied). Too often comparative genomic work will focus on one aspect and leave the reader wondering about all the other ways genome(s) are unique or different from others. This study really dove in and explored the relevant aspects of the E. muscae genome.

The authors used both a priori and emergent properties to shape their analyses (by searching for specific genes of interest and by analyzing genes underrepresented, expanded, or unique to their chosen taxa), enabling a detailed review of the genomic architecture and content. Specifically, I'm impressed by the analysis of missing genes (pFAMs) in E. muscae, none of which are enriched in relatives, suggesting this fungus is really different not by gene loss, but by its gene expansions.

Analyzing species-level boundaries and the data underlying those (genetic or morphological) is not something frequently presented in comparative genomic studies, however, here it is a welcome addition as the target species of the study is part of a species complex where morphology can be misleading and genetic data is infrequently collected in conjunction with the morphological data.

Weaknesses:

The conclusions of this paper are well supported, and I think the clarifications and improvements made to the manuscript in the revision process have greatly improved the paper.

Reviewer #2 (Public Review):

Summary:

This study reveals that short-term social isolation increases social behavior at a reunion, and a population of hypothalamic preoptic area neurons become active after social interaction following short-term isolation (POAiso neurons). Effectively utilizing a TRAP activity-dependent labeling method, the authors inhibit or activate the POAiso neurons and find that these neurons are involved in controlling various social behaviors, including ultrasonic vocalization, investigation, and mounting in both male and female mice. This work suggests a complex role for the POA in regulating multiple aspects of social behavior, beyond solely controlling male sexual behaviors.

Strengths:

A few studies have shown that optogenetic activation of the POA in females promotes vocalization and mounting behavior, similar to the effects observed in males. However, those were the results of artificially stimulating POA neurons, and it was unknown whether POA neurons play a role in naturally occurring female social behaviors. This paper clearly demonstrates that there exists a population of POA neurons that are necessary for naturally evoked female social vocalizations and mounting behaviors.

Weaknesses:

The authors conclude that "In the current study, we identify and characterize a population of preoptic hypothalamic neurons that contribute to the effects of short-term social isolation on the social behaviors of mice." This is an interesting hypothesis, but in my opinion, critical control experiments are missing to support this claim.

All the activity-dependent labeling experiments with TRAP mice, including the subsequent neural activity manipulation experiments (Figures 2, 3, 4, 5E-F), were conducted by labeling neurons only in socially isolated animals, not group-housed animals. The authors labeled neurons after 30-minute social interactions, raising the possibility that the labeled neurons simply represent a "social interaction/behavior population" (mediating mounting and USVs in females and males) rather than a set of neurons specific to social isolation.

I strongly recommend including experimental groups that involve labeling neurons after 30-minute social interactions in group-housed female or male mice and inhibit TRAPed neurons after social isolation or activate TRAPed neurons after group housing. If manipulating the group-housed TRAP neurons has similar effects to manipulating the isolated TRAP neurons, it would suggest the current labeling paradigm is not isolating neurons specific to the effect of social isolation per se. Rather, the neurons may mediate more general social interaction or motivation-related activities. Given the known role of POA in male mating behavior, a group-housed TRAP experiment in males with a female visitor is especially important for understanding the selectivity of the labeled cells.

Without proper controls, referring to the labeled neurons as "POAiso" neurons is potentially misleading. The data thus far suggests these neurons may predominantly reflect a "POA social behavior" population rather than a set of cells distinctly responsive to isolated housing.

Overall, this paper is well-written and provides valuable new data on the neural circuit for female social behaviors and the potentially complex role of POA in social behavior control.

Reviewer #1 (Public Review):

Summary:

Zhao et al. perform a series of experiments aimed at identifying the role of the preoptic area (POA) in controlling the impact of social isolation on same-sex female social behavior. They focus their manuscript on the effects of short-term (3d) isolation and females, both of which have been relatively understudied, making the overall topic of the manuscript exciting and important.

Strengths:

The work highlighted is well designed, the experiments original, and the manuscript is elegant and clearly written. The strengths of the manuscript lie in the attention to multiple facets of social behavior (investigation, mounting, USVs), sex differences, and the use of multiple loss- and gain-of-function approaches.

Weaknesses:

The main weaknesses of the paper are a lack of significance in key findings, and relatedly, concluding effects from insignificant findings. Additional elements could be improved to help strengthen this overall well-rounded and intriguing set of results.

Reviewer #3 (Public Review):

Summary:

How short-term isolation acts on the brain to promote social behavior remains incompletely understood. The authors found that social interactions after a period of acute isolation increased investigation promoted mounting, and increased the production of ultrasonic vocalizations (USVs). This was true for females during same-sex interactions as well as for males interacting with females. Concomitant with these increased behavioral readouts, cFos expression in the preoptic area of the hypothalamus (POA) was found to increase selectively in single-housed females. Chemogenetic silencing of these POA neurons attenuated all three behavioral measures in socially isolated females. Surprisingly, ablation of the same POA neurons decreased mounting duration without impacting social investigation or USV production. While optogenetic activation was sufficient to evoke USV production, it did not affect either mounting or social investigation. In males, chemogenetic silencing of POA neurons decreased mounting but not other behaviors. Together, these data point towards a role of POA neurons in mediating social behaviors after acute isolation but the exact nature of that control appears to depend on the choice of perturbation method, sex, and social context in complex ways that are hard to parse. This study is an essential first step; additional experiments will be needed to explain the apparent discrepancy between the various circuit perturbation results and to gain a more comprehensive understanding of the role of POA in social isolation.

Strengths:

The goal of understanding the neural circuit mechanisms underlying acute social isolation is clearly important and topical. Using a state-of-the-art technique to tag specific neurons that were active during certain behavioral epochs, the authors managed to identify the POA as a critical circuit locus for the effects of social isolation. The experimental design is perfectly reasonable and the quality of the data is good. The control experiments (Figures 2B-D) showing that chemogenetic inactivation of other hypothalamic regions (AH and VMH) do not affect social behavior is indeed quite satisfying and points towards a specific role of POA within the hypothalamus. Using a combination of behavioral assays, activity-dependent neural tagging, and circuit manipulation techniques, the authors present convincing evidence for the role of the preoptic area of the hypothalamus in mediating certain behaviors following social isolation. These data are likely to be a valuable resource for understanding how hypothalamic circuits adjust to the challenges of social isolation.

Weaknesses:

While the authors should be commended for performing and reporting multiple circuit perturbation experiments (e.g., chemogenetics, ablation), the conflicting effects on behavior are hard to interpret without additional experiments. For example, chemogenetic silencing of the POA neurons (using DREADDs) attenuated all three behavioral measures but the ablation of the same POA neurons (using CASPACE) decreased mounting duration without impacting social investigation or USV production. Similarly, optogenetic activation of POA neurons was sufficient to generate USV production as reported in earlier studies but mounting or social investigation remained unaffected. Do these discrepancies arise due to the efficiency differences between DREADD-mediated silencing vs. Casp3 ablation? Or does the chemogenetic result reflect off-manifold effects on downstream circuitry whereas a more permanent ablation strategy allows other brain regions to compensate due to redundancy? It is important to resolve whether these arise due to technical reasons or whether these reflect the underlying (perhaps messy) logic of neural circuitry. Therefore, while it is clear that POA neurons likely contribute to multiple behavioral readouts of social isolation, understanding their exact roles in any greater detail will require further experiments.

Reviewer #2 (Public Review):

The paper has two main merits. Firstly, it documents a new and important characteristic of the re-organization of the brains of the deaf, namely its variability. The search for a well-defined set of functions for the deprived auditory cortex of the deaf has been largely unsuccessful, with several task-based approaches failing to deliver unanimous results. Now, one can understand why this was the case: most likely there isn't a fixed one well-defined set of functions supported by an identical set of areas in every subject, but rather a variety of functions supported by various regions. In addition, the paper extends the authors' previous findings from blind subjects to the deaf population. It demonstrates that the heightened variability of connectivity in the deprived brain is not exclusive to blindness, but rather a general principle that applies to other forms of deprivation. On a more general level, this paper shows how sensory input is a driver of the brain's reproducible organization.

The method and the statistics are sound, the figures are clear, and the paper is well-written. The sample size is impressively large for this kind of study.

The main weakness of the paper is not a weakness, but rather a suggestion on how to provide a stronger basis for the authors' claims and conclusions. I believe this paper could be strengthened by including in the analysis at least one of the already published deaf/hearing resting-state fMRI datasets (e.g. Andin and Holmer, Bonna et al., Ding et al.) to see if the effects hold across different deaf populations. The addition of a second dataset could strengthen the evidence and convincingly resolve the issue of whether delayed sign language acquisition causes an increase in individual differences in functional connectivity to/from Broca's area. Currently, the authors may not have enough statistical power to support their findings.

Secondly, the authors could more explicitly discuss the broad implications of what their results mean for our understanding of how the architecture of the brain is determined by the genetic blueprint vs. how it is determined by learning (page 9). There is currently a wave of strong evidence favoring a more "nativist" view of brain architecture, for example, face- and object- sensitive regions seem to be in place practically from birth (see e.g. Kosakowski et al., Current Biology, 2022). The current results show what is the role played by experience.

Reviewer #1 (Public Review):

This experiment sought to determine what effect congenital/early-onset hearing loss (and associated delay in language onset) has on the degree of inter-individual variability in functional connectivity to the auditory cortex. Looking at differences in variability rather than group differences in mean connectivity itself represents an interesting addition to the existing literature. The sample of deaf individuals was large, and quite homogeneous in terms of age of hearing loss onset, which are considerable strengths of the work. The experiment appears well conducted and the results are certainly of interest. I do have some concerns with the way that the project has been conceptualized, which I share below.

The authors should provide careful working definitions of what exactly they think is occurring in the brain following sensory deprivation. Characterizing these changes as 'large-scale neural reorganization' and 'compensatory adaptation' gives the impression that the authors believe that there is good evidence in support of significant structural changes in the pathways between brain areas - a viewpoint that is not broadly supported (see Makin and Krakauer, 2023). The authors report changes in connectivity that amount to differences in coordinated patterns of BOLD signal across voxels in the brain; accordingly, their data could just as easily (and more parsimoniously) be explained by the unmasking of connections to the auditory cortex that are present in typically hearing individuals, but which are more obvious via MR in the absence of auditory inputs.

I found the argument that the deaf use a single modality to compensate for hearing loss, and that this might predict a more confined pattern of differential connectivity than had been previously observed in the blind to be poorly grounded. The authors themselves suggest throughout that hearing loss, per se, is likely to be driving the differences observed between deaf and typically-hearing individuals; accordingly, the suggestion that the modality in which intentional behavioral compensation takes place would have such a large-scale effect on observed patterns of connectivity seems out of line.

The analyses highlighting the areas observed to be differentially connected to the auditory cortex and areas observed to be more variable in their connectivity to the auditory cortex seem somewhat circular. If the authors propose hearing loss as a mechanism that drives this variability in connectivity, then it is reasonable to propose hypotheses about the directionality of these changes. One would anticipate this directionality to be common across participants and thus, these areas would emerge as the ones that are differently connected when compared to typically hearing folks.

While the authors describe collecting data on the etiology of hearing loss, hearing thresholds, device use, and rehabilitative strategies, these data do not appear in the manuscript, nor do they appear to have been included in models during data analysis. Since many of these factors might reasonably explain differences in connectivity to the auditory cortex, this seems like an omission.

Reviewer #3 (Public Review):

Summary:

This study focuses on changes in brain organization associated with congenital deafness. The authors investigate differences in functional connectivity (FC) and differences in the variability of FC. By comparing congenitally deaf individuals to individuals with normal hearing, and by further separating congenitally deaf individuals into groups of early and late signers, the authors can distinguish between changes in FC due to auditory deprivation and changes in FC due to late language acquisition. They find larger FC variability in deaf than normal-hearing individuals in temporal, frontal, parietal, and midline brain structures, and that FC variability is largely driven by auditory deprivation. They suggest that the regions that show a greater FC difference between groups also show greater FC variability.

Strengths:

- The manuscript is well written.

- The methods are clearly described and appropriate.

- Including the three different groups enables the critical contrasts distinguishing between different causes of FC variability changes.

- The results are interesting and novel.

Weaknesses:

- Analyses were conducted for task-based data rather than resting-state data. It was unclear whether groups differed in task performance. If congenitally deaf individuals found the task more difficult this could lead to changes in FC.

- No differences in overall activation between groups were reported. Activation differences between groups could lead to differences in FC. For example, lower activation may be associated with more noise in the data, which could translate to reduced FC.

- Figure 2B shows higher FC for congenitally deaf individuals than normal-hearing individuals in the insula, supplementary motor area, and cingulate. These regions are all associated with task effort. If congenitally deaf individuals found the task harder (lower performance), then activation in these regions could be higher, in turn, leading to FC. A study using resting-state data could possibly have provided a clearer picture.

- The correlation between the FC map and the FC variability map is 0.3. While significant using permutation testing, the correlation is low, and it is not clear how great the overlap is.

Reviewer #1 (Public Review):

Summary:

Zheng and colleagues assessed the real-world efficacy of SARS-CoV-2 vaccination against re-infection following the large omicron wave in Shanghai in April 2022. The study was performed among previously vaccinated individuals. The study successfully documents a small but real added protective benefit of re-vaccination, though this diminishes in previously boosted individuals. Unsurprisingly, vaccine preventative efficacy was higher if the vaccine was given in the month before the 2nd large wave in Shanghai. The re-infection rate of 24% suggests that long-term anti-COVID immunity is very difficult to achieve. The conclusions are largely supported by the analyses. These results may be useful for planning the timing of subsequent vaccine rollouts.

Strengths:

The strengths of the study are a very large and unique cohort based on synchronously timed single infection among individuals with well-documented vaccine histories. Statistical analyses seem appropriate. As with any cohort study, there are potential confounders and the possibility of misclassification and the authors outline limitations nicely in the discussion.

Weaknesses:

(1) Partially and fully vaccinated are never defined and it is difficult to understand how this differs from single, and double, booster vaccines. The figures including all of these groups are a bit confusing for this reason.

(2) Figure 3 is a bit challenging to interpret because it is a bit atypical to compare each group to a different baseline (ie 2V-I-V vs 2V-I). I would label the y-axis 2V-I-V vs 2V-I (change all of the labels) to make this easier to understand.

(3) A 15% reduction in infection is quite low. It would be helpful to discuss if any quantitative or qualitative signals suggest at least a reduction in severe outcomes such as death, hospitalization, ER visits, or long COVID. I am not sure that a 15% reduction in cases supports extra vaccination without some other evidence of added benefit.

(4) Why exclude the 74962 unvaccinated from the analysis. it would be interesting to see if getting vaccinated post-infection provides benefits to this group

(5) Pudong should be defined for those who do not live in China.

(6) The discussion about healthcare utilization bias is welcomed and well done. It would be great to speculate on whether this bias might favor the null or alternative hypothesis.

Reviewer #2 (Public Review):

Summary:

This paper evaluates the effect of COVID-19 booster vaccination on reinfection in Shanghai, China among individuals who received primary COVID-19 vaccination followed by initial infection, during an Omicron wave.

Strengths:

A large database is collated from electronic vaccination and infection records. Nearly 200,000 individuals are included in the analysis and 24% became reinfected.

Weaknesses:

The article is difficult to follow in terms of the objectives and individuals included in various analyses. There appear to be important gaps in the analysis. The electronic data are limited in their ability to draw causal conclusions.

More detailed comments:

In multiple places (abstract, introduction), the authors frame the work in terms of understanding the benefit of booster vaccination among individuals with hybrid immunity (vaccination + infection). However, their analysis population does not completely align with this framing. As best as I can tell, only individuals who first received COVID-19 vaccination, and subsequently experienced infection, were included. Why the analysis does not also consider individuals who were infected and then vaccinated is not clear.

In vaccine effectiveness analyses, why was time since initial infection not examined as a modifier of the booster effect? Time since the onset of the Omicron wave is only loosely tied to the immune status of the individual.

The effect of booster vaccination on preventing symptomatic vs. asymptomatic reinfection does not appear to have been evaluated; this is a key gap in the analysis and it would seem the data would support it.

In lines 105-108, the demographic description of the analysis population is incomplete. Is sex or gender identity being described? Are any individuals non-binary? What is the age distribution? (Only the proportions 20-39 and under 6 are stated.)

Figure 1 consort diagram is confusing. In the last row, are the two boxes independent or overlapping sets of individuals? Are all included in secondary analyses?

Reviewer #1 (Public Review):

Summary:

In this study, Franke et al. explore and characterize color response properties across primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The authors use awake 2P imaging to define the spectral response properties of visual interneurons in layer 2/3. They find that opponent responses are more pronounced at photopic light levels, and that diversity in color opponent responses exists across the visual field, with green ON/ UV OFF responses more strongly represented in the upper visual field. This is argued to be relevant for the detection of certain features that are more salient when using chromatic space, possibly due to noise reduction. In the revised version, Franke et al. have addressed the potential pitfalls in the discussion, which is an important point for the non-expert reader. Thus, this study provides a solid characterization of the color properties of V1 and is a valuable addition to visual neuroscience research.

My remaining concerns are based more on the interpretation. I'm still not convinced by the statement "This type of color-opponency in the receptive field center of V1 neurons was not present in the receptive field center of retinal ganglion cells and, therefore, is likely computed by integrating center and surround information downstream of the retina." and I would suggest rewording it in the abstract.

As discussed previously and now nicely added to the discussion, it is difficult to make a direct comparison given the different stimulus types used to characterize the retina and V1 recordings and the different levels of adaptation in both tissues. I will leave this point to the discussion, which allows for a more nuanced description of the phenomenon. Why do I think this is important? In the introduction, the authors argue that "the discrepancy [of previous studies] may be due to differences in stimulus design or light levels." However, while different light levels can be tested in V1, this cannot be done properly in the retina with 2P experiments. To address this, one would have to examine color-opponency in RGC terminals in vivo, which is beyond the scope of this study. Addressing these latter points directly in the discussion would, in my opinion, only strengthen the study.

Reviewer #2 (Public Review):

Summary:

Franke et al. characterize the representation of color in the primary visual cortex of mice, highlighting how this changes across the visual field. Using calcium imaging in awake, head-fixed mice, they characterize the properties of V1 neurons (layer 2/3) using a large center-surround stimulation where green and ultra-violet colors were presented in random combinations. Clustering of responses revealed a set of functional cell-types based on their preference to different combinations of green and UV in their center and surround. These functional types were demonstrated to have different spatial distributions across V1, including one neuronal type (Green-ON/UV-OFF) that was much more prominent in the posterior V1 (i.e. upper visual field). Modelling work suggests that these neurons likely support the detection of predator-like objects in the sky.

Strengths:

The large-scale single-cell resolution imaging used in this work allows the authors to map the responses of individual neurons across large regions of the visual cortex. Combining this large dataset with clustering analysis enabled the authors to group V1 neurons into distinct functional cell types and demonstrate their relative distribution in the upper and lower visual fields. Modelling work demonstrated the different capacity of each functional type to detect objects in the sky, providing insight into the ethological relevance of color opponent neurons in V1.

Weaknesses:

While the study presents convincing evidence about the asymmetric distribution of color-opponent neurons in V1, the paper would greatly benefit from a more in-depth discussion of the caveats related to the conclusions drawn about their origin. This is particularly relevant regarding the conclusion drawn about the contribution of color opponent neurons in the retina. The mismatch between retinal color opponency and V1 color opponency could imply that this feature is not solely inherited from the retina, however, there are other plausible explanations that are not discussed here. Direct evidence for this statement remains weak.

In addition, the paper would benefit from adding explicit neuron counts or percentages to the quadrants of each of the density plots in Figures 2-5. The variance explained by the principal components does not capture the percentage of color opponent cells. Additionally, there appear to be some remaining errors in the figure legend and labels that have not been addressed (e.g. '??' in Fig 2 legend).

Overall, this study will be a valuable resource for researchers studying color vision, cortical processing, and the processing of ethologically relevant information. It provides a useful basis for future work on the origin of color opponency in V1 and its ethological relevance.

Reviewer #3 (Public Review):

This paper studies chromatic coding in mouse primary visual cortex. Calcium responses of a large collection of cells are measured in response to a simple spot stimulus. These responses are used to estimate chromatic tuning properties - specifically sensitivity to UV and green stimuli presented in a large central spot or a larger still surrounding region. Cells are divided based on their responses to these stimuli into luminance or chromatic sensitive groups. The results are interesting and many aspects of the experiments and conclusions are well done; several technical concerns, however, limit the support for several main conclusions,

Limitations of stimulus choice<br /> The paper relies on responses to a large (37.5 degree diameter) modulated spot and surround region. This spot is considerably larger than the receptive fields of both V1 cells and retinal ganglion cells (it is twice the area of the average V1 receptive field). As a result, the spot itself is very likely to strongly activate both center and surround mechanisms, and responses of cells are likely to depend on where the receptive fields are located within the spot (and, e.g., how much of the true neural surround samples the center spot vs the surround region). Most importantly, the surrounds of most of the recorded cells will be strongly activated by the central spot. This brings into question statements in the paper about selective activation of center and surround (e.g. page 2, right column). This in turn raises questions about several subsequent analyses that rely on selective center and surround activation.

Comparison with retina<br /> A key conclusion of the paper is that the chromatic tuning in V1 is not inherited from retinal ganglion cells. This conclusion comes from comparing chromatic tuning in a previously-collected data set from retina with the present results. But the retina recordings were made using a considerably smaller spot, and hence it is not clear that the comparison made in the paper is accurate. For example, the stimulus used for the V1 experiments almost certainly strongly stimulates both center and surround of retinal ganglion cells. The text focuses on color opponency in the receptive field centers of retinal ganglion cells, but center-surround opponency seems at least as relevant for such large spots. This issue needs to be described more clearly and earlier in the paper.

Limitations associated with ETA analysis<br /> One of the reviewers in the previous round of reviews raised the concern that the ETA analysis may not accurately capture responses of cells with nonlinear receptive field properties such as On/Off cells. This possibility and whether it is a concern should be discussed.

Discrimination performance poor<br /> Discriminability of color or luminance is used as a measure of population coding. The discrimination performance appears to be quite poor - with 500-1000 neurons needed to reliably distinguish light from dark or green from UV. Intuitively I would expect that a single cell would provide such discrimination. Is this intuition wrong? If not, how do we interpret the discrimination analyses?

Reviewer #1 (Public Review):

Summary:

Willems and colleagues test whether unexpected shock omissions are associated with reward-related prediction errors by using an axiomatic approach to investigate brain activation in response to unexpected shock omission. Using an elegant design that parametrically varies shock expectancy through verbal instructions, they see a variety of responses in reward-related networks, only some of which adhere to the axioms necessary for prediction error. In addition, there were associations between omission-related responses and subjective relief. They also use machine learning to predict relief-related pleasantness, and find that none of the a priori "reward" regions were predictive of relief, which is an interesting finding that can be validated and pursued in future work.

Strengths:

The authors pre-registered their approach and the analyses are sound. In particular, the axiomatic approach tests whether a given region can truly be called a reward prediction error. Although several a priori regions of interest satisfied a subset of axioms, no ROI satisfied all three axioms, and the authors were candid about this. A second strength was their use of machine learning to identify a relief-related classifier. Interestingly, none of the ROIs that have been traditionally implicated in reward prediction error reliably predicted relief, which opens important questions for future research.

Weaknesses:

To ensure that the number of omissions is similar across conditions, the task employs inaccurate verbal instructions; i.e. 25% of shocks are omitted, regardless of whether subjects are told that the probability is 100%, 75%, 50%, 25%, or 0%. Given previous findings on interactions between verbal instruction and experiential learning (Doll et al., 2009; Li et al., 2011; Atlas et al., 2016), it seems problematic a) to treat the instructions as veridical and b) average responses over time. Based on these prior work, it seems reasonable to assume that participants would learn to downweight the instructions over time through learning (particularly in the 100% and 0% cases); this would be the purpose of prediction errors as a teaching signal. The authors do recognize this and perform a subset analysis in the 21 participants who showed parametric increases in anticipatory SCR as a function of instructed shock probability, which strengthened findings in the VTA/SN; however given that one third of participants (n=10) did not show parametric SCR in response to instructions, it seems like some learning did occur. As prediction error is so important to such learning, a weakness of the paper is that conclusions about prediction error might differ if dynamic learning were taken into account.

Reviewer #2 (Public Review):

The question of whether the neural mechanisms for reward and punishment learning are similar has been a constant debate over the last two decades. Numerous studies have shown that the midbrain dopamine neurons respond to both negative and salient stimuli, some of which can't be well accounted for by the classic RL theory (Delgado et al., 2007). Other research even proposed that aversive learning can be viewed as reward learning, by treating the omission of aversive stimuli as a negative PE (Seymour et al., 2004).

Although the current study took an axiomatic approach to search for the PE encoding brain regions, which I like, I have major concerns regarding their experimental design and hence the results they obtained. My biggest concern comes from the false description of their task to the participants. To increase the number of "valid" trials for data analysis, the instructed and actual probabilities were different. Under such a circumstance, testing axiom 2 seems completely artificial. How does the experimenter know that the participants truly believe that the 75% is more probable than, say, the 25% stimulation? The potential confusion of the subjects may explain why the SCR and relief report were rather flat across the instructed probability range, and some of the canonical PE encoding regions showed a rather mixed activity pattern across different probabilities. Also for the post-hoc selection criteria, why pick the larger SCR in the 75% compared to the 25% instructions? How would the results change if other criteria were used?

To test axiom 3, which was to compare the 100% stimulation to the 0% stimulation conditions, how did the actual shock delivery affect the fMRI contrast result? It would be more reasonable if this analysis could control for the shock delivery, which itself could contaminate the fMRI signal, with extra confound that subjects may engage certain behavioral strategies to "prepare for" the aversive outcome in the 100% stimulation condition. Therefore, I agree with the authors that this contrast may not be a good way to test axiom 3, not only because of the arguments made in the discussion but also the technical complexities involved in the contrast.

Comments on revised version:

I want to thank the authors for their thorough and comprehensive work in revising this manuscript. I agree with the authors that learning paradigms might not be a necessity when it comes to study the PE signals, but I don't particularly agree with some of the responses in the rebuttal letter ("Furthermore, conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted."). This is of course correct description for the conditioning paradigm, but the same can be said for an instructed design: the aversive outcome was either delivered or not. That being said, adopting the instructed design itself is legitimate in my opinion.

My main concern, which the authors spent quite some length in the rebuttal letter to address, still remains about the validity for different instructed probabilities. Although subjects were told that the trials were independent, the big difference between 75% and 25% would more than likely confuse the subjects, especially given that most of us would fall prey to the Gambler's fallacy (or the law of small numbers) to some degree. When the instruction and subjective experience collides, some form of inference or learning must have occurred, making the otherwise straightforward analysis more complex. Therefore, I believe that a more rigorous/quantitative learning modeling work can dramatically improve the validity of the results. Of course, I also realize how much extra work is needed to append the computational part but without it there is always a theoretical loophole in the current experimental design.

As the authors mentioned in the rebuttal letter, "selecting participants only if their anticipatory SCR monotonically increased with each increase in instructed probability 0% < 25% < 50% < 75% < 100%, N = 11 participants", only ~1/3 of the subjects actually showed strong evidence for the validity of the instructions. This further raises the question of whether the instructed design, due to the interference of false instruction and the dynamic learning among trials, is solid enough to test the hypothesis.

Reviewer #3 (Public Review):

Summary:

The authors conducted a human fMRI study investigating the omission of expected electrical shocks with varying probabilities. Participants were informed of the probability of shock and shock intensity trial-by-trial. The time point corresponding to the absence of the expected shock (with varying probability) was framed as a prediction error producing the cognitive state of relief/pleasure for the participant. fMRI activity in the VTA/SN and ventral putamen corresponded to the surprising omission of a high probability shock. Participants' subjective relief at having not been shocked correlated with activity in brain regions typically associated with reward-prediction errors. The overall conclusion of the manuscript was that the absence of an expected aversive outcome in human fMRI looks like a reward-prediction error seen in other studies that use positive outcomes.

Strengths:

Overall, I found this to be a well-written human neuroimaging study investigating an often overlooked question on the role of aversive prediction errors, and how they may differ from reward-related prediction errors. The paper is well-written and the fMRI methods seem mostly rigorous and solid.

Comments on revised version:

The authors were extremely responsive to the comments and provided a comprehensive rebuttal letter with a lot of detail to address the comments. The authors clarified their methodology, and rationale for their task design, which required some more explanation (at least for me) to understand. Some of the design elements were not clear to me in the original paper.

The initial framing for their study is still in the domain of learning. The paper starts off with a description of extinction as the prime example of when threat is omitted. This could lead a reader to think the paper would speak to the role of prediction errors in extinction learning processes. But this is not their goal, as they emphasize repeatedly in their rebuttal letter. The revision also now details how using a conditioning/extinction framework doesn't suit their experimental needs.

It is reasonable to develop a new task to answer their experimental questions. By no means is there a requirement to use a conditioning/extinction paradigm to address their questions. As they say, "it is not necessary to adopt a learning paradigm to study omission responses", which I agree with.

But the authors seem to want to have it both ways: they frame their paper around how important prediction errors are to extinction processes, but then go out of their way to say how they can't test their hypotheses with a learning paradigm.

Part of their argument that they needed to develop their own task "outside of a learning context" goes as follows:<br /> (1) "...conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted. As a result, the magnitude-related axiom cannot be tested."<br /> (2) "....in conditioning tasks people generally learn fast, rendering relatively few trials on which the prediction is violated. As a result, there is generally little intra-individual variability in the PE responses"<br /> (3) "...because of the relatively low signal to noise ratio in fMRI measures, fear extinction studies often pool across trials to compare omission-related activity between early and late extinction, which further reduces the necessary variability to properly evaluate the probability axiom"

These points seem to hinge on how tasks are "generally" constructed. However, there are many adaptations to learning tasks:<br /> (1) There is no rule that conditioning can't include different levels of aversive outcomes following different cues. In fact, their own design uses multiple cues that signal different intensities and probabilities. Saying that conditioning "generally only include one level of aversive outcome" is not an explanation for why "these paradigms are not tailored" for their research purposes. There are also several conditioning studies that have used different cues to signal different outcome probabilities. This is not uncommon, and in fact is what they use in their study, only with an instruction rather than through learning through experience, per se.<br /> (2) Conditioning/extinction doesn't have to occur fast. Just because people "generally learn fast" doesn't mean this has to be the case. Experiments can be designed to make learning more challenging or take longer (e.g., partial reinforcement). And there can be intra-individual differences in conditioning and extinction, especially if some cues have a lower probability of predicting the US than others. Again, because most conditioning tasks are usually constructed in a fairly simplistic manner doesn't negate the utility of learning paradigms to address PE-axioms.<br /> (3) Many studies have tracked trial-by-trial BOLD signal in learning studies (e.g., using parametric modulation). Again, just because other studies "often pool across trials" is not an explanation for these paradigms being ill-suited to study prediction errors. Indeed, most computational models used in fMRI are predicated on analyzing data at the trial level.

Again, the authors are free to develop their own task design that they think is best suited to address their experimental questions. For instance, if they truly believe that omission-related responses should be studied independent of updating. The question I'm still left puzzling is why the paper is so strongly framed around extinction (the word appears several times in the main body of the paper), which is a learning process, and yet the authors go out of their way to say that they can only test their hypotheses outside of a learning paradigm.

The authors did address other areas of concern, to varying extents. Some of these issues were somewhat glossed over in the rebuttal letter by noting them as limitations. For example, the issue with comparing 100% stimulation to 0% stimulation, when the shock contaminates the fMRI signal. This was noted as a limitation that should be addressed in future studies, bypassing the critical point.

Reviewer #1 (Public Review):

Summary:

The process of taste perception is significantly more intricate and complex in Lepidopteran insects. This investigation provides valuable insights into the role of Gustatory receptors and their dynamics in the sensation of sucrose, which serves as a crucial feeding cue for insects. The article highlights the differential sensitivity of Grs to sucrose and their involvement in feeding and insect behavior.

Strengths:

To support the notion of the differential specificity of Gr to sucrose, this study employed electrophysiology, ectopic expression of Grs in Xenopus, genome editing, and behavioral studies on insects. This investigation offers a fundamental understanding of the gustation process in lepidopteran insects and its regulation of feeding and other gustation-related physiological responses. This study holds significant importance in advancing our comprehension of lepidopteran insect biology, gustation, and feeding behavior.

Weaknesses:

While this manuscript demonstrates technical proficiency, there exists an opportunity for additional refinement to optimize comprehensibility for the intended audience. Several crucial sugars have been overlooked in the context of electrophysiology studies and should be incorporated. Furthermore, it is imperative to consider the potential off-target effects of Gr knock-out on other Gr expressions. This investigation focuses exclusively on Gr6 and Gr10, while neglecting a comprehensive narrative regarding other Grs involved in sucrose sensation.

Reviewer #2 (Public Review):

Summary:

To identify sugar receptors and assess the capacity of these genes the authors first set out to identify behavioral responses in larva and adult as well as physiological response. They used phylogenetics and gene expression (RNAseq) to identify candidates for sugar reception. Using first an in vitro oocyte system they assess the responses to distinct sugars. A subsequent genetic analysis shows that the Gr10 and Gr6 genes provide stage specific functions in sugar perception.

Strengths:

A clear strength of the manuscript is the breadth of techniques employed allowing a comprehensive study in a non-canonical model species.

Weaknesses:

There are no major weaknesses in the study for the current state of knowledge in this species. Since it is much basic work to establish a broader knowledge, context with other modalities remain unknown. It might have been possible to probe certain context known from the fruit fly, which would have strengthened the manuscript.

Reviewer #1 (Public Review):

Summary

This study identifies a family of solute transports in the enteric protist, Blastocystis, that may mediate the transport of glycolytic intermediates across the mitochondrial membrane. The study builds on previous observations suggesting that Blastocystis (and other Stramenopiles) are unusual in having a compartmentalized glycolytic pathway with enzymes involved in upper and lower glycolysis being located in the cytosol and mitochondria, respectively. In this study, the authors identified two putative Stamenopile metabolite transporters that are related to plant di/tricarboxylic acid transporters that might mediate the transport of glycolytic intermediates across the mitochondrial membrane. These GIC-transporters were localized to the Blastocystis mitochondrion using specific rabbit antibodies and shown to bind several glycolytic intermediates (including GAP, DHAP and PEP) based on thermostability shift assays. Direct evidence for transport activity was obtained by reconstituting native proteins in proteoliposomes and measuring uptake of 14C-malate or 35S-sulphate against unlabelled substrates. This assay showed that GIC-2 transported DHAP, GAP and PEP. However, significant transport activity was not observed for bGIC-2. Overall, the study provides strong, but not conclusive evidence that bGIC-2 is involved in transporting glycolytic intermediates across the inner membrane of the mitochondria, while the function of GIC-1 remains unclear, despite exhibiting the same metabolite binding properties as bGIC-2 n thermostability assays.

Strengths:

Overall, the findings are of interest in the context of understanding the diversity of core metabolic pathways in evolutionarily diverse eukaryotes, as well as the process by which cytosolic glycolysis evolved in most eukaryotes. The experiments are carefully performed and clearly described.

Weaknesses:

The main weakness of the study is the lack of direct evidence that either bGIC-1 and/or bGIC2 are active in vivo. While it is appreciated that the genetic tools for disrupting GIC genes in Blastocystis are limited/lacking, are there opportunities to ectopically express or delete these genes in other genetically tractable Stamenopiles, such as Phaeodactylum triconuteum?

The authors demonstrate that both bGIC-1 and bGIC-2 are targeted to the mitochondrion, based on immunofluorescence studies. However, the precise localization and topology of these carriers in the inner or outer membrane is not defined. The conclusions of the study would be strengthened if the authors could show that one/both transporters are present in the inner membrane using protease protection experiments following differential solubilization of the outer and inner mitochondrial membranes.

It is not clear why hetero-exchange reactions were not performed for bGIC-1 (only for bGIC-2).

In both their previous study (Bartulos et al (2018) and the current study, the authors have shown that Blastocystis express a TPI-GAPDH fusion protein which is located to the mitochondrion. The presence of the TPI domain in the mitochondrial matrix would obviate the need for bGIC-1/2 triose transporters and decrease their value as drug targets. It is noted that Blastocystis still retains some TPI activity in the cytosol, presumably due to expression of a second cytoplasmic isoform, which could account for the presence of the bGIC transporters. However, some discussion on the role of this mitochondrial TPI-GAPDG fusion protein in Blastocystis and other Stramenopiles would be useful.

The summary slide (Fig 7) in the revised manuscript no longer shows PEP being used as a countersolute for the import of G3P and DHAP. Although it complicates the story, the role of PEP as a counter solute should be shown for completeness and also to make sense of some of the statements in the discussion. In particular, as noted by the authors, mitochondrial PEP could be exported back to the cytsol and converted to pyruvate and/or lactate to generate ATP and NAD, although at the expense of ATP synthesis in the mitochondria.

Reviewer #2 (Public Review):

In this manuscript, the authors set out to identify transporters that must exist in Stramenophiles due to the fact that the second half of glycolysis appears to be conducted in the mitochondria. They hypothesize that a Stramenophile-specific clade of transporters related to the dicarboxylate carriers are likely the relevant family and then go on to test two proteins from Blastocystis due to the infectious disease relevance of this organism. They show rather convincingly that these two proteins are expressed and are localized to the mitochondria in the native organism. The purified proteins bind to glycolytic intermediates and one of them, GIC-2, transports several glycolytic intermediates in vitro. This is a very solid and well-executed study that clearly demonstrates that bCIC-2 can transport glycolytic intermediates.

(1) The major weakness is that the authors aren't able to show that this protein actually has this function in the native organism. This could be impossible due to the lack of genetic tools in Blastocystis, but it leaves us without absolute confidence that bGIC-2 is the important glycolytic intermediate mitochondrial transporter (or even that it has this function in vivo).

(2) My impression is that the authors under-emphasize the fact that the hDIC also binds (and is stabilized by) glycolytic intermediates (G3P and 3PG). In the opinion of this reviewer, this might change my interpretation about the uniqueness of the bGIC proteins. They act on additional glycolytic intermediates, but it's not unique.

Reviewer #3 (Public Review):

Summary:

Unlike most eukaryotes Blastocystis has a branched glycolysis pathway, which is split between the cytoplasm and the mitochondrial matrix. An outstanding question was how the glycolytic intermediates generated in the 'preparatory' phase' are transported into the mitochondrial matrix for the 'pay off' phase. Here, the authors use bioinformatic analysis to identify two candidate solute carrier genes, bGIC-1 and bGIC-2, and use biochemical and biophysical methods to characterise their substrate specificity and transport properties. The authors demonstrate that bGIC-2 can transport dihydroxyacetone phosphate, glyceraldehyde-3-phosphate, 3-phosphoglycerate and phosphoenolpyruvate, establishing this protein as the 'missing link' connecting the two split branches of glycolysis in this branch of single celled eukaryotes. The authors also present their data on bGIC-1, which suggests a role in anion transport and bOGC, which is a close functional homologue of the human oxoglutarate carrier (hOGC, SLC25A11) and human dicarboxylate carrier (hDIC, SLC25A10).

Strengths:

The results are presented in a clear and logical arrangement, which nicely leads the reader through the process of gene identification and subsequent ligand screening and functional reconstitution. The results are compelling and well supported - the thermal stabilisation data is supported by the exchange studies. Caveats, where apparent, are discussed and rational explanations given.

Weaknesses:

The study does not contain any significant weaknesses in my view. I would like to see the authors include the initial rate plots used in the main figures (possibly as insets), so we can observe the data points used for these calculations. It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

Reviewer #1 (Public Review):

Summary:

Previous work demonstrated a strong bias in the percept of an ambiguous Shepard tone as either ascending or descending in pitch, depending on the preceding contextual stimulus. The authors recorded human MEG and ferret A1 single-unit activity during presentation of stimuli identical to those used in the behavioral studies. They used multiple neural decoding methods to test if context-dependent neural responses to ambiguous stimulus replicated the behavioral results. Strikingly, a decoder trained to report stimulus pitch produced biases opposite to the perceptual reports. These biases could be explained robustly by a feed-forward adaptation model. Instead, a decoder that took into account direction selectivity of neurons in the population was able to replicate the change in perceptual bias.

Strengths:

This study explores an interesting and important link between neural activity and sensory percepts, and it demonstrates convincingly that traditional neural decoding models cannot explain percepts. Experimental design and data collection appear to have been executed carefully. Subsequent analysis and modeling appear rigorous. The conclusion that traditional decoding models cannot explain the contextual effects on percepts is quite strong.

Weaknesses:

Beyond the very convincing negative results, it is less clear exactly what the conclusion is or what readers should take away from this study. The presentation of the alternative, "direction aware" models is unclear, making it difficult to determine if they are presented as realistic possibilities or simply novel concepts. Does this study make predictions about how information from auditory cortex must be read out by downstream areas? There are several places where the thinking of the authors should be clarified, in particular, around how this idea of specialized readout of direction-selective neurons should be integrated with a broader understanding of auditory cortex.

Reviewer #2 (Public Review):

The authors aim to better understand the neural responses to Shepard tones in auditory cortex. This is an interesting question as Shepard tones can evoke an ambiguous pitch that is manipulated by a proceeding adapting stimulus, therefore it nicely disentangles pitch perception from simple stimulus acoustics.

The authors use a combination of computational modelling, ferret A1 recordings of single neurons, and human EEG measurements.

Their results provide new insights into neural correlates of these stimuli. However, the manuscript submitted is poorly organized, to the point where it is near impossible to review. We have provided Major Concerns below. We will only be able to understand and critique the manuscript fully after these issues have been addressed to improve the readability of the manuscript. Therefore, we have not yet reviewed the Discussion section.

Major concerns

Organization/presentation<br /> The manuscript is disorganized and therefore difficult to follow. The biggest issue is that in many figures, the figure subpanels often do not correspond to the legend, the main body, or both. Subpanels described in the text are missing in several cases. Many figure axes are unlabelled. There is an inconsistent style of in-text citation between figures and the main text. The manuscript contains typos and grammatical errors. My suggestions for edits below therefore should not be taken as an exhaustive list. I ask the authors to consider the following only a "first pass" review, and I will hopefully be able to think more deeply about the science in the second round of revisions after the manuscript is better organized.

Frequency and pitch<br /> The terms "frequency" and "pitch" seem to be used interchangeably at times, which can lead to major misconceptions in a manuscript on Shepard tones. It is possible that the authors confuse these concepts themselves at times (e.g. Fig 5), although this would be surprising given their expertise in this field. Please check through every use of "frequency" and "pitch" in this manuscript and make sure you are using the right term in the right place. In many places, "frequency" should actually be "fundamental frequency" to avoid misunderstanding.

Insufficient detail or lack of clarity in descriptions<br /> There seems to be insufficient information provided to evaluate parts of these analysis, most critically the final pitch-direction decoder (Fig 6), which is a major finding. Please clarify.

Reviewer #3 (Public Review):

Summary:

This is an elegant study investigating possible mechanisms underlying the hysteresis effect in the perception of perceptually ambiguous Shepard tones. The authors make a fairly convincing case that the adaptation of pitch direction sensitive cells in auditory cortex is likely responsible for this phenomenon.

Strengths:

The manuscript is overall well written. My only slight criticism is that, in places, particularly for non-expert readers, it might be helpful to work a little bit more methods detail into the results section, so readers don't have to work quite so hard jumping from results to methods and back.

The methods seem sound and the conclusions warranted and carefully stated. Overall I would rate the quality of this study as very high, and I do not have any major issues to raise.

Weaknesses:

I think this study is about as good as it can be with the current state of the art. Generally speaking, one has to bear in mind that this is an observational, rather than an interventional study, and therefore only able to identify plausible candidate mechanisms rather than making definitive identifications. However, the study nevertheless represents a significant advance over the current state of knowledge, and about as good as it can be with the techniques that are currently widely available.

Reviewer #1 (Public Review):

In this manuscript, by using simulation, in vitro and in vivo electrophysiology, and behavioral tests, Peng et al. nicely showed a new approach for the treatment of neuropathic pain in mice. They found that terahertz (THz) waves increased Kv conductance and decreased the frequency of action potentials in pyramidal neurons in the ACC region. Behaviorally, terahertz (THz) waves alleviated neuropathic pain in the mouse model. Overall, this is an interesting study. The experimental design is clear, the data is presented well, and the paper is well-written. I have a few suggestions.

(1) The authors provide strong theoretical and experimental evidence for the impact of voltage-gated potassium channels by terahertz wave frequency. However, the modulation of action potential also relies on non-voltage-dependent ion channels. For example, I noticed that the RMP was affected by THz application (Figure 3F) as well. As the RMP is largely regulated by the leak potassium channels (Tandem-pore potassium channels), I would suggest testing whether terahertz wave photons have also any impact on the Kleak channels as well.

(2) The activation curves of the Kv currents in Figure 2h seem to be not well-fitted. I would suggest testing a higher voltage (>100 mV) to collect more data to achieve a better fitting.

(3) In the part of behavior tests, the pain threshold increased after THz application and lasted within 60 mins. I suggest conducting prolonged tests to determine the end of the analgesic effect of terahertz waves.

(4) Regarding in vivo electrophysiological recordings, the post-HFTS recordings were acquired from a time window of up to 20 min. It seems that the HFTS effect lasted for minutes, but this was not tested in vitro where they looked at potassium currents. This long-lasting effect of HFTS is interesting. Can the authors discuss it and its possible mechanisms, or test it in slice electrophysiological experiments?

(5) How did the authors arrange the fiber for HFTS delivery and the electrode for in vivo multi-channel recordings? Providing a schematic illustration in Figure 4 would be useful.

(6) Some grammatical errors should be corrected.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Peng et al., reported that 36THz high-frequency terahertz stimulation (HFTS) can suppress the activity of pyramidal neurons by enhancing the conductance of voltage-gated potassium channel. The authors also demonstrated the effectiveness of using 36THz HFTS for treating neuropathic pain.

Strengths:

The manuscript is well written and the conclusions are supported by robust results. This study highlighted the potential of using 36THz HFTS for neuromodulation.

Weaknesses:

More characterization of HFTS is needed, so the readers can have a better assessment of the potential usage of HFTS in their own applications.

(1) It would be very helpful to estimate the volume of tissue that can be influenced by HFTS. It is not clear how 15 mins HFTS was chosen for this functional study. Does a longer time have a stronger effect? A better characterization of the relationship between the stimulus duration of HFTS and its beneficial effects would be very useful.

(2) How long does the behavioral effect last after 15 minutes of HFTS? Figure 5b only presents the behavioral effect for one hour, but the pain level is still effectively reduced at this time point. The behavioral measurement should last until pain sensitization drops back to pre-stim level.

(3) Although the manuscript only tested in ACC, it will also be useful to demonstrate the neural modulation effect on other brain regions. Would 36THz HFTS also robustly modulate activities in other brain regions? Or are different frequencies needed for different brain regions?

Reviewer #3 (Public Review):

Summary:

This manuscript by Peng et al. presents intriguing data indicating that high-frequency terahertz stimulation (HFTS) of the anterior cingulate cortex (ACC) can alleviate neuropathic pain behaviors in mice. Specifically, the investigators report that terahertz (THz) frequency stimulation widens the selectivity filter of potassium channels thereby increasing potassium conductance and leading to a reduction in the excitability of cortical neurons. In voltage clamp recordings from layer 5 ACC pyramidal neurons in acute brain slice, Peng et al. show that HFTS enhances K current while showing minimal effects on Na current. Current clamp recording analyses show that the spared nerve injury model of neuropathic pain decreases the current threshold for action potential (AP) generation and increases evoked AP frequency in layer 5 ACC pyramidal neurons, which is consistent with previous studies. Data are presented showing that ex-vivo treatment with HFTS in slice reduces these SNI-induced changes to excitability in layer 5 ACC pyramidal neurons. The authors also confirm that HFTS reduces the excitability of layer 5 ACC pyramidal neurons via in vivo multi-channel recordings from SNI mice. Lastly, the authors show that HFTS is effective at reducing mechanical allodynia in SNI using both the von Frey and Catwalk analyses. Overall, there is considerable enthusiasm for the findings presented in this manuscript given the need for non-pharmacological treatments for pain in the clinical setting.

Strengths:

The authors use a multifaceted approach that includes modeling, ex-vivo and in-vivo electrophysiological recordings, and behavioral analyses. Interpretation of the findings is consistent with the data presented. This preclinical work in mice provides new insight into the potential use of directed high-frequency stimulation to the cortex as a primary or adjunctive treatment for chronic pain.

Weaknesses:

There are a few concerns noted that if addressed, would significantly increase enthusiasm for the study.

(1) The left Na current trace for SNI + HFTS in Figure 2B looks to have a significant series resistance error. Time constants (tau) for the rate of activation and inactivation for Na currents would be informative.

(2) It is unclear why an unpaired t-test was performed for paired data in Figure 2. Also, statistical methods and values for non-significant data should be presented.

(3) It would seem logical to perform HFTS on ACC-Pyr neurons in acute slices from sham mice (i.e. Figure 3 scenario). These experiments would be informative given the data presented in Figure 4.

(4) As the data are presented in Figure 4g, it does not seem as if SNI significantly increased the mean firing rate for ACC-Pyr neurons, which is observed in the slice. The data were analyzed using a paired t-test within each group (sham and SNI), but there is no indication that statistical comparisons across groups were performed. If the argument is that HFTS can restore normal activity of ACC-Pyr neurons following SNI, this is a bit concerning if no significant increase in ACC-Pyr activity is observed in in-vivo recordings from SNI mice.

(5) The authors indicate that the effects of HFTS are due to changes in Kv1.2. However, they do not directly test this. A blocking peptide or dendrotoxin could be used in voltage clamp recordings to eliminate Kv1.2 current and then test if this eliminates the effects of HFTS. If K current is completely blocked in VC recordings then the authors can claim that currents they are recording are Kv1.1 or 1.2.

(6) The ACC is implicated in modulating the aversive aspect of pain. It would be interesting to know whether HFTS could induce conditioned place preference in SNI mice via negative reinforcement (i.e. alleviation of spontaneous pain due to the injury). This would strengthen the clinical relevance of using HFTS in treating pain.

Reviewer #1 (Public Review):

Summary:

In their paper, Hou and co-workers explored the use of a FRET sensor for endogenous g-sec activity in vivo in the mouse brain. They used AAV to deliver the sensor to the brain for neuron specific expression and applied NIR in cranial windows to assess FRET activity; optimizing as well an imaging and segmentation protocol. In brief they observe clustered g-sec activity in neighboring cells arguing for a cell non-autonomous regulation of endogenous g-sec activity in vivo.

Weaknesses:

Overall the authors provide a very limited data set and in fact only a proof of concept that their sensor can be applied in vivo. This is not really a research paper, but a technical note. With respect to their observation of clustered activity, the images do not convince me as they show only limited areas of interest: from these examples (for instance fig 5) one sees that merely all neurons in the field show variable activity and a clustering is not really evident from these examples. Even within a cluster, there is variability. With r values between 0.23 to .36, the correlation is not that striking. The authors herein do not control for expression levels of the sensor: for instance, can they show that in all neurons in the field, the sensor is equally expressed, but FRET activity is correlated in sets of neurons? Or are the FRET activities that are measured only in positively transduced neurons, while neighboring neurons are not expressing the sensor? Without such validation, it is difficult to make this conclusion.

Secondly, I am lacking some more physiological relevance for this observation. The experiments are performed in wild-type mice, but it would be more relevant to compare this with a fadPSEN1 KI or a PSEN1cKO model to investigate the contribution of a gain of toxic function or LOF to the claimed cell non-autonomous activations. Or what would be the outcome if the sensor was targeted to glial cells?

For this reviewer it is not clear what resolution they are measuring activity, at cellular or subcellular level? In other words are the intensity spots neuronal cell bodies? Given g-sec activity are in all endosomal compartments and at the cell surface, including in the synapse, does NIR imaging have the resolution to distinguish subcellular or surface localized activities? If cells 'communicate' g-sec activities, I would expect to see hot spots of activity at synapses between neurons: is this possible to assess with the current setup?

Without some more validation and physiological relevant studies, it remains a single observation and rather a technical note paper, instead of a true research paper.

Reviewer #2 (Public Review):

Summary:

The manuscript by Hou et al is a short technical report which details the potential use of a recently developed FRET based biosensor for gamma-secretase activity (Houser et al 2020) for in vivo imaging in the mouse brain. Gamma-secretase plays a crucial role in Alzheimer disease pathology and therefore developing methodologies for precise in vivo measurements would be highly valuable to better understand AD pathophysiology in animal models.

The current version of the sensor utilizes a pair of far-red fluorescent proteins fused to a substrate of the enzyme. Using live imaging, it was previously demonstrated it is possible to monitor gamma-secretase activity in cultured cells. Notably, this is a variant of a biosensor that was previously described using CFP-YFP variants FRET pair (Maesako et al, iScience. 2020). The main claim and hypothesis for the MS is that IR excitation and emission has considerable advantages in terms of depth of penetration, as well as reduction in autofluorescence. These properties would make this approach potentially suitable to monitor cellular level dynamics of Gama-secretase in vivo.

The authors use confocal microscopy and show it is possible to detect fluorescence from single cortical cells. The paper described in detail technical information regarding imaging and analysis. The data presented in figures 5-8 details analysis of FRET ratio (FR) measurements within populations of cells. The authors claim it is possible to obtain reliable measurements at the level of individual cells. They compare the FR values across cells and mice and find a spatial correlation among neighboring cells. This is compared with data obtained after inhibition of endogenous gamma-secretase activity, which abolishes this correlation.

Strengths:

The authors describe in detail their experimental design and analysis for in vivo imaging of the reporter. The idea of using a far-red FRET sensor for in vivo imaging is novel and potentially useful to circumvent many of the pitfalls associated with intensity-based FRET imaging in complex biological environments (such as autofluorescence and scattering).

Weaknesses:

There are several critical points regarding validation of this approach and concerns with the data presented that must be addressed:

(1) Regarding the variability and spatial correlation- the dynamic range of the sensor previously reported in vitro is in the range of 20-30% change (Houser et al 2020) whereas the range of FR detected in vivo is between cells is significantly larger (Fig. 3). This raises considerable doubts for specific detection of cellular activity (see point 3).<br /> (2) One direct way to test the dynamic range of the sensor in vivo, is to increase or decrease endogenous gamma-secretase activity and to ensure this experimental design allows to accurately monitor gamma-secretase activity. In the previous characterization of the reporter (Hauser et al 2020), DAPT application and inhibition of gamma-secretase activity results in increased FR (Figures 2 and 3 of Houser et al). This is in agreement with the design of the biosensor, since FR should be inversely correlated with enzymatic activity. Here, while the authors repeat the same manipulation and apply DAPT to block gamma-secretase activity, it seems to induce the opposite effect and reduces FR (comparing figures 8 with figures 5,6,7). First, there is no quantification comparing FR with and without DAPT. Moreover, it is possible to conduct this experiment in the same animals, meaning comparing FR before and after DAPT in the same mouse and cell populations. This point is absolutely critical- if indeed FR is reduced following DAPT application, this needs to be explained since this contradicts the basic design and interpretation of the biosensor.<br /> (3) For further validation, I would suggest including in vivo measurements with a sensor version with no biological activity as a negative control, for example, a mutation that prevents enzymatic cleavage and FRET changes. This should be used to showcase instrumental variability and would help to validate the variability of FR is indeed biological in origin. This would significantly strengthen the claims regarding spatial correlation within population of cells.<br /> (4) In general, confocal microcopy is not ideal for in vivo imaging. Although the authors demonstrate data collected using IR imaging increases penetration depth, out of focus fluorescence is still evident (Figure 4). Many previous papers have primarily used FLIM based analysis in combination with 2p microscopy for in vivo FRET imaging (Some examples: Ma et al, Neuron, 2018; Massengil et al, Nature methods, 2022; DIaz-Garcia et al, Cell Metabolism, 2017; Laviv et al, Neuron, 2020). This technique does not rely on absolute photon number and therefore has several advantage sin terms of quantification of FRET signals in vivo.<br /> It is therefore likely that use of previously developed sensors of gamma-secretase with conventional FRET pairs, might be better suited for in vivo imaging. This point should be at least discussed as an alternative.

Reviewer #3 (Public Review):

This paper builds on the authors' original development of a near infrared (NIR) FRET sensor by reporting in vivo real-time measurements for gamma-secretase activity in the mouse cortex. The in vivo application of the sensor using state of the art techniques is supported by a clear description and straightforward data, and the project represents significant progress because so few biosensors work in vivo. Notably, the NIR biosensor is detectable to ~ 100 µm depth in the cortex. A minor limitation is that this sensor has a relatively modest ΔF as reported in Houser et al, which is an additional challenge for its use in vivo. Thus, the data is fully dependent on post-capture processing and computational analyses. This can unintentionally introduce biases but is not an insurmountable issue with the proper controls that the authors have performed here.

The observation of gamma-secretase signaling that spreads across cells is potentially quite interesting, but it can be better supported. An alternative interpretation is that there exist pre-formed and clustered hubs of high gamma-secretase activity, and that DAPT has stochastic or differential accessibility to cells within the cluster. This could be resolved by an experiment of induction, for example, if gamma-secretase activity is induced or activated at a specific locale and there was observed coordinated spreading to neighboring neurons with their sensor.

Furthermore, to rule out the possibility that uneven viral transduction was not simply responsible for the observed clustering, it would be helpful to see an analysis of 670nm fluorescence alone.

Reviewer #1 (Public Review):

Summary:

Zhang et al. demonstrate that CD4+ single positive (SP) thymocytes, CD4+ recent thymic emigrants (RTE), and CD4+ T naive (Tn) cells from Cd11c-p28-flox mice, which lack IL-27p28 selectively in Cd11c+ cells, exhibit a hyper-Th1 phenotype instead of the expected hyper Th2 phenotype. Using IL-27R-deficient mice, the authors confirm that this hyper-Th1 phenotype is due to IL-27 signaling via IL-27R, rather than the effects of monomeric IL-27p28. They also crossed Cd11c-p28-flox mice with autoimmune-prone Aire-deficient mice and showed that both T cell responses and tissue pathology are enhanced, suggesting that SP, RTE, and Tn cells from Cd11c-p28-flox mice are poised to become Th1 cells in response to self-antigens. Regarding mechanism, the authors demonstrate that SP, RTE, and Tn cells from Cd11c-p28-flox mice have reduced DNA methylation at the IFN-g and Tbx21 loci, indicating 'de-repression', along with enhanced histone tri-methylation at H3K4, indicating a 'permissive' transcriptional state. They also find evidence for enhanced STAT1 activity, which is relevant given the well-established role of STAT1 in promoting Th1 responses, and surprising given IL-27 is a potent STAT1 activator. This latter finding suggests that the Th1-inhibiting property of thymic IL-27 may not be due to direct effects on the T cells themselves.

Strengths:

Overall the data presented are high quality and the manuscript is well-reasoned and composed. The basic finding - that thymic IL-27 production limits the Th1 potential of SP, RTE, and Tn cells - is both unexpected and well described.

Weaknesses:

A credible mechanistic explanation, cellular or molecular, is lacking. The authors convincingly affirm the hyper-Th1 phenotype at epigenetic level but it remains unclear whether the observed changes reflect the capacity of IL-27 to directly elicit epigenetic remodeling in developing thymocytes or knock-on effects from other cell types which, in turn, elicit the epigenetic changes (presumably via cytokines). The authors propose that increased STAT1 activity is a driving force for the epigenetic changes and resultant hyper-Th1 phenotype. That conclusion is logical given the data at hand but the alternative hypothesis - that the hyper-STAT1 response is just a downstream consequence of the hyper-Th1 phenotype - remains equally likely. Thus, while the discovery of a new anti-inflammatory function for IL-27 within the thymus is compelling, further mechanistic studies are needed to advance the finding beyond phenomenology.

Reviewer #2 (Public Review):

Summary:

Naïve CD4 T cells in CD11c-Cre p28-floxed mice express highly elevated levels of proinflammatory IFNg and the transcription factor T-bet. This phenotype turned out to be imposed by thymic dendritic cells (DCs) during CD4SP T cell development in the thymus [PMID: 23175475]. The current study affirms these observations, first, by developmentally mapping the IFNg dysregulation to newly generated thymic CD4SP cells [PMID: 23175475], second, by demonstrating increased STAT1 activation being associated with increased T-bet expression in CD11c-Cre p28-floxed CD4 T cells [PMID: 36109504], and lastly, by confirming IL-27 as the key cytokine in this process [PMID: 27469302]. The authors further demonstrate that such dysregulated cytokine expression is specific to the Th1 cytokine IFNg, without affecting the expression of the Th2 cytokine IL-4, thus proposing a role for thymic DC-derived p28 in shaping the cytokine response of newly generated CD4 helper T cells. Mechanistically, CD4SP cells of CD11c-Cre p28-floxed mice were found to display epigenetic changes in the Ifng and Tbx21 gene loci that were consistent with increased transcriptional activities of IFNg and T-bet mRNA expression. Moreover, in autoimmune Aire-deficiency settings, CD11c-Cre p28-floxed CD4 T cells still expressed significantly increased amounts of IFNg, exacerbating the autoimmune response and disease severity. Based on these results, the investigators propose a model where thymic DC-derived IL-27 is necessary to suppress IFNg expression by CD4SP cells and thus would impose a Th2-skewed predisposition of newly generated CD4 T cells in the thymus, potentially relevant in autoimmunity.

Strengths:

Experiments are well-designed and executed. The conclusions are convincing and supported by the experimental results.

Weaknesses:

The premise of the current study is confusing as it tries to use the CD11c-p28 floxed mouse model to explain the Th2-prone immune profile of newly generated CD4SP thymocytes. Instead, it would be more helpful to (1) give full credit to the original study which already described the proinflammatory IFNg+ phenotype of CD4 T cells in CD11c-p28 floxed mice to be mediated by thymic dendritic cells [PMID: 23175475], and then, (2) build on that to explain that this study is aimed to understand the molecular basis of the original finding.

In its essence, this study mostly rediscovers and reaffirms previously reported findings, but with different tools. While the mapping of epigenetic changes in the IFNg and T-bet gene loci and the STAT1 gene signature in CD4SP cells are interesting, these are expected results, and they only reaffirm what would be assumed from the literature. Thus, there is only incremental gain in new insights and information on the role of DC-derived IL-27 in driving the Th1 phenotype of CD4SP cells in CD11c-p28 floxed mice.

Altogether, the major issues of this study remain unresolved:

(1) It is still unclear why the p28-deficiency in thymic dendritic cells would result in increased STAT1 activation in CD4SP cells. Based on their in vitro experiments with blocking anti-IFNg antibodies, the authors conclude that it is unlikely that the constitutive activation of STAT1 would be a secondary effect due to autocrine IFNg production by CD4SP cells. However, this possibility should be further tested with in vivo models, such as Ifng-deficient CD11c-p28 floxed mice. Alternatively, is this an indirect effect by other IFNg producers in the thymus, such as iNKT cells? It is necessary to explain what drives the STAT1 activation in CD11c-p28 floxed CD4SP cells in the first place.

(2) It is also unclear whether CD4SP cells are the direct targets of IL-27 p28. The cell-intrinsic effects of IL-27 p28 signaling in CD4SP cells should be assessed and demonstrated, ideally by CD4SP-specific deletion of IL-27Ra, or by establishing bone marrow chimeras of IL-27Ra germline KO mice.

Reviewer #1 (Public Review):

Summary:

Inflammatory T cells have been recognized to play an important role in human COPD lung tissue and animal models of emphysema. The authors have previously identified that Th17 cells regulate chronic inflammatory diseases, including in mice exposed to smoke or nanoparticulate carbon black (nCB). Here, the authors interrogate the role of Tc17 cells using similar mouse models. Investigating let-7 miRNA, which induces antigen-presenting cell activation and T cell-mediated Th17a inflammation, they show that the master regulator of Tc17/Th17 differentiation, RAR-related orphan receptor gamma t (RORγt), is a direct target of let-7 miRNA in T cells. Because RORγt expression is elevated in COPD patients and in mouse models of COPD, the authors generate a Let-7 overexpressing mouse in T cells and reduce RORγt expression and Th17 and Tc17 cell recruitment in nCB-exposed mice.

Strengths:

The authors use a previously published RNA-seq dataset (GSE57148) from lungs of control and COPD subjects to explore the involvement of Let-7 in emphysema. They further evaluate Let-7a expression by qPCR in lung tissue samples of smokers with emphysema and non-emphysema controls. Moreover, expression of Let-7a, Let-7b, Let-7d, and Let-7f in purified CD4+ T cells were inversely correlated with emphysema severity lungs. Similar findings were found in their mouse models (CS or nCB) in both lung tissue and isolated lung CD4+ and CD8+ T cells, with reduced let-7afd and let-7bc2 expression.

Using mice harboring a conditional deletion of the let-7bc2 cluster in all T cells (let-7bc2LOF) derived from the CD4+CD8+ double-positive stage, the authors show enhanced emphysema in nCB- or CS-exposed mice with enhanced recruitment of macrophages and neutrophils to the lung. While CD8+IL17a+ Tc17 cells and CD4+ IL17a+ Th17 cells were increased in nCB-exposed control animals, only let-7bc2LOF mice showed an increase in CD8+IL17a+ Tc17 cells. Further, unexposed let-7bc2LOF and let-7afdLOF mice expressed greater RORγt expression in both CD8+ and CD4+ T cells.

Generating a let-7 gain of function mouse with overexpression of let-7g in thymic double-positive-derived T cells, protein levels of RORγt were suppressed in CD8+ and CD4+ T cells of let-7GOF mice relative to controls. Let-7GOF mice treated with nCB showed similar lung alveolar distension as controls suggesting that increased let-7 expression does not protect the lung from emphysema. However, let-7GOF mice showed reduced lung Tc17 and Th17 cell populations and were resistant to the induction of RORγt after nCB exposure.

Weaknesses:

Limited data is shown on the let-7afdLOF mice. Does this mouse respond similarly to nCB as the let-7bc2LOF.<br /> Because the authors validate their findings from a previously published RNA-seq dataset in subjects with and without emphysema, the authors should include patient demographics from the data presented in Figure 1C-D.<br /> To validate their mouse models, the absence of Let-7 or enhanced Let-7 expression needs to be shown in isolated T cells from exposed mice.<br /> In Figure 3, the authors are missing the unexposed let-7bc2LOF group from all panels. This is again an issue in Figure 6 with the let-7GOF.<br /> Because the GOF mouse enhances Let-7g within T cells, the importance of Let-7g should be determined in human subjects. Why did the authors choose to overexpress Let-7g, the rationale is not clear.<br /> The purity of the CD4+ and CD8+ T cells is not shown and the full gating strategy should be included.<br /> The authors indicate that Tc17 and Th17 T cells were reduced in the GOF mouse, it remains unclear if macrophage or neutrophil recruitment is altered in GOF mice.

Reviewer #2 (Public Review):

Summary:

This valuable study characterizes the requirement for individual let-7 clusters to limit the generation of IL-17 producing CD8 T cells and the severity of emphysema in mouse models. Mature let-7 family miRNAs originate from multiple loci, several of which have been reported and/or are reported here to be downregulated in emphysematous lung tissue and/or lung T cells. The results provided are convincing but incomplete, as the let-7 cluster with the most convincing effects on T cell cytokine production is not tested for effects on disease pathogenesis.

Let-7 family miRNAs are largely redundant in function and originate from multiple genomic loci ("clusters"). Erice et al demonstrate that two individual clusters (let7afd and let7bc2) in mice regulate the generation of IL-17 producing CD8 T cells in vitro and in vivo in a model of emphysema. These cells also express higher levels of the IL-17-inducing transcription factor RORgt, encoded by Rorc, which the authors demonstrate to be a direct target of let-7. Since multiple let-7 family miRNAs are downregulated in T cells and lung tissue in emphysema, these data support a model in which reduced let-7 allows increased IL-17 production by T cells, contributing to disease pathogenesis.

Strengths:

The inclusion of miRNA and pri-miRNA expression data from sorted human lung T cells as well as mouse T cells from an emphysema model is a strength.

The study includes complementary loss of function and gain of function experimental systems to test the effect of altered let-7 function, though it should be noted that these involved different let-7 family members and did not yield simple, complementary results for all experimental outcomes.

The most important finding is that deletion of just one let-7 cluster ("Let7bc2") is sufficient to exacerbate emphysema in the nCB and CS models.

Weaknesses:

The human miRNA expression data that motivate functional analyses used sorted CD4+ T cells. The authors note that prior work on let-7 showed that it regulates Th17 (CD4) responses, yet this study's functional analyses are all focused on Tc17 (CD8) T cells. Data in this paper show that Tc17 cells are far less numerous than Th17 cells in the nCB and CS models of emphysema.

Compared with Let7bc2 deletion, Let7afd deletion had a much larger effect on IL17 production by CD8 T cells in vitro, and it also had a larger effect on RORgt expression in untreated mice in vivo, especially in the lung. In the revised manuscript, the authors show that let7afdLOF mice have normal numbers of CD4 and CD8 T cells in the thymus and peripheral lymphoid organs and do not exhibit lung histopathology or inflammatory changes at baseline at least up to 6 months of age. As such, they are set up perfectly to test the requirement for Let7afd in the nCB and/or CS models. These experiments would add strength to the core novelty of this work - demonstration of the functional importance of individual let-7 clusters.

The authors could do more to explain the complexity of the let7 miRNA family and the genomic clusters examined in this study. In particular, it would help to know the relationship between mouse Let7bc2 and corresponding human Let7 clusters. It would also be very helpful to know the relative expression of each mature let-7 family member in Tc17 cells. Are mature miRNAs derived from the Let7afd cluster more or less abundant?

The provided evidence for the effect of Let7GOF has an important caveat that came to light during review. Let7g overexpression caused a marked reduction in Rorgt expression in T cells at baseline and in the setting of nCB challenge, and it reduced the frequency of IL17+ producing CD8 T cells in the lung to baseline levels. Yet there was no change in the MLI measurement of histopathology. However, the responses in the experiment shown in Fig. 6C-D are quite muted compared to those shown in Figure 2. In the response to reviewers, the authors speculate that an anti-inflammatory of doxycycline, required for induction of Let7g in this model, "could account for the differences in the magnitude of emphysemic response".

Although RORgt is a great candidate to have direct effects on IL-17 expression, the mechanistic understanding of let-7 action on T cell differentiation and cytokine production is limited to this single target. As noted in the discussion, others have identified cytokine receptor targets that may play a role, but it is also likely others among the many targets of let-7 also contribute.

Reviewer #1 (Public Review):

Olszyński and colleagues present data showing variability from canonical "aversive calls", typically described as long 22 kHz calls rodents emit in aversive situations. Similarly long but higher-frequency (44 kHz) calls are presented as a distinct call type, including analyses both of their acoustic properties and animals' responses to hearing playback of these calls. While this work adds an intriguing and important reminder, namely that animal behavior is often more variable and complex than perhaps we would like it to be, there is some caution warranted in the interpretation of these data.

The exclusive use of males is a major concern lacking adequate justification and should be disclosed in the title and abstract to ensure readers are aware of this limitation. With several reported sex differences in rat vocal behaviors this means caution should be exercised when generalizing from these findings. The occurrence of an estrus cycle in typical female rats is not justification for their exclusion. Note also that male rodents experience great variability in hormonal states as well, distinguishing between individuals and within individuals across time. The study of endocrinological influences on behavior can be separated from the study of said behavior itself, across all sexes. Similarly, concerns about needing to increase the number of animals when including all sexes are usually unwarranted (see Shansky [2019] and Phillips et al. [2023]).

Regarding the analysis where calls were sorted using DBSCAN based on peak frequency and duration, my comment on the originally reviewed version stands. It seems that the calls are sorted by an (unbiased) algorithm into categories based on their frequency and duration, and because 44kHz calls differ by definition on frequency and duration the fact that the algorithm sorts them as a distinct category is not evidence that they are "new calls [that] form a separate, distinct group". I appreciate that the authors have softened their language regarding the novelty and distinctness of these calls, but the manuscript contains several instances where claims of novelty and specificity (e.g. the subtitle on line 193) is emphasized beyond what the data justifies.

The behavioral response to call playback is intriguing, although again more in line with the hypothesis that these are not a distinct type of call but merely represent expected variation in vocalization parameters. Across the board animals respond rather similarly to hearing 22 kHz calls as they do to hearing 44 kHz calls, with occasional shifts of 44 kHz call responses to an intermediate between appetitive and aversive calls. This does raise interesting questions about how, ethologically, animals may interpret such variation and integrate this interpretation in their responses. However, the categorical approach employed here does not address these questions fully.

I appreciate the amendment in discussing the idea of arousal being the key determinant for the increased emission of 44kHz, and the addition of other factors. Some of the items in this list, such as annoyance/anger and disgust/boredom, don't really seem to fit the data. I'm not sure I find the idea that rats become annoyed or disgusted during fear conditioning to be a particularly compelling argument. As such the list appears to be a collection of emotion-related words, with unclear potential associations with the 44kHz calls.

Later in the Discussion the authors argue that the 44kHz aversive calls signal an increased intensity of a negative valence emotional state. It is not clear how the presented arguments actually support this. For example, what does the elongation of fear conditioning to 10 trials have to do with increased negative emotionality? Is there data supporting this relationship between duration and emotion, outside anthropomorphism? Each of the 6 arguments presented seems quite distant from being able to support this conclusion.

In sum, rather than describing the 44kHz long calls as a new call type, it may be more accurate to say that sometimes aversive calls can occur at frequencies above 22 kHz. Individual and situational variability in vocalization parameters seems to be expected, much more so than all members of a species strictly adhering to extremely non-variable behavioral outputs.

Reviewer #1 (Public Review):

Klupt, Fam, Zhang, Hang and colleagues present a novel study examining the function of sagA in E. faecium, including impacts on growth, peptidoglycan cleavage, cell separation, antibiotic sensitivity, NOD2 activation and modulation of cancer immunotherapy. This manuscript represents a substantial advance over their prior work, where they found that sagA-expressing strains (including naturally-expressing strains and versions of non-expressing strains forced to overexpress sagA) were superior in activating NOD2 and improving cancer immunotherapy. Prior to the current study, an examination of sagA mutant E. faecium was not possible and sagA was thought to be an essential gene.

The study is overall very carefully performed with appropriate controls and experimental checks, including confirmation of similar densities of ΔsagA throughout. Results are overall interpreted cautiously and appropriately.