Reviewer #2 (Public Review):

Identifying and quantifying the tumor specific T cell response continues to be an area of great interest in the context of cancer immunotherapy. The presence of sets of T cells with similar sequence (clusters) is becoming increasingly accepted as a key feature of the antigen-specific T cell response. In this study the authors explore this hypothesis in the context of melanoma. The study uses the bioinformatics tool ALICE which identifies TCR clusters, taking into account "background" clustering which might be expected by chance.

The study reports three key findings: 1. the number of clusters in TILs increases following anti-PD1 immunotherapy. 2. the number of clusters is enriched in the CD39+PD1+ positive TIL fraction. 3. the number of clusters can be used as an indication of the success of in vitro expansions of tumor specific T cells.<br /> Overall, the data provided are convincing, although the number of samples studied is small. The explanation of the figures is occasionally hard to follow, which in its current form lessens the impact of the paper. But the study will certainly be of interest to all those interested in characterising the tumor-specific T cell response in humans, and could form the basis for further more extensive studies to validate the results, and apply them to well-characterised clinical cohorts.

Reviewer #3 (Public Review):

Goncharov et al provide a clear example of the importance of immune receptor repertoire profiling to identify responding tumor-specific T cells. They show that a previously proposed algorithm (ALICE) can be a useful tool to characterize tumor-specific T cell enrichment in grafts and to optimize TIL cultures. These results have the potential to accelerate clinical development of adoptive T cell transfer techniques and are of interest for the community.

The paper is concise and to the point. The conclusions are well supported by the data and the analyses. Some additional explanations regarding the computational analysis can help readability and clarity.

Reviewer #1 (Public Review):

The authors investigate a clustering-based method to find reactive T cells based on their TCR (T cell receptor) sequences following ACT (Adoptive T cell transfer). This method, which was previously implemented as ALICE, find reactive T cell clones in samples by looking for overrepresented clusters of T cells with similar TCR sequences.

By applying the method on published data from Melanoma patients, the authors show an increase in the number of clusters following anti-PD1 immunotherapy. They also find in those clusters many TCRs known to be reactive to melanoma antigens. Clusters are also found in CD39+PD1+ activated T cells.

Overall, the paper shows strong indications that clusters are indeed enriched for tumor reactive TCRs. The overall number of reactive TCRs in the clusters, on the other hand, is not known (and hard to estimate). Specifically, it is not clear how many of the TCRs in the clusters found using this method are indeed reactive against the tumor cells. However, the ones found are excellent candidates for functional assays that determine reactivity. The functional analysis presented in the paper, which involved sorting on CD137, doesn't link the TCRs in the clusters with activation very strongly.

The paper makes a strong case to the usefulness of cluster-based analysis for measuring tumor related response and finding possible reactive TCRs. However, stronger functional validation methods are needed to assess the quality of the TCRs found in the clusters. Further work would investigate this relation in more depth, mainly to pinpoint and improve the sensitivity and accuracy of the inferred tumor related clones.

Reviewer #1 (Public Review):

In this manuscript, the authors introduce a new piece of software, BehaviorDEPOT, that aims to serve as an open source classifier in service of standard lab-based behavioral assays. The key arguments the authors make are that 1) the open source code allows for freely available access, 2) the code doesn't require any coding knowledge to build new classifiers, 3) it is generalizable to other behaviors than freezing and other species (although this latter point is not shown), 4) that it uses posture-based tracking that allows for higher resolution than centroid-based methods, and 5) that it is possible to isolate features used in the classifiers. While these aims are laudable, and the software is indeed relatively easy to use, I am not convinced that the method represents a large conceptual advance or would be highly used outside the rodent freezing community.

Major points:

1) I'm not convinced over one of the key arguments the authors make - that the limb tracking produces qualitatively/quantitatively better results than centroid/orientation tracking alone for the tasks they measure. For example, angular velocities could be used to identify head movements. It would be good to test this with their data (could you build a classifier using only the position/velocity/angular velocities of the main axis of the body?

2) This brings me to the point that the previous state-of-the-art open-source methodology, JAABA, is barely mentioned, and I think that a more direct comparison is warranted, especially since this method has been widely used/cited and is also aimed at a not-coding audience.

3) Remaining on JAABA: while the authors' classification approach appeared to depend mostly on a relatively small number of features, JAABA uses boosting to build a very good classifier out of many not-so-good classifiers. This approach is well-worn in machine learning and has been used to good effect in high-throughput behavioral data. I would like the authors to comment on why they decided on the classification strategy they have.

4) I would also like more details on the classifiers the authors used. There is some detail in the main text, but a specific section in the Methods section is warranted, I believe, for transparency. The same goes for all of the DLC post-processing steps.

5) It would be good for the authors to compare the Inter-Rater Module to the methods described in the MARS paper (reference 12 here).

6) More quantitative discussion about the effect of tracking errors on the classifier would be ideal. No tracking is perfect, so an end-user will need to know "how good" they need to get the tracking to get the results presented here.

Reviewer #2 (Public Review):

BehaviorDEPOT is a Matlab-based user interface aimed at helping users interact with animal pose data without significant coding experience. It is composed of several tools for analysis of animal tracking data, as well as a data collection module that can interface via Arduino to control experimental hardware. The data analysis tools are designed for post-processing of DeepLabCut pose estimates and manual pose annotations, and includes four modules: 1) a Data Exploration module for visualizing spatiotemporal features computed from animal pose (such as velocity and acceleration), 2) a Classifier Optimization module for creating hand-fit classifiers to detect behaviors by applying windowing to spatiotemporal features, 3) a Validation module for evaluating performance of classifiers, and 4) an Inter-Rater Agreement module for comparing annotations by different individuals.

A strength of BehaviorDEPOT is its combination of many broadly useful data visualization and evaluation modules within a single interface. The four experimental use cases in the paper nicely showcase various features of the tool, working the user from the simplest example (detecting optogenetically induced freezing) to a more sophisticated decision-making example in which BehaviorDEPOT is used to segment behavioral recordings into trials, and within trials to count head turns per trial to detect deliberative behavior (vicarious trial and error, or VTE.) The authors also demonstrate the application of their software using several different animal pose formats (including from 4 to 9 tracked body parts) from multiple camera types and framerates.

One point that confused me when reading the paper was whether BehaviorDEPOT was using a single, fixed freezing classifier, or whether the freezing classifier was being tuned to each new setting (the latter is the case.) The abstract, introduction, and "Development of the BehaviorDEPOT Freezing Classifier" sections all make the freezing classifier sound like a fixed object that can be run "out-of-the-box" on any dataset. However, the subsequent "Analysis Module" section says it implements "hard-coded classifiers with adjustable parameters", which makes it clear that the freezing classifier is not a fixed object, but rather it has a set of parameters that can (must?) be tuned by the user to achieve desired performance. It is important to note that the freezing classifier performances reported in the paper should therefore be read with the understanding that these values are specific to the particular parameter configuration found (rather than reflecting performance a user could get out of the box.)

This points to a central component of BehaviorDEPOT's design that makes its classifiers different from those produced by previously published behavior detection software such as JAABA or SimBA. So far as I can tell, BehaviorDEPOT includes no automated classifier fitting, instead relying on the users to come up with which features to use and which thresholds to assign to those features. Given that the classifier optimization module still requires manual annotations (to calculate classifier performance, Fig 7A), I'm unsure whether hand selection of features offers any kind of advantage over a standard supervised classifier training approach. That doesn't mean an advantage doesn't exist- maybe the hand-fit classifiers require less annotation data than a supervised classifier, or maybe humans are better at picking "appropriate" features based on their understanding of the behavior they want to study.

There is something to be said for helping users hand-create behavior classifiers: it's easier to interpret the output of those classifiers, and they could prove easier to fine-tune to fix performance when given out-of-sample data. Still, I think it's a major shortcoming that BehaviorDEPOT only allows users to use up to two parameters to create behavior classifiers, and cannot create thresholds that depend on linear or nonlinear combinations of parameters (eg, Figure 6D indicates that the best classifier would take a weighted sum of head velocity and change in head angle.) Because of these limitations on classifier complexity, I worry that it will be difficult to use BehaviorDEPOT to detect many more complex behaviors.

Finally, I have some concerns about how performance of classifiers is reported. For example, the authors describe "validation" set of videos used to assess freezing classifier performance, but they are very vague about the detector was trained in the first place, stating "we empirically determined that thresholding the velocity of a weighted average of 3-6 body parts ... and the angle of head movements produced the best-performing freezing classifier." What videos were used to come to this conclusion? It is imperative that when performance values are reported in the paper, they are calculated on a separate set of validation videos, ideally from different animals, that were *never referenced* while setting the parameters of the classifier. Otherwise, there is a substantial risk of overfitting, leading to overestimation of classifier performance. Similarly, Figure 7 shows the manual fitting of classifiers to rat and mouse data; the fitting process in 7A is shown to include updating parameters and recalculating performance iteratively. This approach is fine, however I want to confirm that the classifier performances in panels 7F-G were computed on videos not used during fitting.

Overall, I like the user-friendly interface of this software, its interaction with experimental hardware, and its support for hand-crafted behavior classification. However, I feel that more work could be done to support incorporation of additional features and feature combinations as classifier input- it would be great if BehaviorDEPOT could at least partially automate the classifier fitting process, eg by automatically fitting thresholds to user-selected features, or by suggesting features that are most correlated with a user's provided annotations. Finally, the validation of classifier performance should be addressed.

Reviewer #3 (Public Review):

There is a need for standardized pipelines that allow for repeatable robust analysis of behavioral data, and this toolkit provides several helpful modules that researchers will find useful. There are, however, several weaknesses in the current presentation of this work.

It is unclear what the major advance is that sets BehaviorDEPOT apart from other tools mentioned (ezTrack, JAABA, SimBA, MARS, DeepEthogram, etc). A comparison against other commonly used classifiers would speak to the motivation for BehaviorDEPOT - especially if this software is simpler to use and equally efficient at classification. While the idea might be that joint-level tracking should simplify the classification process, the number of markers used in some of the examples is limited to small regions on the body and might not justify using these markers as input data. The functionality of the tool seems to rely on a single type of input data (a small number of keypoints labeled using DeepLabCut) and throws away a large amount of information in the keypoint labeling step. If the main goal is to build a robust freezing detector then why not incorporate image data (particularly when the best set of key points does not include any limb markers)? Are the thresholds chosen for smoothing and convolution adjusted based on agreement to a user-defined behavior? Jitter is mentioned as a limiting factor in freezing classifier performance - does this affect human scoring as well? The use of a weighted average of body part velocities again throws away information - if one had a very high-quality video setup with more markers would optimal classification be done differently? What if the input instead consisted of 3D data, whether from multi-camera triangulation or other 3D pose estimation? Multi-animal data?

It is unclear where the manual annotation of behavior is used in the tool as currently stands. Is the validation module used to simply say that the freezing detector is as good as a human annotator? One might expect that algorithms which use optic flow or pixel-based metrics might be superior to a human annotator, is it possible to benchmark against one of these? For behaviors other than freezing, a tool to compare human labels seems useful. The procedure described for converging on a behavioral definition is interesting and an example of this in a behavior other than freezing, especially where users may disagree, would be informative. It appears that manual annotation doesn't actually happen in the GUI and a user must create this themselves - this seems unnecessarily complicated.

A major benefit of BehaviorDEPOT seems to be the ability to run experiments, but the ease of programming specific experiments is not readily apparent. The examples provided use different recording methods and networks for each experimental context as well as different presentations of data - it is not clear which analyses are done automatically in BehaviorDEPOT and which require customizing code or depend on the MiniCAM platform and hardware. For example - how does synchronization with neural or stimulus data occur? Overall it is difficult to judge how these examples would be implemented without some visual documentation.

Reviewer #2 (Public Review):

Zhang et al examined regulatory regions controlling expression of genes in embryonic serotonergic neurons. They mapped accessible chromatin regions and gene expression using bulk and single cell analysis, performed chromatin immunoprecipitation studies of Pet-1 and Lmx1b transcription factors and investigated effects of Pet1 and Lmx1b loss of function on chromatin accessibility. The study generated a useful resource of genomic data and provided new insights into the dynamic regulation of accessible chromatin regions in postmitotic neurons.

Despite the wealth of new genomic data, the focus of the manuscript is somewhat elusive. The goal seems to be to study the mechanisms that control chromatin accessibility in postmitotic serotonergic neurons during their subtype diversification. The authors provide in depth analysis of Lmx1b and Pet1 binding and effects of knockouts of these factors on chromatin accessibility. The authors also rely on conditional deletion of these TFs to address whether the factors are required to "maintain" TACs. Unfortunately, analysis of these conditional mice is limited to one timepoint, which complicates interpretation of the data. It is also unclear why the authors do not show more global analysis of gene expression changes in the pet1/Lmx1b DKO.

In summary, while the manuscript provides important new data, the model how serotonergic neuron specification is controlled by Pet1 and Lmx1b remains unclear. Most importantly, the interesting single cell data are not well integrated with transcription factor function and with temporal changes in chromatin accessibility. Overall, the manuscript will benefit from clearer writing, explicit stating what hypotheses are being tested and better explanation of the rationale for the performed experiments.

Reviewer #1 (Public Review):

RNA polymerase III and it transcribes are essential for eukaryotic cell growth and survival. Moreover, mutations in RNA polymerase III and its specific transcription factor BRF1 lead to human diseases associated with bone phenotypes, indicating that RNA polymerase III mediated transcription plays a critical role in regulating skeletal cells during development and homeostasis. In work reported by this study, the authors aimed to elucidate the role of Maf1, a repressor of RNA polymerase III, in bone homeostasis using the loss-of-function (Maf1 germline deletion mice) and the gain-of-function (Maf1 bone specific overexpression mice) genetically modified mouse models and in vitro complemental approaches. The authors found that loss of Maf1 and inhibition of RNA polymerase III transcription resulted in decreased osteoblast differentiation in vitro, whereas overexpression of Maf1 promoted this process. In contrast, both Maf1 knockout and overexpression mice exhibited increased trabecular bone mass, suggesting amplified bone formation and/or attenuated bone resorption. The strength of is manuscript is the novelty in that it is the first comprehensive investigation on the role of Maf1 and RNA polymerase III in skeleton biology. The major weakness is the lack of bone histology and histomorphometric analysis of number and function of osteoblasts and osteoclast in vivo. It is especially important when in vitro findings are contradictory with the in vivo results. Overall, the study provides the first and novel insights of Maf1 and RNA polymerase-mediated transcriptions in skeleton biology.

Reviewer #2 (Public Review):

In this manuscript, Busschers et al. present data demonstrating a function of the RNA polymerase III transcriptional repressor and tumor suppressor MAF1 in regulating bone mass. By combining in vivo and in vitro experiments, they provide results that are sometimes difficult to reconcile. For example, general KO of MAF1 in mice but also tissue-specific overexpression of MAF1 in stromal cells resulted in increased bone mass, suggesting that both positive and negative regulation of RNA polymerase III transcription may contribute to enhanced osteoblast differentiation and osteogenesis. Interestingly, primary stromal cells derived from the bone marrow of MAF1-/- mice showed enhanced osteoclastogenesis and decreased osteoblastogenesis, which is in contrast to the results obtained in the mice from which these cells were derived. Suppression of RNA pol III transcription by RNA interference-induced decrease in BRF1 expression or by inhibition of RNA pol III itself using ML-60218 treatment resulted in decreased osteoblast differentiation and thus bone mass. When bone mineralization was analyzed by ALP and alizarin red staining, distinct methods of inhibiting RNA pol III transcription produced different results. Overexpression of MAF1 enhanced ALP and alizarin red staining, whereas treatment with ML-60218 or suppression of BRF1 resulted in less staining. Finally, overexpression of MAF1 in ST2 cells also resulted in decreased osteoblast differentiation. In contrast to these sometimes contradictory results, adipocyte differentiation was consistently affected by different types of regulation of RNA pol III transcription. Overexpression of MAF1 or repression of RNA pol III transcription by BRF1 knockdown or ML-60218 treatment resulted in enhanced adipocyte differentiation. RNA sequencing of samples derived from the different approaches to regulate bone differentiation in this work revealed approach-specific regulation of mRNA expression.<br /> Overall, the data presented in this manuscript paint a complex picture of the regulation of bone differentiation by different influences on the activity of the RNA polymerase III transcriptional apparatus.

Strengths:<br /> The work contains several complementary in vivo and in vitro approaches to analyze the effects of regulated MAF1 expression or inhibition of RNA pol III transcription on osteogenesis and adipocyte differentiation.

The data are well controlled and of excellent quality.

The experiments suggest that bone differentiation is regulated by the activity of the RNA polymerase III transcription system, as any condition affecting this system influences osteogenesis.

Weaknesses:<br /> No clear conclusions can be drawn regarding the mechanisms underlying the observed, sometimes contradictory, effects.

The complexity of MAF1-dependent regulation of gene expression by all three nuclear RNA polymerases has not been adequately considered or discussed.

Consideration of the RNA pol III transcription system focuses exclusively on the expression of type 1 and type 2 promoters, thus neglecting possible effects of gene-external type 3 promoters.

RNA sequencing results are presented only as GO analyses, but the genuine results of the squencing were not reported.

The authors have clearly achieved their goal of showing that MAF1 and RNA polymerase III gene transcription affect bone differentiation. This work broadens the spectrum of processes affected by RNA polymerase III gene transcription. Because of the complexity of the results observed, a tabular summary might be helpful for the reader to quickly and comprehensively grasp the most important findings. Such a table could include the various experimental analyses, the effects on osteogenesis, the effects on adipocyte differentiation, the effects on RNA Pol III activity, and possibly the effects on gene expression determined by RNA-seq.

Reviewer #3 (Public Review):

Johnson and colleagues present a study linking Maf1, a negative regulator of RNA polymerase III, to osteoblast differentiation and mineralization.

A major strength of this study is the use of in vivo and ex vivo models where Maf1 expression is manipulated and separately, models where RNA polymerase III activity is modulated independently of Maf1. A weakness of the study in its current form is the absence of combining these models to discern the dependency of the Maf1 influence on RNApolIII activity for the phenotypes presented.

The authors have clearly demonstrated that Maf1 is important for bone biology in both the in vivo and ex vivo models, which is an important contribution to the field. However, the opposite roles that Maf1 plays in these two models is confusing, despite being biologically interesting and certainly worth further study.

The authors present a very interesting hypothesis that codon usage plays an important role in osteoblast differentiation. This is important as translation rates will be influenced by the available pool of tRNAs which are made by RNApolymeraseIII and regulated by Maf1.

A major impact of this work is defining the importance of RNA polymerase III on osteoblast differentiation and mineralization, which should be taken into consideration when future studies investigate the biology underlying bone development.

Reviewer #1 (Public Review):

Marchetti and colleagues present an ex vivo culture method that enables live imaging studies of Drosophila adult midguts for periods up to 3 days. Important technical innovations include defining an optimized tissue culture media, placing midguts at an air-liquid interface for better oxygenation of the tissue, performing inducible gene expression while imaging, and performing multiplexed imaging of up to 12 midguts in a single culture. Using this ex vivo method, the authors show that midgut progenitor cells proliferate and differentiate in response to epithelial damage ex vivo. The authors exogenously activate the cell cycle, which enables them to trace and analyze the division behaviors of multiple generations of stem cell progeny, including the distances between sibling cell nuclei over time. Finally, proof-of-principle imaging of adult renal tubules and egg chambers is provided.

Altogether, this ex vivo method offers important new advantages that will attract broad interest in the Drosophila community. My main concerns are (1) midgut viability when imaging is performed with a confocal microscope and (2) uncertainty about the authors' classification of asymmetric and symmetric fate outcomes.

Major comments:

1. The ability to perform continuous imaging over periods as long as 72 hours is a significant achievement. As the authors point out, this time scale is several fold longer than the 16 hour viability window of in vivo imaging (Martin 2018) . The multiday timescale is important because it could, in principle, enable live imaging of many fundamental, but slow, cellular behaviors such as enterocyte differentiation.

If I understand correctly, the multi-day experiments in the study were captured using imaging conditions that were particularly gentle: (1) widefield epifluorescence, (2) an interval of 1 hour between time points, and (3) at most two fluorescent channels. By comparison, the 16 hour viability window defined in Martin 2018 was based on confocal imaging at 7-15 minute intervals in 3-4 channels. Can the authors provide information on midgut viability when their culture method is combined with confocal microscopy at minutes-long time intervals? This information is important to help users assess the types of questions that ex vivo culture can address given the widespread use of confocal imaging and the necessity of subcellular spatial or better temporal resolution for certain types of questions.

2. The real-time tracing of multiple stem cell lineages through up to three generations is an impressive first for the midgut. The lineage trees are fascinating to examine. However I am unsure that division fate outcomes can be classified as symmetric or asymmetric using the data that are shown.

2a. Some divisions (9 of 25) were classified as asymmetric because exactly one sibling cell divided at a time point >6 hours before the end of the movie (lines 271-277). In my view, these fate outcomes are ambiguous because it cannot be excluded that the other sibling is a stem cell that would have divided after the movie ended. Although 6/7 sibling pairs that the authors observed exhibited temporally correlated divisions, failure to observe temporally correlated divisions is not a basis for concluding that sibling fates are asymmetric.

2b. Other divisions (8 of 25) were classified as asymmetric based on both the criteria in 2a and the observation that the non-dividing sibling showed increased nuclear size and decreased GFP intensity (lines 277-279). I agree with these criteria, but to my eye, the images in Fig 6 and Video 16 do not clearly show these changes. The nuclear size of the non-dividing sibling in panel G is not significantly different from the (presumably 4N) nuclei of the symmetrically dividing siblings in panel E. The GFP signal of the non-dividing sibling diminishes at the end of the movie, but without the His2Av::mRFP channel, I cannot tell whether the cell has lost GFP or, alternatively, has disappeared from view.

2c. The midguts lack markers to distinguish enteroblasts, enteroendocrine precursor cells, and stem cells. Without these, several types of fate outcomes are indiscernible: Asymmetric divisions that produce a stem cell and an enteroendocrine precursor (which remains diploid and can divide again), symmetric divisions (of enteroendocrine precursors) that produce two enteroendocrine cells (c.f. Chen 2018), and symmetric divisions (of stem cells) that produce two enteroblasts (c.f. de Navascues 2010, Guisoni 2017). Additionally, Kolhmaier 2015 has shown that stg/cycE manipulation results in divisions of SuH+ enteroblasts; these enteroblast divisions cannot be distinguished from stem cell divisions in the movies.

Can the authors either provide additional data that resolves the ambiguity of these fate classifications, or, alternatively, revise the text to describe these data in terms of division timing, displacement, and the other cell behaviors that are observed? In the latter case, speculation about fate outcomes could be added to the discussion.

Marchetti and colleagues present an ex vivo culture method for the Drosophila adult midgut. Numerous, important advantages of their method will attract broad interest in the Drosophila midgut community. In addition, proof-of-principle imaging of adult renal tubule, heart, and egg chambers is also provided. My main concerns are (1) midgut viability when imaging is performed with a confocal microscope and (2) uncertainty about the authors' classification of asymmetric and symmetric fate outcomes in cultured guts.

Reviewer #2 (Public Review):

This work provides a new protocol for extended culture of Drosophila midguts ex vivo and live-imaging for up to three days. This paper reveals a significant improvement of explanted intestines survival compared to previous protocols by optimizing the dissection procedure; by modifying the culture medium so that it approximates the adult hemolymph and by fine-tuning the live-imaging setup. In addition, this new protocol allows temperature-sensitive gene expression or knock-down ex vivo. By successfully performing intestinal stem cell lineage tracing experiments and cell tracking over time, authors demonstrate the potential and the robustness of this system in understanding key intestinal processes such as stem cell proliferation and cell differentiation over time. Interestingly, preliminary results demonstrate the possible use of this protocol for extended culture of other organs and its implication in other areas of research.

The relevance of the new protocol proposed by the authors in the improvement of the extended culture and live-imaging of intestines is well supported by the data. However, additional key control experiments would be needed to increase the confidence in using this protocol for the study and understanding of key intestinal processes.

1) Authors tested the viability of explanted intestines over time by assessing different aspects such as the cell death or by testing the ability of cells to proliferate and differentiate. Adding control experiments to assess the state of the trachea and the visceral muscles, two major components of intestinal processes, would be needed.

2) Authors tested GFP expression at permissive temperature in explanted intestines using intestinal stem cells or enterocytes GAL4 driver and detected no differences compared to in vivo condition.<br /> Did the authors quantify the number of intestinal stem cells at different time points in explanted intestines? Did they see a difference compared to in vivo conditions?<br /> Same questions for other cell types?<br /> This analysis could be a good control to further validate the use of this system for the study and understanding of key intestinal processes.

3) Authors tested the ability of explanted intestines to regenerate following intestinal damage induced by SDS feeding. SDS feeding results in stem cell proliferation and progenitors differentiation in explanted intestines.<br /> Adding control experiments comparing stem cell proliferation and cell differentiation upon control feeding or upon SDS treatment in explanted intestines versus in in vivo conditions would reinforce the use of this system.

Reviewer #3 (Public Review):

In this paper, Marchetti and colleagues present an improved protocol to sustain midguts for up to 3 days for live imaging. Using this system, they examined the homeostasis and regeneration in response to damage and genetic induction. In addition, they identified symmetric and asymmetric division through tracing with multiple cell divisions. At last, this improved protocol can be applied to ovary and renal tubules. Therefore, the overall idea is significant. But they examined symmetric and asymmetric division when RasG12V or stg and CycE is activated by esg-Gal4. Because esg-Gal4 is expressed in both ISCs and EBs and expression of stg and CycE in EBs can drive EBs to divide (Kohlmaier et al. Oncogene 2015), the analysis of different divisions (symmetric verse asymmetric) is not precise based on the cell division of their progenies.

Reviewer #1 (Public Review):

The authors have developed cochlear implant prototypes with microcoils that allow magnetic stimulation of spiral ganglion neurons instead of conventional electrical stimulation. The neuronal response at the cortical level was evaluated in a mouse model. Magnetic stimulation was compared to acoustic stimulation and conventional electrical stimulation. The results obtained by the authors demonstrated a better spatial selectivity with a better dynamic.

The article is well written with an introduction and a problematic allowing to understand the goal of the work by readers not expert of the domain. The scientific approach is logical and progressive allowing to explain the work in a very educational way. The figures are clear and illustrate the quality of the work.

Here are my comments:

Concerning the methodology and in particular the electrical stimulation, it would be necessary that the authors specify that the stimulation was monopolar. this choice of stimulation involves a more important diffusion of the current. This makes the comparison with magnetic stimulation more flattering.

In the discussion, several points should be addressed to better explain to the reader the interest and the limits of the chosen technology :

I think that you should start by reminding the reader that there are other modes of electrical stimulation than monopolar stimulation. bipolar or tripolar stimulation can reduce the diffusion of the current to improve selectivity. this stimulation strategy is already used by some manufacturers in the clinic.

In the animal model used, it is likely that even in spite of recent hearing loss, the trophicity of the spiral ganglion is preserved. This does not reflect the pathological conditions of the implanted patients. Thus, it is not at all certain that the better selectivity is the better dynamics observed with magnetic stimulation can be observed in case of damaged spiral ganglion.

If the passage of current in the microcoils generates a magnetic field, it is possible that an inverse effect, or even a heating effect, could be observed if this type of implant is subjected to an external magnetic field, as in an MRI. Have the authors considered this potential disadvantage in view of a clinical transfer of this technology?

Reviewer #2 (Public Review):

Lee, Seist et al. investigated whether magnetic stimulation of the cochlear would lead to less spread of activity - a major limitation of classical cochlear implants used nowadays - than electrical stimulation. To do so, they measured neuronal responses in the inferior colliculus of mice to acoustic, electric, and magnetic stimulation of the cochlea. The acoustic stimulation consisted of 5 ms long pure frequency tones covering the range from 8 to 48 kHz, whereas the magnetic and electrical stimulations were pulses of 25 um duration presented at a rate of 25 pulses/s delivered at 2 locations along the cochlear (one basal, one apical). The neuronal responses were measured along a 16-channel recording array inserted along the tonotopic axis of the inferior colliculus. The results demonstrate that magnetic stimulation elicited responses that were more spatially constrained and had a larger dynamic range than electrical stimulation. As one of the main limitations of the cochlear implants used nowadays is the large spatial spread of stimulation, these data bring a lot of hope for improving this neuroprosthetic technology and put magnetic stimulation as one of the most promising approaches to improve cochlear implant technologies.

The conclusions of the paper are mostly well supported by data, but some aspects of the experimental procedure, the neuronal response acquisition, and the data analysis need to be clarified and extended.

1) From the current description, it is not clear whether the recording electrode stays at the same location for the acoustic, magnetic, and electrical stimulation, or whether it is removed and reinserted. If it is removed and reinserted, it might be that slightly different regions of the IC are recorded from, or that the brain gets slightly damaged on every new insertion. A more detailed quantification of the brain state or neuronal responses would then be a welcome addition. This could be done in several ways. For example, the spontaneous activity or general excitability of IC neurons could be compared across the three different stimulation paradigms in the few experiments they were performed in the same mice (l. 407). Another possibility would be to compare electrical stimulation responses when performed before vs. after the magnetic stimulation (l. 403). More generally, any possible paired-statistical analysis (i.e., when the same recording sites were used to compare the different stimulating methods) would be welcome.<br /> 2) Related to my previous comment, it is written that "experiments were terminated when responses to magnetic stimulation were no longer robust" (l. 406). Why would responses lose robustness? If this is due to damage of the recorded neurons or to cochlea damage, it will most probably also affect the results overall and hence the conclusions of the manuscript.<br /> 3) In a number of figures, only example data are presented (Figures 2, 3, 6). To give the reader the possibility to judge the variability of the results across different experiments (and hence the robustness of the results), it would be important to show also average values, or - in cases this is not relevant - at least 3 example mice.

The advantages and limitations of magnetic stimulations are well described in the introduction and discussion sections and leave the reader with the information that is needed to evaluate the potential strengths and weaknesses of the technique. These sections also nicely emphasize that future experiments have to be performed to further characterize this stimulation strategy.

Reviewer #3 (Public Review):

This article describes a new way to activate auditory nerve fibers (ANFs) by magnetic stimuli (generated by micro-coils) instead of electrical currents (generated by conventional electrodes). The activation of ANFs triggered by the micro-coils seems clear but several physiological quantifications are inappropriate and the major claims are based on a very small number of experiments. I sincerely encourage the authors to continue their experiments and use more straightforward ways to quantify their results (closer to the raw data) to progress toward clarifying their effects.

In the case of severe and profound deafness, cochlear implant is the solution to recover partial hearing and speech understanding. Cochlear implant is probably the most successful neuroprothesis but it still has limitations, especially as it is difficult to focus the currents inside the cochlea, the electrodes being in contact with a conductive liquid named perilymphe.<br /> In this study, the authors aim at describing a new way to activate the auditory nerve fibers (ANFs) by the use of small coils (micro-coils) which are supposed to confine ANF activation more narrowly than can be achieved with conventional electrodes used in cochlear implants. The authors recorded neuronal activity from the inferior colliculus (a subcortical auditory structure) and claim that the spread of activation is narrower with magnetic stimulation compared to electric stimulation. They also point out that the dynamic range is wider with the magnetic stimulation than with electric stimulation. Finally, they show that the evoked responses in the inferior colliculus also occurred in mice chronically deafened indicating that the micro-coils directly activate the ANFs. Activation of the ANFs triggered by the micro-coils seems clear, however, to what extent this activation differs between electric and magnetic stimulation; and differs with acoustic stimulation is unclear. Several basic quantifications are missing and the quantifications performed here are not appropriate. In addition, all the claims are based on very small samples.

Quantification of the frequency response area FRA using the d' index is very puzzling. If the authors want to quantify the breadth of the tuning curves they can use the Q10dB, the Q40dB or the Octave distance which are classically used in auditory neuroscience. Comparing the different levels of stimulus intensity to determine the breadth of tuning to sounds and to electric/magnetic stimuli does not make any sense.

Quantification of the spectral spread of activation used in figure 4A-B is not correct. Based on the 11 animals tested with ipsilateral tones (and not contralateral tones), the authors estimated that each electrode corresponds to a particular frequency, then the between-electrode distance is converted in an octave distance. First, what is the purpose of converting distances into octave? In fact, there is no possibility to calibrate the acoustic stimuli and the electric/magnetic stimuli the same way: we cannot know if a particular sound intensity (e.g. 80dB) corresponds a particular voltage (for magnetic stimulation) or intensity (for electric stimulation). By using ipsilateral sounds instead of contralateral sounds, the authors largely underestimated the acoustic inputs reaching the recording sites (because the main ascending pathways cross the midline between the cochlear nucleus and the superior olivary complex). Therefore, the comparisons between acoustic and electric/magnetic activation cannot be properly assessed, which is the crucial part of this paper.

Reviewer #2 (Public Review):

Cellular mRNA stability is regulated by a complex set of features including transcript polyA tail length, codon optimality, and internal elements that recruit RNA-binding proteins to promote RNA degradation or stabilization. In this manuscript by Suñer et al, the authors show that two RNA-binding proteins, CPEB4 and TTP, act in an opposing manner to regulate the stability of mRNA transcripts in macrophages and help regulate the inflammatory response. Specifically, CPEB4, a cytoplasmic polyadenylation element (CPE) binding protein, binds to CPEs present in the mRNAs of anti-inflammatory genes in macrophages to help stabilize these transcripts and promote inflammation resolution. The authors show that CPEB4 is upregulated in the blood of sepsis patients and in lipopolysaccharide (LPS)-challenged macrophages, and that CPEB4 KO mice have increased cytokine levels and an exacerbated inflammatory response that impairs their survival of sepsis. These results link inflammation response and resolution to CPEB4 levels in macrophages.

Next, the authors show that Cpeb4 mRNA levels are regulated by the LPS-activated p38a MAPK, where KO or inhibition of p38a in macrophages resulted in stabilization of the Cpeb4 mRNA. RNA-immunoprecipitation and RNA half-life measurements suggest this p38a-dependent stability results from the differential binding of AU-rich element (ARE)-binding proteins HuR and TTP to the Cpeb4 mRNA (which contains AREs), either stabilizing (HuR binding) or destabilizing (TTP binding) the transcript.

Finally, the authors use co-immunoprecipitation, RT-qPCR, and RNA half-life measurements to show that CPEB4 and TTP regulate the stability of mRNA transcripts that play key roles in LPS response and inflammation. These transcripts contain CPEs and AREs, which can be differentially regulated by the binding of CPEB4 and TTP, to promote stability or decay, respectively. Although the effects of CPE:ARE ratio on endogenous mRNA stability in cells appears somewhat complex, luciferase reporters bearing different combinations of CPEs and AREs suggest these elements help to directly determine the stability of mRNA transcripts during inflammation response.

Overall, this thorough work proposes that RNA-binding proteins CPEB4 and TTP play important roles in regulating inflammation-associated mRNA transcripts by binding to CPEs or AREs to promote RNA stability or degradation. While most of the claims in the paper appear reasonably well-supported by the experimental data, I do have some concerns on the robustness and significance of the presented data in some cases. The authors succeed in making a generally compelling case that CPEB4 plays a key role in regulating mRNA stability to impact inflammation resolution, but some of the individual claims identified, that appear to be more weakly supported by the presented data, should be addressed and/or clarified.

Reviewer #1 (Public Review):

Resolution of immune responses are essential for organism health. In this manuscript, Suner et al. studies the role of CPEB4 during the response to LPS, which underlies sepsis. In the initial part of the manuscript the authors clearly demonstrate, using an animal model, that CPEB4 is necessary for survival following LPS stimulation. The authors then, using a combination of genetic and pharmacological approaches show that CPEB4 is induced in monocytes/macrophages during the LPS response via the previously described mechanism involving p38alpha, HuR and TTP. Consequently, it is argued that inability to induce CPEB4 hampers resolution of the LPS-response. This part of the study is in general well supported although some of the statements relative to the informatics analyses could be clarified.<br /> 1. It is mentioned that deconvolution was applied but it is unclear how and what the presented data actually corresponds to (Fig. S1A-D).<br /> 2. Several of the differences indicated as statistically significant in Fig. S2E (for example for INFg, inflammatory response), do not seem to indicate biologically meaningful differences.<br /> As CPEB4 affects mRNA-stability the authors next strive to identify mRNAs which are targets for CPEB4-dependent post-transcriptional regulation. Following an unbiased approach, the authors propose that CPEB4 is critical for regulation of anti-inflammatory factors that in turn would underlie resolution of the immune response. While being a logical continuation of the studies, this part of the manuscript has several weaknesses:<br /> 1. There is an inconsistency regarding how proposed targets are studied and the results seem inconsistent. For example, in figure 4E Dusp1 and Il1rn are validated as CPEB4 targets. In figure 4F-G the focus is then shifted to SOCS1. Then the results from SOCS1 are extrapolated to other targets in Fig. 4H but Fig 4H data do not seem to correspond to Fig S4C data (e.g. 4H indicates that Socs3 is less expressed in Cpeb4-/- after 6h while S4C indicates that these are essentially identical; for Tnfaip3, the opposite regulation is indicated in 4H as compared to S4C after 6h). As it seems that 4H and S4C are based on the same data it is hard to understand. In figure 4J cyclin B1 3'UTR with or without CPEs is evaluated while it would have been logical to focus on endogenous targets studied in other panels in figure 4. In aggregate, the link between CPEB4 and targets which resolve the immune response can be better substantiated.<br /> The hypothesis from the authors is that these proposed downstream targets of CPEB4 underlie the resolution of the LPS-response. Although this is a plausible hypothesis, it should be noted that there are no experiments showing this.

In the final part of the manuscript the authors examine how the interplay between RNA elements for HuR/TTP (ARE) and CPEB4 (CPE) interact to modulate mRNA levels during the LPS-response. It is suggested that it is the relative number of AREs vs CPEs that determine the pattern of regulation following LPS-stimulation. Although this part of the studies left some questions untouched (e.g. why are AREs not active when there is no CPE; or do these patterns of regulation correspond to modulation of poly-A tails) the conclusions are intriguing and supported by the data. Yet, although this may be technically very difficult, the conclusions could be strengthened by e.g. studying the role of CPEs for the endogenous genes of interest studied in Fig. 5D-E. This could be important as there is ample co-variance between not only AREs and CPEs (as indicated in Fig 5C) but also a range of other RNA elements which may also affect the stability of mRNA.<br /> Finally, the authors present a model for their findings (Fig. 6A). The model well illustrates the findings of the paper although the data supporting activation of anti-inflammatory factors depending on CPE appears to be a weak link.

Reviewer #1 (Public Review):

In this manuscript, Zobeiri and colleagues investigate the activity of cerebellar Purkinje cells relative to various types of head and neck movements. They find that many Purkinje cells encode both vestibular and neck proprioceptive information. Notably, vestibular and proprioceptive information tend to be in the same direction, whereas in previous recordings this group found that in the fastigial cerebellar nucleus, the direct target of this region, vestibular and proprioceptive information tend to cancel each other out. The authors put forward a model that suggests this difference is explained by convergence of different Purkinje cells onto fastigial neurons.

The authors are obviously experts in this field, and the analyses are performed at a highly sophisticated level. However, I found the manuscript quite difficult to read, and struggled at times to understand the significance of the results. What seems to be the most significant finding, that Purkinje cell activity can explain the encoding of neurons in the fastigial nucleus, is not well developed given how counterintuitive the result appears.

Reviewer #2 (Public Review):

The manuscript addresses an important question regarding sensory processing related to self-motion. The main experiment is clearly described and demonstrates that neurons display a diversity of responses from purely reflecting vestibular input (head-in-space motion) to predominantly body motion, and any combination between. Of particular interest, is that the response of the Purkinje cells are profoundly different than its downstream target, the fastigial neurons which signal only head-in-space or body motion. This substantive difference in neural representations between these two connected brain regions is surprising.

The manuscript also provides a simple population model to show that fastigial responses could be generated from Purkinje cell activity, but only from combining at least 40 neurons. While the model provides some insight on the potential interaction between Purkinje cells and fastigial neurons, I think the model assumes no other input to the fastigial neurons. However, I would assume that there is likely a strong input from mossy fibers onto the fastigial neurons that also target the Purkinje cells. This mossy fiber input will certainly provide vestibular and neck proprioceptive input to the fastigial nucleus. Thus, the Purkinje cell input may be essential for countering the mossy fiber input leading to separate representations for head and body motion in the fastigial nucleus.

Another issue is the limited number of neurons recorded in the secondary experiment with only 12 bimodal neurons and 5 unimodal (although there appears to be only 4 neurons in Figure 5C). Such a small sample impacts the estimated tuning properties of Purkinje neurons in Figure 5D and the results from the population model. This needs to be clearly recognized.

Reviewer #3 (Public Review):

In this study, the authors characterize the simple spike discharges of Purkinje cells in the anterior vermis of the macaque during passive vestibular and neck proprioceptive stimulation. The activity of most Purkinje cells encoded both vestibular (whole-body rotation) and proprioceptive (body-under-head rotation) stimuli. Although the vestibular and proprioceptive responses were, on average, antagonistic in the preferred direction, consistent with a partial transformation from head to body coordinates, response properties for both modalities were highly variable across neurons. Most cells responded under combined vestibular and proprioceptive stimulation (head-on-body rotation), and these responses were well-approximated by the average of the responses to each modality individually. Vestibular responses exhibited gain-field-like tuning with changes in head-on-body position, though these changes were significantly smaller than the shifts observed for neurons downstream in the rostral fastigial nucleus. Finally, a weighted average of the responses of approximately 40 Purkinje cells provided a good fit to the responses of postsynaptic fastigial neurons.

Overall, these results provide important and novel insights into the implementation of coordinate transformations by cerebellar circuitry. The experiments are well-designed, the data high quality, the analyses reasonable, and the conclusions justified by the data. The manuscript is clear and well-written, and will be of interest to a broad neuroscientific audience. I have no major concerns. I have a few minor suggestions for improving this manuscript, described below.

1 - The authors may wish to discuss earlier work in the decerebrate cat by Denoth et al. (1979, Pflügers Archiv), which provided evidence that the responses of Purkinje cells in the anterior vermis to head-on-body tilt is relatively well-approximated by averaging the responses to neck and macular stimulation alone.

2 - To better convey the heterogeneity of responses across the sample of Purkinje cells, two additional supplemental figure panels might be useful: (1) the vestibular, proprioceptive, summed, and combined sensitivities in each direction (as in the Fig. 3C insets) for each individual neuron (perhaps as a series of subpanels), and (2) scatterplots of response phase for proprioceptive vs vestibular stimulation for bimodal neurons (with separate panels for preferred and non-preferred directions).

3 - Can the authors provide additional information on the approximate location of the recorded neurons (lobule and zone or mediolateral position)? Is it possible that some project to the vestibular nuclei, rather than the rFN? This consideration seems especially relevant for the interpretation of the pooling analysis in Fig. 6, which seems to assume that Purkinje cells are sampled from a sagittal zone with overlapping projections in the rFN (or, at least, that the response properties of the sampled neurons are representative of the properties in a corticonuclear zone). Some additional discussion on this point would be helpful.

4 - When weighted averages of Purkinje cell responses are used to model rFN responses, my intuition would be that w_i is near zero for v-shaped and rectifying Purkinje cells. That is, the model would mostly ignore them, as data from both directions appear to be included. Is this the case? A more detailed description of the fitting procedure would also be helpful.

5 - Another potential interpretive issue in the averaging analysis concerns the presence of noise on single trials. The authors could briefly comment on whether more Purkinje cells might be needed to predict rFN responses on a single trial in real time.

Reviewer #1 (Public Review):

Chen et al. embark into a comprehensive analysis of physiological and behavioral aging in a mixed-bred (Diversity Outbred, or DO) mouse population. They aim to analyze spontaneous trajectories in mouse aging from longitudinal data acquisition, using commercially-available monitoring cages, able to detect a diversity of aging-related changes in individual mice physiology and behavior.

This work has two major strengths: the extensive data generated and the analytical tour-de-force to extract relevant features from multi-dimensional aging data.<br /> Overall, the authors reached their goal and I congratulate them for the clarity and thoroughness of the analyses conducted.

The main question of this work is somehow subordinate to their approach. If I were to summarize their main question, I would say "can we extract spontaneous aging trajectories/features from non-invasive behavioral monitoring in mix-bred mice"? Overall, the authors answer this question and discuss the implications of their findings. This work helps generate a clear separation between the concepts of chronological aging from biological aging (CASPAR approach), providing an integrated measure of both, and relating this measure with individual data sources. The authors further provide important insights into the concept of aging-related decline in resilience, which their multi-dimensional data integration convincingly support. This work will likely have important impact on future studies focused on integrated measures of physiological/behavioral aging. What is not entirely clear so far from this work, is how future work by other groups will be able to benefit from these data and approaches, i.e. how accessible and scalable are the analyses presented in this work to different experimental designs, e.g. where more sparse data are obtained. The authors should make the data easily available/accessible to the public, as well as their code.

While this work is comprehensive and rather impressive, the way it is written so far does not focus on the results, but rather on the methodology.

Reviewer #2 (Public Review):

In their study, Chen et al. consider a set of 415 genetically diverse, outbred mice. This population is assembled from eight distinct cohorts, each entering the study at a separate chronological age ranging from three to twenty-four months. By employing a commercially-available automated-phenotyping system, the authors collected high-dimensional phenotyping data that quantifies both behavior and physiologic properties like oxygen consumption. Animals were placed in the phenotyping system for week-long measurement intervals, alternated by three-week intervals in more standard cages. In this way, the authors cleverly overcome challenges in longitudinal measurement by stitching together eight overlapping longitudinal time series into a single forty-week characterization of the entire murine lifespan.

The authors found many of their measurements covary at short timescales according to an individual's behavioral state-sleeping, eating, running, etc. To control for this effect, the authors developed a hidden markov model that allowed them to automatically identify an animals' behavioral state, thus segmenting longitudinal measurements into distinct behavioral stages. This allowed the authors to more accurately study the long-term effects of aging by removing the confounding effects of short-term behavioral changes.

The authors find that circadian rhythms changed with chronological age, as did energy expenditure while resting declined. In fact, eighty percent of all metrics correlated significantly with chronological age.

The authors genotyped each mouse using an array of SNP probes, allowing them to identify genotype-phenotype correlations. The authors observed a low heritability on average among all traits (median correlation = 0.22), but found that these heritable factors tended to affect multiple phenotypes simultaneously. Notably, the heritability of body mass was relatively high, in agreement with previous studies.

Irrespective of genetics, 250 features clustered into 20 groups based on covariation over time. The authors identified a general increase in the covariation of traits between and within these clusters as animals aged. The authors refer to these increases in covariation as "decreases in resilience".

Finally, the authors developed a model of aging that integrates phenotypic data and lifespan data. This model appears to draw implicitly from concepts developed by OO Aalen and James Vaupel under the name of "frailty" models, positing that each individual exhibits a characteristic rate of aging that contributes to differences in lifespan among peers. The authors fit their model using a maximum likelihood approach-implemented using gradient boosted decision trees-that allows them to estimate the relative rate of each individuals' aging using longitudinal phenotypic data and compare this to inter-individual differences in lifespan. The authors' model produces rather unimpressive predictions of chronological age, with correlations ranging between 0.5 to 0.75 depending on model tuning. The model has more difficulty predicting an individuals' remaining lifespan, only correlating between 0.25 and 0.425 depending on model tuning.

*Strengths*

The main strengths of this manuscript are its thoughtful study design, which combines high-dimensional phenotyping, genotypic data, and large population size. An impressive effort went into collecting these measurements and the result seems likely to be useful for many future analyses. An additional strength of this manuscript is the HMM model. By subdividing time-series measurements into distinct short-term behavioral periods, long-term trends in behavior and physiology can be identified without the confounding influence of short-term behavioral states. Finally, the authors' "CASPAR" model seems like a thoughtful attempt to relate longitudinal phenotypic aging to lifespan, even if its performance is not yet so impressive.

*Weaknesses*

The manuscript is substantially weakened by a lack of clarity on several important conceptual points. First, the authors appear to assume that any change that occurs at month-long timescales must be "aging". The authors choose to discard the first day of measurements in a cage to account for behavioral adaptation, demonstrating their concern for distinguishing behavioral adaptations from aging phenomena. However, the authors' efforts to do this seem rather cursory, as mice surely learn and adapt over time-scales longer than twenty-four hours. The reader is left wondering to what extent this study measures the phenotypic consequences of aging, and to which extent is the study measuring long-term adaptation of individuals to a four-week rotation schedule in and out of different cages.

As a second conceptual issue, the authors adopt a rather shallow and limited practical definition of the term "resilience". Conceptually, they define resilience as "the ability of a system to maintain function in the face of change", which seems reasonable and corresponds with the general thinking about resilience. However, in practice, the authors define resilience as the inverse of correlation among traits-an animal is more "resilient" when its different phenotypic traits are less correlated. This practical definition lends itself well for measurement using the data in this study, but leads to an incongruity between conceptual and practical definitions of "resilience". Correlation of traits is not uniquely determined by an organism's resilience--there could be any number of reasons for traits to increase in covariance beyond a failure of resilience. Any change in the physiologic relationship between two traits will alter the causal structure of the traits' interactions and therefore alter the trait's covariance. Are the authors arguing that any change in physiology must inherently involve changes in resilience? A more convincing practical definition of resilience would involve a more direct test of conceptual definition, as defined by the authors as "the ability of a system to maintain function in the face of change". For example, the authors might have provided some sort of physiologic challenge and measured animals' response to it-a physical stress test, a test of thermoregulation in response to changes in temperature, the speed of adaptation to a novel environment. Given the data collected, the authors can measure many interesting aspects of aging, but they do not seem adequately justified in calling one of these aspects "resilience".

The manuscript also raises technical concerns. First, it is unclear whether all analyses in the manuscript are performed using features normalized body mass or whether only analyses in certain sections of the manuscript are performed using features normalized for body mass. The details here are crucial because improper normalization would undermine the main conclusions of the manuscript. Normalization of multiple features to any shared reference has the potential to introduce a correlation between normalized features and the shared normalization factor. In fact, many approaches for normalization to body mass will always introduce a correlation between normalized features and body mass, with the only exception being if the un-normalized features and body mass are perfectly correlated. If the authors normalize traits before performing their various correlation analyses, such normalization could introduce artefactual correlations between traits. Any normalized quantity will correlate with body mass and all traits correlated with body mass will in consequence correlate with each other. In summary, the authors must explain their normalization procedure in more detail to identify or exclude any improper normalization that could confound their analyses. Analyses at risk of being confounded include the heritability analysis, the network analysis of phenotypes during aging, and the CASPAR analyses.

In the methods section, the "CASPAR" model is described clearly. However, the intuitive description provided in the main text invokes the concept of an "unavoidable tension" between chronological age and inter-individual heterogeneity in the aging rate. The reviewer finds this latter description unhelpful and potentially misleading. The sigma parameter can in some sense be considered a hyperparameter, because tuning it alters the model's behavior and performance. However, the sigma parameter is, more importantly, a potentially measurable property of the system being studied. Individuals within the population exhibited some amount of variability in their individual aging rates, which if measured would determine the value of an empirically-grounded sigma parameter. Unfortunately, the authors are currently unable to estimate this sigma empirically and so they can only speculate about its true value. The authors are correct that different assumptions regarding variability in individual aging rates will produce different model behavior and differential performance in predicting chronological age and aging-rate heterogeneity. However, the authors err in implying that any "tension" exists in some grander, theoretic sense. More simply, the authors simply cannot currently measure an important parameter of their model. Readers would benefit from a clearer description of this parameter and the challenges in statistical inference it highlights.

Though impressive, this study's data has two limitations that the authors already acknowledge: 1) an absence of lifespan data for all animals and 2) a limited population size. Despite such limitations, the current data represents an impressive effort that will likely support many additional analyses.

Finally, the authors seem to neglect substantial prior experimental characterizations of phenotypic aging and methodological work in studying multi-dimensional phenotyping of aging. For example, in nematodes a similar characterization has already been performed: CN Martineau et al PLoS computational biology 2020, and related analytic methods have already been developed that show similar performance: Zhang et all Cell Systems 2016. If the authors wish to draw conclusions that generalize beyond their particular mouse model, they cannot focus myopically on only mouse experiments.

In summary, the manuscript describes a solid and commendable effort that has produced a valuable data set. However, in contextualizing and analyzing this data, the authors fall noticeably short of their self-proclaimed "sophistication and rigor".

Reviewer #1 (Public Review):

Ecological preferences and life history strategies impact the evolution and phenotypic diversity of salamanders. Using geometric morphometric analysis, the authors demonstrate that both the shape of the palate and several non-shape variables (particularly associated with vomerine teeth) are ecologically informative in early stem- and basal crown-group salamanders. The morphology of the palate is subject to convergence constrained by feeding mechanisms, and metamorphosis is significant in the expansion of ecomorphospace of the palate in early salamanders. The work will add to the knowledge on the early evolutionary pattern of salamanders.

Reviewer #2 (Public Review):

In this manuscript, Jia and colleagues statistically demonstrate, using geometric morphometric analysis, that the palate is a reliable proxy in ecological reconstructions for early salamanders, and the morphospace of the palate is predominantly shaped by ecological constraints and also displays stepwise evolutionary pattern. The authors also provide evidence that the common ancestor of salamanders was metamorphosed and terrestrial, and shared unified lifestyles with other modern amphibians. The results of the study are of interest to a wide range of zoologists.

Reviewer #3 (Public Review):

The manuscript investigates, using a large dataset and a broad array of methods that account for phylogenetic nonindependence of the data, whether the shape of the palate correlates with habitat (water, land, or both) in a clade of extant salamanders. After demonstrating that this is the case, it infers the lifestyles of Cretaceous and Jurassic supposed members of that clade as well as a few other early salamanders. If the used phylogenetic tree is indeed accurate, the conclusions are very robust. The methods will be widely imitated to research similar questions all across the tree of life.

Reviewer #1 (Public Review):

Masters athletes are viewed as a useful model to study the effects of human ageing that can be somewhat disassociated from the combined effects of increased inactivity, and the current study provides data on specific differences in the muscle proteome compared to those less active older people. Notably, the MA were successfully competing at a high level and are of an age were neuromuscular decrements would expected to be most severe (80yrs). The authors have employed a range of methods of which the most prominent is proteomic analyses of muscle biopsies, and although in a subset of participants only, this should not be considered a small study. Primary outcomes reveal a range of proteins which are differentially observed in MA, a large portion of which relate to mitochondrial function. These findings are further underpinned to a certain extent by histochemically assessed muscle fibre sections and mitochondrial DNA copy numbers. New insights into an extremely rare cohort are provided which are highly relevant to an ageing human population.

Mass spectrometry analyses employing tandem mass tagging is a robust method to study the human muscle proteome and the methodological description and supplementary data represent a significant body of analysis. Confidence in these outcomes are also further unpinned by previous work from members of the group, again relating to human muscle proteomics and ageing. Specific proteins relating to nuclear pore complex and spliceosome activity reported, for the first time in aged human athletes. There are, however, a number of points that require greater clarification and/or discussion.

An association of enhanced mitochondrial function in highly exercised individuals, which is greater than those less active, is not overly surprising. Nevertheless, additional analyses within the MA may further reveal the potential role of over represented proteins relevant to mitochondrial function and individual performance, such as VO2MAX and peak cycle workrate. Of particular interest here is the training and competition history of the MA which appears to be fairly short, and the majority would have been considered as aged/old prior to competing in their respective disciplines. As non lifelong exercisers the implication here is they have reversed mito decrements normally observed with ageing (alluded to throughout), or, the MA were predisposed to higher physical function prior to engaging in competition. The limitations of cross-sectional design commonly preclude such insights, but this point does deserve further discussion.

Reviewer #2 (Public Review):

The study authors conclude that preservation of mitochondrial structure/function proteins underlies the better performance of octogenarian master athletes than non-athletes. I do concur with the authors that this most likely is an important factor that contributes to the exceptional performance of the master athletes. One thing to consider is perhaps that these things may be just normal training adaptations that can even be elicited in octogenarians who start training. In fact, there is ample evidence that even when one starts training later in life (see for instance Hepple et al, JAP, 1997) still gains in maximal oxygen uptake and muscle mass/strength can be achieved. The point is therefore that perhaps these are not so much signs of 'preservation' but rather 'training-induced' adaptations. It would be interesting to see whether training of non-athlete octogenarians results in the same pattern of structural/functional mitochondrial proteins as seen in the octogenarian master athletes. So, I have some problems with the term 'preservation' as they may just have what is expected after training.

Reviewer #2 (Public Review):

Strengths of this study include the wide-ranging evaluation of frailty. Measurement of frailty and its effect on brain and liver function.

A weakness is the lack of head-to-head comparison of the senolytic and senostatic agents in the in-vivo and in-vitro. It would also be helpful to see the effects of specific agonists and antagonists for pathways the authors are targeting to comparatively evaluate the therapeutic activity of the drug treatment being tested.

Reviewer #1 (Public Review):

Individuals who survive cancer treatment can experience health challenges that accelerate ageing and can lead to the development of frailty and early mortality when compared to others of the same age without a history of cancer. The authors propose that cancer therapy-induced cell senescence contributes to premature ageing in these individuals. The present study investigates whether a brief intervention with drugs that ablate senescent cells (senolytic drugs) or drugs that inhibit the damaging signalling molecules released by senescent cells (senostatic drugs) can block the progression of radiation-induced frailty and disability in a mouse model. The study shows that irradiation-induced frailty and disability can be reduced by a brief exposure to senolytic or senostatic drugs up to a year after the initial radiation exposure and that such therapies are at least partially beneficial even if administered after premature ageing is established.

Strengths:

Although several prior preclinical studies have explored adjuvant senolytic/senostatic drug therapy in the setting of chemotherapy, earlier work used short-term follow-up and focussed on adverse effects on specific body systems. Important advances made by Fielder and colleagues are: 1) the authors have followed mice for a long time after exposure to radiation plus senolytic drug treatment (up to one year); and 2) they have used a diverse array of system-wide and integrative measures (e.g. frailty assessment as well as tests of strength, coordination and cognition) to assess effects on health globally. These data provide strong preclinical evidence that short-term exposure to senolytic/senostatic drugs following radiation therapy can improve health over long time frames.

Weaknesses:

The authors have been careful in their conclusions, and most are well supported by their data. Still, there are some weaknesses to the data reported by Fielder et al.

1) The introduction is lengthy, but it does not provide a rationale for all aspects of the work, and this makes it difficult to follow some of the proposed experiments. For example, the authors spend a lot of time discussing the selection of the senostatic, metformin but reasons for the other specific drugs used have not been provided in the introduction (e.g. navitoclax, dasatinib and quercetin are mentioned in the abstract but first appear in the methods section of the paper). Rapamycin is used in some studies but not discussed. Some relevant information is found in the results section, but this comes too late in the manuscript.

2) Dose selection is important in studies of senolytic drugs, but the authors did not introduce the rationale for the doses chosen in the introduction. Where they do mention this in the results section, they claim that the doses used are "...comparable to the lower range of therapeutically used doses..." with no references. This should be introduced - with supporting references - and discussed in the discussion.

3) The selection of the tissues/cell lines chosen for investigation should be clarified/justified as well as listed in the methods. The authors mention effects of senolytics on liver toxicity and sarcopenia in the introduction. This could be used to justify studies on liver and quadriceps, although this should be made explicit and linked to functional assays where possible. No rationale for studies on the brain and cognition has been provided in the introduction and many other tissues could have been investigated (e.g. kidney, fat etc). Similarly, it would be helpful to know why the authors selected human lung MRC5 fibroblasts.

4) The authors emphasize their work on metformin over the other drugs used throughout the manuscript. A more balanced manuscript with more emphasis on the senolytic interventions could address the issues raised here.

5) The authors have completed their studies using male mice only, so the generalizability of their findings to females is uncertain, as they note in their discussion. They also use only young adult mice subjected to radiation therapy. The authors justify the work in the introduction based, in part, on accelerated ageing seen in long-term survivors of childhood cancers but they do not test their interventions in juvenile mice. Older individuals also experience chemotherapy. The work should be extended, not only to female animals but also to younger and older mice.

Despite these shortcomings, in general the authors' claims and conclusions are justified by their data.

Reviewer #1 (Public Review):

Lee et al report the incidence of remyelination in the non-human primate model of multiple sclerosis. EAE was induced in marmosets and serial 7 tesla MRI identified cerebral white matter lesions. Thirty-six focal lesions classified as demyelinated or remyelinated based upon proton-density images were assessed by histopathology. Fifty-one % of these lesions were identified as remyelinated. These studies have implications for preclinical testing of pro-myelinating agents in individuals with MS.

Strengths:<br /> The MRI data presented is of high quality and demonstrates the value of multisequence 7-Telsa MRI. The sequential imaging clearly identify alterations in signal intensity on proton density-weighted images that are consistent with demyelination and remyelination.

Weaknesses:<br /> While the MRI aspects of this study are of high quality, the pathological correlates of these MRI abnormalities need better confirmation. The lesions identified by MRI are very small (often less than a mm3). Some indication of how MRI and histological lesion sites were co-registered would be helpful. How was the brain sliced? Where the lesions visible macroscopically on the fixed slices? How many sections were cut to identify the lesion? Lesions were characterized as acute or chronic. Acute lesions in MS brains contain an abundance of macrophages/monocytes, lack of myelin, and on rare occasions myelin protein debris. The acute lesion shown in Fig 2 is difficult to classify. The lesion should be space occupying and convincingly demonstrated by a low magnification image that includes both lesional and non-lesional areas. The lesion area should have an accumulation of Iba1-positive cells and a dramatic reduction in PLP staining compared to surrounding normal appearing white matter. The staining for oligodendrocytes (ASPA and Olig2) in Fig 2 may identify a small centrally located decrease in oligo number, but this area does not correspond to differences in Iba1 or PLP staining. Scale bars are needed on the histological figs and some comment on lesions size would be helpful. Is the size of the lesions similar by MRI and pathology?

There are similar concern regarding remyelinated lesions. What Is the size of the lesions in stained sections? What percentage of the lesional area is occupied by myelin? Are the myelin internodes shorter and thinner than myelin in normal appearing white matter.

Reviewer #2 (Public Review):

The identification of an in vivo imaging strategy to follow demyelination and remyelination in multiple sclerosis (MS) and MS -like experimental lesions is a critical goal for regenerative medicine. MS represents one of the best target diseases for regenerative therapies, with clear evidence for an endogenous regenerative process to target and recognition that the progressive disability in patients with chronic disease results from the axonal degeneration consequent to regenerative failure. There is considerable controversy as to the best strategy for MR imaging in assessing remyelination. This results, in part, from the gulf between rodent models, where the CNS repairs rapidly and efficiently following demyelination and the diseased human CNS where any regeneration can be much slower and complicated by chronic inflammation.

A potential solution to this is the development of a large animal model that better recapitulates the human cellular pathology and enables the development of imaging protocols that can be used in the clinic. This study does exactly that, studying lesions in six marmosets following induction of acute inflammatory demyelination (EAE) as occurs in MS. Brains were examined by MR imaging after EAE induction, and lesions identified and followed with serial imaging before histological examination to confirm the cellular phenotype. The results show that a high percentage of the lesions undergo spontaneous remyelination and that this can be detected by the change in the demyelination associated signal visualized by proton density weighted (PDw) MRI. Despite the inevitably small number of animals studied, the result is robust although the intriguing findings the steroids had no effect and that remyelination is stronger in males do probably need larger numbers.

Reviewer #3 (Public Review):

Lee, Sati and colleagues investigated whether remyelination can be detected non-invasively using MRI in common marmosets with experimental autoimmune encephalomyelitis (EAE). The authors subjected the marmosets to serial MRI during the course of the pathology. The results of PDw and MTR sequences were compared to those of histopathological analyses performed on brain tissue after the animals reached the end point. They found that PDw was more efficient in detecting remyelinated lesions than MTR. The authors also found that early treatment with methylprednisolone had no effect on remyelination. Moreover, the authors observed less remyelination in females compared to males.

Strengths: These experiments are valuable as non-invasive detection of remyelination in pre-clinical models is a indispensable for testing the efficacy of pro-remyelinating agents prior to clinical studies. Moreover, the animal model used (marmoset EAE) is probably the one that mimicks MS lesions the best, which further supports the importance of the results presented. In addition, the manuscript, particularly the discussion section, is well written, and it suitably addresses and clarifies some issues relevant to the experimental design (low animal numbers, the comparability of different paradigms used to induce EAE, and the potential impact of applying corticosteroids early after lesion detection).

Weaknesses: The main caveat of this manuscript is that histopathological analyses performed appear insufficient to validate the MRI findings regarding demyelination/remyelination, as well as the activity of demyelinating lesions (acute demyelinating versus chronic). This could be improved by addressing the following points:

1. The criteria to define different lesion types should be clearly presented (numbers/nature of inflammatory cells, their positivity for different myelin antigens, numbers of oligodendrocytes/OPCs, axonal markers), referenced, and applied when performing histological classification.

2. Quantification of histological parameters is lacking. Statements such as "decrease in numbers of oligodendrocytes/oligodendrocyte depletion/axonal loss" etc should be corroborated by quantification of specific cellular/axonal markers in lesion areas, as compared to normally myelinated tissue (normally appearing white matter). For example, in Fig 2, based on the image of ASPA/Olig2 labeling, the authors mention "loss of oligodendrocytes", but such loss is apparent only in the small area in the center of the lesion, while the remaining area negative for PLP contains many ASPA+ cells. Quantification of ASPA in the lesions versus NAWM would unequivocally clarify this issue. The same is true for Bielschowsky staining and inflammatory cell markers-quantification would provide solid data. Quantification of inflammatory cells (possibly using additional markers), and co-labelings with different myelin antigens would be very helpful in distinguishing between acute demyelinating and chronic demyelinated lesions (histologically).

3. Regarding remyelinated lesions, it would be useful to see Luxol Fast Blue staining pattern at lower power and appreciate paler staining of the remyelinated area as compared to non-demyelinated white matter.

Additional information:<br /> Related to the above-mentioned point, it would be interesting to present additional histological data/discussion for the animals treated with methylprednisolone (MP). From Figure 5, it seems that MP treatment (applied at week 24-25) resolved demyelination of the first lesion in M#5, but the second lesion in M#5 presented developed after MP treatment was completed (around week 32). This suggests that no differences in the total percentage of remyelinated/total lesions in MP-treated versus MP non-treated animals were observed because most lesions in MP-treated animals developed after MP treatment was completed. It would be interesting to find out whether there were any histological particularities in early lesions in MP-treated animals (even though there should be very few of these). These data would fit nicely with the relevant paragraph presented in Discussion.

Reviewer #2 (Public Review):

The authors compiled camera-trap datasets from across North America to test hypotheses about how animal species adjust their daily activity cycle to urban development and human activity. They found that multiple species adjust their diel cycle, with human activity clearly supported as a driver.

The paper is very well-written. It is clear, concise, and the narrative is lovely to follow. The background information provides a strong foundation. I do note that previous research on diel activity from camera traps is a little sparse, selecting only a couple cursory examples.<br /> I have no other suggestions for the Introduction, which is a nice read.

Methods:

The methods used are novel, interesting, and suitable to the questions at hand.

How might the different sample sizes in different cities, impact the results? Were there any correlations between sample size and the attributes you measured, such that bigger, more intensely developed and used cities were sampled more than smaller, less developed cities? I appreciated the information presented in Table S4, and I note that cities varied widely in the various metrics. Some correlation tables and variance inflation factor (VIF) estimation should also be presented to assure the reader that the highly unbalanced sampling design necessarily arising from UWIN did not influence the results and hence conclusions.

Why did you choose to discretize animal detections into these bins, rather than using continuous time as several animal activity packages allow? The use of Ridout and Linkie (2009)'s R packages is very common in diel activity pattern analysis and I wonder why you chose this categorical approach instead? I suspect it has to do with the necessary sample sizes, which are restrictive, but I would like to see your rationale here.

Line 501: You used city as a random effect, which makes sense. However, did you consider using city-scale attributes as fixed effects? A random effect is essentially a bin for unexplained variation, but there are several attributes of city (Table S4) that might explain some variation expressed in this level of the sampling hierarchy. This relates to my comment above about whether within-city attributes might be masking (or amplifying) some of the fixed effects that you did model. Notwithstanding these comments, the analysis selected is appropriate to the question and conducted properly.

Results:

The Results are clear, concise, and well-presented. I have no comments or suggestions for improvement.

Discussion:

This is also well-written and clear, following an enjoyable logical narrative. The conclusions follow soundly from the results. I have very little to offer to the Discussion, despite my best efforts. I might suggest that some context of the importance of urban wildlife here might be useful in your closing sentences. This paper will have a strong impact in the field, but this is not fully conveyed therein. Critics might doubt the importance of urban wildlife, given that most of wildlife occurs outside urban areas. The growth of urban areas globally, and the projections for the future, signal that urban areas encroaching on wildlife ranges will only grow, requiring that we plan human spaces that can also accommodate wild spaces.

Reviewer #1 (Public Review):

Gallo et al. use camera trap data collected across a range of cities in the US to explore how mammals adapt the timing of their activity to a human-dominated activity. They found that activity patterns are highly flexible, varying across and within species, but overall were able to determine that mammals in urban areas can adapt their activity to reduce risk. The diversity of species involved means that no overall pattern emerged, but the species-specific patterns discussed by the authors are justified by the data.

The argument in the introduction needs tightening, and further clarification and information are required in the methods. The terminology also needs greater consideration. Artificial light at night and the skyglow that it generates means that there is often light well above natural levels throughout the night, and as such the term the 'darkest hour' should be revised.

Reviewer #1 (Public Review):

Solving the puzzle of this paper was clearly not easy, and the authors used an impressive set of tools and statistical methods to get to the bottom of what they observed in a very creative way. However, the presentation of the manuscript and its relevance could perhaps be improved.

First, I find the arguments in some parts of the manuscript to be a bit awkwardly formulated. For example, there is much discussion about social evolution and the paradox of why cells invest into rhamnolipid production, but this does not seem to be the topic of the paper, which focuses more on understanding P. aeruginosa's metabolism. Instead, there is very little discussion about the origin of these isolates and to what extent these findings may be relevant for P. aeruginosa's natural environment. I understand that this may be very speculative, but there could at least be more discussion on why glycerol was chosen as a growth medium, and what would happen if a more realistic growth medium were used instead. What environment does this bacterium experience and might it be surrounded by other species that could reduce oxidative stress?

The overall message of the paper could be clarified: essentially, cells only produce rhamnolipids when they are not experiencing oxidative stress. I am sure the message is more nuanced, but this is not clear from the current abstract.

Reviewer #2 (Public Review):

Santamaria et al. combined phenotypic analysis, growth curve analysis, metabolomics, flux balance modelling and transcriptomics in order to study the mechanisms behind the diverging levels of rhamnolipid secondary metabolite production in clinical Pseudomonas aeruginosa isolates when grown on glycerol as a sole carbon source. They show that lower levels of rhamnolipid production can be linked to a lower ability to reduce the oxidative stress caused by primary metabolism on glycerol as the sole carbon source. The data are consistent with a model of regulation where microbes can produce secondary metabolites -such as rhamnolipids- only after they meet the 'primary requirements of energy production, biomass synthesis and reduction of oxidative stress'. This adds another layer to the possible regulatory mechanisms microbes can use to minimize the individual cost of cooperation via secondary metabolites.

Overall the data analysis is sound and of a remarkable depth. The findings are well-substantiated and the goals, methodologies, results and interpretations are clearly described.

My main question is how relevant growth on glycerol as a sole carbon source is for clinical Pseudomonas aeruginosa strains. The key finding of this work is that rhamnolipid production depends on the ability of the strains to tolerate oxidative stress associated with growth on glycerol as a sole carbon source. Since growth on glycerol puts substantial strain on the primary metabolism it is conceivable that the oxidative stress associated with metabolism in this artificial condition will be higher or acting on different cellular components than in the natural habitats within the body. This raises the question as to whether the observed regulation is an evolutionary adaptation or rather an artifact of growing the isolates in this lab environment. The observation that a substantial part of the clinical strains did not have the ability to deal with the oxidative stress during growth on glycerol suggests that strains do experience lower levels of oxidative stress within the body. Please motivate.

Several mechanisms of metabolic prudence have been described. It would be good to systematically compare similarities and differences between the proposed mechanism and earlier described mechanisms. This should provide a more nuanced view of the novelty of the proposed mechanism.

Reviewer #1 (Public Review):

The authors of this study conducted a long-term ecological study using a night-trap to determine how Episyrphus balteatus migrates in China. Furthermore, stable isotope analysis was used to identify the heterogeneous origins of migrant hoverflies. The authors also employed population genetics to demonstrate that hoverfly populations are not locally isolated, consequently supporting indirect migration events of E. balteatus as well. Several approaches support the same conclusion. Overall, the authors provide sufficient evidence to indicate that E balteatus migrates seasonally. It is, however, difficult to understand what the authors want to express in the later part of the manuscript (from Figure 5 to Figure 8). Lastly, it is still unclear whether hoverflies migrate at night on purpose or if other factors influenced their behavior at night.

Reviewer #2 (Public Review):

This study of the migration ecology of the hoverfly Episyrphus balteatus is quite exceptional in both the long-term nature of the study, and in the diverse array of techniques applied to the study. The authors should be congratulated on their ambition and comprehensive approach, as in more than 20 years of research in this field I have never seen a paper with quite so many techniques used to support their conclusions. Firstly, a long-term dataset (16 years) of nightly light-trap catches from a small island in the centre of the Bohai Gulf, East China, at least 40 km from the nearest mainland, is used to explore the seasonal and annual patterns of nocturnal over-sea migratory flights of this species - the data clearly demonstrate that the species is an abundant migrant, commonly engaging in nocturnal flights over the sea. Secondly, the authors document that the migrants feed on, and frequently transport, a very diverse array of plant pollen using two complementary techniques (morphological identification of pollen grains on the body surface, and DNA barcoding of ingested pollen), which shows that this species is a very important provider of pollination services. Thirdly, the authors employ a variety of techniques to demonstrate that the hoverflies captured on the island are long-range migrants either from south of the trapping location (during the spring migration period) or from north of the trapping location (during the autumn migration period). These techniques include: (1) atmospheric trajectory simulations; (2) identification of pollen from plants only found in distant regions; (3) stable isotope analyses of wing material; and (4) population genetics.

The authors come to three important conclusions, two of which are strongly supported by the data, but one isn't supported in my opinion. Firstly, they conclusively demonstrate that this species of hoverfly is a highly abundant, consistent, bi-directional long-range migrant which makes annual movements through East China. Their data provides very strong support for this finding, and it matches previous findings on this species in Western Europe (Wotton et al. 2019; Gao et al. 2020); it is very interesting to see similar patterns of migration at opposite ends of the Eurasian landmass. Secondly they demonstrate the importance of this species for pollination in East Asia, and their pollen analyses provide excellent support for this aspect, again confirming the previous findings from Western Europe (Wotton et al. 2019). Thirdly, they conclude that nocturnal migration is an important feature of the migration ecology of this species, something which has not been discussed elsewhere in the literature; for reasons I will explain in the more detailed comments, I do not believe their data support this third contention, and I think this part of the manuscript needs to be rewritten.

My overall opinion of this manuscript is that it contains some highly interesting and important data which strongly support the previous studies of this species, and demonstrate that the migrations of this hoverfly are an important component of agro-ecosystem in East Asia. However, in my opinion the manuscript suffers from having too many strands, none of which are afforded the space necessary to fully explain and explore their findings. While I applaud the ambition of the authors and the extremely comprehensive nature of the study, I think there is basically too much material for a single paper. My advice would be to split the paper into at least two studies, and I provide suggestions for this in the more detailed comments to the authors.

Reviewer #3 (Public Review):

Little known about the migration of hoverfly in eastern Asia, and this paper delineated the trans-regional movement of hoverfly in China with very solid evidences from various ways, including searchlight trapping, stable hydrogen isotope, population genetics, pollen marker and molecular gut-content. Overall, this is a wonderful work and a great example of scientific detective work to understand insect long-distance migration. Here, I provide some comments that I hope can improve the paper.

1) "Given the substantial night-time dispersal of E. balteatus, this species possibly adopts a 'dual' migration strategy". Because Beihuang Island is an island about 44 km away from the mainland of Liaoning Province, and 60 km away from the mainland of Shandong Province. Through the distance is not much very far, it is still possible that the catches of hoverfly take daytime migration and have to continue their journey in nighttime over sea.

2) The authors present a great deal of work, and they tried to show all results they have obtained. I think some of the result could be moved into the Supplementary Material, and some key conclusions need further explanation. For example, Figs. 6-8 are three large figures but accompanied only a very short paragraph that describes them. I think each figure could be simplified, and more description and more explanation would be welcome.

3) The presentation of the narrative could be improved.

Reviewer #1 (Public Review): 

The authors perform very careful growth speed and growth fluctuation analysis of microtubules growing in vitro in the presence of either GMPCPP or GTP. This is essentially a re-examination of highly cited work published by Gardner et al in 2011. The quality of the current analysis is improved compared to previous work, because the authors use a label-free imaging method providing higher signal-to-noise-ratio data and allowing longer imaging at higher time resolution, and because the fluctuation analysis is technically more advanced. The main conclusions are that growth fluctuations are lower than previously published by Gardner et al., however in the presence of GTP they are still higher than expected, as reported previously, but less dramatically different than proposed previously. The authors propose a kinetic model that includes the possibility of GTP hydrolysis causing a hypothetical (but plausible) slowdown of tubulin addition when a GDP tubulin is exposed at the microtubule end to explain the larger growth fluctuations in the presence of GTP. This is an important study proposing a new model for the origin of the natural growth fluctuations of microtubules. In the future, this work will also have an impact on our understanding of how regulators of microtubule polymerization act. Overall this is a carefully performed study, with especially the experimental and data analysis part being of very high quality. 

Questions that the authors might want to address: 

1. Can the measured growth fluctuations in the presence of GMPCPP be explained by an even simpler 1-dimensional single protofilament growth model? Or is indeed a 2-dimensional model required that the authors use here. 

2. Can the measured taper of growing microtubule ends be used to further constrain the fits to the data? 

3. The authors mention that they choose the optimal kon from the fits to the GMPCPP data also for the fits to the GDP data, if this reviewer understood correctly. Is this justified, given that the longitudinal interactions are probably different in a GMPCPP and a GTP lattice? 

4. How reliably can the kinetic model of the authors predict the GTP hydrolysis rate at growing microtubule ends and how does this rate compare to previously published measurements or models?

Reviewer #2 (Public Review): 

This is a very thorough and clear study, in which the authors used IRM to measure time series for growing MT lengths with high resolution and accuracy and for long time intervals. This precision and duration of measurements allowed them to quantify not only the growth rates, but also fluctuations of these rates. Then, they turned to thier previously used computational Monte Carlo model, which considers MT lattice and assigns rates of arrival and affinities to tubulin dimers depending on local MT tip geometry: there is a difference whether the tubulin is binding to the lonely protofilament tip, or into the 'corner', with added lateral interaction. 

The elegant part of the study is this: it is impossible to fit the model parameters uniquely from just average growth kinetics, but fluctuation measurements give the additional constraint, which allows to make an interesting and novel conclusion: the dimers bind to the protofilament tips slowly but tightly, so basically the MT growth can be accounted for by individual tip growth. 

All these results were obtained in the absence of hydrolysis. Then, the authors use GTP tubulin and find that the fluctuations increase drastically. Their model can only fit the measurements assuming that sometimes a GDP-subunit occurs at the MT tip, and this hinders the growth. This is somewhat at odds with what researchers think, but I find this conclusion logical.

Reviewer #3 (Public Review): 

This paper applies rigorous quantitative microscopy to an open problem in biophysics, namely the kinetics of microtubule dynamic instability. Previous studies that analyzed these kinetics found them to be "fast", which is to say that tubulin binds very frequently to the end of a microtubule, but falls off almost as frequently (Gardner et al. Cell 2011). This "rapid self-assembly kinetics" is arguably the prevailing conceptual framework for microtubule polymerization. In contrast, the present study finds the kinetics of polymerization to be "slow", with infrequent binding events that persist for longer periods of time. The conceptual shift from "fast" to "slow" has significant implications, in particular for the mechanisms of microtubule polymerases. 

The difference in results from Gardner et al. Cell 2011 comes from 2 places. First, the authors use interference reflection microscopy (IRM) instead of fluorescence. Using IRM allows them to image growing microtubules for long time intervals at high frame rates. Thus, a single microtubule can generate a long plot of length versus time, in contrast to Gardner, who concantenated many short traces together to create a long plot. Second, the authors apply sub-pixel drift correction to their movies and show conclusively that pixel-based drift correction contributes to the appearance of "fast kinetics". Figure 1 (and its supplements) are an outstanding example of technical rigor, where different analyses are displayed side-by-side to justify the conclusion of slow kinetics, particularly for the growth of GMPCPP-tubulin. 

With GTP-tubulin in the reaction, growth is significantly more variable. To explain the increased variability, the authors use a computational model to test a particular hypothesis, namely that the tubulin at the very end of a microtubule can be in the GDP state, and that these terminal GDP-subunits have a reduced affinity for incoming dimers. In other words, the simulations argue that exposure of a GDP subunit at tip could "poison" that protofilament, and because that protofilament now lags behind the others, the microtubule end position fluctuates. But the manuscript is missing an experimental corrolary for their model of GDP exposure. And there are other potential explanations for why GTP-tubulin growth could be more variable than GMPCPP-tubulin growth. For example, we know that GMPCPP microtubules are stiff and uniformly 14-pf. Perhaps growth fluctuations are linked to tubulin's flexibility, which is included as a parameter in some computational models (e.g., Zakharov Biophys J 2015). The modeling here has demonstrated that GDP exposure is sufficient to explain growth variation, but they have not demonstrated that it is necessary, which would require experiments. The authors should spend part of their discussion considering alternative models and arguing explicitly for why trans-acting nucleotide makes sense. 

The idea that GDP exposure could "poison" a protofilament end reminded me of eribulin and Doodhi et al., Curr Biol 2016. After all, eribulin is a bona fide poison (err, microtubule-targeting anti-cancer drug). Doodhi et al. defined the binding site for eribulin as the terminal end of b-tubulin, meaning that it blocks incoming subunits. They showed that the drug perturbed dynamic instability significantly, induced catastrophes, created "split EB comets", etc. Is the poisoning effect of eribulin related to the poisoning effect of GDP-exposure? Are eribulin and GDP-exposure both explainable as alterations in longitudinal affinity? A discussion of this comparison would be interesting. 

Lastly, the relationship of to the authors' previous computational work (Piedra et al. MBoC 2016) needs further elaboration. In Piedra et al., their model allows GTP exchange into the poisoned GDP-terminal subunit. In this manuscript, the exchange is disallowed, which is the same as saying that its rate is 0. Is this reasonable? In Fig. 3B of Piedra, they plot how catastrophe frequency is affected by the rate of GDP->GTP exchange. If exchange is slow, then the impact of exchange on catastrophes is minimal. Is the same true for growth? The current manuscript should be viewed as an opportunity to elaborate on Piedra to the extent possible. It's clear in Piedra that the GTPase rate itself matters in terms of the sensitivity of catastrophes to GDP->GTP exchange rates. The authors write "a finite rate of exchange would only modulate the amount of GDP on the microtubule end for a given GTPase rate; it would not eliminate the 'poisoning' effect of GDP exposure that increases fluctuations in growth rate." But the interesting question is the sensitivity of the growth rate to the finite rate of GDP->GTP exchange.

Reviewer #1 (Public Review): 

The authors argue that in the absence of flow-sensing feedback, fluid-structure coupling alone is sufficient to generate upstream orienting behaviors of fish. If true, this would be an interesting phenomenon of moderately wide interest.

The strengths of this paper are: 

1) A needed consideration of coupled interactions in fluids that can potentially augment or replace flow-sensitive feedback behaviors. <br /> 2) A simplified mathematical model that reveals an interesting passive hydrodynamic mechanism of rheotaxis that exists only above critical flow speeds <br /> 3) The authors do a respectable job combing the literature for lateral line studies. 

The weaknesses of this paper are: 

1) The discrepancy between what can be supported by the biological literature and the simplification of the model is large. One has the impression that the authors are fitting a round peg in a square hole rather than uncovering a realistic mechanism for behavior in the absence of sensory information. Part of this is not the authors' fault, it is the lack of relevant experiments (e.g. inconclusive or indirect) in the biological literature. <br /> 2) The authors' claims are not justified by their data. They acknowledge shortcomings of their model as a departure from real animals, neglecting elasticity and inertia of the fish and added mass effects. Water is known for its non-linear properties, and yet their model assumes a linear hydrodynamic feedback system. <br /> 3) Biological relevance is lacking. Real fish don't orient in the absence of all sensory inputs, and yet the model does not account for vision, balance and touch. <br /> 4) No discussion or interpretation of neural feedback (reafference and motor copy re Bell and Bodznick) that could alter the interpretation of their results in the context of the literature. <br /> 5) Justification of results based on few biological papers that have their own shortcomings. <br /> 6) The relevance and importance of the finding is exaggerated.

Reviewer #2 (Public Review): 

The paper describes a dipole model of fish swimming. The model is very much based on existing work. But more importantly the model entails several parameters and is validated in rather qualitative terms. I would suggest comparisons of this 2D model with 2D viscous simulations that should be easy to produce. At the moment there are far too many parameters that are evaluated in rather qualitative terms. There is no sensitivity analysis of any form to warrant reassurance as to the validity of the results. In turn the results have only some qualitative value.

Reviewer #3 (Public Review): 

This manuscript proposes a hydrodynamic model of a fish in a channel flow. This work is based on important assumptions (dipole model, potential flow, parabolic channel flow) that lead to a simple dynamical system. This dynamical system is only stable when the incoming flow is over a threshold value. This result is compared with experimental data of the literature. 

Although the problem addressed is interesting, the assumptions of the model are not justified and probably not appropriate in the context studied. First, the dipole model used to model the flow generated by the fish does not seem appropriate to study small animals that swim with bursts. Second, the channel flow is a superposition of a constant velocity and a parabolic profile, which is not what is expected at moderate Re. Finally, the feedback mechanism based on vorticity does not seem plausible and, since vorticity is a linear function of the cross-stream coordinate in a parabolic flow, it is not distinguishable from visual feedback. 

The other issue is the comparison with experimental data. The model predicts a channel flow threshold, that is necessary to have a stable point. But this is not the only prediction, it also predicts the dynamics around this point, for instance. The authors choose to only compare the threshold and their comparison presented as tables is mostly inconclusive.

Reviewer #1 (Public Review):

TMEM175 is a recently (Cang et al., 2015, Sell 162) discovered new type of cation channel, strongly diverging from the 2+4TM+pore loop fold of canonical K+/Na+/Ca2+ channels. It has been found to be relevant for the development of Parkinson's disease. Oh et al. recently published a cryoEM structure of the human TMEM175 (Oh et al. 2020, Elife 9). This is a follow-up work in which they perform further structural refinement and molecular dynamics simulations to elucidate the mechanism of selectivity in this channel.

The calculations and experiments confirm the hypothesis formulated in their own previous and other works that a hydrophobic constriction formed by a ring of leucines (isoleucines in bacterial isoforms) in the center of the hourglass-shaped pore provides the gate for the channel as well as plays a major role in selectivity. They find that selectivity of K+ over Na+ arises from the interplay of the dehydration energies and ion-protein-interaction energies of the two ions: Both the bulk water and the channel pore actually favor Na+. But the water favors Na+ more than the pore does, leading to a better permeability for K+. These data are interesting, because they show how the electrostatics of a whole pore contribute to create an alternative selectivity mechanism for K+ ions.

The conclusions of this paper are mostly well supported by the data, however a lot of interesting aspects could be worked out better and alternative hypothesis and publications in the field are not considered adequately.

Reviewer #2 (Public Review):

TMEM175 is a unique potassium channel that lacks a canonical selectivity filter. In this work, Oh et al. elucidated the mechanisms of permeation and ion selectivity in TMEM175. Specifically, they improved the resolutions of two existing cryo-EM maps of TMEM175 - in a closed and a putatively open state.<br /> With the reprocessed structures (not published at the time of the review), the authors used an enhanced sampling molecular dynamics (MD) simulations technique (multiple-walker Metadynamics) that allowed to reveal the main features of ion permeation. First, the previously putatively open structure was found to be indeed conductive in simulations. A single-ion mechanism, distinct from the multi-ion characteristic for canonical potassium channels, was observed, enabled by a novel collective variable in Metadynamics simulations. This variable avoided preliminary assumptions about the ion permeation mechanism. Second, a crucial part of TMEM175 was found to be a hydrophobic constriction, formed in the pore by four isoleucine residues (two per monomer). The largest energetic barrier for ion permeation was shown to be located there, as ions needed to experience a large degree of dehydration in order to pass this constriction. However, the dehydration penalty was shown to be offset through favorable electrostatic interactions of potassium ions with the channel. The ability of the open structure of TMEM175 to conduct ions was further confirmed using MD simulations with applied electric field.<br /> Another important aspect of this work was the clarification of the selectivity of TMEM175 for potassium ions. Using a similar MD approach but with sodium ions instead of potassium, a higher barrier at the constriction was detected. Together with free energy perturbation simulations, this suggested the driver for the selectivity to be the difference in dehydration energy between sodium and potassium ions in the constriction. The role of the constriction for selectivity was further underlined by simulations and electrophysiological recordings of TMEM175 mutants: an enlarged constriction lead to a lower selectivity for potassium ions.<br /> This study provides a mechanism for ion permeation and selectivity in a potassium channel that differs greatly from other ion channels. Given the previously shown association of TMEM175 mutants with Parkinson's disease, this mechanistic insight from this work may lead to a better understanding of this association. The conclusions in the manuscript are certainly exciting and informative, however not fully supported by the data.

Reviewer #3 (Public Review):

Oh et al. examine the structure and function of a non-canonical K+ channel, TMEM175, using a combination of techniques (cryo-electron microscopy, computer simulations, and electrophysiology). They show that a surprisingly localized segment of the pore interior controls not only gating but also ionic selectivity of the channel. Improved re-processing of published EM data leads to a refined structural model of the open state of the channel that is subjected to detailed analysis using molecular dynamics simulations. Biased-sampling simulations using metadynamics confirm that a thin and narrow hydrophobic constriction consisting of 4 amino acid side chains, which is too narrow to allow water or ion permeation in the closed state of the channel, constitutes a free energy barrier to permeating K+ ions in the open state of the channel. Free energy perturbations confirm the moderate preference for K+ over Na+, which is attributed to a smaller desolvation penalty for K+ at the constriction. The role of the constriction in ionic selectivity is tested by electrophysiology measurements.

Strengths: This is a well designed and executed study that adds to the field of K+ channels and ion channels in general. The overall complementarity between the techniques used in the study is excellent and helps support the conclusions of the paper. The inference from the structural model that the channel is open is confirmed by the simulations, and the electrophysiology confirms the role of the constriction predicted by the simulations.

In addition, the excellent agreement between the free energy profiles or potentials of mean-force (PMF) for K+ and Na+ permeation across the length of the pore determined by metadynamics and the free energy perturbation results for the reversible replacement of K+ by Na+ at the barrier top and in bulk water validates the computational methodology, suggesting that both calculations are converged. The agreement between the relative barrier heights in the PMF and the relative free energy of the two cation types in water and at the barrier top is not trivial and offer independent validation of the relative "solvation free energy" at the constriction by exploiting two distinct pathways in a thermodynamic cycle (DeltaDeltaG calculation).

Reviewer #1 (Public Review):

Here using visuomotor rotation task the authors examine if associative learning applied to sensorimotor learning/ adaptation and see if integrative account of these two forms of cerebellar-dependent learning applied. There is a useful introduction to the article referencing past work on contextual effects seen in motor learning.

Relating motor control experiments to classical conditioning approaches to associative learning is certainly interesting.

The authors paired movement-related feedback with neutral auditory or visual contextual cues that served as conditioning stimuli. The authors found trial-by-trial changes in feedforward movement kinematics and the results seem convincing.

I found the methods really quite hard to follow. I also feel the overall presentation of results and the discussion could be clearer and more concise.

Reviewer #2 (Public Review):

This paper provides a compelling account of the role associative learning plays in sensorimotor adaptation. In contrast to previous work, the authors show that arbitrary stimuli (light/sound) can be used as contextual cues to differentiate between sensorimotor perturbations/states. The authors describe these results in the context of associative learning, and across 2 experiments provide evidence for 2 key signatures of associative learning: differential conditioning and compound conditioning. The authors believe the key parameter for observing such associative learning is ensuring a strict temporal relationship between the cues and their associated movement-related sensory outcomes. This is clearly written article that uses well-designed experiments to not only provide new insight into a phenomenon that has received a lot of previous attention (i.e., the inability to use arbitrary stimuli as contextual cues in adaptation) but also places these results in a novel mechanistic context (associative learning). Whilst sensorimotor adaptation (and the tasks used to assess it) feel heavily overused, this work is important in trying to align 2 key cerebellar processes which often feel difficult to integrate. I can envisage the concepts proposed (and the tasks developed) within this article being the foundation of a rich new line of inquiry into the role of associative learning in adaptation.

Despite many positives, there is a key issue with the current paper which make some of the author's conclusions unjustified. Specifically, the authors predict & conclude that the key parameter for observing associative learning when using arbitrary stimuli as contextual cues is the temporal relationship of these cues to the feedback. They provide compelling evidence of associative learning however at present provide no evidence of the importance of this temporal relationship. Considering this is assumed to be the key difference between the current results and previous work who have failed to find an effect, this is a key omission. Other issues include:

Exp 1 probe phase results: Whilst not significant (n-1 x n interaction), there seemed to be a clear difference between CS+ trials within the different trial n-1 contexts (Fig 1D). In fact, this difference seems bigger (and as consistent) as the meaningful/significant differences which are focused on. Interestingly, the RW model predicts a clear n-1 x n interaction however it is not discussed why (Fig 1F). To me it seems that the behaviour (at least partially) and model reflect an interaction between trial n-1 and n during probe trials however this is currently not discussed.

Exp 1 magnitude of effect: Supplementary figure 1 (raw heading data) reveals that the contextual effects observed in Figure 1 were relatively small. Specifically, the differences between CS+ vs CS- (1-degree) are approx. 6% of the total adaptation that occurred (15-degrees). Whilst this is referred to within the final exp 1 analysis (fig 2B), the magnitude of these contextual (associative learning) are not explicitly discussed. Although I believe the results are important, the article reads as if these conditioning effects were large when in fact other people might conclude that conditioning had little impact on adaptation (as similar adaptation was observed across both contexts (assumed as this data is not currently provided) and performance looks very similar to exp 2 where there was no 0-degree context).

Exp 2 results: It was unclear why the RW model would predict a negative heading angle within the single CS conditions (Fig 3C)? Whilst a weaker conditioning response would be expected due to compound conditioning, would you not expect this still to be positive? Why would the model predict extinction to occur and why is this seen in the behaviour? The details of this result (and the predictions of the model) are currently not discussed.

What is the CS (confusion between results & discussion)? Between lines 395-410 the authors describe the primary CS as being the heading angle ('the movement plan itself, rather than the target cue, that constitutes the primary CS'), however in the results (lines 74-96) they describe the CS as being the arbitrary cue ('When considered through the lens of classical conditioning, the arbitrary cues are the conditioned stimuli (CSs)') and the CR being the heading angle ('the conditioned response (CR) would be the movement heading angle elicited by a CS'). As a result of this discrepancy, this section of the discussion was confusing (lines 387-410 & then again from line 433). Are the authors saying that sometimes the heading angle/plan is the CS and other times it is the CR...? How does this all align?

Reviewer #1 (Public Review):

Fukuda et al investigated patterns of DNA methylation in human male germ cells, aiming to explain why some elements in the human genome are resistant to the global wave of DNA demethylation occurring during primordial germ cell differentiation. Many of these are transposable elements of various kinds, notable targets of repression mechanisms in germ cells to prevent their spread between generations of individuals. The authors have found links between subfamilies of transposable elements and the presence of binding sites for specific KRAB zinc finger proteins, a large family of epigenetic regulators. The authors then further dissect these findings, with correlation to differentially methylated loci between individuals in sperm.

The study is well designed and although much of the initial analysis was done with a limited sample size (sperm from 2 donors), the important conclusions have been replicated in a second dataset with a few more donors, and further confirmed them with independent experiments by amplicon sequencing. The result are compatible with current knowledge of the KZFP family, as they are known to affect DNA methylation levels in stem cells. The findings related to interindividual DNA methylation level differences are interesting, especially in regard to their potential to trigger biological problems such as infertility. This is also somewhat related to recent publications in the field on metastable epialleles associated with transposable elements in both mice and human, a few of which have been linked to KZFPs so far.

There is a few weaknesses, but they are appropriately discussed by the authors themselves. For example, they acknowledge that they are working with an incomplete set of KZFP binding factors binding sites - the family contains 350 protein-coding genes in humans, with data for binding for approximately 230 of them. Also, the sample size is low and some of the wording related to conclusions could be toned down to. Finally, most conclusions of the paper are purely descriptive / correlative - again, the authors acknowledge this in a late section of the manuscript, but some sentences in other parts are worded in a way that could lead some readers that these are facts and not speculation.

Nonetheless it is reporting an important and novel finding that expands our understanding of the ways KZFPs can subtly affect human biology and paves the way for further studies.

Reviewer #2 (Public Review):

Fukuda et al. use whole genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) data obtained from sperm and human primordial germ cells (hPGCs), as well as KRAB-ZFP protein ChIP-seq data obtained from HEK293T cells, to study the relationship between DNA methylation, KRAB-ZFP binding and genome-wide transcription of LINE-1 (L1), SVA and LTR12 retrotransposons.

This work aims overall to elucidate pathways silencing retrotransposons in the male germline, in particular making new (and known) links between ZFPs and DNA methylation. The focus here ends up being on immobile retrotransposons, as L1s (bound by ZNF93 and ZNF649) and SVAs (bound by ZNF28 and ZNF257) capable of mobilisation either do not have binding sites for the identified ZFPs, or have far fewer than their older relatives. The relationships between L1, ZNF93 and ZNF649 has been reported previously (Jacobs et al., 2014, Nature; Fernandes et al., 2018, bioRxiv). That older retrotransposons have more binding to these ZFPs, and are more methylated in hPGCs, is based mainly on correlation. Overall, I thought the subject matter was interesting but I have substantial reservations around the analyses, particularly the more novel results related to SVA. As the work stands it is not clear whether ZNF257 or ZNF28 are reinforcing DNA methylation on SVA. The claims around this repression being transcriptionally-directed or varying significantly amongst individuals, for biological as opposed to technical reasons, appear preliminary at this stage.

Specific comments:

1) The use of WGBS to analyse very young retrotransposons, like L1HS and SVA_F, has potential caveats. One of the most important of these is that the CpG islands most likely to be differentially methylated for these elements, in somatic cells at least, are internal to their sequences (e.g. PMID: 33186547). This includes the SVA VNTR sequence, which is where the vast majority of proposed ZNF28 and ZNF257 binding motifs reside (Fig. 2F). Does WGBS, using only uniquely mapped reads as done here, resolve these regions sufficiently to identify differential methylation?

2) Why does Fig. 1D have only 36 full-length L1HS copies? The definition of a full-length L1 here (>90% consensus length) should yield (from memory) >300 reference L1HS copies.

3) It would be useful to explain the inclusion of LTR12 as a representive ERV, as opposed to, say HERVK, which has been studied in hPGC like cells recently (PMID: 35075135).

4) The exo ChIP-seq for a variety of ZFPs was obtained from published data generated using HEK293T cells, whereas the WGBS is from sperm and hPGCs. What evidence can the authors point to to be reasonably sure that the ZFP binding patterns from HEK293Ts carry over to the male germline in vivo?

5) In Fig. 3C it appears quite a few L1PA3s have ZNF649 peaks and yet the motif for ZNF649 has two mismatches to the L1PA3 consensus (Fig. 3F). Yes, L1HS has one more mismatch than L1PA3. It would be useful to explain further why two mismatches are acceptable whereas 3 completely abolishes binding.

6) Line 244: "More than 90% of full-length SVA_B-F copies could be analyzed by SVA amplicon-seq". What is the basis for this calculation? Presumably the amplicon-seq doesn't give information as to where on the genome the SVA resides.

Reviewer #1 (Public Review):

In their manuscript, Rafiei et al. investigate the molecular architecture of the microtubule-associated protein, doublecortin-X (DCX), bound to the microtubule by integrating data from chemical cross-linking experiments with available crystallographic and cryo-EM structures. DCX contains two doublecortin (DC) domains (termed N-DC and C-DC) connected by a linker region and an unstructured C-terminal tail. The DC domains have both been shown to be important for its binding to microtubules. Prior work has shown that DCX interacts with the GTP microtubule lattice through its C-DC and the GDP-lattice through its N-DC. In addition, it is well-established that DCX cooperatively binds the microtubule lattice, but how this cooperativity is achieved is still unclear. This study evaluates inter- and intra- DCX crosslinking using a protein isotopic labeling technique. Combined with modeling, they are able to show that DCX binds to microtubules through its N-DC, which subsequently induces DCX to self-associates through its C-DC and C-terminal tail domains; however, they do not perform any additional biochemical, single-molecule, or ensemble binding assays to support this model. This paper will be of interest to the microtubule community.

Reviewer #2 (Public Review):

The neuronal MAP doublecortin contains two homologous DC domains, referred to as NDC and CDC. Disease-causing mutations cluster in these domains and both have been implicated in microtubule binding. However, the stoichiometry of DCX:tubulin dimers on microtubules is 1:1, suggesting only one of these domains is DCX's primary microtubule binding module. Early structural studies by Kim et al, 2001, identified different properties of NDC and CDC, despite their predicted homology. High resolution structures of both NDC and CDC have since been determined using X-ray crystallography and NMR - the domains do adopt the same overall fold, although DCX CDC structures were determined either a) bound to nanobodies (Burger et al, 2016; 5IP4) or b) forming a domain swapped dimer in a protein purified at pH 10.5 (Rufer et al, 2018; 6FNZ).

The structures of microtubule-bound DCX have also been determined using cryo-EM - these show DCX's primary microtubule binding site is in the valley between protofilaments at the corner of four tubulin dimers. Most recently, the structures of full-length DCX at different microtubule polymerization time points have been captured at ~4A resolution (Manka & Moores, 2020). The structures of microtubule-bound CDC (6RF2) and microtubule-bound NDC (6REV) were thereby determined, but only a single DC domain at the DCX primary binding site has ever been observed.

Thus, despite the accumulated DCX structural data, a number of significant questions remain - notably, how is the full-length protein involved in binding to microtubules and what is the structural origin of the cooperative microtubule binding by DCX, which is mediated by CDC (Bechstedt and Brouhard, 2012)

Rafiei et al use an integrated structural modelling approach, synthesizing cross-linking mass spectrometry data of microtubule-bound DCX with existing structural information to provide new perspectives on DCX's microtubule binding mechanism. The particular strengths of this approach are that the data are both detailed, and capable of capturing the heterogeneity and dynamics of the system. The incorporation of prior structural knowledge into the workflow mean that these analyses sit alongside existing data, rather than being completely independent from them.

Overall, the authors confirm findings in the literature that NDC is DCX's primary microtubule binding domain for microtubules polymerized for >30 minutes. They also find that CDC mediates microtubule-binding dependent dimerization, which could explain DCX's cooperative behavior. There are several aspects of the study that would benefit from further analysis and/or discussion to clarify potential limitations of, or assumptions in, the approaches taken:

1) Although the authors report that the crosslinker used in their mass-spec experiments has been optimized for use with microtubules, it is not clear how general DCX binding is in this context. Specifically, how accessible are the well-buried DCX-tubulin interfaces at the primary binding site to the chemical cross-linkers on which the analysis depends? Accessibility issues could explain the results depicted in Fig. 3A, B, in which modelling that relies strictly on cross-links places NDC towards the outer edge of the protofilament, whereas inclusion of cryo-EM data in the integrated model places NDC in the inter-protofilament valley.

2) Based on analysis using the nanobody-bound CDC structure (5IP4), CDC appears to behave distinctly compared to NDC, such that CDC-derived cross-linking data are not consistent with the canonical inter-protofilament binding site. It would be good know whether this depends on the particular PDB used. It would be important to repeat this analysis using the microtubule-bound structure of CDC (6RF2), given that this structure is conformationally distinct from PDB:5IP.

3) Building on these findings relating to DCX-microtubule interactions, further analyses focus on DCX-DCX cross links, the formation of which are shown to be microtubule-dependent. The authors observe that >80% of DCX-DCX crosslinks involve the CDC domain and the C-terminus of the protein (C-tail), which is also consistent with NDC being the major point of microtubule interaction. However, a crucial aspect of this analysis is how readily microtubule-mediated oligomerization of DCX-DCX can be discriminated from the non-specific interactions that occur due to the high local concentrations on the microtubule surface. Given the proposed primary microtubule binding role of NDC, either set of interactions would presumably involve CDC and C-tail. Additional control experiments would have been beneficial here.

Although their data do not allow them to discriminate between different oligomerization states of DCX, the authors focus on dimer formation, and they interrogate their data based on interactions between CDC domains either i) retaining a globular fold or ii) adopting the "open" state seen in the 6FNZ domain-swapped dimer. According to the authors: "Based purely on fit of crosslinks, globular or domain-swapped modes are not distinguishable (Fig 4B). However, modelling of the main cluster shows strong similarity to the domain-swapped dimer structure"

This is a pivotal point of the manuscript. However, the precise quantitative basis of this discrimination is not clearly described. A useful control for these experiments could also be a previously published NDC-NDC chimera (Manka & Moores, 2020), which binds microtubules at the same inter-protofilament site but which lacks the CDC domain that is potentially mediating oligomerization.

The authors present an appealing model for CDC-mediated dimerisation of DCX on the microtubule lattice, but do not directly test its functional relevance. It will be crucial to explore the significance of dimer formation further. In the meantime, while questions concerning the mode of interaction of DCX (and its relatives) with the microtubule lattice are very much alive, the findings in the current study are not currently definitive.

Reviewer #3 (Public Review):

Rafiei et al. use crosslinking mass spectrometry and integrative/hybrid structural modeling to study the interaction of the regulatory protein, doublecortin (DCX), with microtubules. Specifically, they use a heterobifunctional, amine-reactive and photoreactive crosslinking reagent to generate residue-level contacts within DCX and between DCX and the alpha- and beta-tubulin subunits in the microtubules. The authors show that because of the short timescale of the crosslink formation, this approach proves superior when compared to conventional solution crosslinking chemistries such as those using homobifunctional succinimide esters. The crosslinking restraints are subsequently used to provide a model for the interaction of DCX with mictotubules at domain level resolution. Finally, the resulting model is interpreted in view of a proposed mechanism for microtubule nucleation and stabilization.

The study uses crosslinking to study a highly challenging system, i.e. the binding of a multi-domain regulatory protein (that itself homodimerizes) to an extended tubular structure, the microtubule, in what is probably a dynamic interaction. DCX consists of two ordered domains connected and flanked by unstructured regions, resulting in a lot of flexibility in the molecule and many possible domain orientations within the dimer and with the microtubule. Crosslinking, in isolation, is typically not the technique that one would consider ideally suitable to characterize such a system. However, the authors could successfully and convincingly demonstrate that using an optimized crosslinking strategy in combination with integrative modeling, deeper insights into the architecture of such an assembly can be obtained.

Given the limited resolution of the crosslinking restraints, the obtained experimental data does not allow for a exhaustive description of the structure of the system. For example, the location of the N-terminal DCX domain can more precisely determined so that it may be concluded that this domain is the primary interaction site, while the location of the C-terminal domain remains more ambiguous. As for the self-assembly of DCX, no clear preference of any orientation of the monomer units in the dimer is observed. This is not a deficiency of the work per se, but only reflects the relatively low accuracy distance restraints.

In summary, I consider this a very interesting application with impact on structural and functional biology.

Reviewer #1 (Public Review):

Staphylococcus aureus is an important bacterial pathogen of humans. Strain CC398 is unusual because it is associated with both humans and livestock. Human infections can originate from livestock, leading to concerns over 'spillover' of antibiotic resistance, which is common CC398. This study aimed to assess the severity of these concerns by investigating the genomes of a large collection of over 1000 CC398. They focused on antibiotic resistance genes and human immune evasion genes that tend to be inherited together and can be spread 'horizontally' between bacteria via 'mobile genetic elements' (MGEs). They found that different MGEs behaved quite differently, and this has implications for spillover. Some tetracyline resistance genes are highly stable and have been maintained since the origin of the livestock-associated CC398s about 60 years ago. This may be relevant because of the use of tetracyclines in farming. Other antibiotic resistance genes are less stable, having been acquired about 35 years ago. Human immune evasion genes come and go much more rapidly. The authors conclude that the stability of antibiotic resistance genes, compared to human immune evasion genes, means that when spillover occurs, antibiotic resistance is likely to be carried with it, and may not be lost quickly even in the absence of farming-associated antibiotics.

Reviewer #2 (Public Review):

The authors sought to reconstruct the evolutionary dynamics of mobile genetic elements (MGEs) in S. aureus using an impressive collection of genomes isolated over more than half a century. Their results confirm that the emergence of the CC398 livestock associated clade coincided with acquisition of the Tn916 transposon, which was then stably maintained. Following this, the CC398 clade acquired methicilin resistance via type V SCCmec, which was largely also maintained, but occasionally lost/truncated or replaced by other SCCmec types. In contrast, human associated pathogenicity genes were repeatedly lost in human-associated and livestock-associated samples. The authors conclude that different dynamics operate for resistance as do pathogenicity genes. The methodology regarding the analysis of the sequence data looks appropriate. The manuscript could more clearly articulate why finding maintenance of Tn916 is important, for instance, is it expected to impose a fitness cost in the absence of selection for tetracycline resistance? Further, from an evolutionary perspective, the authors could be more convincing about why directly comparing the patterns of acquisition of resistance genes and pathogenicity genes is a desirable thing to do.

Reviewer #3 (Public Review):

Matuszewska and colleagues aimed to describe the dynamics of mobile genetic elements in the S. aureus lineage CC398, which is split into a livestock-associated and a human-associated clade. They reconstruct the evolutionary history of this lineage and date several key events in the transition from the human to livestock hosts. Thereby, they are able to re-confirm several previous findings and add relevant knowledge about the dynamics of mobile genetic elements which were crucial in this host transition. They conclude that antimicrobial resistance genes may be maintained in the lineage longer than the lineage requires to acquire certain virulence genes leading to human adaptation.

The authors use a comprehensive collection of publicly available whole-genome sequencing data for this lineage of S. aureus and use state of the art analysis to investigate its population structure and the dynamics of mobile genetic elements within the lineage. These analyses have not previously been performed on such an extensive dataset and in this completeness. The results are in good agreement with previous findings and support their conclusions well. The stated aims are achieved.

The article is well structured, well written and the results are summarised in clear high quality figures, which makes the complex results easily available to the reader. A major drawback of the study is, however, the fact that most of the obtained results are a confirmation of previous knowledge. Hence, the contribution to the field is in providing a comprehensive overview of this knowledge, together with the dating of some of the key events in the evolutionary history of this lineage.

Reviewer #1 (Public Review):

In this study, Lensch et al., describe a novel approach to study the mechanisms of gene repression at the single cell level using a reporter construct expressing fluorescent proteins whose expression can be repressed by inducible expression of the KRAB or HDAC4 repressor proteins. The fluorescent reporter genes were either adjacent, separated by a 5 kb spacer or flanked by one or two cSH4 insulator elements. The reporter constructs were integrated into fixed genomic sites in two different cell lines and expression of the fluorescent reporter proteins monitored at the single cell level by imaging and flow cytometry following Doxycycline-inducible expression of the KRAB or HDAC4 repressor proteins. This approach revealed that repression KRAB or HDAC4 followed different kinetics, different mechanisms and with different distance dependency. Interestingly, the authors show that the cSH4 insulator did not always block the spreading of repression, but can play a role in coordinating the reactivation of gene expression. Despite the fact that the system used is artificial and simplified, the approach highlights how such approaches can be used to make mathematical modeling of the coordinated repression or activation of closely linked genes.

Reviewer #2 (Public Review):

This study explores how the transcriptional status of a gene can affect its neighbours. For this, the authors insert a dual reporter system location in two cell lines, separating or not the two reporters by a 5kb-spacer with or without an insulator, and subjecting one of them to repression either with a KRAB module or the histone deacetylase HDAC4, analysing by time-lapse microscopy and FACS how repressing one reporter impacts expression from the second. The approach is elegant, the work well conducted and its results nicely presented, with interesting differences observed between the impacts of the two repressors. However, a major concern regards the generalities drawn by the authors from a very limited set of observations (2 cell lines, 2 genomic loci, 2 chromatin modifiers, 2 promoters, a single distance of 5Kb as spacer, one insulator). Short of scaling up their analyses very significantly they should tone down their conclusions and refrain from statements such as "we propose a new model of multi-gene regulation, where both gene silencing and gene reactivation can act at a distance, allowing for coordinated dynamics via chromatin regulator recruitment" or (lines 66-68) "we used these findings to form a kinetic model that leverages information from changes in histone modifications to understand the dynamics of gene expression during both silencing and reactivation. Our results show that targeted transcriptional silencing affects neighboring genes". By comparison, a number or previous studies including by Amabile et al. 2015 and Groner et al. 2010 (both referenced but not much commented on), although centered exclusively on the impact of KRAB and devoid of the nice time-lapse analyses presented here, were much broader and already made many of the points stated in the present work, including for the latter study the demonstration that KRAB-mediated silencing can spread overall several tens of kb with an average maximal efficiency for promoters located within 15kb or less, results in loss of histone H3 acetylation, drop in RNA PolII and gain of H3K9me3 at these promoters through long-range spreading of this mark and of HP1beta from the initial KRAB-binding site and is dependent on the ability of KAP1 to recruit HP1. The present paper would considerably gain from placing its results in the context of the sum of these previous studies, discussing specifically what it truly adds to their conclusions.

Reviewer #3 (Public Review):

Heterochromatin can spread to neighbouring regions via feedforward "reader-writer" mechanisms and repress its target genes through physical compaction. However, little is known about the dynamics of heterochromatin spreading and the kinetics of target gene repression. In this manuscript, Dr. Bintu and colleagues use a synthetic approach by recruiting tetR-KRAB or tetR-HDAC in doxycycline inducible manner to upstream regions of two constitutive promoter driving reporters in tandem or spaced by 5kb to allow real-time measurement of heterochromatin spreading based on reporter gene expression upon dox induction/withdrawn. The authors also established the system in CHO cells and in K562 cells, for comparison. The authors revealed that KRAB-mediated H3K9me3 spreading is fast, and a function of spatial distance, leading to distance-related delay in gene silencing. In contrast, HDAC-mediated deacetylation is slow, and is subject to potential stochastic interactions between neighbouring nucleosomes, and therefore displays less delays in silencing. Furthermore, in contrast to common belief, widely adopted insulator has little effects on heterochromatin spreading in both KRAB and HDAC-mediated silencing. Finally, mathematic modelling reveals potential roles of histone acetylation and the acetylation reader-writer feedforward loop in fighting against HDAC-mediated spreading of gene repression.

A few limitations of the general conclusions are that, perhaps not unexpectedly, differences were seen in the behavior of the reporters at the integration sites in one cell line versus the other. This, of course, is not a fault of the authors and rather reflects the rigor of their approach. For example, no insulator configurations inhibited spreading of silencing upon HDAC4 recruitment in CHO cells, but insulators did attenuate HDAC4-mediated silencing in K562 cells. There were also differences in background expression of the constructs in the two cells. These issues raise challenges in general conclusions from the study, and underscore the particularities of genome function in different contexts.

Although the synthetic approaches adopted in this study can help tease out individual functions of chromatin regulators, previous studies using dCas9-fused with KRAB domains to inoculate heterochromatin domains in megabases of natural sites in the human genome indicated that spreading of H3K9me3 heterochromatin domains does not necessarily lead to gene silencing, and gene repression is more associated with the loss active histone marks, such as H3K27ac and H3K4me3. Therefore, it is possible that the model of kinetics of gene silencing in this current synthetic system may be valid in short distance (~5kb), but may over-estimate the roles of H3K9me3/HDAC spreading on gene expression in much larger scale.

Reviewer #1 (Public Review):

This study by Bhandare et al. applies endoscopic fluorescence imaging with head-mounted miniscopes and genetically encoded calcium sensors in awake behaving mice to document patterns of multicellular (including neurons and glial cells) calcium activity within circumscribed regions of the medulla oblongata (retrotrapezoid nucleus-RTN, Raphe magnus and pallidus nuclei, lateral parafacial region- pFL). These regions are proposed to have important chemosensory functions for the regulation of respiratory responses to elevated systemic CO2 (hypercapnia) and are critical for homeostatic regulation of breathing in mammals. Analyzing chemosensory properties of these medullary regions has been the focus of numerous studies, but the problem of analyzing regional multi-cellular chemosensory responses in the awake freely behaving rodent has not been previously addressed, so this paper represents an advance for the field. The authors importantly demonstrate chemosensory responses of neurons and astrocytes in RTN and Raphe, and activity profiles of neurons in pFL, and they describe substantial regional heterogeneity of cellular responses to hypercapnia in the RTN and Raphe regions. From this heterogeneity and distinct regional differences in chemosensory responses, the authors propose functional roles of these regions for detecting different aspects of the hypercapnic stimulus. In general all of the results presented suggest as justified by the data presented that cellular activity profiles in these various regions are more complex and encode different features for respiratory regulation than would be predicted from neuronal activity recordings in anesthetized animals. 

Strengths: (1) The authors demonstrate the successful technical application of the deep endoscopic fluorescence imaging approach for multicellular calcium activity imaging from key medullary structures involved in respiratory control in freely behaving mice. (2) Their novel results indicate functional diversity of neuronal responses and complexity in the encoding of chemosensory signals in key regions that have not been previously described from in vivo studies in anesthetized animals. 

Weaknesses: While the experiments are technically well executed for the most part in terms of implementing this imaging approach in freely behaving mice, important clarifications about experimental design and data analyses are required, and the authors do not fully discuss important technical limitations that may significantly affect interpretation of the results. A major concern with this imaging approach is whether the targeted regional neuronal and glial populations have been adequately sampled throughout the regions studied to reasonably understand the spatial and functional heterogeneity of the neuronal or glial hypercapnic responses. There is also the problem that cell identify has not been adequately established in some regions (e.g. RTN, pFL), which the authors need to specifically address to fully justify their conclusions about significance of their results. This is a particular problem for RTN neurons in which the chemosensory neurons that encode graded elevations of CO2, which were rarely found in this study, have an established molecular phenotype and this phenotype has not be sufficiently verified to know if the various response patterns identified in the freely behaving mouse are actually associated with this functional cell type. 

So while these new results indicate diversity of regional neuronal responses, many of these responses differ from the existing literature on how these cells are proposed to respond to CO2 from experiments with anesthetized rodents. Most notably, neurons in the RTN region were found to have an adapting excitatory response or were inhibited, rather than the expected preponderance of graded neuronal responses encoding the level of CO2; pFL neurons failed to exhibit a sustained expiratory-related oscillation predicted from studies suggesting that this area contains a conditional expiratory oscillator; and astrocytes failed to respond in terms of calcium signaling with elevated CO2. This underscores the need for additional technical clarifications to ensure reliability of the results, and for the authors to amplify discussion of the important caveats with their experimental design and functional interpretations.

Reviewer #2 (Public Review): 

The approach used here is a powerful method to monitor cellular activity in vivo. As the authors point out, this method allowed them to study activity of putative central chemoreceptors in unanesthetized adult mice, providing information that has not been attainable before using the standard approach of electrophysiological recordings from neonatal or anesthetized juvenile rodents. The results they obtained were different than expected, and call into question the hypothesis of primacy of the RTN in CO2 chemoreception. 

The results provide unique information that is very valuable in understanding the respiratory response to hypercapnia, but there are three issues with interpretation that the authors should more explicitly address, and which may alter some of the conclusions. 

First, since recordings were made from neurons in an intact brain, synaptic inputs were intact and all responses that were measured were due to a combination of intrinsic responses, synaptic input and glial modulation. The authors briefly acknowledge this, but it does not always seem to be taken into account when the results are discussed. Instead, some of the text seems to imply that the responses are all intrinsic. There should be an explicit discussion of the role of synaptic connectivity, and they should discuss the relationship of their results with data from more reduced preparations (about which there is little discussion). 

Second, expression of GCaMP6 was driven by the synapsin promoter in all RTN neurons and in one-third of raphe neurons, so all nearby neurons were transfected. There was comparison to post hoc immunostaining for vGlut2, Neuromedin B+ or TPH, but it is not clear what the identity of the recorded neurons was in many cases. This is mentioned, but then the text glosses over the lack of clear identification. 

Third, GCaMP6 measures calcium levels, not membrane potential. It is a pretty safe bet that in a given neuron calcium levels are a rough surrogate for firing rate, but there may not be a linear relationship. For example, adaptation may reflect slow inactivation of calcium channels rather than a decrease in firing rate. Likewise, in some neurons calcium levels may not increase as much as in others. For example, neurons with a low dynamic range (e.g. 5-HT neurons that don't increase their firing rate very high even when maximally activated), or those without many calcium channels, may not increase their calcium levels as much as other neurons. For glia it is not clear that "activation" by hypercapnia would always cause a change in intracellular calcium or membrane potential, and yet signaling pathways could still be engaged that influence neighboring neurons. 

These issues should be discussed. However, if the results are taken at face value, there are several surprises in the results. 

A graded or sustained response was exceedingly rare (4%) among RTN neurons. Instead, 22 of 46 RTN neurons adapted to continuous exposure to hypercapnia. It is widely accepted that chemoreceptors need to maintain a sustained increase in firing that is proportional to low levels of CO2 for as long as they are exposed. An abundance of papers have shown that respiratory motor output and ventilation respond to a constant increase in CO2 without adaptation or roll-off. The finding of adaptation of the response of RTN neurons is surprising, and different than has been reported from electrophysiological recordings from neonatal or anesthetized juvenile rodents. The authors interpret these results in the following way: "Although adapting responses to hypercapnia have not been described before, the responses of the neurons matched changes in minute ventilation (VE) calculated from the WBP of the mouse (Fig 2G). Furthermore the average Ca2+ trace of all 22 EA neurons showed a consistent waveform (Fig 2H) that matched the average of the rectified and smoothed WBP trace obtained from all respective mice. This correspondence between features of the responses in these neurons and the adaptive ventilatory response, supports the hypothesis that these are a physiologically important class of chemosensitive neurons." However, on inspection of the trace of VE for a single animal shown in Fig 2G, and the trace of "WBP Av ReSm" shown in Fig 2H, there is actually not any adaptation. When both of these traces are expanded (stretched) in the vertical direction, and a horizontal line is added at the level of the baseline, it is obvious that there is a graded increase in ventilation in proportion to CO2, as expected. This observation calls into question the relevance of the adapting response of RTN neurons to chemoreception. 

What the authors seem to be referring to is a brief burst of activity in the WBP trace at the onset of 3% CO2 in Figure 2G, but there are similar bursts at other times when there is no change in CO2. There is no burst when going from 3% to 6%. These very brief, high amplitude bursts look like movement artifact. Did the authors rule that out? They show that movement doesn't induce an artifact in neuronal recordings, but movement artifact is very common in WBP. Were these bursts due to a response of the animal to sound or a pressure pulse induced by the change in gas? In many of the other WBP traces shown there is rarely a burst of activity with similar timing shortly after the switch of CO2, while there are many bursts that occur at random times unrelated to gas changes. 

Page 12, Top paragraph: "plethysmographic changes in breathing are well-known to adapt to step changes in inspired CO2 (e.g. Fig 2G,H)..." Do the authors have references for this assertion? 

Many individual RTN neurons actually do have adapting responses to hypercapnia. This is not what is expected of respiratory chemoreceptors, since as above ventilation does not adapt to a continuous hypercapnic stimulus. However, the authors conclude that "detection of change in PCO2 is an important role for RTN neurons." There is no evidence for this statement. There is no supporting evidence for any functional role of such adaptation by chemoreceptors. Some pattern generating neurons and motor neurons may adapt, but if chemoreceptors have adaptation that has not been demonstrated. Rapid step changes in CO2 probably don't occur often in vivo and the system may not have evolved to respond to them. 

A substantial fraction of raphe neurons (42%) responded as expected for chemoreceptors with a graded or sustained increase in activity in response to a step increase in CO2. The existence of such a response in 5-HT neurons has previously been questioned on the basis of recordings from anesthetized juvenile rodents, so this paper adds important and novel information. 

A substantial fraction of RTN neurons (11%) and raphe neurons (38%) displayed a decrease in activity in response to hypercapnia. It is not clear if these inhibitory responses were intrinsic or synaptic. The authors provide an explanation for this related to GABA input, but another possibility is that 5-HT neurons that are stimulated by CO2 inhibit other 5-HT neurons by activation of 5-HT1a autoreceptors. Inhibited RTN and raphe neurons may also not be involved in control of breathing. Likewise, in several places the authors suggest that tonic RTN neurons "provide tonic drive to the respiratory network." However, it is possible that these neurons are not respiratory. Just because they are in/near the RTN does not mean they are chemoreceptors. 

Page 8, 2nd paragraph: "...overall glial cells did not appear to be strongly stimulated by CO2 in ways that could make a major contribution..." Is there any evidence that glial calcium levels need to rise in order for glia to influence neighboring neurons? They don't have action potentials, and calcium dependent vesicular fusion, if it occurs at all, is not the only mechanism of neurochemical release from glia. Glia may influence neurons without any change in membrane potential or a rise in calcium. 

Page 15, Concluding remarks: "Raphe neurons tended to be active during the entire CO2 stimulus and conceivably these neurons are likely to take over from RTN neurons under pathophysiological levels of CO2." It is hard to understand how the authors come to this conclusion. The logic is never explained. The data are more supportive of the opposite conclusion. 42% of raphe neurons respond with a graded or sustained increase in firing in response to a rise in CO2 of as little as 3%, whereas most RTN neurons rapidly adapt (in only 1-2 minutes) to 3% CO2 and don't increase to 6% CO2 (a level that strongly stimulates breathing). The data are more consistent with the conclusion that at low levels of CO2, RTN neurons would have little or no effect, while raphe neurons would be expected to provide continuous activation of the respiratory network across the whole CO2 range studied.

Reviewer #3 (Public Review): 

The brainstem cell types that are involved in ventilatory responses to hypercapnia are a matter of great importance to our overall understanding of the control of breathing. This paper seeks to use a cutting-edge, in vivo cell imaging approach (miniscope) to detect changes in cell activity that accompany elevations in CO2 in unanesthetized mice. It samples a multitude of cell types, including some previously suggested to serve as CO2 chemosensors for respiratory control. The observations reported here run largely in opposition to the existing understanding of how those cells respond to CO2 (e.g., serotonergic neurons inhibited by CO2, "RTN" neurons inhibited by CO2 or with an adapting excitatory response, astrocytes unresponsive to CO2). Based on this, and apparently unbothered by the lack of any functional characterization of the recorded cells, the authors develop a detailed speculative model for their role in respiratory control. 

1. A major technical issue with this work is the inability to adequately rule out movement artifacts. The authors provide some indirect evidence that the measured Ca transients are independent of movement, but these are not convincing. For example, the GFP signal measured in different mice cannot be an adequate control for movement artifacts in other GCaMP-expressing mice. My understanding is that Inscopix miniscopes are capable of dual color imaging to detect a co-expressed fluorescent marker in the same cell, a better control. It is also worth noting that even this control does not rule out a movement-evoked change in GCaMP fluorescence for reasons other than the cell moving in and out of the plane of focus, e.g., from effects of movement elsewhere that are transmitted to the recorded cell. This may be especially an issue for astrocytes that are notoriously prone to producing calcium transients when mechanically disturbed (Marina et al., Nature Comm, 2020). It is also surprising that the CO2 challenges, interpreted to reflect a wide variety of cellular response patterns, were not applied in repeated or alternately ordered fashion (0-3-6, 0-6-3). This experimental protocol could have more convincingly verified a consistent response in each individual cell, supporting the designation of these as true activity patterns and, at the same time, dissociated common CO2-associated response patterns from any more randomly associated movement artifacts. A time-honored approach in electrophysiology, especially in vivo, is the use of peristimulus averaging to tease out signal from noise. 

2. Another major technical issue deals with cell identification. For astrocytes and serotonin neurons (at least in some cases), an attempt was made to restrict GCaMP expression to the targeted cell groups by using viruses including GFAP (gfaABC1D) or SERT promoters. Not so for the RTN or the pFL. In these cases, a non-specific neuronal promoter (synapsin) was used to drive GCaMP expression, with the obvious problem that the recordings were made from unidentified cells. Although this might be overlooked for the pFL, a theoretical cell group for which no cell-specific marker has been identified, it is impossible to justify for the RTN. The molecular phenotype of CO2-sensitive RTN neurons has been well-established, and viral vectors using a Phox2b promoter have been employed for many years to preferentially target those RTN neurons. There are not a lot of RTN neurons (maybe 700-800 in mice) and there are many other neurons in the same brainstem region. Thus, the likelihood that some of these other neurons were transduced with GCaMP and accounted for the measured responses to CO2 seems high. Notably, a recent paper from the Mulkey group (eLife, 2021) demonstrated that Sst-expressing parafacial interneurons in the same region are activated, inhibited and unaffected by CO2. 

It is important to acknowledge that the authors tried, post hoc, to identify some of their GCaMP-expressing parafacial cells as bona fide RTN neurons, based on immunostaining for NMB and VGLUT2. Unfortunately, the immunohistochemistry presented is not believable. First, there are no controls provided for the specificity of the antibody staining, and no references attesting to the quality of the antibody - this is unacceptable (see Rhodes and Trimmer, J Neuroscience 2006; Saper, JCN, 2005; Saper & Sawchenko, ibid, 2003). This is especially problematic for this antibody-based detection of somatic staining for a vesicular transporter and a neuropeptide, both of which are typically detected in nerve terminals and undetectable in cell bodies. A further concern is the floccular appearance of the NMB staining. Finally, even if the staining were validated as specific for the relevant antigens, the issue with cell identification would persist. That is, demonstrating that some of the GCaMP-expressing neurons were VGLUT2- and NMB-positive RTN neurons provides no guarantee that the recorded cells were also RTN neurons. 

(A further note on the antibody staining issue. There are also no quality control details provided for any of the other antibodies that were employed in this work.) 

3. For the raphe, it is not clear what information is added from the experiments from unidentified cells obtained with the synapsin-promoter driven GCaMP. For the SERT-driven GCaMP-expressing cells, the preponderance of CO2-inhibited cells is surprising given the extensive work from Richerson and colleagues. 

4. There was very little effect of CO2 on calcium in RTN astrocytes, a finding again at odds with much compelling work, e.g., from Gourine and colleagues, among others, who have found that CO2 activates those glial cells. Was the camera able to capture the astocytes near the ventral medullary surface that have been most associated with CO2 activation and control of breathing? Do the authors have independent histochemical evidence that the gfaABC1D promoter indeed restricted GCaMP expression to glial cells? Also, how does one conclude based on the strength of the calcium signal whether or not the astrocytes could play a functional role - at what threshold would they decide the signal is big enough? and on what would they base that decision. 

5. The pFL section is also problematic since again we have no idea about the identification of the neurons expressing GCaMP using the non-specific synapsin promoter. This is really an exploration of the unknown with the unknown, and the suppositions advanced regarding causality for control of active expiration based only on time-associated Ca signals in unidentified cells.

Reviewer #3 (Public Review):

This work builds on the Stockbridge previous efforts to determine the structure of Gdx, an SMR homolog that has a much narrower substrate profile and functions as a toxic metabolite exporter (specifically guanidinium), rather than promiscuous toxin exporter like EmrE. Strength of the work is the large number of structures for EmrE, the SMR for which the function and transport mechanism has been most extensively studied. Structural data is important for understanding the molecular basis for promiscuous multidrug recognition and transport. 

Given the resolution is in the 3-4Å range for the substrate bound structures, it is important to examine the density of not just the substrate, but also key sidechains in the active site when assessing how EmrE binds different substrates. I appreciate that this density is shown for the higher resolution TPP+ and methyl viologen bound structures to really demonstrate the strength of the conclusions that E14 and W63 change position to accommodate planar vs tetrahedral substrates. 

Another strength is the comparison of the low pH EmrE and Gdx structures illustrating the difference in hydrogen bonding network within the central pore region, and the insights this provides into the difference in side chain orientations and promiscuity of these two homologous transporters. These insights into the substrate recognition mechanisms are important for understanding the divergence of the two SMR transporter subfamilies and may be helpful for understanding how proteins achieve promiscuous vs specific binding more broadly. 

Two areas require further detail and discussion to be added to the manuscript: 

1. While I agree that the L10 monobody has provided a valuable tool to facilitate structure determination of SMR family members, and the individual point mutations made to enable monobody binding are unlikely to cause significant functional or structural defects in EmrE, I would appreciate more discussion of the potential impact of the monobody on EmrE structure? The comparison with prior EM data is consistent with the monobody not having a significant impact on the overall arrangement of transmembrane helices, but I am more concerned with potential impact on the flexible loop regions. This was discussed in more detail in the prior Gdx-Clo structure paper from the Stockbridge group, but revisiting this is important here. This is particularly relevant because of the role the loops play in closing off the transporter on one side of the membrane. Figures highlighting the density of the loop regions on both the closed and open face of the transporter with the monobody interactions highlighted would be helpful in assessing this. In addition, it would be worthwhile to consider whether this structure can provide insight into how the L51I (and I62L) mutation near the end of TM2 (Lehninger eLife 2019;8:e48909) preferentially stabilizes EmrE in an open-to-one side conformation. 

2. What is the exact pH at which each of the substrate-bound crystal structures were determined? The pH of the apo crystal structure is listed in the tables and discussed in the text of the manuscript, highlighting that this is a low-pH structure and thus represents the proton-bound state of the transporter (not truly apo). The methods state that the (drug-like, proton is also a substrate) substrate-bound structures were crystallized at pH 6.5 or pH between 7.1-7.3 depending on the buffer. But I do not see the exact pH listed in the tables for each of the different crystal forms or discussed in the text. This information is important because EmrE is a proton-coupled transporter. 

The results state "To understand how different substrates interact with EmrE, we screened a variety of transported compounds in crystallization trials at pH values {greater than or equal to}6.5, where the E14 sidechains are expected to be deprotonated, favoring binding of the positively charged substrates." This is not correct. The pKa values of E14 in drug-free EmrE are 7.0 and 8.2 at 25 {degree sign}C (Morrison, J Gen Phys 2015, 146:445). EmrE is able to bind drug-like substrate and proton simultaneously, although only one of the E14 remains protonatable (Robinson, PNAS 2017, 114:E10083). For EmrE bound to tetraphenylphosphonium, the pKa of the E14 residue that remains protonatable 6.8 {plus minus} 0.1, thus crystallization conditions near neutral pH may result in a mixture of drug-substrate-bound and drug-substrate-plus-proton bound transporter.

Reviewer #1 (Public Review): 

The discovery of the multi-drug resistant transporter EmrE years ago has raised hopes that, being significantly smaller than other multi-drug transporters, it can be used as a simple model. As it turned out, however, it has been rather difficult to figure out its transport mechanism, and until we (Fleishman et al 2006) modeled its structure based on cryo-EM data, even its membrane topology (being dual) was unclear. Here, Stockbridge and colleagues finally managed to fulfill the early hopes. Taking advantage of a new in house developed multipurpose crystallization chaperone, they managed to determine the high-resolution structure of apo-EmrE as well as co-complexes with various substrates. Remarkably, they noticed that EmrE's backbone remain more or less unaltered and that the ability to accommodate chemically diverse substrates is mostly due to sidechains that change rotameric states. They also determined the structure of a homologue with less broad substrates spectrum and saw that compared to this reference transporter, whose binding site residues are held fixed by hydrogen bonds, EmrE's equivalent residues are engaged in much less hydrogen bonds and much more flexible. 

Main strengths here are characterization of so many high-resolution structures of EmrE, and the addition of functional assays showing that the constructs used are functional and physiologically relevant. Additional strength is the clever use of these structures and the structures of the homologue to decipher the transport mechanism is detail. Finally, another strength is that the multipurpose crystallization chaperone may be useful for other members of the family, and the overall approach for other multi-drug transporters.

Reviewer #2 (Public Review): 

The strength of the manuscript is in the description of six new structures of EmrE at a resolution sufficient for building an atomic model and understanding how the antimicrobial agents bind. What is notable is that the X-ray structures fit extremely well to a low resolution density map of EmrE determined by electron cryo-microscopy of the transporter embedded in a lipid bilayer, suggesting that the structure is a good representation of a physiologically relevant state. This is in contrast to a recently determined NMR structure of EmrE that does not fit the density so well. The quality of the X-ray structures allows the positions of amino acid side chains to be determined, thus allowing robust conclusions to be drawn regarding the molecular details of binding of the antimicrobial agents. The results are supported by extensive previously published work on EmrE performed by site-directed mutagenesis and activity assays. The manuscript is very clearly written and presented. I do not find any significant weaknesses in the manuscript.

Reviewer #1 (Public Review):

Inward-rectifier Kir2.1 K+-permeable channels contribute to establishing the resting membrane potential in multiple cell types and are associated with several human diseases. In these and other proteins, most amino acid determinants for folding, stability, trafficking and function are not well understood. In the present manuscript, Willow Coyote-Maestas and collaborators apply deep mutational scanning and FACS-seq approaches to systematically assess the impact of all possible single-residue substitutions in the Kir2.1 channel on its folding/trafficking to the plasma membrane and its ability to conduct K+ ions. The value of integrating data from both surface-trafficking and function of an ion channel sheds light into clinically-relevant data and structure-function relationships. By using a fluorescence-based high-throughput trafficking assay, the authors identify multiple regions in the Kir2.1 channel that are highly sensitive to perturbation and that are organized into structural domains mainly involving intra-subunit interactions. Using a membrane-intercalating, charged dye, the authors also assay the ability of the channel variants to conduct K+. The results from the trafficking and functional assays are generally consistent with known structure-function relations for these proteins and raise multiple intriguing hypothesis related to different aspects of channel function. By comparing the results from both assays, the authors identify that regions associated with channel gating and allosteric regulation are spatially segregated from those associated with folding, stability and trafficking, and have distinct sensitivities to mutational perturbation. The mapping of these regions constitutes a relevant starting point to understand how the requirements for conformational dynamics and structural stability are balanced in these proteins to enable their biological functions. Finally, the authors identify that channel variants with a large negative impact on their surface trafficking ability are underrepresented in human gene variant databases, pointing to the essential function of these proteins and suggesting a strong negative selection for those variants in the population. The authors relate their measured fitness scores with expert-validated benign human variants to establish thresholds to predict the likelihood of pathogenicity for variants of unknown significance present in the databases.

The data presented is of high quality, there is high reproducibility between replicates, and good coverage depth for the variants. This constitutes the first study of its kind for its size and for quantitating both surface trafficking and ion channel function, yielding reams of new and interesting information. However, for this same reason, a more critical assessment and validation is required to solidly establish this new approach, the significance of the datasets that are reported, and the many specific observations pointed out throughout the work. In general, sources of error are not adequately discussed throughout the work, some examples being sequencing errors, nonspecific antibody binding, and PCR errors. More specific improvements to the presentation, analysis, and discussion of the data are warranted to fully realize the potential of this approach and are detailed below.

Firstly, the signal-to-noise ratio in these approaches is limited compared to methods with lower throughput. Even in best-case scenarios like this manuscript, there are much fewer individual observations per variant relative to e.g. a FLIPR multi-well assay averaging signals from millions of cells per variant. The FACS experiment for functionality (Suppl. Fig. 3F) in particular has a very limited dynamic range, and no additional data is shown to provide quantitative support for the choice of gates. Without additional data for cells expressing individual channel variants with defective permeation, it is hard to evaluate how accurate the selection assay is in discriminating between channels with loss of function or gain of function phenotypes. The results of the surface-trafficking experiment did yield distinct populations providing more confidence in the ability of the assay to discriminate between phenotypes, which is an excellent result. We unfortunately do not see similarly distinct populations in the function-based selection, suggesting that it has an overall decreased sensitivity.

A concern is that no effective discussion or quantitation is provided to assess to extent to which there are variants with solidly negative surface expression scores and neutral or positive function scores. Mutations that severely disrupt folding or trafficking generally also lead to a complete lack of functional channels in the plasma membrane, as pointed out by the authors on lines 390-393, such that function fitness scores are expected to correlate strongly with variants with very negative surface expression scores. Analysis of this aspect of the data could provide an excellent means to critically assess the accuracy of the functional fitness scores.

The use of the literature as means to test the accuracy of observations is not very effective and it is unclear how systematic the comparisons are between the experimental results presented here and phenotypes described in the literature using other approaches. Only observations from the literature that agree with the authors' observations are discussed, without addressing whether there are also discrepancies. Further, discussion of published experimental observations are hard to trace back to the data as presented in the manuscript, as the figures are very complex. Further, the text does not discuss relevant per-residue scores that seem inconsistent with the authors' interpretation. For example, the functional assay yields permissive results for certain substitutions at the GYG selectivity filter sequence Glycine residues, contrary to the idea that these are immutable. Similarly, substitution of the glycine hinge at position 176 with asparagine or lysine yields positive fitness scores in the permeation assay, counter to the expected flexibility requirements for that position. Analogously, certain substitutions at the PIP2 binding residues appear to be inconsistent with the expected receptor-ligand interactions (e.g., negative residues yield positive function fitness scores at R80 and W81). In general, it is unclear how the robustness of the per-residue results compares with the pre-position averaged data. Establishing this is important to adequately interpret the results and extract the most useful information. Many potentially interesting observations thus remain speculative and would benefit from additional experimental validation. Some of these examples include the increased surface expression of N386E, N386D, T150, Y153, the positive effect in function of N224K and of the residues surrounding the hinge at G176, and importantly, at least some of the predicted phenotypes for the variants of unknown significance.

The existence of a co-translationally folded biogenic domain is overstated, as the nature of the assay precludes distinctions between different steps along the folding, tetramerization and trafficking of channels, and are based on findings on another protein. It is also unclear if any quantitative parameters were used by the authors to identify the specific regions of the C-terminus required for Golgi export, as some of the secondary structure domains listed on line 157 appear to be more permissive to perturbation than others.

The distinction between intra- and inter-subunit interactions being primarily associated with surface expression or function could be analyzed in a more systematic manner, and otherwise remains anecdotal to those regions specifically mentioned in the text, rather than the entire protein.

Finally, limited information on the sequencing method is provided; specifically, the length of the amplicon is not described, nor how stringent the conditions were to discriminate between SPINE-library mutations and those caused by errors at different stages of the study, and the strategy used to assess the presence of additional mutations outside the SPINE-derived variant tiles d. It is also unclear whether replicates reflect different libraries, different recombined cell populations, or different aliquots from one cell library after recombination.

Reviewer #2 (Public Review):

The authors use deep mutational scanning to introduce almost every possible amino acid substitution at every residue in Kir2.1, and then assess the consequences for assembly, trafficking and channel activity, using single cell fluorescent activated cell sorting and deep sequencing approaches. Experimental determination of mutational consequences is a very meaningful advance over purely computational predictions, and the present analysis shows that trafficking mutations are under-represented in such computational variant effect databases. The results provide a deep catalog of the consequences of each mutation that will be of great potential use in assessment of clinical relevance of identified natural variants.

Reviewer #3 (Public Review):

Coyote-Maestas et al. have elegantly and comprehensively addressed pressing questions in the fields of both protein biochemistry and ion channel physiology in this paper, using Kir2.1 as a model system for an application that could be widely adopted to many ion channels. There are, to my mind, two keys elements that any reader should take away from this manuscript. First, they outline a clear model for how to leverage deep mutational scanning (DMS) for the functional analysis of ion channels. DMS analysis has been used historically to map permissive and non-permissive sites for mutational substitutions. These are frequently paired with biophysical or biochemical analysis, and scans are usually limited to sub-domains or small proteins. Rarely do such studies probe the full capacity of a large, multi-subunit protein as done in this paper. Second, they adapt two flow cytometry based functional assays of ion channel activity (surface expression and channel conductance) to fully map the contributions of each mutation in their library to the common physiologically relevant deficits of these proteins driving human disease.

They have maintained a clear focus on using this screen to fully enumerate and define the domains of Kir2.1 involved in its full maturation and activity. Impressively, their data analysis and highlighted mutational deficiencies map exceptionally well to the already known disease causing variants of Kir2.1. These observations build confidence that this method of analysis can reveal potential disease-causing mutants, including identified variants in this study that exist in the human population but have not yet been characterized as disease relevant (likely due to low population prevalence). In addition to clinical relevance, the authors also enumerate the boundaries of domains that had been previously hypothesized as key elements in the trafficking, export, assembly, and function of Kir2.1 and significantly improve the resolution of which residues and substitutions are deleterious to function and trafficking of this important protein.

The data within this paper will serve as a blueprint for further dissection, analysis, and engineering of Kir2.1 and other ion channels for many years into the future.

It should be noted that the mutational coverage in this study is not complete. "No data" is observed for roughly 7% of possible amino acid substitutions in their functional analysis studies. This is likely due to insufficient library coverage of these positions in their originating stable cell lines. This is not unusual for libraries of this size; however, the absence of data is not necessarily random. Specific amino acids and domains have less coverage than others (example, AA350-354, AA251, AA150-190, AA53, etc). Readers should be aware of this as a limitation in the analysis of these domains. While complete, and absolute data of every possible positional substitution would be valuable, the lack of data at these positions does not diminish the overall interpretations, functional observations, and conclusions of the study. Rather, this gaps should simply be carefully considered if using this dataset for comprehensive modeling or interpretation of Kir2.1 or other ion channels in computational or functional characterization efforts.

Coyote-Maestas et al. achieve a critical milestone in this manuscript, creating a foundational dataset for the biochemical understanding of all residues of an ion channel in the two functions most highly correlated with disease, trafficking and conductance. This paper will serve as a road map to future studies aimed at developing similar datasets in the ion channel field and beyond.

Reviewer #1 (Public Review):

Previously, using rigorous genetic, bioinformatic and cell-based biochemical analyses, the same group discovered SLAM1, an outer membrane protein in Neisseria spp., which mediates the membrane translocation of surface lipoproteins (SLPs) (Hooda et al. 2016 Nature Microbiology 1, 16009).

Here, authors reconstituted this system in proteoliposomes using minimal purified components including the translocon Slam1 and the client lipoprotein TbpB. Authors further coupled the system to TbpB-expressing E. coli spheroblasts and LolA, the Slam1-specific periplasmic shuttle system. Using the digestion pattern of TbpB by Proteinase K as a readout, authors confirmed that Slam1 indeed served as a translocon for SLPs. As a step forward, authors found that Skp, a periplasmic chaperone (holdase), was critical to the membrane-assembly and translocation of TbpB.

Strengths:

Overall, this is a solid biochemical study that demonstrates the role of Slam1 as a translocon for SLPs. The experimental design is neat and straightforward. The specific role of Skp in SLP translocation is interesting. This reconstituted system will serve as a novel platform for further elucidation of the Slam1-mediated SLP translocation mechanisms. The manuscript is overall well written.

Weakness:

There are several major concerns, however.

1) It is not fully convincing whether these findings are novel and significantly advance the field. Identification of minimal components in a biological process and their reconstitution are always challenging and thus, this study is an achievement. Nonetheless, I am not sure whether we have learned novel molecular insights besides the confirmation of the group's previous discovery. The specific role of Skp in translocation is interesting but not surprising, considering that periplasmic holdases are already known to be extensively involved in the biogenesis of periplasmic and outer membrane proteins.

2) Although authors developed nice assays (Figs. 1 and 2), it was not verified whether TbpB protected from Proteinase K digestion had "correct" conformation and membrane-topology. Authors performed a functional assay on TbpB (Fig. 5a), but this result was obtained from a cell-based assay, not from the reconstituted system.

Although the data in Figs. 1 and 2 clearly show that the membrane association of TbpB depends on Slam1, it does not mean that the "translocation" has actually occurred in the proteoliposomes. Probably, more rigorous analysis on the Proteinase K-protected portion of TbpB (for example, mass spec) seems necessary (that is, whether the proteolytic product is expected based on the predicted topology).

3) The manuscript has a couple of missing supporting data.

3a) Lines 87-89: "From our analysis, we found that the Slam1 from Moraxella catarrhalis (or Mcat Slam1) expressed well and the purified protein was more stable than other Slam homologs."

>I cannot find the expression and stability data of various homologs supporting this sentence.

3b) "Lines 216-219: Furthermore, the processing of TbpB by signal peptidase II and subsequence release from the inner membrane was unaffected suggesting the defect in surface display by Skp occurs after the release of TbpB from the inner membrane (Fig. 4a)."

>The result supporting this sentence seems missing or this sentence points to a wrong figure.

4) Some statistical analysis results are not clear, making some conclusions not convincing.

4a) Figure 4a top "Exposure of TbpB on the surface of K12 E. coli"

> Apparently, all three data points for (Delta_DegP+Slam1+TbpB) are very closely distributed. Accordingly, (WT+Slam1+TbpB) vs (Delta_DegP+Slam1+TbpB) data look significantly different (difference is ~0.2). But the two data were assigned as "Not Significant". Similarly, in the comparable in vitro data (Figure 4b), the intensity for Slam1 (WT + Proteinase K - Triton) looks larger than that for Slam1 (Delta_DegP + Proteinase K - Triton). So, the DegP contribution should not be ignored.

4b) Figure 5a top "Exposure of TbpB on the surface of N. meningitidis"

> What is the p-value for WT vs Delta_Skp data? Are the two data significantly different? The p-value range for (*) is not shown.

Reviewer #2 (Public Review):

The article addresses the function of SLAM, a protein which the authors have shown previously to be involved in the traffic of lipoproteins to the bacterial surface. The authors have performed a series of experiments to assess the impact of SLAM on the delivery into proteoliposomes of the model lipoprotein TbpB either added exogenously or presented by E coli spheroplasts. They identify a periplasmic chaperone, Skp, which enhances transport of TbpB and other lipoproteins to proteoliposomes, and show the contribution of endogenous Skp to lipoprotein transport in Neisseria meningitidis.

The authors set up an in vitro translocation assays using purified components from different bacteria. This is reasonable as the assays can be challenging to establish and require proteins that can be expressed and are stable. It would be helpful however if the sources of the proteins and how they are tagged (for their detection) is clearly documented in the article and the figures. In keeping with this, the figures describing the assays could be improved (ie 1A, 2A, 3A and C). Despite this, the results presented in Fig 1 and 2 clearly demonstrate the role of SLAM as a translocase, and the authors have included appropriate controls for their assays; the translocation of a OmpA to demonstrate that the Bam complex is functional in their hands in an important control and should be included in the main figures.

Experiments outlined in Figure 3 and Table 1 demonstrate the interaction specific of TbpB and another lipoprotein HpuA with Skp, a previously characterised periplasmic chaperone. This is performed by pull-downs and MS as well as immunobloting.

A critical result is shown in Figure 4 in which SLAM and TbpB are introduced into E coli, and the role of endogenous Skp is assessed. Importantly, the absence of Skp reduces but does not eliminate TbpB surface expression. The authors could speculate on the nature of Skp-indendent surface expression of TbpB, as this result mirrors what they find in a meningococcal strain lacking Skp (Figure 5A). It appears that Skp might be required for the correct insertion/folding of lipoproteins given their result in Figure 5B (currently, this could be changed into 5C) which tests the binding of transferrin to the bacterial surface. Clearly this could be influenced by an effect of Skp on TbpA, which acts as a co-receptor with TbpB.

In summary, the authors have used appropriate assays to reach their conclusions about the role of SLAM as a translocase and the contribution of Skp to the localisation of lipoproteins to the surface of bacteria. The findings presented are robust and shed new insights into the sorting of proteins in bacteria, an incompletely understood process which is central to microbial physiology, viurlence and vaccines.

Reviewer #3 (Public Review):

Slam was identified as an outer membrane protein involved in the translocation of certain lipoproteins to the cell surface in Neisseria meningitidis. Slam homologs were also identified in other proteobacteria. However, direct evidence that Slam is an outer membrane translocation device is still missing. In this paper, the authors set up an in vitro translocation assay to probe the role of Slam proteins in the translocation of the lipoprotein TbpB. Although they provide strong data supporting the role of Slam in lipoprotein translocation, further molecular dissection is required to unambiguously establish Slam as a lipoprotein translocator. The work is interesting and the paper clearly written. The authors also discovered a functional link between the periplasmic chaperone Skp and Slam-dependent lipoproteins, which is a novel and interesting finding.

Reviewer #1 (Public Review): 

The authors image local voltage and calcium influx in the dendrites of mouse superficial cortical pyramidal neurons while simulating synaptic input using glutamate uncaging. They show that both the degree of amplification of local calcium influx observed during back-propagating action potentials and the calcium influx evoked by the action potentials themselves vary widely across dendritic branches but are poorly correlated. The signals due to APs vary by dendritic branch. They go on to show convincingly that the reason some dendrites show smaller signals is that the APs are attenuated at some branch points leading to a failure to exceed the threshold for calcium channel activation. In contrast, since calcium influx through NMDA receptors has a less steep voltage dependence (Fig. 8A) they are less affected by the attenuation, leading to decorrelation. 

This is a very thorough and well done analysis of a set of issues that have implications for the ways in which dendritic morphology affect plasticity "rules." The underlying principles are largely previously understood, but their implications (e.g. the difference between voltage dependence of calcium channel and NMDA receptor calcium influx) are not widely appreciated and yet have important effects on the resulting integration. In addition, the study is valuable because various alternative explanations (e.g. lack of calcium channels in some dendrites) have been convincingly ruled out. The results are likely to be of interest to neuroscientists and biophysicists concerned with neuronal plasticity and dendritic computation.

Reviewer #2 (Public Review): 

Landau and colleagues use an impressive set of techniques, including somatic and dendritic electrical recordings and dendritic Ca2+ and voltage imaging, to study the effect of dendritic morphology on dendritic Ca2+ signaling associated with backpropagating APs (bAPs). The authors aim to test the hypothesis that the amplitudes of bAP-dependent spine Ca2+ signals depend on the branch pattern complexity of the dendritic domain that the dendrite or spine is part of. The novelty is that their approach highlights the role of the branching patterns proximal AND distal to the dendrite of interest. This is an important refinement of findings in past studies that have described that the amplitudes of bAP-dependent dendritic Ca2+ signals decrease as a function of the electrotonic distance of the soma. The authors begin in fact by replicating this well-documented result. However, they emphasize the variability of these Ca2+ signals when comparing dendrites/spine that are part of different dendritic branches but matched for distance to the soma. To go after the reason for this variability, the paper first defines two types of dendrites/dendritic spines based on the Ca2+ signal amplitude associated with a single bAP, dendrites/spines with high bAP Ca2+ signals (high delta Ca2+) and those with low bAP Ca2+ (low delta Ca2+) signals. These two groups of dendrites will be contrasted throughout the paper, but how the amplitude value separating these groups was found remains unclear. Next, a set of experiments excludes differences in voltage-gated calcium channel (VGCC) density or differences in the ability of bAPs to invade specific dendritic branches in the absence of synaptic input as potential sources for this difference. Instead, using computational modeling and detailed morphological analyses, the paper concludes is that the bAP amplitude is more attenuated in the low delta Ca2+ branches because low delta Ca2+ dendritic branches are surrounded by more elaborate branching patterns leading to a smaller overall impedance. Lower impedance leads to an increased bAP attenuation and smaller bAP-associated Ca2+ signals due to decreased VGCC opening. Overall, this manuscript is written and organized in an intuitive way, and this study is an impressive technical tour-de-force. However, one way or another, most findings of this study recapitulate or refine previous results, as mentioned by the authors themselves (e.g., Water et al, 2003; Magee and Johnston, 1997) and/or can be predicted based on cable theory.

Reviewer #3 (Public Review): 

This interesting paper examines how dendrite geometry influences back-propagating action potentials (bAPs) and their associated Ca2+ signals (∆CaAP). The authors use an elegant combination of 2-photon Ca2+ imaging, 2-photon uncaging, 1-photon voltage imaging, and modeling. They first show that different spines and dendrites can have very different ∆CaAP signals, which they divide into low and high groups. They also show that sites with low ∆CaAP still undergo large amplification when paired with uncaging EPSPs (uEPSPs). They show that the low ∆CaAP dendrites both support bAPs and have Ca2+ channels that could in principle evoke signals. However, using voltage imaging, they show that bAP amplitude is smaller in the low ∆CaAP dendrites. They show this depends on increased dendritic complexity at these dendrites, which is associated with lower impedance. In this case, some additional voltage imaging experiments could be very useful to fully explore these ideas. Lastly, they use simulations to show how branch structure can influence both bAPs and synaptic responses. Overall, I think this is careful and well-written study that augments our understanding of dendritic signaling.

Reviewer #1 (Public Review): 

Nuclear Pore Complexes (NPCs) controlling the trafficking between nucleus and cytoplasm are known to under changes during aging. However, their underlying cause and association with aging factors were unclear. In this manuscript, the authors investigated the link between a well-known aging factor in yeast, rDNA circles, and age-related NPC changes. They found that 1) NPC-bound DNA circles displace cytoplasmic components and nuclear baskets of the NPC in aged cells; 2) these remodels NPCs are not recognized by defective and not specifically limited to old NPCs; 3) NPC remodeling is caused by acetylation of NPC basket component; 4) remodeled NPCs are a cause of aging; 5) remodeled NPCs specifically affect the mRNA export process. 

The experimental systems were well designed to address their questions. The data presented are of high quality in general and support their major conclusions. This manuscript clearly links NPC remodeling and dysfunction during aging to DNA circles known to accumulate during yeast aging. Importantly, they also demonstrated some of the mechanistic details of this process: specific NPC components being displaced due to DNA circle binding; regulation of this process by protein acetylation; and the specific functions of NPCs being affected. Hence, this manuscript has made a significant progress toward our understanding of mechanism of action by a well-known aging factor and should be of interest to researchers studying yeast and cellular aging, nuclear pore function and aging, as well as those interested in the functions of protein acetyltransferase SAGA.

Reviewer #2 (Public Review): 

Meinema et al. investigated the poorly understood mechanism of how extrachromosomal rDNA circles (ERCs) promote aging in yeast cells. ERCs are well-established aging factors that are derived from ribosomal DNA (rDNA) repeats cut out of the genome during aging. Notably, ERCs are known to associate with nuclear pore complexes (NPCs) via the nuclear basket, yet how this interaction affects NPC architecture and function remains unclear. 

By combining a previously-established ERC reporter assay, a microfluidic yeast aging platform, and quantitative co-localization imaging, Meinema et al. show that tethering of NPCs to ERCs displaces the key nuclear basket component Mlp1, Mlp2, Nup60 and Nup2. This finding is in agreement with previous proteomics data. Notably, the authors convincingly show that tethering to ERCs is necessary for NPC remodeling, as aging alone is not sufficient to cause basket loss. Further arguing a against damage through aging model is the finding that basket-less NPCs are not recognized as defective by the ESCRT III quality control machinery. Yet, NPC remodeling is not without consequences, as the authors show that a number of transport factors involved in mRNA export showed reduced interaction with ERC-tethered, basket-less NPCs. A strength of the paper is the clever use of yeast genetics and mutagenesis to systematically perturb the interaction between ERCs and NPCs. This allowed the authors to identify that acetylation of basket components by the SAGA complex drives their displacement from ERC-bound NPCs. 

Taken together, the authors conclude from their findings that ERC binding results in specialized NPCs with reduced mRNA export capacity, and that this NPC specialization promotes aging. However, the authors do not yet test this model rigorously enough to draw such firm conclusions and exclude the possibility of NPC damage-driven aging. In particular, the ERC-induced loss of FG nucleoporins such as Nup116, Nup42 and Nsp1 raises concerns about the integrity of the NPC permeability barrier. This bears the risk of collapsing the RanGTP gradient that fuels all nucleocytoplasmic transport, and thus have far-reaching consequences. Similarly, the paper would benefit from clarifying if the nuclear transport receptors Kap60 and Kap123 (and their cargoes) get stuck in ERC-tethered NPCs or pass more efficiently, as this is central to distinguish between specialized and defective NPCs.

Reviewer #3 (Public Review): 

This study by Meinema et al. explores changes to nuclear pore complex (NPC) composition associated with extrachromosomal DNA (ecDNA) anchoring with aging in budding yeast. The major new concept is that NPC remodeling driven by the displacement of the nuclear basket by ecDNA and concomitant loss of the cytosolic mRNA platform, is an example of NPC specialization, which may also be detrimental to cells and drive aging. This somewhat challenges the idea espoused by others that NPC damage might contribute to aging - an idea that the authors try to rule out. In general, the data are of good quality but the cause and effect relationship between the tethering of DNA circles, SAGA, acetylation of Nup60 and the loss of cytosolic nups remains uncertain. There is little direct data presented, for example, that DNA circles "displace the nuclear basket" and alternative explanations are not considered.

Reviewer #1 (Public Review):

This paper aims to identify enhancers controlling human cardiovascular development. The authors identified a set of highly conserved regulatory elements bioinformatically and tested one of these in vivo, in medaka, and in vitro, in hESC differentiated into endothelial cells. They find deletion of this enhancer had no significant effect on the expression of FLT1 mRNA in the human cell line or on the formation of tube formation. However, deletion of the orthologous enhancer in medaka showed phenotypic effects in blood clot formation. This paper is of interest to researchers in cardiovascular genetics. The data provides insights into the function of an enhancer controlling FLT1. The paper demonstrates the utility of transgenic assays of enhancer function using medeka but the major limitation is that it is comprised mostly of negative results, and the key claim that this enhancer in humans has a crucial role in regulating cardiovascular development is not justified by the data.

Reviewer #2 (Public Review):

In their manuscript, Stolper et al identified and characterized a conserved enhancer element located in the intron of FLT1, a gene known for its role in vasculogenesis. They successfully demonstrated that the human enhancer sequence (enFLT1) was able to drive robust cardiovascular gene expression in vivo in medaka. However, deletion of enFLT1 in vitro did not significantly alter the expression of FLT1 nor affected angiogenesis, although it induced differential expression of many genes related to cardiovascular development. Finally, they showed that deletion of the medaka endogenous enflt1 enhancer by CRISPR/Cas9 caused an increase in blood clot formation in the yolk of F0 injected embryos. This study employed rigorous analyses following a logical thought process, to narrow down enhancer candidates and identify the chosen target. The experimental validations were well designed and executed. Unfortunately, many of the results fall short in demonstrating a direct regulation of the claimed target gene (FLT1) by enFLT1 and the function of the endogenous enhancer in vivo.

Reviewer #3 (Public Review):

This manuscript from Stolper and colleagues describes a highly conserved transcriptional enhancer element within the FLT1 locus that is bound by Nkx2-5 in human pluripotent stem cell-derived cardiomyocytes and is proposed to regulate FLT1 expression. Stolper and co further demonstrate that a region encompassing 358 bases of the human FLT1 enhancer can drive reporter gene expression in the cardiovascular and neural systems of medaka. This is a strength of the study, though the assessment of reporter gene expression should be substantially expanded. The team next deleted a region encompassing 635 bases of the FLT1 enhancer in human embryonic stem cells, differentiated these cells into endothelial cells and investigated the impact of enhancer deletion on endothelial cell gene expression and tube forming ability. Intriguingly, while expression levels of FLT1 were not significantly altered in differentiated endothelial cells, the expression of a small number of genes was changed, suggesting that the enhancer might regulate genes other than Flt1. Enhancer deletion revealed that there was not a major impact on the ability of endothelial cells differentiated from embryonic stem cells to form tubes in angiogenesis assays, while the ability of cells in which exon 1 of Flt1 was deleted to form tubes was elevated, consistent with established roles of Flt1 in regulating endothelial cell proliferation. These data suggest that at least in this model, the Flt1 enhancer studied does not play a major role in regulating Flt1 expression. The greatest strength of the study is the finding that deletion of the enhancer in medaka resulted in an increased proportion of embryos exhibiting blood clots, suggestive of cardiovascular dysfunction. This observation deserves more extensive investigation; a detailed analysis of cardiac and vascular development in enhancer mutant fish should be undertaken. I expect an expanded study to be of significant and broad ranging interest to the vascular and developmental biology communities.

Reviewer #1 (Public Review):

Auxier et al. investigate the evolutionary dynamics of nuclear level selection in dikaryons of basidiomycete fungi. This research aims at clarifying a long-standing problem in fungal genetics, namely the evolutionary significance of dikaryons, the mysterious but dominant nuclear arrangement of the zygobiotic (2N) phase in basidiomycete fungi. This arrangement occurs when the mated mycelium maintains the nuclei of the two mates in a spatially distinct, but paired, arrangement through numerous cell divisions before production of a fruiting body. The alternative is that the mated mycelium would be diploid, like most eukaryotes, but evidence for such a system is limited to a few examples. In most basidiomycetes, the gamete is the haploid nucleus, and therefore the standard dikaryotic condition maintains the potential for remating through dikaryon-monokaryon matings, and in this research, it is this particular difference that the authors focus on modeling. Another curious phenomenon that is related to the basidiomycete life cycle is that dikaryon-dikaryon pairings inevitably result in rejection and no mating, thus creating a concept that the dikaryon is individualistic and cannot be invaded. What would happen if that assumption was relaxed?

Here the authors develop an agent-based model to test how nuclear behaviors in mated mycelia can influence selection for allocation to fitness components and population fitness. The authors contrast three distinct nuclear behaviors (diploid, standard dikaryon, and open dikaryon [scenario of constant somatic reassortment]) under a number of parameters. Importantly, they model tradeoffs between reproductive and vegetative traits (mycelial growth, mating, and sporulation). The general findings were that with the dikaryotic life cycles, populations often become heavily biased towards nuclei that behave selfishly (also referred to as parasitic) in that they maximize their own fitness to the detriment of the total population (as measured by population size). In the case of the open dikaryon, the population crashes under most conditions. The key parameter for stability of most of the simulations has to do with lambda, the number of fitness related loci.

The conclusions of the paper are supported by the data, and the authors have done a good job of incorporating important aspects of the biology of the system into the paper. This will be a paper that impacts the field because it will be a touchstone for the numerous researchers who wonder about the subject. Perhaps the most important insight is that the individualistic behavior of dikaryotic mycelia is required to prevent the system from collapsing due to selfish nuclei; this individualistic behavior is incredibly well supported across many mushroom species. Some aspects of the paper left me quite intrigued.

1. Much of the paper rests on the effects of the number of fitness related loci. Yet, fitness is a complicated phenotype comprised of multiple aspects of vegetative growth, sporulation, mating ability etc. Much of the stability only comes when the fitness phenotypes are inherited as a single unit. I feel that the actual model is weak in terms of what these fitness loci represent, given that clearly vegetative growth is never going to be determined by a single Mendelian locus. The authors should clarify and speak consistently about what lambda represents. How lambda influences the updating algorithm could also be better explained. Despite this weakness, this model can improve our intuition that reconciling these tradeoffs can be accomplished if they become manifested as alternative extreme strategies controlled by a single large locus as observed in the outcome of the simulations.

2. I think this spatially explicit model is very useful, because capturing the underlying dynamics of a di-mon mating requires this spatial consideration. I wonder, however, how spatial heterogeneity might influence the outcome. If resources were distributed unevenly in space, it might favor genotypes that invested more in reproduction over mating as there may be dispersal limitations. I also am interested in what would happen if you incorporated size of a dikaryotic/diploid mycelium in reproductive output. It might be that you get a strong positive relationship between the two. I can imagine that a selfish nucleus could invade into recipient mycelium and establish a dikaryotic genotype, but then not actually have enough resources to reproduce sexually. It is interesting that in this context, the less promiscuous diploid fungus Armillaria is also the one known to have the largest sized individuals.

3. As mentioned, I think the authors have done a good job of infusing realism into their model. I think it would help to add a general discussion about what factors might favor or at least permit a diploid system to emerge given that such systems exist. Another way of thinking about this would be whether a system of a standard dikaryon could be invaded by a mutation leading to diploidy; or conversely in the diploid system if a mutation led to dikaryons (exploring both cases of recessive and dominance of mutations) could be informative.

Reviewer #2 (Public Review):

The fungal mycelium is a habitat, or 'constructed niche', within which nuclei live. Nuclei from an existing dikaryon can mate with another monokaryon, to form new dikaryotic partnerships, but there are 'self-incompatibility' barriers that prevent new nuclei entering existing dikaryons.

Auxier, Czaran and Aanens paper reports evolutionary simulations of mating behavior in basidiomycete fungi. Nuclear types in fungal dikaryons benefit from retaining the ability to form new dikaryons with monokaryons that are encountered but this has costs for the fitness of existing dikaryons. (Three fitness components-mycelial growth rate, production of meiospores by dikaryons, mating fitness-were subject to mutation. The re-normalization of fitness components after mutation ensured that there was a trade-off among the fitness components.) In the simulations in which new matings were allowed between existing dikaryons, there was a rapid collapse of fitness because of high investment in extra matings.

The paper presents an advance in our understanding the complex evolutionary forces acting in the 'Buller phenomenon' (matings between monokaryons and dikaryons). These forces are complex and analytically intractable (For example, cubics of gene frequencies appear as soon as one has three partners). The authors approach this problem by simulations. I have mixed feelings about simulations for complex, poorly understood, biological phenomena (you get out of them what you put into them; one must always leave out many of the complexities). Simulations are best thought of as a kind of experiment in which various factors are varied. The authors approach the simulation in this light as an exploration of possible underlying processes.

Reviewer #1 (Public Review):

This manuscript introduces a novel approach for identification and tagging of specific neuronal populations called SNAIL, or "Specific Nuclear-Anchored Independent Labeling". This approach begins with identification of population-specific open chromatin regions (defined using single nucleus ATAC-seq or bulk ATAC-seq from isolated populations) to feed a machine learning algorithm that enables comparisons of these regions between the targeted cell type and other cell types. The manuscript demonstrates the efficacy of this system in identification of thousands of novel DNA elements that are accessible in Parvalbumin-expressing interneurons in the mouse cortex that are not accessible in other cortical populations. Next, SNAIL uses these sequences to drive a promoter-less AAV reporter construct expressing the nuclear anchored SUN1-GFP. In validation experiments, the manuscript reports selective expression of GFP in PV+ cells, with enrichment ratios beating the current "gold standard" technology. Further, the manuscript highlights that cells expressing this reporter driven by two separate SNAIL-selected sequences have open chromatin signatures that are highly similar to PV+ interneurons isolated/identified with other approaches. Overall, the results of the manuscript are compellingly presented, and computational predictions are tested with experimental observations where appropriate (with proper controls). While the technology has not been extensively validated in other brain regions or other species, the these tools will be made available to the research community, and should enable nuclear tagging of other selected neuronal populations of interest. Further, as the tools described here can be delivered entirely via AAVs, this platform will enable cell type tagging in model organisms for which transgenic lines are not commonly available, or even expression of other transgenes for control of cell function or genetic perturbation.

It should also be noted that the general idea of SNAIL (using putative enhancer elements to drive reporters or effectors in a targeted cell population) is not new. In fact, a recent report (PMID 32807948) used a similar strategy to effectively express transgenes in parvalbumin interneurons across three vertebrate species. Likewise, other reports have used open chromatin profiling to identify enhancers expression of transgenes by AAVs (PMID 33789083, 33789096). Therefore, the ultimate utility of the SNAIL approach will likely depend on extension of this platform to other targeted populations, and will require further demonstration that the enhancer candidate sequences used here also effectively target PV neurons in other brain regions and in other species. However, this computationally rigorous manuscript represents a necessary and fundamental first step in this process.

Reviewer #2 (Public Review):

To achieve this goal, the authors use a series of machine learning approaches to find sequence information within differential regions of open chromatin between cell types that best predict the cell-type specific function of enhancers. The author first built support vector machines that could classify sequences from astrocyte versus neuron and inhibitory versus excitatory open chromatin data, then validated the classifiers on known cell type specific promoters. They then classified PV+ neuron open chromatin regions versus non-PV cell open chromatin, as well as comparing to datasets from excitatory and VIP+ neurons. Importantly they also made CNN classifiers and SVM classifiers from clusters of single-nucleus ATAC sequencing data, which is key to advancing their cell type comparisons to the broader condition of cell subtypes. To test the quality of their classifiers, they compared them against the sequences of experimentally tested putative PV enhancers and evaluate the comparisons. Finally, they use their optimal sequences to generate vectors and show co-expression with PV+, and they analyze the optimal sequences for the likely TFs that drive this cell-type specific expression.

Bioinformatics methods represent an efficient means to achieve the goal of developing tools for increasingly specific manipulations of neuronal cell types. Machine learning tools are particularly powerful and unbiased way to find sequence patterns and the authors show evidence to experimentally validate their computational outcomes. The application of the method to single cell data makes it especially useful in the context of the explosion of that data now appearing in databases. If the method turns out to be widely applicable when applied to additional datasets, this will of significant importance for the field.

I have no major concerns about the quality of the data or the statistical analyses. My only concerns are about how certain data are interpreted or described.

Reviewer #3 (Public Review):

Recent years have given us increasing insight as to the diversity of cell types in the brain and other tissues as well as novel approaches to target them. Often these approaches are combinations of viral vector-based transfection and cis acting native regulatory DNA elements (i.e. enhancers). This paper addresses two important issues in the search for specificity, first providing a (largely previously described) means to increase the representation of relatively rare cell types in a sample via labeling nuclei to facilitate isolation, and then providing a semi-automated means of sorting through the increasingly large numbers of putative regulatory elements one obtains with modern epigenetic and bioinformatic methods. The authors proposed approach is based on an in silico filter using machine learning to identify sequence characteristics in enhancers specific for particular cell types. This is a very rational approach, focusing on the functional characteristics of the enhancers. Interestingly, they do indeed find some functionally important characteristics in the form of particular TF-binding motifs general for successful enhancers to drive transgene expression specifically in PV+ neurons.<br /> If the method works as well as it seems, it will give the community another valuable means to winnow down the dizzying number of hits involved in enhancer selection, which would be of great benefit to the field. This is not solely a technical manuscript, however... in addition this work provides some insight into the functional interaction between enhancers and transcription factors in particular cell types of the brain, the complexity of which we are only starting to appreciate, so the paper has some interesting biology as well. Taken together, it has the makings of an impactful paper.<br /> There are some issues, however. First and foremost, as it stands now it is unclear how much better the in silico filters improve upon just raw chromatin accessibility, let alone other methods. Judging from Figure 1 sup 4a, the correlation between specificity in vivo and predicted activity is driven mostly by enhancers E1, E22 and E29. I would like to see the correlation scores without these enhancers. Further in fig 1 sup4b, there seems to be a strong correlation between specificity in vivo and accessibility to begin with. Please include a comparison between these two correlations. Also, what would be much more convincing as a demonstration of added value would be to test which one is "correct" in those few instances that the two measures deviate, see #4 below.<br /> Second, the authors present scATACseq as the only way to find enhancers. There are in fact more ways that if incorporated will also improve prediction of which genomic regions are functional, active enhancers, which are "poised", and which are simply accessible, most notably ChIP-seq data, though this is without a doubt more resource intensive than an in silico filter. There are many examples, but of particular interest is the work by Ernst and Kellis (PMID: 29120462), as well as the work by Axel Visel and Len Pennacchio. They respectively use models based on additional epigenomic information and modifications associated with active enhancers for their selection, and provide good comparators as to what else is out there. However, it is important to note that this could be combined with their algorithm.<br /> Third, the authors gloss over what the models actually do, and do not explicitly compare them to other means of enhancer selection (this could go in the discussion). From the text it was unclear to me exactly what happened and how the rankings occurred. Furthermore, the graphs in 1B-E are insufficiently explained. Yes, it is true that there are hidden levels in , but the algorithm should be explained well enough to know what the limitations are, and whether there can be biases "baked in" towards e.g. particular kinds of TFs.<br /> Finally, the two novel enhancers the authors find (SC1 and SC2) are selected from the 90th percentile. There are likely several dozen or even hundreds of enhancers here, so the authors need to be more forthcoming about their selection criteria. SC1 is arguably just picked as the highest scoring hit, but what about SC2? Which characteristics led to manually pick this particular enhancer? Were other enhancers tested for specificity and failed? At the end of the day, the utility and impact of SNAIL depends upon the extent to which it aids the generation of celltype specific tools beyond the current state of the art. The authors show two examples of at least somewhat PV-specific vectors as proof of concept, but this seems a bit thin, as they could arguably have been picked from the chromatin accessibility data alone (see Figure1 Suppl 6b vs. c). To sum up, this is a potentially quite valuable addition to the toolkit for making celltype-specific vectors, but just exactly how valuable is not yet clear (see recommendations for authors).

Reviewer #1 (Public Review):

In their manuscript, Bhat et al present a sequencing based method to analyze the dynamic activity of the replisome to replicate DNA. They studied particularly the speed of replication for steadily growing E. coli cells, growing in rich media (LB) at different temperatures. DNA replication is a most essential cellular process which needs to be coupled to other cellular processes to allow growth and replication. A better quantification of the replisome speed is thus important to derive a more integrative understanding of the microbial cell. The method introduced by the authors is a nice approach to infer the speed of replication depending on the position of the replisomes along the chromosome and can thus largely improve our understanding of replication in vivo. The authors particularly report that replication speeds are varying with temperature and speeds further oscillate with the position of the replisome. Particularly the oscillations appear to be important to think about when aiming for a more mechanistic understanding of growth. However, repeats to confirm the results are missing, the manuscript would benefit from a better comparison with published approaches, and results could be put into a better physiological context.

Reviewer #2 (Public Review):

The paper deals with experiments and theory for the variations in replication speed throughout the cell cycle. It is known that due to the structure of the bacterial cell cycle the frequencies of different loci in the genomes are different (with genes closer to the origin of replication appearing more frequently). This has been taken into advantage experimentally in previous works. Here, the authors extend the theory to account for fluctuations in the replication velocity as well as a cell-cycle-dependent speed, and analyze using sequencing data the variations in the speed for E. coli, showing interesting oscillatory patterns in the speed. The work is elegant and nicely executed.

Comments:

- The interpretation in terms of a speed-error trade-off is rather speculative and perhaps less emphasis should be placed on it (e.g. in the abstract and the top of p.9).

- The idea of using the frequency inferred from sequencing was also used in: Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples, Korem et al. Science. (2015)<br /> Are the oscillations also observed in those measurements? If so, is there information which could be gleaned from them?

- Is it obvious a priori that Eqs. 7-9 are correct, since they do not account for the age-structure within the population? (i.e. genomes do not have a "rate" to switch to another state). The derivation in the appendix which accounts for this appears to me more systematic and compelling.

- There is a systematic difference in the dependence of speed and growth rate on temperature, which the authors discuss. What is the expected change in cell size if the Cooper-Helmstetter model is correct? Should it be observable experimentally? Is it?

- Lines 131-133: why is the average DNA per cell the product of the two other averages? Is this an approximation or are the two other variables uncorrelated?

- This study was done in the regime of fast growth. It is known that for E. coli there are many changes in the cell cycle properties when the doubling time (at 37 Celcius) exceeds 60 minutes (i.e. the regime where there are no overlapping replication forks). How do the results change in slow growth conditions?

Reviewer #3 (Public Review):

In this study, Bhat et al., characterize the effect of increasing temperature on replication rates in fast growing E. coli. For this, they develop a whole genome sequencing-based method to derive replication speed and position information from DNA abundance measurements. Using this assay, they find that replication speed increases with increasing temperature in a manner following the Arrhenius law. They also observe periodic fluctuations in the speed of the replisome, the pattern being consistent with the average mutation rate described previously. Based on this, the authors suggest that there is a tradeoff between replication speed and accuracy.

Strengths:<br /> This study develops a quantitative method for inferring replisome dynamics from high throughput genome sequencing. This allows the authors to derive unique insights on the effects of temperature on replication rates (and cell cycle). A particularly interesting observation is with regards to the wave-like behaviour in replication speed that the authors compare to mutation rate patterns from Niccum et al., 2019.

Limitations:<br /> The key conclusions of this work need to be better synthesized. There seems to be several observations made, but how they together inform about the impact of temperature on replisome dynamics remains unclear: Relationship between replication speed and temperature (and that it follows the Arrhenius law) is well-described in this study, but is not wholly unexpected. In addition, the authors suggest an increase in replisome number with increase in temperature but do not discuss the same. The authors further discuss their observations in light of the Cooper and Helmstetter model (L140-150), but this reviewer is left feeling confused about the context of the same and what it means for the understanding of temperature impact on replisome speed. Finally, how are the wave-like replisome dynamics generated? Are these driven by genome characteristics? If the pattern is reflective of regions of faster DNA synthesis (and hence increased mutation rate), then does the mutation rate itself increase with increasing temperature in a similar fashion. A better synthesis and discussion of the key results will help appreciate unique findings of this study.

Reviewer #1 (Public Review): 

The authors constructed synthetic tRNAs with different 4-base anticodons and recorded their efficiency in decoding a series of quadruplet codons in Escherichia coli. Phage based library generation and selection was used to survey several quadruplet codons for their potential to incorporate each of the 20 standard amino acids. Additional library-based mutagenesis was used to identify optimal bases as positions surrounding the anticodon. Finally, mass spectrometry was used to identify tRNAs that appear to enable selective or ambiguous decoding of different quadruplet codons. Overall, the manuscript provides exciting new data and represents an important exploration of the potential and limitations of a 4-base genetic code. 

The manuscript should be revised as some statements are not supported by the data. For example, the concluding remark "our deliberate exploration of the evolution of functional quadruplet translation will launch synthetic efforts to assemble a 256-amino acid genetic code." While a complete 4-base genetic code would have 256 codons, the authors have neglected to discuss the potential for degeneracy in that code. Limitations of quadruplet decoding resulting from competition with normal 3-base decoding is not clearly addressed.

Reviewer #2 (Public Review): 

The manuscript of DeBenedictus et al describes careful and comprehensive investigation of the requirements for translation by tRNAs decoding 4-base codons. There is considerable interest in engineering organisms to use 4 base codons, as it would allow 256 codons to recode to alternative amino acids etc in synthetic biology. Here the authors tested whether there is a fundamental limitation in using natural tRNAs as scaffolds for 4 base codon reading by engineering their anticodon loops. They tested 57 of the possible 256 codon-anticodon pairs, and all twenty isoacceptors. They applied a combination of simple luciferase assays for readthrough of a single 4-base codon with an expressed tRNA mutant, in parallel measuring the growth defects of the different tRNA mutants. Their initial results focused on 4 anticodons, where the last base is repeated twice, to attempt to ensure efficient aminoacylation by codon-recognizing aminoacyl tRNA synthetases. Overall, the efficiencies of the tRNAs for suppression are poor, leading to 1-2% of protein production compared to wild-type triplet decoding in their reporter system, at best. They apply molecular evolution techniques to attempt to optimize the 4 base anticodon context, and show improvement for a tRNAser scaffold by changes in positions 32, 37 and 38 flanking the anticodon. Finally they tested the amino acids incorporated at the 4 base codon position in a test protein, and found that incorporation was homogeneous, with mainly one amino acid incorporated and often it was that encoded by the quadruplet tRNA. However, in several instances, arginine was incorporated irregardless of the identity of the tRNA. This was explained by the low specificity for ArgRS for the anticodon and has been observed previously. 

Overall, the manuscript tackles a complex, important problem in synthetic biology in a comprehensive fashion. The efficiencies of 4 base decoding are exceptionally low, but there is hope presented here that through evolution approaches such efficiencies can be improved. I personally would have liked to see both deeper mechanistic and biochemical questions probed here-are the tRNAs modified and where, what are their aminoacylation efficiencies, what indeed are the problems with translational efficiencies? Yet the authors are frank that their purpose is elsewhere, and more a proof of concept that 4 base codons can work comprehensively without crosstalk. The writing and precise experiments are often confusing. For example, the nature of the pili selection experiment is not well characterized by the figures. The authors should also engage in deeper discussion of what worked-why were certain tRNA anticodons more amenable to decoding than others. Even some speculation would be useful to the community to deepen these studies.

Reviewer #3 (Public Review): 

This manuscript would be appealing to a broad audience, subject to the following revisions: 

1. It would be helpful to explain the criteria that were used to select the 21 E. coli tRNAs (including f-Met) that were the starting point for this study. Given a choice, it seems the authors preferred either G or C at the third codon position. They do not appear to have taken into account codon usage in E. coli or an effort to maximize orthogonality among the chosen codons. 

2. Do the various reporter proteins (luciferase, pIII, and sfGFP) tolerate deletion of the amino acid that is encoded by the mutated codon? If so, what is the possibility of a ribosomal frameshift to skip this position? In the mass spec analyses, did the authors seek to detect a tryptic fragment corresponding to deletion of Tyr151? For each reporter protein, it should be noted what is the wild-type amino acid encoded by the mutated codon. The Addgene links provided in the Methods section are broken. 

3. The mass spec analyses are a critical component of this study, but are not mentioned until near the end of the manuscript. The fact that such analyses confirmed the incorporating of the quadruplet-coded amino acid should be stated in the abstract and in the last paragraph of the introduction. Otherwise many readers (including me) will be carrying doubt until those data are presented. The tryptic digest fragment depicted in Figure 4A appears incorrect. Cleavage would be expected following Lys140 and Lys156, generating a product two residues shorter than what is shown. 

4. The last sub-section of the Results belongs in the Discussion. In that sub-section the authors discuss the prospects for the combined use of multiple quadruplet codons. It needs to be stated clearly that this has not been done in the present study, although in the Introduction the authors reference prior studies where up to four unique quadruplets were co-translated from a common transcript. Nor does the present study investigate the possibility of multiple occurrences of the same quadruplet codon within one transcript. Based on the reported results with a single occurrence, the effect of multiple occurrences on translation efficiency is likely to be severe. Neither of these qualifiers diminish the significance of the present study. 

5. In the discussion regarding the tolerance of aminoacyl tRNA synthetases to altered codon size, the authors make the excellent suggestion that synthetases that arose later during evolution may be more precisely tuned to triple anticodon recognition. It would also be worth noting that the decoding site of the ribosome is likely to have become more precise over the course of evolution. As the proteome expanded, there would have been strong selection pressure favoring increased fidelity of translation, whereas during the early history of life, especially if there were fewer amino acids to distinguish, the entire translation apparatus is likely to have been more permissive.

Reviewer #1 (Public Review): 

This study reports that different splice variants of SynGAP1 differentially regulate cognitive function and seizure protection in mice. The authors used three different mouse lines and systematically analyzed the expression patterns of different SynGAP1 splice variants in the brain and their impacts on cognitive function and seizure protection. The authors also analyzed excitatory synaptic transmission and synaptic plasticity in these mice and attempted proteomic analyses to better understand the underlying mechanisms. The overall conclusion of the study is that the SynGAP1-alpha variants are more important than the SynGAP1-beta variants for the regulation of cognitive function and seizure protection in mice.

Reviewer #2 (Public Review): 

Murat Kilinc et al. studied behavioral phenotypes of three Syngap1 mutant mice in order to identify the roles of distinct SYNGAP C-terminal variants. The first mutant mouse (IRES-TD mouse) with insertion of IRES-TDtomato cassette in the last exon (exon21) showed elevated open field activity, reduced time in the induction of seizure by flurothyl, less freezing behavior in remote contextual fear memory recall, and increase in frequency and amplitude of mEPSCs in L2/3 somatosensory neurons. In addition, IRES-TD mice showed a reduction in total SynGAP protein, alpha1, and alpha2 isoforms and increased beta isoform in the forebrain. The second mutant mouse (beta* mouse) with a mutation in the early splice acceptor of exon19 showed a slight reduction in open field activity, increase in time for seizure induction, no change in freezing behavior in remote contextual memory recall, and decrease in frequency and amplitude of mEPSCs in L2/3 somatosensory neurons. Beta* mice showed no change in total SynGAP protein, a modest increase in alpha2, and a reduction in beta in the forebrain. The third mutant mouse (PBM mouse) has point mutations in exon21 for disrupting the function of the PDZ-binding motif (PBM) of SynGAP to interact with PSD95. This mutant showed elevated open field activity, reduced time in the induction of seizure, less freezing behavior in remote contextual memory recall, and increased frequency and amplitude of mEPSCs in L2/3 somatosensory neurons. PBM mice showed no change in total SynGAP, alpha2, and beta proteins but reduced immunoblot signal of alpha1 in the forebrain. This reduced immunoblot signal was proposed to be related to less sensitivity of the alpha1 specific antibody to the mutated isoform. By thorough behavioral and physiological analyses of three independent mutant mouse lines, the authors conclude that the level of alpha isoforms, rather than the total SynGAP, is critical in several neural circuit functions related to cognition and seizure protections. Previous studies revealed multiple roles of SynGAP in neural circuit development and activity-dependent regulations. This new study provides important information about the isoform-specific functions of SynGAP, especially the critical role of alpha isoform content for proper synapse and circuit activity. 

The results obtained from multiple mutant mouse lines support the key claims of the paper. Still, there are several points that may require more experimental data or otherwise changing the interpretation of the data. 

1. One of the key messages of this manuscript is the amount of alpha isoforms, but not the total amount of SynGAP, is critical in multiple behavioral phenotypes in mutant mice. In order to discuss the importance of isoforms, essential information is a relative abundance of each isoform in both wild-type and mutant mice. Throughout this manuscript, the comparisons within isoforms were performed, but no information about relative abundance between isoforms was provided. It is also unclear there are any differences in the relative abundance of isoforms in different brain regions studied in this manuscript, including the forebrain, hippocampus, and somatosensory cortex. The estimate of relative abundance should be provided, or any technical difficulty in this estimation should be explained. 

2. The phenotypic similarity between IRES-TD mice and PBM mutant mice suggests critical roles of alpha isoforms in multiple behavioral phenotypes. However, the effect of PBM mutant still needs to be carefully evaluated. If alpha1 is the only isoform expressed in the brain, the interpretation of introducing PSD95-nonbinding mutant is straightforward, but in the presence of other isoforms, dominant-negative effects of PBM mutant should be considered. It is possible that PBM mutant complexed with different isoforms impair localization or function of other isoforms, leading to an effect similar to the reduction of total SynGAP protein. Clarification of this point by additional experimental data is necessary. For example, in Figure 6A, did the PSD fraction from the PBM mutant contain a similar amount of alpha2 and beta isoforms? Also, in Figure 7, native PSD95 complexes from Syngap1PBM mutants were characterized. In the PSD95 complexes, was the amount of other SynGAP isoforms unchanged? 

3. The authors selected remote contextual fear conditioning coupled with protein analysis in the forebrain. This selection may be based on the motivation of finding deficits in forebrain-related long-lasting memory in mutant mice. It is unclear why the authors selected Morris water maze as the second behavioral test, which is not designed to evaluate long-lasting memory. The rationale behind selecting two distinct memory-related behavioral tests, remote contextual memory test and water maze-based training performance, should be explained. In addition, the phenotype in the Morris water maze was difficult to interpret. SynGAP heterozygote mice show impairment, but IRES-TD mice showed no change. This is inconsistent with other behavioral tests. Beta* mice showed improvement in the training session, but the 24 h probe test did not show a difference. It is difficult to connect the data with the result of contextual fear memory. This point should be discussed.

Reviewer #3 (Public Review): 

SYNGAP1 is one of the most prominent risk genes for a number of neurodevelopmental disorders, including autism, intellectual disability, epilepsy and schizophrenia. However, its biological roles are still being uncovered. One aspect of this complexity is the role of its many splice variants. In this manuscript, the authors have created and analyzed several genetically modified mouse lines in which they altered the expression levels, and protein interaction sites in a subset of the isoforms of the Syngap1 protein. They then performed an extensive analysis of the mRNA and protein levels of all isoforms, behavioral and physiological phenotypes in mice, assessed seizure susceptibility, and examined cellular and molecular alterations in synapses in these mutant mice. They found that reduced expression of the alpha forms was damaging, while their increased expression was protective in mice. 

This work is likely to be very impactful on the field, because it makes an important step forward in clarifying the roles of specific splice variants in physiological and behavioral processes relevant for neurodevelopmental disorders. One important implication of this work could be that increasing the expression of the alpha form using genetic tools, such as gene therapy, could have beneficial therapeutic effects in human patients.

Reviewer #1 (Public Review):

Tan et. al develop an SMLM method for determining the number of subunits in oligomeric proteins where each subunit is labeled with two fluorescent markers of separable colors in fixed cells. Rather than counting each subunit, their approach infers the number of subunits based on the statistical likelihood of observing the protein at all in one of the color channels, and uses the other color channel to estimate the fraction of labeled proteins that are not observed. Their approach requires first calibrating an experimental system using labeled proteins of known stoichiometry to determine the probability of observing each marker in that setup, which thereafter can be used to determine the number of subunits in similarly labeled proteins of unknown stoichiometry. They apply their approach to several anion exchangers/transporters of unknown stoichiometry and validate their result with native gels. The approach is limited to populations of fairly uniform stoichiometry, but has some marked advantages over other methods such as bleach step counting in that it is feasible to use fluorophores with low probabilities of detection and can readily be applied to proteins in cells at higher densities. These advantages will be very useful to experimentalists for understanding the oligomeric assembly of proteins in native cells. Some clarification of the methods and assumptions are needed for a more general readership.

Reviewer #2 (Public Review):

Summary:

In contrast to many other SMLM methods which aim to count subunits in membrane protein complexes, the authors aim to deduce the average oligomerisation state from the probabilistic co-detection of at least 1 'reporter' fluorophore, which has relatively poor detection efficiency, with the detection of at least 1 fused 'marker' fluorophore. They derived a simple theoretical framework, calibrated the method using proteins of known oligomerisation state (validated against high-resolution clear native gel electrophoresis), and applied it to clarify the oligomerisation state of six SLC26 and SLC17 family member membrane proteins.

Major strengths and weaknesses:

The proposed concept is new and interesting. It has the potential to overcome some, though not all, limitations of existing techniques. For example, the concept is limited to measuring the average oligomerisation state and as such is not suitable to measure a distribution of (higher) oligomerisation states.<br /> The implementation of the concept is suboptimal in both, theoretical and practical, aspects:<br /> On the theory side, a rigorous probabilistic framework for the assignment of the most likely oligomerisation state is missing. This includes a sensitivity analysis of Equation 1 (or, better, of Equation 6) which highlights at which n or p this method is most sensitive. Also, no confidence intervals for fitted values of m and p were provided which could be used in such a sensitivity analysis.<br /> On the practical side, the SMLM detection/processing details are not state-of-the-art (PSF fit with fixed SD 2D Gaussian; not using maximum likelihood estimation for fitting; DBSCAN algorithm to group raw (single-frame) data). In conjunction with setting a minimum value of 6 (PAmCherry) and 10 (mVenus) for the number of localisations per cluster, these together might contribute to the poor detection efficiency for PAmCherry of 0.12, which is in contrast to the reported maturation efficiency of the protein, and which the authors attribute to protein misfolding.

Appraisal of whether the results support their conclusions:

The authors were successful in establishing their new concept. The conclusions about the oligomerisation state of SLC family membrane proteins are, despite the methodological shortcomings, convincingly supported by the data.<br /> The authors' measured oligomerisation states of candidate membrane proteins which formed homo-dimers up to tetramers. They did not attempt to measure stoichiometries of different subunits. The title of the paper thus is misleading. Although the technique could be applied to measure the oligomerisation state of different subunits in independent samples using different expression constructs, and thus an average stoichiometry could be determined, it is not suitable to directly measure stoichiometries of different subunits in the same sample.<br /> It is unlikely that the author's attribution of the very low detection efficiency to a 'misfolded' fraction of proteins is the only possible explanation.

Discussion of the likely impact of the work

If this analysis was further improved (see limitations above) and offered as an open-source software tool, it could find wider-spread application and complement existing methods to measure the oligomerisation state of membrane proteins from monomers to tetramers using relatively standard PALM approaches.<br /> A potential limitation is that labs which wish to adopt this method are required to perform a whole set of calibration measurements to experimentally determine the detection efficiency p (and the 'misfolding' parameter m), see Figure 4A, which is relatively laborious.<br /> The presented results on the oligomerisation state of SLC family membrane proteins are of direct interest to researchers in this area of molecular cell biology.

Reviewer #1 (Public Review):

The manuscript by Heo et al. describes the cryoEM structure of the somatostatin receptor 2 (SSTR2) bound to its agonist SST-14 and a heterotrimeric G protein. Somatostatin receptors are biologically important, with roles in acromegaly and a variety of other diseases. The structure of one of these receptors is therefore significant and likely to be of interest to a number of researchers. The manuscript is a bit disappointing in that it is purely descriptive, with no functional experiments to test proposed ideas around ligand recognition and specificity. At a minimum, It would be helpful to see site-directed mutagenesis to test the importance of specific contacts identified in the structure (accompanied by binding assays or signaling, with appropriate controls for differences in expression level). This would significantly improve the manuscript and the breadth of its appeal.

Reviewer #2 (Public Review):

- A summary of what the authors were trying to achieve. 

In this study the authors aimed at providing structural insights into how somatostatin binds to the type 2 receptor. This peptide hormone is having key role in regulating the endocrine systems so those structural studies are critical for drug development targeting SST receptors.

- An account of the major strengths and weaknesses of the methods and results. 

The methodology to achieve their goal (biochemistry and CryoEM) is strong. The weaknesses are more related to how the authors put this work into the pharmacological context of SST receptor family and the discussion around the ligand-specific binding to SSTR2.

- An appraisal of whether the authors achieved their aims, and whether the results support their conclusions.

The authors definitely achieved their aims and their study provides important structural information regarding the binding of endogenous agonist, the activation of the SSTR 2 and its G protein coupling. Again, this is just a matter of how to discuss the structural data and to highlight the most relevant structural features for the fundamental aspect of GPCR function and for the SSTR2 pharmacology (and drug discovery).

- A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community.

The study will likely impact on the field of GPCR structural biology and somatostatin pharmacology.

Reviewer #1 (Public Review):

This paper addresses an important gap in the literature, namely testing the role of the ventrolateral prefrontal cortex (vlPFC) in large-scale networks and in particular in the salience network (SN). A translational and multimodal approach was chosen in which tract-tracing in non-human primates (NHP) was used to quantify the anatomic connectivity strength between the different vlPFC areas and frontal and insular cortices. Next, seed-based functional connectivity analyses in NHP and human resting-state functional connectivity MRI (fcMRI) were used to validate the tract-tracing results. In sum, this study shows that the vlPFC contains nodes for all three tested networks, the VAN, DAN, and SN and the authors conclude that it may play a key role as an attentional hub.

Reviewer #2 (Public Review):

Trambaiolli and colleagues combine ground-truth tract tracing experiments in macaques with translationally-relevant resting-state functional connectivity analyses of fMRI data collected from both macaques and humans. Analysing these data, they comprehensively show that the ventrolateral prefrontal cortex (vlPFC) is a hub connected with two regions that are part of the salience network (SN): the anterior insular cortex (AI) and dorsal anterior cingulate cortex (dACC). The methods are state of the art and combining multiple approaches means that the limitations of one method can compensate for the limitations of the other. The main result they report is the strong connection of the vlPFC region, area 47/12, with both dACC and AI. Then using fMRI functional connectivity analyses from a single macaque they show that anatomical connections identified using tract tracing are mirrored by activity correlations between 47/12, AI and ACC. Extending this work to resting-state fMRI data collected from 1000 humans, the authors show that there is a coupling between 47/12, ACC and AI. Based on these findings, the authors suggest vlPFC should be included as one node of the SN alongside the other two regions. These results are relevant as vlPFC is already part of the dorsal and ventral attentional network that have been identified in humans. Its inclusion as one of the nodes of the SN as well therefore has important implications for cognitive neuroscience and basic understanding of functional networks and their hubs. Based on this, vlPFC would appear to be a major hub as it links multiple functional networks.

Despite the importance of the work and generally solid methods, there are a number of issues with the current work that need to be addressed. Most notably some additional analyses are required to ensure the validity and reliability of the results that are reported, especially in the macaque imaging data where analyses appear to have been conducted on a high-quality dataset from a single macaque.

Reviewer #3 (Public Review):

This is an interesting quantitative study of the anatomical connections of a region of prefrontal cortex that has often been overlooked because it is at the border of what is typically called ventrolateral prefrontal cortex and orbitofrontal prefrontal cortex (the unusual location is apparent in figure 2b). Sometimes it is included as part of ventrolateral prefrontal cortex, sometimes as part of orbitofrontal cortex and sometimes it is simply given little attention because ventrolateral prefrontal cortex studies focus on the inferior convexity and orbital studies focus on the region between the orbitofrontal sulci. The idea that this is a special region that is different to both the rest of ventrolateral prefrontal cortex and probably the rest of orbitofrontal cortex is important because it helps us understand some otherwise puzzling reports about the orbitofrontal and ventrolateral prefrontal cortex.

To investigate the connections of the caudal and orbital part of 47/12, Trambaiolli report the distribution of tracer labels across ventralateral prefrontal, insular, and cingulate cortex when tracer injections were made in a number of these areas. This provides the initial key evidence for specialized sub-regions in 47/12. Second, they follow this up with an examination of the patterns of correlation in activity between sub-divisions of area 47/12 and other brain regions that are apparent in analysis of resting state functional magnetic resonance imaging (fMRI) MION contrast data taken from a macaque. Finally, they report an analogous analysis of resting state fMRI BOLD contrast data from human participants that leads them to infer similar patterns of interconnections between the cytoarchitectural similar areas of the human brain.

The quantitative analysis of connections was an unusual strength of the study as was the comparison of tracer data in macaques, fMRI connectivity data in macaques, and human fMRI connectivity data.

Reviewer #1 (Public Review):

As an essential subunit of cohesin, RAD21 is a known regulator of large-scale genome organization, acting via a mechanism called loop extrusion to facilitate enhancer-promoter contacts in the genome. Given that enhancers play a key role in cell-specific gene expression patterns and activity-dependent responses, the long-range looping structures enabled by cohesin have been predicted to regulate key aspects of neuronal function. To test this idea, this manuscript from Calderon and colleagues uses both conditional deletion or inducible degradation of RAD21 in cortical neurons (both in vitro and in vivo) to examine resulting effects on gene expression, morphology, and stimulus-dependent transcriptional responses. The major finding of the manuscript is that loss of cohesin in primary neuron cultures results in downregulation of over 1000 genes, with an enrichment for genes involved in synaptic function and neuron differentiation. Not surprisingly, this manipulation also produces robust effects in vivo, impairing cortical layer organization, neuronal complexity, and spine density. Using careful bioinformatic analysis that includes chromatin contact information, the manuscript reports that the predominant effects of RAD21 loss are on long-rage chromatin interactions. Specifically, while RAD21 depletion decreased expression of many genes at baseline, a core set of secondary response genes, characterized by delayed response to depolarizing stimuli or neuronal growth factors, were preferentially affected by the manipulation. Inducibility of a subset of these genes is lost upon RAD21 depletion, and genes with longer chromatin contacts (as measured by HiC interactions) were among the most affected. Notably, RAD21 depletion had few effects on short-range chromatin interactions (or stimulus-dependent loop formation), demonstrating selectivity in its contribution to activity-dependent transcriptional responses in neurons.

Overall, the results of the manuscript are compellingly presented, the experiments have appropriate controls, and the manuscript is well organized. The strengths of the manuscript are the extensive validation of specific RAD21 knockdown/deletion in cortical excitatory neurons, a systematic characterization of RAD21 depletion effects at the morphological, transcriptional, and chromatin levels, and the use of inducible approaches to manipulate RAD21. The interpretation that cohesin plays distinct roles in regulation of secondary response genes (which tend to be involved in longer chromatin loops) is supported by RNA-seq evidence that stimulus-regulated expression of these genes is lost following RAD21 depletion. In contrast, the evidence that cohesin effects scale with chromatin loop length is largely correlational, and the manuscript lacks a more systematic interrogation of this relationship. Similarly, the manuscript would benefit from a more comprehensive analysis comparing the effects of RAD21 depletion on constitutive and inducible chromatin loops in primary neuron cultures. However, this rigorous manuscript represents a necessary and fundamental first step in identification of the mechanisms by which cohesin (and by extension, chromatin looping) regulates stimulus-dependent gene expression in the nervous system.

Reviewer #2 (Public Review):

This is an interesting paper describing neuron-specific chromatin loop regulation, with the main finding centered on role of the cohesion complex in context of activity-dependent gene expression and the observation that 'cohesin dependence of constitutive neuronal genes....scaled with chromatin loop length'. At its core, these are, from the neuroscience perspective, very novel findings.

Basically, the authors report that Immediate Early genes (IEG) with chromatin loops far shorter than 100Kb are much less affected in conditional mutant neurons with floxed RAD21 cohesin subunit deletion . In contrast, secondary activity-regulated genes (SRGs)with average loop length scaling beyond several hundred Kb are highly sensitive to the loss of RAD21. The authors further strengthen their observation in parallel experiments with Rad21Tev/Tev neurons (this model they recently published, Weiss et al, 2021) with inducible protease digestion of RAD21.

The strength of the paper is the methodological rigor as it pertains to the study of gene expression changes (incl. two activity induced paradigms, KCL and BDNF) in two types of mutant neurons of the cohesin RAD21 subunit.

This is an interesting paper describing neuron-specific chromatin loop regulation, with the main finding centered on role of the cohesion complex in context of activity-dependent gene expression and the observation that 'cohesin dependence of constitutive neuronal genes....scaled with chromatin loop length'. At its core, these are , from the neuroscience perspective, very novel findings.

Basically, the authors report that Immediate Early genes (IEG) with chromatin loops far shorter than 100Kb are much less affected in conditional mutant neurons with floxed RAD21 cohesin subunit deletion. In contrast, secondary activity-regulated genes (SRGs)with average loop length scaling beyond several hundred Kb are highly sensitive to the loss of RAD21. The authors further strengthen their observation in parallel experiments with Rad21Tev/Tev neurons (this model they recently published, Weiss et al, 2021) with inducible protease digestion of RAD21.

The strength of the paper is the methodological rigor as it pertains to the study of gene expression changes (incl. two activity induced paradigms, KCL and BDNF) in two types of mutant neurons of the cohesin RAD21 subunit.

Reviewer #3 (Public Review):

In this manuscript the authors study the consequences in neurons of knocking out the cohesin subunit Rad21. The authors have previously performed a version of chromatin conformation capture called 5C in which they are able to generate very high-resolution chromatin interaction maps across focused regions of the genome. In that study they focused on several activity-inducible genes and showed that there were both pre-existing and activity-inducible interactions of putative enhancers with the promoters of activity-inducible genes. Here to determine if Rad21 is important for those interactions and their functional consequences on gene regulation, they do two different knockouts in postmitotic neurons (cell type cKO and rapid TEV-mediated cleavage). Loss of Rad21 led to impaired expression of many neuronal genes at baseline as well reduced branching and spine density, by comparing against previous HiC maps, the authors show that the most affected genes are those with the largest loops. Then they move on to activity-regulated genes, where they compare the effects of Rad21 deletion on their 5C maps as well as gene expression. These data show that activity-induced genes expression and inducible looping between promoters and putative enhancers proceed largely normally in the absence of Rad21, though large CTCF loops are disrupted.

Understanding the mechanisms of chromatin organization in the nucleus is important and this group has one of the best methods for studying high resolution chromatin interactions. Knocking out Rad21 is a reasonable strategy to disrupt looping and the 5C data support that the authors did successfully change some aspects of loops in postmitotic neurons that are important for neuronal development. However, the most notable finding in the data is that for the most part, activity-induced gene expression and activity-induced changes in promoter looping to putative enhancers were unaffected in Rad21 knockout neurons. This is rather different from the results of a previously published Rad21 knockout, though the authors don't discuss this.

Overall this is a well-executed study that presents descriptive data about the functions of cohesin-mediated chromatin architecture in neurons and offers data that suggests that Rad21 is mostly not required for activity-dependent transcription.

Reviewer #1 (Public Review):

This study is addressing a very important topic in animal cognition, namely how concepts like zero or negation can emerge in non-linguistic animals. We know that animals can represent objects when they are no longer available to their sight. But the question is whether they can represent the absence of an object. While previous research show that some species of mammals and birds can maintain object in mind even when they are occasionally occluded, there is no clear evidence that they represent absence when objects are expected to be not present at a specific location.<br /> Children are capable to express linguistically the absence of an object as a negation and they do so in a numerical context. These capacities emerge developmentally and seem to be linked to other faculties which rely on an approximate number system. In cognitive sciences, there are ample debates about how we represent number concepts and how we are sensitive to numerical differences, including empty sets, which may correspond to the concept of 'zero' (i.e. lack of numerosities).

Is there any equivalent within a non-linguistic domain? This question is scientifically extremely stimulating and challenging. Neurophysiological experiments in monkeys show that there are neurons coding the presence or absence of a stimulus. Other behavioral studies also provide some evidence pointing to the possibility that some animals represent absence or understand the concept of 'zero'. However, more robust experimental evidence is still needed.

Thus, the current study approaches this conundrum by exploiting an animal model (the chick imprinted on an object) that in the last few years has become extremely relevant to address outstanding questions related to the evolutionary origins of cognitive capacities in animals.

Within this framework, a simple and straight forward methodology (looking behavior in a violation paradigm) has been applied in a series of experiments, which have elegantly circumvented such conceptual problem.

Authors investigated in chicks their capacity to represent the absence of an object by assessing their looking behavior in violating expectation paradigms where experimenters manipulated the presence or absence of objects during three different phases. In a key condition, in the first phase no object was present in the arena. Then a screen was lifted to occlude the chick's view and an object was secretly introduced behind the screen. The sliding screen was then removed and it appeared in chick's view, thus violating its expectancy of absence.

The results show sex differences in the ability of chick to represent the absence of an object with a left-eye bias. Authors interpret left-eye bias as an attempt to identify object at a location where 'nothing' was expected to be.

Present findings are indeed an original contribution to the field even though some of the results are somehow difficult to interpret. For example, males do not show any effect. According to one hypothesis females would be more interested to social stimuli. However, previous studies show females' left-eye bias for novel object and right-eye bias for conspecifics. Thus, if the left-eye bias is a signature of an attempt to identify a social stimulus one should have expected to find right-eye bias for the object stimulus presented in these experiments. The interpretation of present findings therefore seems not always in line with the literature.

One way to clarify this would be that of exposing chicks to different categories of imprinting stimuli (e.g. social vs non-social). This critical experiment would help in understanding if the females' stronger capacity to encode absence than males is due to their higher sensitivity to social stimuli.

From an evolutionary perspective, if females' left-eye bias is a chicks' signature to identify the unexpectedly appearing object, given its survival importance, such early competence should be present in males' chicks too.

Reviewer #2 (Public Review):

The research detailed in this manuscript investigates whether young chicks represent the absence of objects. This is the first time this ability has been studied spontaneously in such a population, as opposed to after many trials of experience. It may also be the first experiment to measure chicks' looking time in violation of expectation paradigms.

The overall idea that chicks may represent absence and that the eye side looking bias (e.g., Lateralization Index) might be sensitive to violations of expectation regarding the absence of objects, but not regarding the presence of objects, is very interesting. Study 2 is particularly impressive in its controls.

Some additional background material and details about methodology/analyses would better enable the reader to evaluate whether the data support all conclusions, especially those regarding sex-dependent representation of absence. In particular:

1) Previous research with rooks in this domain is mentioned briefly in one sentence near the end of the Introduction. It would be helpful to know that, if this or similar research has already been conducted with another bird species, how the current research in chicks further significantly advances knowledge.

2) More background review on eye usage with respect to novelty would be useful to the reader in the Introduction: e.g., the theory behind why this occurs, whether it is specific to birds, etc.

3) It would be important to know why 8-day-old chicks were the age chosen to use in these particular experiments.

4) It is unclear why sex was a factor in the ANOVAs-statements of plans or predictions in this regard would be helpful. This is especially true since so much of the Discussion unexpectedly focuses on findings related to such analyses.

5) In Study 2, there are no untransformed mean looking time results given in the text, as there were for Study 1. To evaluate whether conclusions are supported by the data, these data would be helpful to include.

With the clarifications summarized above, this could contribute substantial new knowledge to the fields of ethology, cognitive psychology, and neuroscience.

Reviewer #3 (Public Review):

Szabó et al tested the representation of absence of objects in 8-day-old chicks, using a violation of expectation paradigms, in an elegant series of four experiments. The Authors designed a new paradigm to assess this fresh topic, obtaining data that support their conclusions. A deeper integration of this evidence with the previous literature on object permanence and numerical comprehension would help in understanding even better the relevance of these findings. In general, the study was conducted at high standards and I did not detect any objective errors in the paper.

Reviewer #1 (Public Review):

I read with interest the manuscript "Selection for infectivity profiles in slow and fast epidemics, and the rise of SARS-CoV-2 variants". I think that the method provides an important step forward in dissecting the nature of selection during a pandemic, allowing changes in transmission rate and generation time to be estimated from case numbers of different variants over time.

Reviewer #2 (Public Review):

This work presents a clear perspective on the relation between (relative) transmissibility, transmission advantage and generation time. The approach to infer these multiple parameters using the time dependence of the effective reproduction number is brilliant and innovative. Although it must be emphasised that due to the longitudinal time series required, it tends to work better for post hoc studies, rather than for real-time assessment of the features of a novel strain. Complex patterns of cross-protection between strains, or differential immunity from vaccination, are also likely to induce strong biases in this approach. Hence, this inference is probably inappropriate for scenarios like Omicron spreading among partially vaccinated/immune populations. However, if the strains offer complete cross-protection, this work provides a new interesting method to infer the relative transmissibility and timing of transmission of different strains.

Reviewer #1 (Public Review):

This well-written, convincing paper ties together three major topics. The authors first detail a general strategy to combine CRISPRi approaches previously reported by the authors in S. pneumoniae with FACS to identify larger or smaller cells. The goal is to carry out a CRISPRi screen coupled to FACS to identify genes whose decreased expression distorts pneumococcal cell shape, with focus here on increased cell size. A strength of this strategy, which the authors call SCRilecs-seq, is the availability of a robust CRISPRi system and fluorescent-protein labeling methods in S. pneumoniae that have been developed and reported in several previous publications from the Veening lab. Sorting based on increased forward light scattering (FSC) indicative of increased cell size led to the identification of 17 genes, whose decreased expression leads to increased FCS. This set includes genes involved in cell division, peptidoglycan (PG) synthesis, and teichoic acid synthesis, including two operons in the mevalonic acid synthesis pathway. The paper then explores how mevalonic acid synthesis is linked to cell size and PG synthesis, and further, how inhibition of this pathway can be used to potentiate amoxicillin killing of resistant pneumococcal strains.

The shift to an interesting biological problem means that the SCRilecs-seq method is presented here as a workable pilot method that could be further optimized. The authors point out in the Results and Discussion several classes of known essential genes that mediate cell size that were not detected in this first screen ("false negatives), some of which are in operons with other essential genes. They also point out that the encapsulated D39 used forms chains of cells that must be separated by vigorous vortexing that could potentially lead to loss of sensitive cells. Besides mentioning some potential issues, the authors might consider including additional suggestions of steps that could be taken in future studies to further optimize the SCRilecs-seq method. For example, isogenic unencapsulated D39 mutants do not form chains and often show more severe cell division and PG synthesis phenotypes than encapsulated strains. Therefore, unencapsulated strains would obviate the need for vortexing and perhaps increase the shape phenotypes caused by expression inhibition of some genes. Additional suggestions about ways to optimize the method in the future would add to this paper.

The second topic concerns how the mevalonic acid synthesis pathway causes elongation of pneumococcal cells. This section forms a playbook on following up candidates detected in SCRilecs-seq screens. The authors construct depletion/complementation merodiploid strains for operon 1 and operon 2 that encode genes in the pathway. They confirm elongation of cells by static and time-lapse phase-contrast microscopy and statistically robust determinations of cell lengths. They demonstrate complementation in strains with and without the fluorescent-protein reporters. As expect, from the pathways, deletion mutants of operon 1 can be fed mevalonic acid for growth. These physiological data are of high quality. One question that is not fully resolved is why depletion of operon 1 or operon 2 expression in culture leads to a drop in culture OD that levels out, which is interpreted as surviving cells, whereas depletion on agarose pads leads to complete lysis by microscopy. Likewise, starvation of an operon 1 mutant for mevalonic acid leads to complete lysis of the culture. Whether the depleted cultures actually contain survivors or debris can be checked by Live/Dead staining. Suppressor accumulation is suggested, but seems not tested. These phenotypes in different growth conditions might be tied together a bit more. Nevertheless, transformation assays and the mevalonic acid starvation experiments show that the pathways are essential in pneumococcus.

Experiments that localize FtsZ-rings or regions of active PG synthesis with fluorescent-D-amino acids led to a remarkable result. TEM indicates that elongated cells depleted for operon 1 or operon 2 expression start to pinch in a little, but stop. Similarly, depletion of operon 1 or operon 2 expression leads to elongated cells with multiple unconstricted FtsZ-rings and relative faint bands of FDAA labeling with the around cell diameters. Constricted FtsZ-rings and FDAA labeling less than cell diameters are absent. This pattern strongly supports the interpretation that septal ring closure and PG synthesis does not occur, while PG elongation continues at a reduced level. This pattern is highly reminiscent of the cells depleted for the GpsB regulator that is required for septal closure and PG synthesis, but phenotypically acts like a negative regulator of PG elongation. An interesting future question is whether the residual peripheral PG elongation during depletion is carried out by PBP2b:RodA as during normal growth or by other PBPs as part of a stress response.

The authors further test whether cell elongation upon mevalonate limitation occurs because of reduced undecaprenol-phosphate amount and whether this correlates with capsule, teichoic acid, or PG synthesis, that all use undecaprenol-phosphate as a carrier. In a well-designed series of physiology experiments, the authors first showed that mutants blocked later in the pathway to undecaprenol synthesis have the same elongation morphology as that caused by mevalonic acid depletion. In addition, only a late block in PG synthesis produced MraY depletion produced cells with the elongation phenotype observed during mevalonic acid synthesis. In contrast, deletion of capsule did not produce a growth defect, and depletion of teichoic acid synthesis led to elongated cells with a completely different cell morphology defect. The inference from the matching phenotypes is that the division defects caused by mevalonic acid limitation are largely caused by a lack of PG precursor, and this limitation is leads to residual PG elongation, but no septal closure. Several reasonable hypotheses for the mechanism of this differential synthesis are presented in the Discussion for future testing. Although the physiological data are high consistent with this interpretation no direct determinations of the final Lipid-II precursor were included in this study.

The authors did one further series of clever experiments to understand the phenotypes caused by mevalonic acid limitation. They applied the SCRilecs-seq method to cells depleted for mevalonic acid to identify decreased gene expression that would lead to even longer or smaller cells. The results show that depletion of gene expression involved in cell division or septal PG synthesis (e.g., FtsW, PBP2x) further elongated mevalonate-depleted cells, whereas genes involved in blocking protein expression, energy metabolism, or PG elongation (e.g., DivIVA, RodA, PBP2b) led to smaller cells.

The last topic builds on the idea that synergy between two antibiotics is often greatest when they target the same process or pathway. Since locking mevalonic acid synthesis limits undecaprenol and blocks PG synthesis, then there may be synergy with the beta-lactam antibiotic, amoxicillin that inhibits PBP transpeptidase activity, especially in amoxicillin-resistant clinical strains. To test this idea, the authors built on a previous result from Staphylococcus aureus showing that the FDA-approved drug fertility drug, clomiphene, inhibits undecaprenol synthesis. The authors used cell elongation morphology and mevalonic acid depletion to confirm that clomiphene likely inhibits undecaprenol synthesis in S. pneumoniae, although Lipid II levels were not determined. In addition, synergy between clomiphene and amoxicillin inhibition was observed for the virulent, sensitive D39 strain and for three more recently isolated amoxicillin-resistant clinical strains. This synergy did not occur between clomiphene and antibiotics that do not inhibit PG synthesis. An attempt was made to test the synergy in a murine lung model of infection with one of the clinical strains (19F) that showed an intermediate synergy between clomiphene and amoxicillin. However, no synergy was detected in vivo, perhaps because insufficient clomiphene dosing. Further experiments could try other clinical strains with greater in vitro synergy (e.g., 23F) or improving the clomiphene dosing.

Together, this paper presents a number of important new findings that will strongly impact the field. A successful pilot screening method has been developed for S. pneumoniae, a major human pathogen. This method will undoubtedly be optimized, refined, and expanded in future screens. The screen pointed to the critical role of mevalonic acid in pneumococcal cell shape determination. While not totally unexpected, this paper is the first to systematically study this pathway in pneumococcus. This line of investigation led to the remarkable observation that mevalonic acid and undecaprenol deficiency preferentially blocks septal closure and septal PG synthesis over weakened PG elongation, not necessarily by the normal peripheral PG elongasome proteins. The basis for this phenotype will be explored in future studies. Finally, once characterized, depletion of undecaprenol synthesis showed synergy with amoxicillin in amoxicillin-resistant clinical strains of pneumococcus for the first time. Thus, this paper goes from unbiased screening, to characterization of a pathway that affects cell shape through modulation of PG synthesis, to manipulation of this pathway for antibiotic potentiation in resistant strains.

Reviewer #2 (Public Review):

A major aspect of the authors' manuscript is their "sCRilecs-seq" method. This method sorts a CRISPRi library according to cell size and identifies mutants with significant cell size defects. Despite the promise of this novel, fundamentally sound method, much optimization of the experimental and/or analytical methods is required before this method will be of broad utility to the microbiological community. The major issue is regarding the reproducibility of the data, which then causes major issues with hit identification and limits the power of the method. To the extent that the authors wish to emphasize the method as part of the manuscripts' significance, these issued must be addressed head on and resolved.

The authors use their method to identify 17 operons with significantly larger cell size. Both operons encoding components of the mevalonate pathway are in this set, which suggests that inhibiting mevalonate synthesis may synergize with amoxicillin, an aminopenicillin antibiotic. In a series of thoughtful and elegant experiments, the authors show that indeed, inhibiting UppS (which synthesizes Und-PP from Farnesyl-PP for which mevalonate is an upstream precursor) using clomiphene sensitizes cells to amoxicillin. Although this finding may be of some clinical relevance, its significance is lessened by the fact that clomiphene has been shown to sensitize both Staphylococcus aureus MRSA and B. subtilis to beta-lactams, including amino-penicillins since at least 2015. Given the conservation of this synergy between MRSA and B. subtills, it is not surprising that it holds for Streptococcus. Moreover, since this synergy has been previously observed, it is not clear that the authors' sCRilecs-seq method was necessary to discover it.

Considered as a whole, the authors' method and follow-up experiments have the potential to uncover novel aspects of Streptococcus biology, but at the current level of analysis, it falls short of this goal. In my opinion, this paper could be substantially improved if the sCRilecs-seq method and/or analysis were improved, and if the authors' findings were better contextualized to highlight differences and similarities to MRSA and B. subtilis.

Reviewer #3 (Public Review):

This manuscript describes a powerful high throughput screening in the bacterial pathogen Streptococcus pneumoniae, that couples genome-wide CRISPR interference depletion with FACS sorting of elongated cells. This approach is therefore not limited to measuring changes in fitness but can be used to screen for mutants with any phenotype that can be detected by flow cytometry.

The results from the screen uncovered an important role of the mevalonate pathway on cell length, as well as new factors with unknown functions required for proper cell morphology in Streptococcus pneumoniae.

Upon depletion of mevalonate, overall peptidoglycan (PG) synthesis rate decreased. However, peripheral PG synthesis for cell elongation continued after septal peptidoglycan synthesis for cell division was inhibited. This suggests a form of regulation that directs PG synthesis towards septal or peripheral, depending on the availability of PG precursors. However, this mechanism is not identified.

Finally, authors use the knowledge gained from the screening to design a combination therapy of amoxicillin with clomiphene that resensitizes amoxicillin-resistant S. pneumoniae strains. This is in agreement with previous data from Eric Brown´s lab showing that clomiphene potentiates the activity of β-lactam antibiotics against methicillin-resistance Staphylococcus aureus strains.<br /> The authors then show that clomiphene/amoxicillin combination was not effective in vivo, using a murine pneumonia disease model, possibly because the active concentration of clomiphene in the lung was too low.

The manuscript is very clear and the experiments were carefully done. There are two major points that should be addressed

1.Authors mention that depletion of mevalonate operons prevents cell division and leads to cell elongation. This conclusion is based on cell morphology (longer cells) and on microscopy experiments assessing peptidoglycan incorporation (Fig 4D). However, it is not clear from Fig 4D that there is no septal synthesis. For example, in the panel corresponding to depletion of mevalonate operon 1, the top cell is constricted in the middle and the RADA labelling shows a constricted ring, similar to what is seen for the wild type strain. Authors should point clearly to what they consider peripheral and septal synthesis to be; should overlay the green and red signals so that localization of PG synthesis over time can be more easily seen; and should discuss their data in the context of the recent model for peptidoglycan assembly during the cell cycle of S. pneumoniae by the Morlot group (https://doi.org/10.1016/j.cub.2021.04.041) which proposes that "the ovoid-cell morphogenesis (relies) on the relative dynamics between peptidoglycan synthesis and cleavage rather than on the existence of two distinct successive phases of peripheral and septal synthesis".

2. Authors propose that the elongation phenotype due to downregulation of the mevalonate pathway is caused by "insufficient transport of cell wall precursors across the cell membrane due to a limitation in the production of undecaprenyl phosphate (Und-P)". However, this conclusion is based almost exclusively on the similarity of phenotypes of the uppS deletion mutant and the mevalonate mutants. The levels of Und-P were not measured. An alternative to measuring these levels could be adding exogenous Und-P, which should revert the elongation phenotype. In S. aureus addition of exogenous Und-P suppressed the activity of clomiphene, indicating that cells are able to incorporate the compound (doi: 10.1073/pnas.1511751112)

The authors focus only on the elongation phenotype upon mevalonate depletion. However cells are also considerably wider (cell width increases 1.35X). This is similar to what happenes in Bacillus subtilis, where clomiphene was shown to cause swelling of cells (doi: 10.1073/pnas.1511751112). It would be interesting to discuss what may be the cause for this phenotype.

Reviewer #1 (Public Review):

The hypotheses that 'Air Pollution Particles Hijack Peroxidasin' and thereby inhibit immune surveillance is striking, and of such broad and practical significance that it deserves thorough investigation. It adds to an already important set of reasons for particle inhalation be consider as promoters of cancer. The concept that the in situ adsorbed layer (protein corona) on the surface of particle can itself become an active catalyst in production of aberrant matrix is innovative. This concept as it matures could raise many new questions, for example linked to why different pollutant particles have different risks, and many other practical questions that have long eluded investigators. While this effect reported here is far from the only potential risk from such particles, it could well turn out to be a significant effect, with potential to be eliminated.

The chain of logic is that (1) particles adsorb a corona of peroxidasin (PXDN) and thereby (2) proactively catalyse type IV collagen (Col IV) crosslinking, (3) thereby inducing thickening of tissue matrix and (4) hampering migration of anti-tumor immunocytes. -decreasing the mobility of cytotoxic CD8+ T lymphocytes and impairing the local immune surveillance.

The hypotheses are intriguing, and each segment of this logic is backed up by appropriate experiments. The hypothesis is so broad and far reaching, and involves so many steps, that it is challenging to fully and conclusively prove each of these points and make them unassailable. Certainly, some of the steps in the argument will require much more research in future, especially those that establish the adsorbed enzyme as the sole actor in aberrant matrix. However, rather than a point by point questioning of the strength of each argument, in my view, it is more constructive to say the authors have done enough to make the overall hypothesis credible.

It is probably important to stress that these effects are not the only ones that particles induce that may be liked to early stages of cancer, and indeed to metastases, but experts looking at this article are likely to feel that the whole question is sufficiently interesting and sufficiently argued that it should be investigated in great detail.

Reviewer #2 (Public Review):

This manuscript focused on the bioactivity of inhaled fine particulate matter (FPM) in promoting lung tumor progression. The authors presented carefully performed work with impressive quantity. They shed light on that FPM accelerated tumorigenesis through disordering interstitial extracellular matrix in lung tissue and subsequently impairing early immune defense to tumor cells. Besides, they found that FPM's bioactivities are endowed by an unexpected enzyme, peroxidasin, related to the collagen crosslink and the latter's abnormal high enzymatic activity. These findings are promising to provide a new potential target for preventing FPM-relevant diseases.

Reviewer #3 (Public Review):

Smoke and air pollution have been linked to lung cancer in many public health reports. While tobacco usage is associated with an increased mutational burden in lung cancer cells and thus recognized as a carcinogen, the mechanism underlying the association between air pollution and lung cancer remains unclear. In this manuscript, the authors raised a new hypothesis, that inhalable fine particulate matter (FPM) acts through the extracellular matrix to inhibit the migration of immune cells, which impairs the clearance of tumor cells. They tested the hypothesis in mouse tumor models and found that the FPM directly promoted tumor progression through selectively crosslinking type IV collagens. They further demonstrated that FPM exerted its effects by recruiting and activating peroxidasin on its surface. The results of the study suggested that targeting peroxidasin may be used as a conceptually new strategy to prevent cancer.

Reviewer #1 (Public Review): 

The authors of this study carried out two carefully designed field and a glasshouse experiment simulating effects of rapid warming on soil carbon loss. They did this by transplanting alpine turfs from their cold environment to lowland warm environment. They found that when lowland plants were inserted into alpine turfs under these lowland climatic conditions (referred to as warming treatment combined with warm-adapted plant introduction) they rapidly increased soil microbial decomposition of carbon stocks due to root exudates feeding the microbes. 

The question is how well this experimental setup mimics what would happen if lowland plants would be inserted into alpine turfs in situ (which have already experienced considerable warming over the past decades), perhaps with an additional warming treatment there. A further question is if alpine plants inserted in turfs at alpine climatic conditions would have a similar effect as lowland plants inserted in turfs at lowland climatic conditions. 

I suggest that the authors consider these questions when they draw conclusions about the results from their experiments. It would also be interesting to discuss the relevance of sudden strong warming effects relative to slower warming, potentially allowing ecosystems to adjust via changes in genetic composition of species (i.e. evolution) or species composition of communities (i.e. community assembly).

Reviewer #2 (Public Review): 

The authors were trying to test whether the migration of lowland plants into alpine ecosystems affects the warming impact on soil carbon. To achieve this goal, the authors first did two field experiments (moving intact turf from high-elevation to low-elevation to simulate warming) in the Alps, and then did a greenhouse pot study to explore the potential mechanisms for the results observed in the field experiments. 

The main strenghs of this work are the combination of a field experiment (conducted at two sites) and a greenhouse pot experiment (to explore the detailed mechanisms). Moreover, a number of techniques were used to measure plant traits, soil DOM and microbial properties (e.g. CUE, growth) which help to find the potential mechanisms. 

The main weaknesses of this work are below: 

1) The two field experiments are very short-term (<1 year), but the results were that warming and/or warming+lowland plants led to very high amount of soil C loss (up to ~40%, Fig. 1). I was shocked to see these results as many field warming studies have shown undetectable change in SOC even after years or decades. The authors did not provide a good explanation for this rapid and large change in SOC. 

2) The greenhouse experiment was used to explore the potential reasons for the amplified loss of soil C in the field experiment. However, a key result was based on incubation of disturbed soils (8 g) and a two-pool modeling of the respiration data from the short-term incubation. This may not provide a good estimate of the true turnover rate of SOC under different plant species (even in the greenhouse condition). If rhizosphere priming was the proposed mechanism (as hinted by the authors), a better approach (such as 13C labeling) is needed to measure microbial respiration from intact soils (with plant/root presence). 

3) Some details of the sampling or measurement are very crucial and affect the results/interpretations. For example, in the field experiment, the soil core was only 1-cm diameter. Considering the spatial heterogeneity of soil carbon in field plots, this small volume may not well represent the true soil condition. Moreover, in the field plots, did soil bulk density change after planting of lowland plants or warming? This will affect the measured SOC concentration (mg/g) even the SOC stock (g/m2) did not change. 

The authors provide a lot of data from two well-replicated experiments, which is applaudable. However, I have concerns on some of the key results and conclusions as explained above. I would like the authors to further elaborate these concerns.

Reviewer #3 (Public Review): 

The authors investigated the effect of warming and herbaceous plant migration on soil carbon (C) content using an ecosystem monolith transplant experiment along an elevation gradient in the Swiss Alp mountains. They observed, approximately 1 year after the transplant, that warming alone had little effect on soil carbon content (monoliths transplanted to a lower elevation with higher temperature remained unchanged in C content) but that the presence of lowland (warm-adapted) herbaceous plants in combination with warming had a negative effect on soil C content. The authors then conducted a glasshouse experiment and used a series of field and laboratory measurements to explore potential mechanisms explaining the observed changes in soil C content in the field. They concluded that soil C losses under lowland plant migration were likely mediated via increased microbial activity and CO2 release from soil C decomposition. 

The research questions are extremely relevant to our understanding of the feedback between soil C dynamics and climate warming and remain an unexplored part of this debate. Moreover, both field and laboratory experimental designs are robust, with all the relevant and necessary validation checks needed for transplant experiments; the laboratory techniques employed to measure the range of microbial and plant variables potentially explaining soil C dynamics are adequate and modern; and the statistical analyses are appropriate. These elements make the present data set very relevant and valuable. The manuscript is also very well and clearly written. 

However, I have two major concerns, casting doubt respectively on the main field results and on the proposed explanatory mechanisms. 

First, at no point is bulk density mentioned and it does not appear to have been measured. This is critical because changes in soil C concentration (which was measured and reported here, in mg C g-1 soil) does not necessarily indicate an actual change in the quantity of C present in the soil (C stock, in unit mass C per unit soil volume, or per unit surface area to a constant depth) if this is accompanied by a change in bulk density: if less C per unit mass of soil (lower C concentration) is concurrent with more mass of soil in a constant volume (higher bulk density), this could mean that no change in C stocks actually occurs (or that even an increase occurs). In the present study, it is possible that the presence of lowland plants increased bulk density as compared to only alpine plants, compensating the lower C concentration and resulting in no change in C stocks. This is perhaps not likely, but it is too critical an issue not to be quantified (or at the very least discussed). 

Second, even assuming that no changes in bulk density occurred and that indeed soil C stocks decreased under warming combined with lowland plant migration, the interpretation of the results are, in my view, at least incomplete. Certainly, the results do not support the claim that soil C losses were mediated via increased microbial decomposition of soil C with the certainty suggested by the authors. Generally speaking, I see three issues with the interpretation: 

• Very schematically, increased microbial respiration and soil C losses from decomposition is only one of two equally likely pathways potentially explaining soil C losses (the other being decreased C inputs to the soil from the plant community). The possibility that decreased soil C content was simply mediated by decreased inputs of C to the soil is hardly explored at all in the study (there is a quick mention of it (L155), but differences in plant biomass are interpreted only for their correlations with microbial activity (L160-166), not as a component of the C balance. Plant traits are measured and analysed but not in a way that can be used to test the hypothesis of changing C inputs. The presence of "more productive traits" (L141) for the lowland plants does not directly relate to differences in the quantity of C inputs to the soil, nor is it interpreted in relation to inputs. Even the interpretation of changes in ecosystem respiration seem to omit the possibility of changes in plant respiration (L208): "depressed microbial respiration per unit of soil was also evident at the ecosystem scale in that warming accelerated total ecosystem respiration but its effect was dampened in plots containing lowland plants". This statement was made despite no significant differences in microbial respiration per unit soil in the field data, and disregards the possibility that the dampened effect in plots with lowland plants could be due to lower plant respiration.

• For the glasshouse experiment, I agree that the results indicate that (L115); "lowland plants accelerated microbial activity by increasing the quantity of root exudates", but not that (L112): "these findings together imply that lowland plants accelerate alpine soil C loss" because stimulating microbial activity is not per se an indicator of soil C loss. It is now well-known that the activity of microbes is not only a motor for soil C losses, but also a key mechanism leading to transformation of C inputs from plants that leads to the subsequent stabilisation of C in the soil. This is actually clearly stated further down in the manuscript when interpreting the field microbial data (L190. Furthermore, there is no direct evidence that the pots with lowland plants were losing more C than those without. Therefore, results from the glasshouse experiment could be interpreted differently: a larger fast cycling pool of soil C constituted of recently photosynthetically fixed exudates associated with higher microbial activity could well be interpreted as an early indicator of more C stabilisation, particularly since the absorbance index seems to indicate more microbially derived product in the DOC. It would have been great to measure microbial biomass C over time (as well as CUE, and mass specific growth and respiration), to see if higher respiratory activity was associated with higher biomass. The lack of differences in microbial biomass between the plant community treatments at the end of the 6 weeks does not show that the quantity of microbial biomass produced over the whole incubation period remained constant. In a word, more respiration of a larger fast cycling pool is not an indicator of future soil C loss (in the presence of plants).

• The interpretation of the microbial variables measured in the field line up better with current conceptualisations of the role of microbes in C cycling (but overall interpretation still lacks consideration for plant C inputs). However, interpreting those data measured once 1 year after the transplant to explain the changes that happened gradually over this whole year is a risky and difficult exercise. How do we know that CUE, Rmass, Gmass etc... measured then represent what they were a day, a week, a month before? There is an attempt to deal with this timing issue by comparison with the glasshouse experiment, but only Cmic and Rmass can really be compared and it only very partially fills in the gap in time. Besides, the interpretation of this comparison can be questioned: in the glasshouse, Rmass was higher for the lowland plant pots (as compared to alpine plant at constant temperature) but actually remained constant between the comparable treatments W and WL in the field (Fig 2m). The results from the field, therefore, do not "support observations from the glasshouse experiment" in this context (L197) and neither do they "confirm (...) that this persists for at least one season" (L199). Finally, the thinking around the pulsed nature of C losses seems misplaced because there are no evidence that soil C losses had stopped after a year in the field (no measurements of soil C content are presented after that year).

Reviewer #1 (Public Review):

This paper by Schapiro and colleagues interrogates psychophysical data from human participants performing different variants of a task that requires judgments to be made about the spatial locations of visual stimuli. Some task variants necessitate the maintenance of one or more stimulus locations over a delay period ('Perceived' task blocks), thus requiring working memory; other variants necessitate computing the average location of several stimuli that in some cases are separated in time ('Computed' blocks), thus additionally requiring the integration of multiple pieces of stimulus information that is generally characteristic of deliberative decision-making. Through manipulation of different task factors (stimulus set size; delay duration) and application of sophisticated computational models that model memory and decision representations as diffusing particles driven by multiple, sometimes shared sources of random noise, the authors illuminate how well-known capacity and temporal limitations of working memory can place strong constraints on the accuracy of decision-making. Moreover, they demonstrate how the nature of this constraint depends on the specific strategy that is employed to solve the decision-making problem, which varies across individuals and task variants.<br /> The paper breaks promising new ground in explicitly connecting computations for working memory and decision-making - two essential cognitive functions that have each been intensively studied, but often independently from one another. As such, the paper should be of broad appeal. One of the main strengths of the paper is that it establishes a principled framework within which shared and unique sources of variability in working memory and decision-making behaviour can be modelled and decomposed, which will surely be of benefit to researchers in these areas. The insight that individuals appear to employ different strategies ("average-then-diffuse" [AtD] vs. "diffuse-then-average" [DtA]) on the decision-making task variants, potentially in an adaptive, context-dependent fashion, is also very interesting and warrants further investigation.<br /> These highly positive points notwithstanding, I also feel that the paper in its current form has some limitations. These centre around clarity of presentation; appropriateness of some modelling choices; and possible missed opportunities to clarify both the consequences of strategy choice, and the apparent differences between working memory and decision computations:

Clarity of presentation:<br /> I regrettably found the Results section to be a difficult read, and several key aspects of the approach and findings were only clarified for me following a careful reading of the Methods section. I mention this as the first point of concern in my review because, as described above, I feel there is much of interest in the paper, but I am concerned that the at times impenetrable nature of the Results might turn off readers and limit the paper's impact on the field. Most prominently, there is insufficient explanation of key model predictions that may be counterintuitive for many readers; a lack of clarity around what individual model parameters capture; and confusing elements to how the model fits are presented.

Appropriateness of modelling choices:<br /> If I understand correctly, the A parameter (governing the relationship between the diffusion constant for a single point and the constants for multiple points) is estimated differently in the AtD and DtA models: in AtD, it's estimated using only data from Perceived blocks with set size > 1, and it plays no role in the AtD process (only, instead, in the memory maintenance process during the delay period of Perceived trials); whereas in DtA, it's estimate using data from both the same Perceived blocks, *and* the Compute blocks at equivalent set sizes. This raises two concerns. The first is that, because the A parameters in each model are effectively fit to different data, any comparison of the parameter estimates (which is invited by placing them in same table and by some of the discussion in the text [p.9]) needs to be carefully qualified in the associated text. The second concern is to my mind more serious: that there is an implicit assumption in the fitting of the DtA model that the A parameter is fixed across Perceived and Computed blocks. There is to my mind a strong argument against making this assumption: that Perceived trials with set size > 1 require working memory maintenance of a *conjunction* of stimulus features (location and colour), whereas the latter require maintenance (assuming the DtA process is employed) of only a single feature per stimulus (location); thus, it can reasonably be expected that the effect of load may be more severe in Perceived than Computed blocks. From what I can make out, this possibility is not allowed for in the presented model fits.

Implications of model fits:<br /> I feel that more could be done to clarify the nature and implications of two important features of the presented results. The first of these is the strategy used by different individuals in different task contexts. All else being equal presumably the DtA strategy should be preferred to the AtD strategy, because it incurs less of a time-dependent increase in error. There is no investigation, though, of whether indeed the participants who adopt DtA are indeed overall better performers on Computed blocks; or alternatively whether there may be some tradeoff evident in the data. One can imagine, for example, that DtA is the more demanding and energetically costly strategy to adopt (since it requires active maintenance of N points rather than a single point over time), and may only be employed to counteract other sources of error, for example by participants for whom non-time-dependent noise sources are especially large. There is minimal speculation, and from what I can tell no comprehensive effort to address such questions in the manuscript.<br /> The second feature of the results that I feel is somewhat neglected is an exploration of the *differences* between the working memory and decision-making components of the behaviour on Computed trials. My impression is that in the modelling framework, decision-specific computation is captured entirely by additional non-dependent noise sources (eta_MN) but these are given little attention in the manuscript.

Reviewer #2 (Public Review):

This paper uses human psychophysics to study the limitations of memorizing several objects at different spatial locations (working memory) and computing their average location. The authors convincingly show that both perceived and computed variables are subject to working memory constraints (limited capacity and decreasing precision with time). The observed working memory limitations are consistent with classical findings. Mathematical models based on diffusive bump attractor dynamics are presented that allow, in principle, to distinguish different task strategies for computing the average location. The paper is very well written, and the different model predictions are exposed clearly. However, the experimental evidence for the two different strategies is rather limited and additional analyses are needed to confirm that there are indeed two strategies. Moreover, the paper does not convincingly address the question of temporal evidence integration, a hallmark - and in my view - main feature of perceptual decision making.

Strengths

The investigation of how a latent variable (the computed average) degrades over time is a novel and interesting experimental paradigm to link findings from working memory studies (that usually do not require a computation or evidence accumulation) and perceptual decision making experiments (that often probe categorical choices).

The mathematical models are well-grounded in mechanistic models of working memory and make interesting predictions.

Weaknesses

The paper studies the integration of evidence over time only in a very limited setting (either two stimuli presented sequentially or 4 stimuli simultaneously and 1 sequential). As the authors point out evidence integration means to update a "decision variable" over time (line 287: "evidence accumulation over time (i.e., in which a new piece of evidence is used to update a computed quantity"). However, for almost all subjects the DtA model, in which the decision variable is computed at the end of the trial, fits the data as well as the AtD, the model that actually relies on updating a computed quantity (Fig 10, delta LL in the range of -3 to +3). Based on this, I don't think it is clear whether the sequential condition experiment tests evidence integration per se or rather the degradation of working memory with sequentially presented cues.

The authors claim that some subjects follow the AtD strategy and others the DtA strategy but experimental evidence for this claim seems very weak. I take Fig 10 as an example (Fig. 6 is similar). The authors conclude from the data in Fig 10 that on the population level there is no significant difference between the models. On an individual subject level, the delta_LL values are small (for most subjects | delta_LL | < 3) which I would interpret as either model fitting the data equally well. I think in order to claim that there are indeed two different strategies in place, it needs to be shown that the data can only be explained by heterogeneous strategies (for example following a methodology as in Stephan et al Neurimage 2009 and Rigoux et al Neuroimage 2014). The alternative explanation is that the data does not allow to distinguish the two different strategies. In the text, it seems ambiguous now what exactly the finding is (compare line 244 "(...) participants had roughly equal tendencies to use either of the two strategies" implying that we can distinguish which strategy individual subjects are following, vs. line 257 "(...) neither of which was more likely than the other for a given participant" which implies the opposite).

Reviewer #1 (Public Review): 

This study concerns insular activity recorded from 7 human participants while they viewed depictions of others in pain, evidenced by movies of both facial expressions made by a model or a hand being hit by a belt. Overall, the study has much to recommend it. The iEEG data are rare and difficult to acquire, and the authors performed a number of interesting and creative analyses. These include analyses of correlations with subjective rating, timing of pain rating-correlated iEEG signal relative to facial and motion information in the movies (and assessments of independent raters), and analyses of functional connectivity leveraging Neurosynth and a previously unpublished fMRI study. The evidence for insular encoding of perceived pain from hand movies seems to be strong, but the evidence for encoding from facial expressions is weak. It may be, however, that some electrodes encode pain intensity from facial expressions reliably. The main signal was a broad-band (20-170 Hz) signal that occurred in the first second after hand presentation, and perhaps somewhat later for faces, corresponding generally to when pain-related information appeared in the stimuli. 

Assuming the "trend-level" responses related to pain facial expressions are reliable, there are several other interesting characteristics that emerged from the analyses. The analyses suggested overlapping, but separable, distributions of insular locations that encode pain from hands, faces, or both. This is consistent with work on population coding in other areas, and suggests (as the authors argue) that signals at many locations cannot be reduced to "salience" in general as they code for pain inferred from specific stimulus types. These results add to the literature, and appear to correspond with other fMRI studies that have examined intensity-coding of perceived pain. For example, Krishnan et al. 2016, eLife found that among individual brain areas that predict intensity of perceived pain from pictures of hands and feet, the insula was among the most strongly predictive. (They also found that a distributed network including other brain regions as well was much more strongly predictive). Zhou et al. 2020 eLife studied perceived pain from both facial expressions and pictures of body parts. They identified an overlapping area of the mid- and anterior insula that predicted perceived pain across both stimulus types. That area may be similar to the locations with overlapping encoding observed here, and the distribution across the insula of differentially predictive signals for body parts and faces may be similar to the distribution observed here. Both these studies analyzed relationships between brain activity and trial-by-trial ratings of perceived pain, and so are directly comparable. 

The present results are also consistent with earlier studies that did not test the relationship with perceived pain, but tested multiple types of stimuli related to pain or other emotions. Corradi-Dell'Acqua et al. 2011 studied fMRI responses to pain-related, non-painful but threatening images, and neutral images, and found responses in the insula to both types of negative images. Later, Corradi-Dell'Acqua et al. 2016 extended this overlap analysis to local multivariate patterns of activity in response to shock pain and disgusting tastes administered to self and other, and to perceived unfairness in the Ultimatum Game. They found evidence for common patterns, particularly in the right anterior insula. 

Based on these studies, it would be interesting to see whether the iEEG signals recorded in this study would respond similarly to other types of aversive stimuli, including somatic pain. That would inform the field on whether they are related to pain perception or to another, correlated affective state. Though the authors rightly argue that the differential encoding of perceived pain implies that the entire insula cannot simply be encoding "salience". However, neurons respond to complex configurations of properties, and it may be possible to find signals in the insula or elsewhere that respond to many different combinations of stimulus properties, including conditional ones (e.g., only aversive stimuli delivered to the hand) without truly "representing" or encoding the perception of pain per se. Conclusively identifying a representation of perceived pain, or any other construct, is a noble but difficult challenge, however, and this work takes a step in this direction. 

Another interesting comparison would be the comparison with somatic pain. While early studies identified common patterns for observed and experienced pain in the anterior insula (Singer et al. 2004, Lamm 2011, and the Corradi-Dell'Acqua et al. papers), studies that used multivariate patterns to predict trial-by-trial pain experience (both observed and experienced) found distinct predictive patterns with little evidence for overlap (Krishnan et al. 2016, Lopez-Sola et al. 2017), though some evidence for an observed-pain predictive pattern transferring to somatic pain was found by Zhou et al. 2020. It's not yet clear whether the iEEG recordings observed here generalize to pain experience. 

There are a number of additional limitations to keep in mind: 

1. Notably, the authors do not intend to interpret the generalizabllity to direct pain experience or other affective states, or specificity to pain compared with other affective conditions; but without more information about these, it is difficult to tell what the signals in the insula actually represent. It leaves open the possibility that there is another, better explanation for activation of insular neurons than perceived pain. e.g., It could be about representation of the body more generally, rather than perceived pain specifically. Could they be coding for choices (ratings) themselves? Baliki found that insular activity correlates with rating intensity of a simple visual stimulus, and other studies (e.g., Grinband et al., Neuron) have found that the insula correlates with simple perceptual magnitude decisions.This will be an ongoing project for future work. 

2. A nice feature is the comparison of insular electrodes random electrodes "throughout the brain", but what electrode locations were available, in how many individuals, and what is their distribution? Surely there are not electrode placements *everywhere* in the brain. 

3. The stimulus set chosen was limited, and appears to relate to one specific type of painful stimulus on one hand model, and one set of facial expressions made by one female model. As it's well known in general that neurons often have complex receptive fields, it's unclear whether other types of painful hand stimuli or facial expressions made by other models would yield similar findings. Perhaps the insula would respond more strongly to other faces - or perhaps not at all. Other studies have shown that women's pain is discounted (Zhang et al. 2021). The need for diverse sets of stimuli to establish relationships with brain activity that are not stimulus-specific is becoming increasingly recognized (e.g., Yarkoni 2020, Westfall and Yarkoni). 

4. There do not seem to be significant brain correlations within faces alone that survive correction for multiple comparisons. Fig 3 shows a "trend"-level result, not significant. Could this indicate a "hand vs. face" effect that appears as a correlation in Fig 2? If hands are rated higher than faces, and hands produce greater BBP in the insula, then any electrode that responds to hands more than faces will show up as a correlation between brain and rated intensity. The way to test this would be to test and show correlations within hands and faces separately, but these were apparently not significant for faces. 

5. The iEEG signals are compared with fMRI indirectly, via Neurosynth and another new fMRI study. It would be useful to compare the maps with the cross-modal (body parts and faces) insula patterns predictive of observed pain from Zhou et al. 2020 in particular, which are available for download. How do the locations of activity patterns in this fMRI study correspond to the present iEEG locations, both in terms of common encoding across hands and faces and differential encoding.

Reviewer #2 (Public Review): 

Taking advantage of the high spatio-temporal resolution of intracerebral EEG, the aim of this study was to characterize the electrophysiological responses of the human insula that may be elicited by viewing pain being experienced by another. 

Patients were presented with two kinds of video clips: short videos of a hand being slapped by a belt and short videos of a face expressing pain while the hand was exposed to painful electrical stimuli. The authors found that both types of stimuli elicited broadband activity within the insula which correlated with reported intensity ratings. 

A strength of the manuscript is that, to better understand the time course of the elicited responses and their relation to perceived intensity and take full advantage of the temporal resolution of iEEG recordings, the authors conducted an in-depth analysis of the motion and shape information contained in each video clip, to understand how variations in these stimulus features as a function of time could be used by the participants to decode intensity of the viewed experience. Most importantly, the authors also characterized the relationship between the temporal dynamics of these stimulus features (motion and shape) and the time course of the correlation between insular activity and pain ratings. 

A question that one could raise - especially for the hand condition - is whether part of the trial-by-trial correlation between insular activity and ratings was the consequence of a relationship between that activity and low-level motion/shape features of the video clips, rather than a reflection of the insula being involved in "intensity coding for the pain of others". Fortunately, this question was at least partly addresses with the available data, by showing that the recorded insular activity correlated with motion energy when the motion was associated with pain (during the slapping of the belt), but not while the motion was innocuous (during the initial lifting of the belt). 

Nevertheless, as mentioned by the authors themselves, future experiments using additional control stimuli such as stimuli matched in terms of motion content but differing in the emotions they convey are critical to better understand the specificity of the described insular responses. 

While the broad-band cluster correlating with pain ratings for hand stimuli appears convincing - both in terms of strength and spatial distribution across electrode contacts - , the correlation between insular activity and pain ratings to face stimuli appeared more marginal and spatially scattered. For this reason, it is important to interpret cautiously the observed differences in the topographical distribution of the insular responses in the hand and face conditions. This is already acknowledged by the authors in the discussion section.

Reviewer #3 (Public Review): 

The study contains a very large number of analyses and tests. In some sense, this is both a strength and a weakness. It is a strength because it offers a more comprehensive description of the responses in the insula and how they might contribute to intensity of coding for pain-of-others. It is a potential weakness because each analysis involved decisions that can be somewhat questioned in terms of approach, appropriateness and validity. A thoroughly written review of the paper would therefore lead to many, many pages of detailed questions and comments, which I will not pursue here. I will give the authors the benefit of the doubt and assume that most of them are reasonable. 

However, because the study involved recording across 85 electrodes across time, the authors need to provide a more detailed description of the several treatments of multiple comparisons. They mention "Corrections for multiple comparisons are performed when repeated testing is done across timepoints using either FDR corrections, or by calculating a null distribution of cluster statistics." but this is insufficient and merits a subsection explaining the overall logic and necessary information for all instances involving multiple comparisons. For example, the method described by Maris and Oostenvald (2007) is excellent but not described clearly enough. 

One-tailed testing is controversial but again I won't quibble with its use in some of the analyses. But I simply don't understand the motivation in some cases. For example: "Averaging BBP power over the entire pain period revealed that out of 85 macro contacts, 27 (32%) showed a significant positive correlation (assessed as p1<0.05, Fig. 2c)." What justifies a one-sided test of this correlation? I think in this case (and possibly others) two-tailed tests would be more appropriate. 

Two out of the 9 patients were excluded due to "poor behavioral performance" but further information about the exclusion criteria were not sufficiently discussed. 

Data from 28 unit recordings were provided as additional evidence of pain-of-other coding. This is a very low number of units across only 3 patients, especially given that the results are based on 13 units that showed higher firing during the pain period compared to the baseline period. My own take is that these results probably should not take part of the manuscript, but other reviewers and the editor may disagree (besides, I don't agree that reviewers should tell authors what to include or not in their manuscripts!). In any case, the wording related to these findings should be revised to reflect the exploratory nature of these results. For example, I do not believe these results warrant labels such as "hand/face specific". 

The authors report timing effects in the range of 40-320 ms. They cite the well-known study by Krolak-Salmon and colleagues. But it is difficult to know what to make of the current results. On the one hand, latencies on the range of 200-300 ms (across the brain) would be compatible with some studies (but not others), how does one interpret latencies as low as 40-60 ms in the insula, which presumably are not really feasible. On the other hand, the results in the 560-1000 ms range are consistent with many studies but are discussed as "too slow". I don't know what the editor would suggest here, but I'll defer to their opinion about how to handle this. 

Despite familiarity with fMRI I found section 2.7 very difficult to follow. Based on the other reviews/editor, if the authors decide to keep this section, I would very much welcome a careful rewrite of this section. 

My final comment is about how the Discussion (and other parts of the paper) talks about "selectivity for Hand or Hand stimuli". The study makes use of a fantastic stimulus set from the research group. But if I understand the set correctly, the same actor is used for different levels of pain (face- and hand-based). While this is an excellent set to study some aspects of coding related to stimulus "preference" I don't believe it's general enough to establish "selectivity". Accordingly, I think it would be more reasonable to avoid the claims of "selectivity".

Reviewer #1 (Public Review):

The work by Byazrova and colleagues examines B cell responses following Sputnik V vaccination in naïve individuals, as well as individuals who were previously infected with SARS-CoV-2. A strength of the work is that there have been few very studies examining immune responses following Sputnik V vaccination, this paper goes beyond simply measuring the neutralising antibody response and encompasses a detailed investigation into plasma cell and memory B cell responses. Similar to findings examining responses to other SARS-CoV-2 vaccines, they show that individuals with a prior history of SARS-CoV-2 infection mount a stronger neutralising antibody response following a single dose of vaccination than naïve individuals. Following 2 doses of vaccine, antibody responses were generally still superior in previously infected individuals, including neutralising antibodies against the ancestral and Beta variants.

A weakness of the study is the size of the cohort, which limits the conclusions that can be drawn from the data. The last figure of the manuscript attempts to group the patients based on their B cell responses and finds that 3 naïve patients cluster with the previously infected individuals and these patients have been termed 'high-responders'. However, I note that patient 19 is within this cluster, and I am wondering if they are truly a naïve individual. ELISA data presented in supplementary figure 2 shows that this patient possessed anti-RBD IgG antibodies, although lacked anti-N antibodies. Studies have shown that anti-nucleocapsid antibodies wane faster than those directed against spike, so perhaps the authors need to consider that this patient was not truly naïve prior to vaccination.

It would also be of interest to readers if an analysis of neutralising antibody titres against the delta variant were investigated. This variant is now the dominant in most regions including countries where Sputnik V is in use and therefore the protection afforded by Sputnik against this variant is pertinent.

I think it is also important to include historic control samples when performing pVNT assays to control of off-target effects, particularly when using undiluted sera or media from stimulated cells. Were any of these controls performed? Additionally, why only test against ancestral virus when using antibodies from stimulated cells? Inclusion of variants in these experiments could provide additional information about affinity maturation over time and the impact on recognition of different variants.

Reviewer #2 (Public Review):

In this manuscript, Byazrova and colleagues assessed aspects of the humoral immune response to the Sputnik V COVID-19 vaccine, deployed extensively in Russia and selected countries globally. A cohort of 22 individuals were recruited, encompassing 5 who had previously been infected with SARS-Cov-2, and longitudinally followed over the course of a two immunisation schedule. In naïve individuals, two doses was sufficient to raise robust titres of binding and neutralising antibodies against the SARS-CoV-2 spike, whilst convalescent individuals experienced a rapid recall of humoral immunity after a single shot that surpassed levels obtained in fully immunised naïve individuals. Antibody levels were stably maintained out to ~85 days post immunisation and a degree of neutralisation escape against the Beta variant of concern were reported.

A strength of the study is the in-depth phenotypic characterisation of the plasmablast and memory B cell responses to immunisation, which were quantified using flow cytometric and ELISpot approaches. In terms of weaknesses, the small cohort size limits the robustness of the conclusions, and the lack of a direct comparison to other available vaccines does not allow any conclusions to be made about the comparative benefits or limitations of the Sputnik V platform over alternative platforms. In addition, a characterisation of anti-vector responses would have been informative to guide deployment of Adenoviral vectored vaccines in the future.

Overall, this study complements suggests the broad immunogenic properties of Sputnik V largely mirror that of other COVID-19 vaccines deployed to date. The findings support the idea that a single immunisation of any vaccine is sufficient to boost protection in previously infected individuals, while two or three immunisations are required in naïve individuals to reach similar serologic outcomes.

Reviewer #3 (Public Review):

Byazrova et al. examined the effect of previous infection on Sputnik V vaccination elicited anti-SARS-CoV-2 spike antibodies and neutralization. They found that neutralization is enhanced. Interestingly, the authors also observed higher numbers SARS-CoV-2 spike RBD specific antibody secreting and memory B cells in vaccinated previously infected participants. In these participants, there were prominent B cell responses like anti-spike RBD IgG secretion and neutralization capacity of antibodies derived from in vitro stimulation which were absent in the vaccinated only participants. This may show qualitative differences between vaccinated only and previously infected and vaccinated participants.

Reviewer #1 (Public Review):

This is a very careful and systematic hybrid system analysis of the mechanism underlying alternating bursting in mutually inhibitory neurons or half-center oscillators (HCOs). By clever use of dynamic clamp, the authors create HCOs between non-connected living neurons (from the crab stomatogastric ganglion) of the same type by adding artificial synapses and h-current. This hybrid system allows them to manipulate synaptic threshold as a control variable to engage different oscillatory mechanisms escape and release, which are based on a theoretical understanding of HCO operation. They also have control of synaptic and h-current conductance and dynamics (activation-deactivation) and manipulate these variables or as proxies for changes in temperature of circuit operation. Using the synaptic threshold control variable to set escape or release mode they discern difference of these manipulations on burst characteristics in escape vs release modes. In separate experiments, they also add a modulatory current (similar to a persistent Na current) in dynamic clamp and explore it effects on HCOs in escape and release modes. The end result is a thorough analysis of how oscillator mechanism in an HCO, a basic circuit building block, affects circuit responses to perturbation and modulation.<br /> The experiments are well performed, and a deep and rich data set is generated that is appropriately analyzed. The findings are significant for all interested in oscillatory network function and its resilience to perturbation and modulation.

Concerns:

Robustness is often mentioned but is not precisely defined. Operationally robustness seems in this paper to stand for robustness to 1) activity regime change under parameter variation, 2) stability of burst characteristics with parameter variation, and 3) slow-wave amplitude, spiking strength (spike frequency), and symmetry of bursting. These are three very different things and should be clearly differentiated in the text so that when robustness is mentioned, the type of robustness is made clear. Perhaps robustness should be limited to the first, activity regime, and some other terms used for the other two.

On several occasion in the text the authors refer to irregularity in bursting of the hybrid HCOs, but this is not quantified beyond displaying exemplars that seem to have irregular bursting. Pooled data should be analyzed in the different modes and manipulations and analyzed for statistical difference in the CoV of cycle frequency (or period) and burst duration. Similarly, the authors cite changes in symmetry in bursting in exemplars but do not present pooled quantitative data in support of the claim, just visual inspection of exemplars.

In the stomatogastric networks, synaptic transmission is largely graded (based on release mediated by the slow wave of oscillation) and not so much spike-mediated, so it is reasonable that synaptic threshold should be a control variable in this system. Moreover, spikes, recorded in the cell bodies are not reflective of their amplitude at the SIZ. In other system transmission can be largely mediated by spikes. At the beginning of the paper (Figure 1), it is clear that release mode in their hybrid HCOs depends on spike-mediated transmission because synaptic threshold is above the slow-wave depolarization, thus spike frequency is a key feature determining the mechanism of oscillation. However, in escape mode the transmission is purely graded because synaptic threshold is so low that transmission is saturated by the slow-wave depolarization and spikes contribute little if anything, thus spike frequency is immaterial to the mechanism of oscillation. This situation should be addressed at the beginning of the paper in reference to Figure 1. How this spike-mediated vs. graded balance plays out in the mixed mechanism modes remains to be explored.

In Figure 1C, the authors show convincingly that there is a vast landscape where their hybrid HCO operate in a mixed mechanistic mode somewhere between escape and release corresponding to synaptic thresholds in the middle range. This mixed mode is addressed only with a single exemplar in Figure 8B as a case for how modulation affects mixed mode circuits. The Discussion should reflect plainly that this mixed mode is likely common in biological circuits and may go hand-in-hand with significant reliance on spike-mediated transmission.<br /> The authors state "The modulatory current (IMI) restores oscillations in release circuits but has little effect in escape circuits." but this is supported by a single exemplar (Figure 8E) and no pooled data is presented.

Reviewer #3 (Public Review):

The authors demonstrate that the mechanisms of switching between components of the reciprocally organized half-center network are not fixed and may shift to favor a release or escape mechanism depending on factors such as the synaptic threshold, Ih conductance, and synaptic conductance. This is a fundamentally important study because reciprocally organized networks are ubiquitous and found virtually in every organism.<br /> This study leads to the important conclusion that a given rhythmic output alone does not reveal the underlying rhythmogenic mechanisms. A rhythmic output is not based on one "fixed" mechanism, but on the interplay between different rhythmogenic modes. Moreover, because of this interplay it is impossible to predict how this network will respond to perturbations.

The study is an important reminder that even a small two neuron network with a well defined, extremely simple "connectome" is strikingly flexible and complex: an important lessons for those aspiring to obtain complete connectomes in mammals in the hope to reveal the secrets of the brain.

Reviewer #2 (Public Review):

This manuscript provides a very detailed and thorough examination of an important issue in neural circuit research, namely how the mechanisms underlying neural activity relate to robustness in the face of perturbations. It examines the simplest neural circuit possible, one involving just two neurons that reciprocally inhibit each other, which is capable of producing rhythmic alternating activity. The research shows that there is a continuum of mechanisms based on synaptic and membrane properties of the two neurons that can generate a robust output. At one end of the continuum, each neuron escapes from the inhibition of the other. At the other end, each neuron releases the other from inhibition. In the middle, both mechanisms contribute to generation of rhythmic activity. The effects that perturbations such as temperature and neuromodulators have on the circuit depend upon where the mechanism of oscillation lies along this continuum.

This paper has several important strengths:

It uses dynamic clamp technique to artificially couple two real neurons and provide them with a membrane conductance that they don't normally have. This is a powerful technique that merges experimental and theoretical neuroscience because the researchers are able to systematically alter parameter values such as synaptic strength and ionic conductance that are not feasible to modify biologically. Yet they are also monitoring the activity of real neurons.

The manuscript thoroughly represents the results and convincingly demonstrates how release and escape mechanisms are differentially affected by perturbations. The method of data visualization is very effect at summarizing complex results.

An important conclusion drawn from the results is that half-center oscillators using a release mechanism are more robust to variations in synaptic and membrane conductance.

Another important conclusion is that the same circuit can produce a similar output using different mechanisms and that it is not possible to know which mechanism is used without looking at the effect of perturbation.

The weaknesses in the manuscript are minor and are merely aspects related to the presentation of the work, not its substance.

Reviewer #1 (Public Review):

In this study, Zheng and colleagues report the novel findings that in diabetic models hyperglycemia suppress HIF1a in a PHD-dependent manner, and this in turn leads to increased mitochondrial ROS and cell death. Both the increased ROS and the cell death are prevented by increasing HIF1a activity either pharmacologically or genetically.

The paper is novel, informative, and with interesting translational implications. The authors used a variety of in vitro and in vivo models for the testing of their hypothesis, with special emphasis on a model of diabetic nephropathy.

Reviewer #2 (Public Review):

The manuscript by Zheng et al addresses the question of whether abnormal HIF stabilisation in response to hypoxia could be responsible for the increased ROS generation in diabetes, and whether hyperglycaemia could be the driver for the ROS damage and cell death in hypoxia. Diabetes complications across multiple organs are associated with oxidative damage and are accompanied by restricted oxygen delivery due to vascular dysfunction. Thus, understanding how these two phenotypes are linked by diabetes is an important question for advancing our understanding of diabetes complications and to identify novel therapeutic targets.

Strengths

This study uses multiple different techniques to address this question, using cell culture, animal models as well as human samples.

Mechanistic conclusions are based on both genetic and pharmacological approaches, adding strength to the key findings.

This is an excellent continuation of high-quality work conducted by this group in this field. The conclusions have far reaching consequences within the field.

Weaknesses

Although the authors establish a translational pipeline for their findings, from cells to animals to humans, the findings from the human studies could be interpreted in alternative ways to that presented. Cells cultured for 24hrs in hypoxia have sufficient time to activate the HIF transcription factor, its downstream targets and result in a functional outcome for the cell. Humans exposed to hypoxia for 1 hr will not have the same time to induce the HIF-dependent effects, and other mechanisms will be at play. To some extent this is due to the difficulties of performing mechanistic studies in humans, however, care should be taken in not oversimplifying findings and instead highlighting alternative conclusions.

Reactive oxygen species are a group of molecules comprising different species with different reactivities. It is important to be clear which aspects of ROS and their downstream damage are being measured with these methodologies

Care must be taken to ensure the correct statistical analysis is performed based on the groups assessed, the study design and the scientific question being asked.

Reviewer #3 (Public Review):

Strengths:<br /> 1. Oxidative stress and damage is central to pathology of diabetic complications. As mitochondria are a key generator of ROS-mediated damage, the authors nicely connect glucose-dependent HIF1a deficiency with the development of mitochondrial ROS-mediated damage.<br /> 2. Approaches to understand and target oxidant stress in diabetic complications are elusive and the authors nicely delineate a PHD2-dependent mechanism by which HIF1a levels decline, subsequently giving rise to renal dysfunction.<br /> 3. Notably, improvement of HIF1a levels by PHD2 pharmacologic or genetic inhibition appears to ameliorate renal injury independent of glycemic control. This could be of high translational value as therapies to ameliorate diabetic nephropathy do not exist currently in the clinic.

Weaknesses:<br /> 1. The mechanism by which hyperglycemia precipitates PHD2-dependent HIF1a degradation and activation of renal injury is not clear.<br /> 2. The induction of mitochondrial damage to elicit mitochondrial ROS and subsequent renal compromise downstream of HIF1a deficiency is proposed to be via PDK1. It would strengthen the paper if the PDK1-dependent mechanism was further solidified.<br /> 3. Clinical data on patients with uncontrolled T1D and impaired circulating hypoxia responses are very interesting, but it is unclear how they directly relate to the renal specific findings presented in the remainder of the manuscript.

Reviewer #1 (Public Review):

This is an interesting study of the relation between vividness of visual imagery and the pupillary light response that can result from it. The authors collected data in two experimental paradigms, which they ran in two independent samples. One of these samples was a larger group of psychology students; the other a self-reported group of people with aphantasia. In a first paradigm, the authors show that a lack of vivid imagery is associated with a smaller (or even absent) pupillary light response. Using a second paradigm, binocular rivalry, they show that the degree to which imagery primes binocular rivalry is correlated (to a degree that is quite striking) with the magnitude of the pupillary light response to imagined stimuli. These results were obtained both for low-scoring individuals in the large sample as well as for the aphantasics. The study provides objective evidence for the absence of imagery in individuals that self-report as aphantasic.

The paper is well written and all the necessary controls for potentially confounding variables are in place. For instance, age or visual persistence are discussed and excluded as alternative explanations based on convincing analyses. A particular strength of the manuscript is that the authors report positive results for pupillary responses in the group with aphantasia. That is, these individuals show regular pupillary responses to changes in physical stimulus brightness as well as to cognitive load. Another strength is that the group of aphantasics was invited separately and not determined post-hoc in the initial sample.

In summary, there is a lot to like about this paper. I have three comments / questions that I think should be addressed, however.

1. A point that I would like to see analyzed and discussed is the role of eye movements. The authors do not report any analyses of fixation behavior or the frequency of saccades in the two groups. These should be analyzed and reported. The only mention of fixation control is in lines 423-424, but the authors remain at a very superficial level, stating that footage from this scene camera of the pupil labs eye tracker was "assessed to ensure fixation on the computer monitor". Does this mean that participants could look anywhere provided they looked at the monitor?



2. In Figure 1D (also lines 120-124), the authors show a correlation between vividness ratings and the pupillary light response. I assume that participants differ substantially in their distributions of responses. So these correlations could be a consequence of individual differences or they could provide evidence for trial-by-trial variation. There might be ways to find out. For instance, is there evidence for these correlations at the level of individuals? Does the correlation persist if individual vividness-response distributions are normalized to span the same range for each observer?

3. In lines 314-315, the authors state that the pupillary light response to imagined stimuli may serve as an objective indicator of aphantasia. I think this is taking the interpretation of the data too far, mainly for two reasons. First, the authors haven't shown that low pupillary light response predicts aphantasia in a group of people that does not self-report as aphantasics before the test. Second, the absence of a pupillary light response (in a new sample with no additional controls) could also indicate a lack of motivation to engage in imagery. The authors should thus clarify that such tests would always have to be combined with positive tests that show the commitment of participants to the task instructions.

Reviewer #2 (Public Review):

Kay et al. investigated visual mental imagery in the general population and the lack thereof in individuals with aphantasia by measuring the pupillary light response to imagined light and dark shapes. Their findings are twofold. First, they show a link between pupil size change and perceived vividness of imagery and corroborate this finding using another established objective measure of vividness. Secondly, they found a lack of such a pupillary light response in a group of individuals who maintain no visual experience of imagery. This demonstrates the usefulness of using the pupillary light response as a measure of subjective vividness of imagery and potentially demonstrates the first physiological finding in aphantasia.

Strengths

The experiment incorporates several different dimensions into a single clean design that is useful for isolating and tracking multiple relevant measures. First, by having the brightness of the perceived and imagined shapes vary across trials, the authors could show that changes in the pupillary light response correspond to changes in imagined brightness. The authors also added in an independent number-of-objects dimension since pupil size also varies with cognitive effort. This provided evidence that aphantasic subjects were attempting to imagine, since the pupil size did change with set size, even when it didn't change with brightness. Finally, by having subjects report the perceived vividness of each imagined image, the authors could link subjective experience of imagery to the pupillary light response.

The authors also strengthen their findings by comparing changes in pupil size to an objective measure of imagery vividness. By leveraging the fact that imagery mimics vision's ability to bias a perception during binocular rivalry, the authors avoid the severe limitations present in measures that rely on introspection only.

Weaknesses

Due to the inherently private nature of mental imagery, ruling out fabrication or demand characteristics is extremely difficult. This is especially true in aphantasia research, as we are often looking for the absence of an effect rather than an enhancement. Readers should keep in mind that, while the authors made some effort to confirm that the aphantasic subjects were attempting to imagine, the potential for this and other biases were not ruled out. Without the use of probes to test subjects on the remembered/imagined objects and reporting the outcomes of catch trials, it is difficult to tell whether subjects were fully engaging with the stimuli.

Readers should also take the pupillary light response as a tool to add to the battery of assessments for aphantasia, not as one that a diagnosis can be based on alone. While the authors do show a group level difference in pupil size in response to imagined shapes and claim it as a "new low-cost objective measure for aphantasia", it should be remembered that this manuscript does not demonstrate the tool's efficacy in identifying individual subjects with aphantasia. The absence/presence of an imagery pupillary light response does not confirm/rule out aphantasia.

Overall, the manuscript helps characterize an intriguing condition that until relatively recently received little empirical attention. These findings support the internal experiences described by aphantasic individuals, experiences that are often met with skepticism. Importantly, the authors have also offered the field a new objective physiological approximation of imagery vividness which can be incorporated into a number of study designs examining changes in imagery. The majority of previous measures relied on self-report alone and often suffered from the limitations of language (e.g., what it means for something to be "like vision" can be very different for different people). This manuscript also adds to the growing body of evidence of the power of internally generated signals, which can apparently reach all the way down the visual hierarchy to the eyes themselves.

Reviewer #1 (Public Review): 

In this paper the authors dissect the across-the-genome consequences of sexual recombination in Trypanosoma cruzi, a serious human pathogen, which some of the co-authors study for decades. They also did the seminal discovery of hybrid formation in this species almost 20 years ago and this is a follow-up enabled by whole genome sequencing and analyses. The data is novel, with importance outside of the field. 

Major strength is the dissection of set of hybrid strains, kept for several years and 800 generations, nothing trivial with a pathogen with a potential to infect the staff. While the conclusions are not revolutionary and have to some extent been made in yeast, it is surprising how different the outcome of sex is in T. brucei and T. cruzi. Also the data on ploisy is certainly novel for all trypanosomatid parasites. The same applies for the dramatic loss of up to 23 kb per generation, the increased presence of SNPs after the hybridization etc. 

I don't have suggestions for additional analyses, as those presented seem to me comprehensive and justifying the conclusions. I have some mostly minor comments that should help the authorst to improve the moanuscript.

Reviewer #2 (Public Review): 

By following T. cruzi cultures for 5 years (~ 800 generations) the authors were trying to observe the mechanisms by which the parasite re-shapes its genome under laboratory conditions (long-term passage in culture). By analyzing clones that arose from a genetic cross, the authors were also trying to characterize in detail the process of hybridization (genetic exchange), which results in an increase in DNA content (ploidy) and the subsequent events that reduce DNA content by chromosome/gene loss that lead to mosaic aneuploid cells. The authors achieved their aims and the results support their conclusions. 

Major strengths: 

The major strengths of the methods are the chosen parasite clones used for the experiment, following up on the descendant clones from the experimental cross described originally by Gaunt MW et al (2003). And the analysis of these clones over long-term passage in culture. By focusing on this particular set of T. cruzi clones, they maximized the chances of observing drastic changes on the ploidy and mutational landscape of these genomes. This is something difficult to achieve for T. cruzi under standard conditions. 

The major strengths of the results presented lie in the validation of the mechanism of genetic exchange proposed by Gaunt et al in 2003 (now observed and inspected in greater detail). It also confirms that T. cruzi is a constitutive aneuploid organism, displaying mosaic aneuploidies with a plastic genome. 

Weaknesses: 

The weaknesses of the study lie on the use of a single sequencing technology (short-reads) that certainly limited the ability of authors to observe other genome shaping events (structural variants, translocations, complex rearrangements, breakpoints). The lack of a phased diploid genome assembly for the hybrids (or some other means of taking advantage of long range information for constructing haplotypes) also prevented observing recombination between parental chromosomes. 

Impact: 

The paper is a very important contribution that builds up on previous important findings (Gaunt MW et al 2003), and provide a comprehensive look at events that ensue after genetic exchange by hybridization (cell fusion) in T. cruzi. The data would be extremely useful for the community of scientists doing research on this important pathogen. 

Additional context: 

Readers should be familiar with "parasexuality" or "cryptic sexuality" as described for other unicellular organisms such as Candida albicans (fungal pathogen). On top of a parasexual genetic exchange process achieved by hybridization (fusion of diploid cells to produce tetraploid ) kinetoplastids such as Leishmanias and Trypanosoma cruzi (as shown herein), are very plastic genomes showing varying degrees of "mosaic aneuploidies".

Reviewer #3 (Public Review): 

The authors cultivated Trypanosoma cruzi parents and their hybrids in vitro for 800 generations and investigated changes in DNA content and genome diversity over time. Hybrid clones were generated in vitro from a cross between two TcI strains; this cross was done within the context of a research study published in 2003 (Gaunt et al. 2003; https://doi.org/10.1038/nature01438). Here, the authors sequenced the parents and their hybrids, cultured them for 5 years and then re-sequenced all parasite clones. Using extensive genome analyses, the authors demonstrated that hybrids were tetraploid and that there is a reduction in DNA/genome content following hybridisation. This pattern resembles the parasexual mechanism, rather than canonical meiotic recombination, as has been observed in other microorganisms such as Candida albicans. 

Strengths:

The main strength of this paper is that the authors investigated the genetic consequences of hybridisation and clonal reproduction experimentally. Virtually all studies investigated these processes using "natural" isolates, where many confounding factors could complicate the correct interpretation of the data at hand (see for instance the review of Ramirez and Llewellyn, 2014; https://doi.org/10.1111/mec.12872). Here, the authors sequenced clones from the only genetic exchange event observed experimentally in T. cruzi (Gaunt et al. 2003). In addition, the authors went at length by culturing parental and hybrid clones for 5 years, which is a relatively laborious and time-consuming process, allowing them to follow the evolution of hybrid genomes under long-term in vitro culturing. This effort provided unique data demonstrating that tetraploid T cruzi hybrids undergo genome erosion. 

Weaknesses:

One of the main limitations of the study is that it investigates hybrids from one single cross. We now know that T cruzi parasites - like many other protozoans - display disparate reproductive strategies and rates of genetic exchange, even within single disease foci (e.g. Schwabl et al. 2019; https://doi.org/10.1038/s41467-019-11771-z). Here, the study investigates the impact of hybridisation from one single cross that was done decades ago, and for which it was already postulated that hybridisation followed a parasexual process (Gaunt et al. 2003). Hence, the aim of this paper is essentially restricted to investigating the genetic consequences of parasexual hybridisation followed by clonal evolution in vitro. This should be clearly explained when outlining the aims of this paper, highlighting that it investigates one of many possible reproductive strategies that T cruzi employs. 

Insufficient analyses are performed to support the key claims in the manuscript by the data presented. In particular: 

a) One of the main claims is that tetraploid Tcruzi hybrids undergo gradual genome erosion. I agree with the authors that there is genome erosion, but this is not gradual for all hybrid clones. The largest reduction in DNA content occured at the beginning of the culturing experiment, and three of six hybrid clones show a similar DNA content after 800 generations of culturing. This is also apparent from the microsatellite data where alleles were mainly lost in only one of the three hybrid strains. These results are completely ignored by the authors. Within this context, it is unfortunate that the authors sequenced the parental and hybrid clones at only two time points, and not at intermediary time points, which would allow pinpointing the genomic loss events during the first tens of generations of culturing. 

b) Another main claim of the study is that surface molecule genes represent regions of the genome with higher genetic diversity and more rapid evolution. However, these surface molecule genes are often highly repetitive, and such regions are generally masked before variant calling because variant calling within such regions often lead to false-positive SNPs. During culturing, it is evident that mitotic recombination events may reshuffle such repetitive regions, which will also lead to the identification of new (but false) variants by the end of the experiment. The bio-informatic analyses are not sufficient to convince me that the authors have adequately dealt with the repetitive nature of the T cruzi genome to allow such claims.

Reviewer #1 (Public Review):

Challa and Ryu et al aimed to develop a series of sensors that can detect poly(ADP-ribose) (PAR)-a nucleotide-like protein modification important in various diseases-in cell lysates, living cells and animals, with greater sensitivity with temporal and spatial precision. One major strength of the manuscript is that they have successfully developed two split-protein systems (fluorescence- and luciferase-based) to monitor PAR levels after systematic evaluation of various combinations of ADP-ribose-binders. They have demonstrated the specificity using appropriate controls (e.g., inhibitors that reduces or increase PAR levels), and tested in various physiological conditions (such as DNA damage and adipogenesis). In addition, they have demonstrated that the system works in cell lysates and living cells using both systems and living animals using the luciferase system with a sensitivity of 1000 cells. Therefore, compared with previous attempts to make PAR sensors, these new tools are more sensitive. These tools may thus be useful for investigating PAR dynamics in cellular or animal models, which is important for various physiological and pathological settings.

While these tools are more sensitive than existing tools, it is unclear whether a dynamic range of 6-fold (GFP) and 3-fold (luciferase) provide sufficient sensitivity for properly understanding the PAR dynamics (which was thought to increase as much as 100-fold in DNA damage settings). In addition, it is unclear whether the fold increases in both fluorescence and luminescence linearly correlate with the traditional measures by western blot. For example, Figure 1F indicates on the western blot that there was a precipitous drop of PARylation after 5 min, but the GFP signal indicated a linear drop. It will be important to quantify the signals on western blots and test how correlate their data with the GFP/luciferase data in scatter plots for their various sets of data. Would this system under-estimate the changes and be not sensitive enough to subtle changes that may be 1-2 fold measured by traditional means? Similarly, how is their quantitation in Figure 2 compared with traditional immunofluorescence? Lastly, for the luciferase signal in Figure 3B and C, the corresponding signal in western blots are missing. Therefore, it is difficult to estimate the background signal. If Niraparib, as in other figures, eliminates PAR signals on western blot, these data would indicate half of the basal signal are background, which is rather high.

Having said that, tool development is an evolution process. These tools will provide a good foundation for future development. Therefore, understanding these limitations (dynamic range, quantitative sensitivity correlation, and background) will provide a better assessment of the utility of these new tools for investigating PAR biology.

Reviewer #2 (Public Review):

In this study, the authors attempted to extend their own work and that of others in the field in developing probes to detect the signaling molecule, poly-ADP-ribose (PAR) that can be used in the test tube, in cells and in tumor models.

Major strengths include the development of a set of probes with data demonstrating utility and efficacy. Further, the authors show the assay to be useful in cell models and tumor models.

Some weaknesses include what appears to be a high level of background in the assay. Further, regarding methods, the exact probes (sequences) being evaluated are not defined.

This is one of several new PAR probes being developed over the last few years but may have widespread utility due to the quantitative nature of the bioluminescent assay.

Reviewer #3 (Public Review):

In this manuscript, Challa et al. developed a set of PAR Trackers (PAR-Ts) based on dimerization-dependent fluorescent protein and split-protein reassembly of luciferase for both in vitro and in vivo studies. The PAR-Ts contain a PAR-binding domain WWE fused to both parts of dimerization-dependent GFP (ddGFP) or split Nano Luciferase (NanoLuc) with LSSmOrange. The ddGFP version (PAR-T GFP) allows for real-time assessment of dynamic PAR production in vitro and in living cells, while the split NanoLuc version (PAR-T Luc) allows detection of PAR production in tissues in living mammals (though the authors implied PAR-T Luc can monitor the dynamics of PAR level in animals). The major drawback is that, while the authors demonstrated some applications of these PAR trackers (PAR-T) in both culture cells and in animals, the data of PAR-T GFP on cancer cells and the data of PAR-T Nano luciferase may not be sufficient to support the authors' claim that the new tool can detect spatial and temporal dynamics of PAR in cells and in animals. That said, the new tools can potentially expand the capability of cell biologists to visualize and study the PAR production process in both normal and disease states with improved sensitivity and tissue compatibility.

Detailed comments:<br /> 1. One of the major issues of this manuscript is the lack of time-course data for PAR-T luminescent sensors to demonstrate temporal monitoring of PAR levels in animals. If the binding of two split Nano Luciferase parts is irreversible, the application might be limited. However, according to the literature (Scientific Reports volume 11, Article number: 12535 (2021)), the split Nanoluc technology should be able to detect dynamic changes. Either way, a set of time-course data would be necessary. The authors need to provide evidence to support their statement "The high sensitivity and low signal to noise ratios of the PAR-Trackers described here enable spatial and temporal monitoring of PAR levels in cells and in animals."<br /> 2. Figure 2- figure supplement 2. For the detection of spatial dynamics of PAR signals in cancer spheroids, the authors did not provide sufficient evidence as only static images of different spheroids in different conditions were provided. And 2 out of 3 fields of view only include one spheroid. In addition, there is no time-course image data showing the spatial patterns of PAR in cancer cells are dynamic.<br /> 3. In the caption of Figure 2 -figure supplement 1 (B and C), it states "Immunofluorescence assay to track PAR formation in response to H2O2.", but there is no evidence showing any antibodies were used there.<br /> 4. It seems that Figure 3 B and C does not support the statement "we observed specific detection of firefly luciferase with D-Luciferin and NanoLuc with furimazine with no cross-reactivity" And it is unclear why the authors refer Fig. 3B and C after that statement as those data seems not supporting this claim. Similarly, the statement "Moreover, the luminescence of PAR-T Luc is only 30-fold lower than intact firefly luciferase." Was not supported by Fig. 3B. In fact, the differences between PAR-T Luc and intact firefly luciferase were ~1000 fold in vivo, judging from Fig 5B. It is also unclear which data of the construct was used to plot Fig. 3C.<br /> 5. Fig. 4C, it seems that Firefly luciferase was consistently brighter with PARGi, and I wonder if such difference is statistically significant. The authors did not perform a two-way ANOVA test for the firefly luciferase dataset.<br /> 6. The statement "Moreover, none of these sensors can detect PAR accumulation in vivo." seems to lack support. Have the authors proved that with evidence? I would recommend using the following statement instead: "Moreover, none of these sensors has yet demonstrated detection of PAR accumulation in vivo"<br /> 7. For the in vivo experiment, it is unclear about the benefits of normalizing the PAR-T radiance to the Firefly luciferase since the signals from Firefly luciferase did not overlap well with that from the PAR-T nano luciferase, which may cause bigger variations.<br /> 8. Judging from the data of Fig 3 supplement 1E, the signal intensity from the split firefly luciferase-based PAR-T sensors was ~10000 fold less than intact firefly luciferase, not ~1000 fold. It makes more sense to give up the split firefly luciferase for ~10000 fold differences since the signal intensity from the split nano luciferase was ~1000 fold less than intact firefly luciferase (Fig 5B).<br /> 9. "Therefore, developing tools to measure ADPR dynamics in cells and in vivo is critical for better understating the various biological processes mediated by ADPR". "understating" should be "understanding".

Reviewer #1 (Public Review): 

A number of metabolic traits show differences between reciprocal crosses of inbred mouse strains. These can be conceptualized as parent-of-origin effects. Differential expression (DE) at an unimprinted locus can be a pleiotropic side-effect of allele-specific expression (ASE) at an imprinted locus. There is no parent-of-origin effect at the unimprinted locus, in the sense that there would be no change in expression at this locus if the parental origin of the two alleles were reversed while keeping parental origin of alleles at the imprinted locus unchanged. Sexual recombination will have the effect of randomizing alleles at the unimprinted locus relative to alleles at the imprinted locus. 

Expression of the imprinted gene Nnat and unimprinted gene F2r were correlated in the author's analyses of reproductive fat pads from their mice and their interaction was predictive of basal glucose levels. In a single-celled analysis, using an existing database, expression of the paternally-expressed imprinted gene Nnat increases and expression of the unimprinted gene F2r decreases along an adipogenic trajectory in preadipocytes. 

One reason why small mammals, such as mice, socialize is to keep warm. Within a huddle or nest, heat generation consumes individual substrates for a communal benefit and this can create selection for imprinted expression when members of groups are asymmetric kin. This conflict has been discussed in the context of the effects of imprinted genes on brown adipocytes that use UCP1 to 'uncouple' oxidative phosphorylation in mitochondria (see Current Biology 18: R172). A UCP1-independent mechanism of non-shivering thermogenesis in skeletal muscle, and beige adipocytes (see Frontiers in Endocrinology 11: 498, involves 'uncoupling' of the SERCA channel that is regulated by Nnat. The role of Nnat is SERCA-dependent thermogenesis is yet to be established.

Reviewer #2 (Public Review): 

The authors conducted experiments to examine whether non-imprinted genes interacted with imprinted genes, explored gene pairs that may affect phenotype, and identified two genes, Nnat and Cdkn1c that may initiate parent-of-origin effects. A major strength is the testing of these predictions in a new cohort by manipulating phenotype by diet. 

I focus my review on the design. My major concern is the nature of the group assignment to diet, which would require different statistical analysis. 

"At three weeks of age, animals were weaned into same-sex cages and randomly placed on high fat (42% kcal from fat; Teklad TD88137) or low-fat (15% kcal from fat; Research Diets D12284) isocaloric diets" <br /> - To be sure I and readers can understand, were the animals first placed into same-sex cages, then the cage was randomly assigned to a diet? If so, the unit of analysis is the cage, and results need to be analyzed as though the animals are not independent within cages. This does not currently seem to be the case, and the analyses not valid. <br /> - Please describe how many animals were housed per cage and how many cages there were for each diet. <br /> - Please describe the method of randomization. 

To fully assess the methods and facilitate reproducibility, additional information is needed to describe items as recommended by the ARRIVE guidelines (https://arriveguidelines.org/sites/arrive/files/documents/ARRIVE%20guidelines%202.0%20-%20English.pdf). This includes: the number of animals represented in each experiment/figure (this is not clear throughout the text); the sex of animals used in each experiment; whether order of measurements or animal/cage positioning were randomized (or if not); whether any blinding was performed; housing conditions if available (e.g., room temperature and humidity, light/dark cycle), additional details about diet (whether ad lib, water quality), whether any animals were excluded from analysis after being assigned to a diet; cage type and bedding.

Reviewer #3 (Public Review): 

Macias-Velasco et al. aimed to demonstrate that non-imprinted genes could generate parent-of-origin effects on metabolic traits, such as glucose concentrations, through interactions with imprinted genes. They used four populations at different levels of intercrossing of inbred mice, and by doing so were able to demonstrate that non-imprinted genes interact with imprinted genes and by doing so impact the animal's phenotype. They focused on two genes in particular, Nnat, and F2r, in high fat-fed female mice as the covariation of these two genes associated with basal glucose concentrations and the relationship. They provided a biological validation of this relationship by demonstrating it consistently across multiple generations. Interactions between imprinted and non-imprinted genes have been previously demonstrated, but the present study took it one step further to identify one possibly reason as to why there is such a prevalence of parent-of-origin effects by detailing the interactions of ASE and DE genes and how that interaction leads to a specific phenotype. The genes the authors identified appear to play a role in adipogenesis. The results may allow for better prediction of an individual's phenotype based on their genome. 

The authors conducted a lot of work, and provided a lot of data for the reader, but the paper can be strengthened by the following: 

In the results the authors refer to females on a high-fat diet. It would be useful for the reader to put this in a bigger context and explain the implication of diet. It was unclear whether the figures represented sexes combined, and if so, it would have been useful to show the results in males, even if they were null. The authors demonstrated that Nnat expression covaries with F2r in high fat-fed females, yet used available scRNAseq data collected from C57BL/6J epididymal adipose tissue to examine which cell types express these two genes and whether the negative correlation persisted across an adipogenic trajectory (which it did). In mice, the visceral fat pads in the perigonadal region are known as epididymal in males and periovarian in females. Although it was not implicitly stated that these cells were from males, it is presumed by the name of the fat pad. The authors should address possible limitations and considerations related to sex differences, and possibly even strain differences in these comparisons. 

The clarity of the methods and materials needs to be improved. Specifically, to allow for others to reproduce the data and to provide greater transparency, in addition to following the eLife guidelines. The authors should follow the ARRIVE guidelines and cite this in the manuscript. With the multiple populations of mice used, it would make it easier on the reader if the sample size and sex were more clearly outlined. Although the authors state that the mice were randomly placed on high-fat or low-fat diet, how the animals were randomized was not outlined. Another possible consideration would be to include a figure outlining the study design, including sample size/sex for the various populations and components of the study. Also, please identify why the sample size was decided, and whether there were any inclusion/exclusion criteria.

Reviewer #1 (Public Review): 

JMML is a rare pediatric leukemia, emanating from mutations in the RAS pathway. One of the most frequent genetic causes are loss of function mutations in PTPN11. Using genetically-engineered zebrafish, the investigators show that a chronic inflammatory state is present. 

Comments: 

1. A mouse model for Noonan Syndrome with overlap with JMML, PTPN11 D61G , displays myeloproliferative, cardiac, and craniofacial disease. Here, the zebrafish ptpn11 D61G displayed a wide penetrance depending on allelic burden. 

2. The hematopoietic effects in the affected fish involve the myeloid compartment. There appears to be no zebrafish ortholog for GM-CSF, and instead the author look at effects of Gcsf. They note enhanced GM colony formation -- but Gcsf should not promote macrophage development. In addition, the effect in human is that of spontaneous growth of CFU-GM. The authors would need to address the differences with human JMML malignant hematopoiesis. 

3. The use of MEK or PI3K inhibitors do not themselves implicate proinflammatory response (line 273). These agents are not anti-inflammatory but have a wide range of effects. They are as much anti-proliferative. To demonstrate inhibition of proinflammatory response would require true anti-inflammatory agents. Dexamethasone targets lymphocytes, and may also reduced cytokine release by macrophages in fish. Controls should include genes that are biomarkers for inflammation (i.e., not l-plastin or c-myb).

Reviewer #2 (Public Review): 

In Solman's et al study they explore the impact of PTPN11 mutations (gene that encodes for the protein-tyrosine phosphatase SHP2) associated with Noonan syndrome (NS), juvenile myelomonocytic leukemia (JMML) and JMML-like myeloproliferative neoplasm. They use a zebrafish model and JMML patient cells. They create a zebrafish model using CRISPR/cas9 introducing D61G mutation, a common mutation present in these patients. These mutants showed a phenotype similar to NS in homozygosis and heterozygosis with different penetrance. Mutants are smaller, presented craniofacial defects, heart edema and absence of the swim bladder. They also presented hematopoietic abnormalities including myeloid hyperproliferation. Single cell mRNA sequencing of HSPCS from zebrafish mutants and JMML patients showed an excessive proinflammatory response. Interestingly they found the same response in both species. With these results, they conclude the study using anti-inflammatory agents to prove that the inflammatory response can be ameliorated in JMML-like MPN patients. Using the zebrafish shp2 mutants they showed improvement of c-myb and l-plastin expression in Shp2 mutants. Finally, they suggest that pharmacological inhibition of the inflammatory response can be a therapeutic option for human patients. The conclusions of this study are well supported for the data provided.

Reviewer #3 (Public Review): 

The authors of this paper model the D61G mutation in zebrafish, creating a model consistent with the human Noonan syndrome, which is predisposed to a JMML and MPN like syndrome. They use RNA-seq to identify the potential cellular abnormalities in either the HSPC or monocyte/macrophage clusters, which nominates an inflammatory signature as being pathogenic. They complement this with analysis of human JMML patients, showing a similar inflammatory signature. 

The study nicely provides a new model that can be used as the basis of future studies in the field. Because the mutant variably displays phenotypes along a spectrum from NS to MPN, different researchers can choose to focus on this as they see fit. Where the manuscript falls short is in more clearly delineating the defect in HSPC vs. monocyte/macrophages (especially in comparing fish to human) and at least a hint of the involved mechanisms.

Reviewer #1 (Public Review): 

In this study, Barrasso et. al., investigate the previously reported positive association between the commensal P. aminovorans and V. cholerae in the human gut during infection. The authors find that P. aminovorans and V. cholerae interact in vitro to form a dual-biofilm. Using a suckling mouse model of infection, the authors also demonstrate that V. cholerae gut colonization is enhanced in the presence of P. aminovorans, and that this colonization enhancement depends on the ability of V. cholerae to produce biofilm exopolysaccharide and biofilm proteins. Overall, the experiments are well-performed and the findings are interesting. My major comment is that the authors should perform some further analysis to demonstrate a definitive causal relationship between the abundance of P. aminovorans and V. cholerae colonization, which would help to strengthen their conclusions. 

1) The authors find a positive correlation between the abundance of P. aminovorans and V. cholerae infection by the observation that 6 of 22 infected individuals harbored detectable levels of P. aminovorans in rectal swabs, compared to only 2 of the 36 uninfected individuals (Figure 1). The authors then go on to demonstrate that there is an increase in the colonization of V. cholerae (CFU) in the presence of P. aminovorans in the suckling mouse model on infection (Figure 2B and Figure 2C). The author's conclusions would be strengthened by demonstrating a positive association between the presence of P. aminovorans and the abundance of V. cholerae in the human samples (from Figure 1). The authors demonstrate that the presence of P. aminovorans is associated with the number of people infected with V. cholerae, but not that the presence of P. aminovorans also leads to higher levels of V. cholerae in the 6 of infected individuals harboring detectable levels of P. aminovorans, compared to the infected individuals that did not. This additional analysis would help to solidify the authors conclusions that the presence of P. aminovorans enhances the colonization of V. cholerae during infection. 

2) It's surprising that the relative abundance Proteobacteria does not change much after the introduction of >10^6 CFU of P. aminovorans, which would be expected to represent a significant proportion of the abundance of the total bacteria in the small intestine (Supplemental Figure 1). It would be important for the authors to determine whether the addition of P. aminovorans and not the displacement of other members of the Proteobacteria Phylum leads to the increased V. cholerae CFU in Figure 2B and Figure 2C. 

3) Expression analysis should be performed to determine whether there is an increase in virulence factor expression in V. cholerae in the presence of P. aminovorans. This important given that previous studies have demonstrated that biofilm growth leads to the upregulation of V. cholerae virulence factors, which may enhance colonization.

Reviewer #2 (Public Review): 

In the manuscript "Impact of a human gut microbe on Vibrio cholerae host colonization through biofilm enhancement" the authors studied the interaction between the human associated microbiota member Paracoccus aminovorans and the human pathogen Vibrio cholerae. A previous study, where authors from the same lab analyzed microbiota composition of individuals infect and non-infected with V. cholerae led to the hypothesis that P. aminovorans could increase colonization of Vibrio cholerae. In the present manuscript the authors used a murine model to test this hypothesis and in vitro laboratory cultures to identify possible mechanisms involved in the interaction between P. aminovorans and V. cholerae. 

They could show that in a murine model P. aminovorans indeed increases the colonization levels of V. cholerae. 

With laboratory cultures they also showed that P. aminovorans increases the ability of V. cholerae to form biofilms. Importantly, the P. aminovorans dependent increase in V. cholerae biomass was specific to V. cholerae cells in biofilm mode, and not a general increase in growth Because an increase in growth was observed for cells in the biofilms but not in planktonic conditions. Moreover, components required for biofilm formations, such as Vibrio exopolysaccharides, were required for the observed induction of P. aminovorans increase in V. cholerae biofilm formation and in gut colonization. The authors propose that P. aminovorans induces biofilm formation in V. cholerae and that promotes V. cholerae gut colonization. 

Overall, the study described here is well written and the conclusions are generally well supported by the data. 

Importantly, this study shows that indeed there is a direct interaction between P. aminovorans and V. cholearae and thus supporting the hypothesis that the observed increase in V. cholerae colonization in the presence of P. aminovorans is the result of this direct interaction. The results from in vitro studies shown here demonstrating the formation of dual species biofilms with these two organisms, in addition to the observation that the P. aminovorans mediated increase in gut colonization of V. cholerae is no longer observed when mutants incapable of forming biofilms are used, provide strong support to the proposal that the formation of dual species biofilms are a likely mechanism explaining the ability of P. aminovorans to enhance V. cholerae virulence. In future work it will be interesting to see the formation P. aminovorans and V. cholerae dual species biofilms directly in the gut, to obtain direct support for the role of the biofilms in the gut. 

More broadly, this work highlights the importance of looking at the interactions between members of the microbiota and pathogens to understand different host susceptibility to infection outcomes. Other studies have looked at how members of the microbiota can decrease pathogen intestinal colonization. Here, an increase in pathogen colonization is demonstrated by an interaction with a specific microbiota member. Identification of these interactions can be important to identify infection susceptibilities, but also to develop strategies that prevent these interactions as new ways to decrease infections.

Reviewer #3 (Public Review): 

The presence of the organism Paracoccus aminovorans in stool was previously shown to correlate with susceptibility of humans to infection with V. cholerae and to enhance agglutination and growth of V. cholerae. In this manuscript, the authors use a neonatal mouse model as well as in vitro models to demonstrate that the association between Paracoccus aminovorans and V. cholerae occurs in a VPS-dependent biofilm and enhances colonization of the neonatal mouse intestine. 

The strengths of this manuscript: 

1) Examination of P. aminovorans-V. cholerae interaction in the small intestine of the neonatal mouse model. V. cholerae colonizes the terminal ileum yet most of the human microbiota studies examine stool, which is unlikely to be representative of the terminal ileum. In addition, adult models of infection such as the gnotobiotic or antibiotic-treated mouse display colonic but not true ileal colonization. Furthermore, this colonization is not dependent on the V. cholerae toxin co-regulated pilus, which is necessary for human infection. In fact, flow in the colon is slow enough to allow growth without true attachment to the surface. This may explain why, as the authors note, the diarrhea of cholera clears most of the microbiota from wtool samples. Therefore, stool exiting the colon and the adult mouse are not ideal for studying the interaction between the microbiota and V. cholerae during infection. By using the neonatal mouse, the authors choose a host compartment that is relevant to human disease. The findings of the authors that P. aminovorans improves V. cholerae colonization of the small intestine are very convincing. 

2) Use of microscopy to detail the distribution of the two organisms in culture. Imaging clearly demonstrates subdomains of the biofilm that contain mixtures of P. aminovorans and V. cholerae. 

The weaknesses of this manuscript: 

1) Specific markers for VPS exopolysaccharide and P. aminovorans are not used: The authors conclude that V. cholerae increases VPS synthesis in response to P. aminovorans based on increased WGA staining in regions of biofilms where P. aminovorans is concentrated. One concern is that WGA is not a specific marker for VPS. It adheres to GlcNAC residues, which could also be present in an extracellular polysaccharide synthesized by P. aminovorans. 

Furthermore, the authors image biofilms that include neon-green-expressing V. cholerae and unlabeled P. aminovorans by staining with FM4-64. Regions of the biofilm with predominantly FM4-64 staining are presumed to have greater numbers of P. aminovorans. This is more convincing because the shape of these cells is coccoid as might be expected for P. aminovorans. However, this is not a feature that provides specificity. Because the authors also indicate that these clusters of Pa are surrounded by V. cholerae¬-synthesized VPS, it is important to definitively identify these cells as Pa. 

2) There is no examination of activation of VPS synthesis or other virulence factors at the transcriptional level. The authors conclude that VPS synthesis is activated by WGA staining but do not provide additional data to show whether this activation occurs at the transcriptional or post-transcriptional level. If transcription activation of vps genes were observed, this would bolster the WGA staining result.

Reviewer #3 (Public Review):

While multiple laboratory studies - including some by the authors of this manuscript - have found that giving mice testosterone pulses induces a conditioned place preference, the role of such pulses in nature have not been studied before. In an ambitious field experiment, the authors administer testosterone to wild California mice to study its function in a more ecologically relevant setting. They then track the behavior of the injected male mice and of their pair bonded female partners to study physical movement and ultrasonic vocalizations. While these efforts are commendable, there are limitations to the results and the interpretations.

1. While the authors find that mice injected with testosterone spend more time at the nest, it is not clear that the effect is specific to the nest or if testosterone would induce a conditioned place preference to other parts spatial locations as well. Moreover, it is not clear from these analyses if animals are spending more time at the nest simply because testosterone made them sick, for example.

2. What is the evidence that the experimental manipulations are mimicking natural testosterone pulses at the nest?

3. While it is clear that testing large numbers of animals in an experiment such as this is not trivial, the sample sizes are too small to support many of the results, especially when the authors attempt to estimate the effect of so many covariates. For example, there are only 4 male mice injected with testosterone that have pups. Fitting so many variables when overall sample size is small is problematic and can lead to false positive results.

Reviewer #1 (Public Review):

This study investigated the biological relevance of transient fluctuations of circulating testosterone (T) experienced by males during social encounters. The authors propose that T pulses have rewarding properties that influence social interactions and place preference. As California mice are monogamous and bi-parental, one prediction was that T pulses influence the attendance of males to the nest. To test this possibility, the movements and vocalizations of pairs of wild California mice identified as mates were followed in the field by telemetry as well as thermal and auditory recordings for 3 nights following the administration to males of three daily short live testosterone injections. The results show that males indeed spent more time in the nest, and even more so if pups were present, suggesting that one function of T pulses is to increase paternal care. T pulses administered to males also reduced time spent by their mate in the nest, regardless of the presence of pups, suggesting that male attendance to the nest allows another use of the female's time. T pulses also resulted in increased production of ultrasonic vocalizations (USVs) by the pair, in a smaller bandwith in treated males and in a change in the types of USV predominantly produced. Together these data thus provide important new information on the significance of acute and short lived changes in testosterone availability to reproductive behavior and fitness in this species. The impact of this work is expected to extend beyond this specific species.

Overall, the methods are transparent, sufficiently detailed and clear. The conclusions are for the most part supported by the data.

Strengths :

Sex steroids are chemical messengers producing slow and lasting responses that prime the circuits underlying behaviors. These actions are mediated by transcriptional changes and their effects are typically studied in response to long-term (seasonal) changes in hormonal circulating concentrations. Yet, the concentration of sex steroid hormones, including testosterone, can rapidly vary in response to social encounters or stressful events and induce rapid responses that are mediated by membrane-initiated actions. Much less is known about these rapid effects of testosterone and even less about their impact on behavior and reproductive success. The demonstration that repeated T pulses induce changes in time allocation and communication, which translate a change in behavioral activities, in a complex and natural environment is thus an important achievement. Moreover, because these effects are thought to reflect a form of conditional place preference, they also provide an illustration of how short lived hormonal secretion can exert long term effects on behavior and reproductive fitness independently of a direct action on gene transcription.

Weaknesses :

The authors present this experiment as a modification of classical conditioned place preference (CPP). If this notion is important to understand the frawework of this study, whether the present experimental design constitutes real CPP is debatable, as the authors cannot provide evidence that conditioning truly occured. What occured prior or immediately after the injection is not known. And, the stimuli an individual was exposed to prior to or immediately after an injection may have been different between the three injections and between the different subjects of this experiment. This is of course not detracting from the main findings and conclusions of this study whose results clearly highlight an effect of treatment on place preference but it seems inaccurate to consider the experimental design as a conditioned place preference, even if the underlying mechanism may involve reinforcing properties of testosterone.

The description of the different types of USVs and what was analyzed here is actually not totally clear such that it is not always easy to interpret the results. The method section about audio recordings describes a variety of ultrasonic vocalizations broken down into sonic vocalizations (SVs), which are further categorized based on the number of calls they are composed of (1SV, 2SV, etc), bark calls as well as simple and complex sweeps. Although SV, barks and complex sweeps are defined, the difference between simple and complexe sweeps is not clear. Moreover, the results only report effects on SVs and barks, but the discussion concludes on sweeps (line 263) which is confusing.

The results presented in table S3 are confusing. Tables S1 and S2 clearly report information relative to the amount of time males and females, respectively, spent in the nest (which is tehn broken down following different covariates). What Table S3 represents is less clear. The legend indicates that it represents pair time at the nest (but this is broken into male and female data) while the main text mentions within pair comparisons which would suggest that a difference between the time spent by each pair member was computed. How these data were obtained is not described. This is important because this information is key to establish a relationship between the time spent by the two pair members.

Reviewer #2 (Public Review):

In this manuscript by Petric et al, male California mice in a natural habitat with and without pups received 3 SQ injections of testosterone over 5 nights and the researchers used remote sensing equipment to record behaviors over 3 nights. They found that males administered testosterone spent more time at the nest than males given a control injection. Between males that were given testosterone, those with pups spent more time at the nest than those without pups. However, in control mice, males also spent more time at the nest if they had pups.

Interestingly, females pair-bonded with males who received testosterone injections spent less time at the nest. The authors then showed that in pairs where the male received Testosterone injections, there was also an increased amount of total USVs at the nest. In addition, pairs who spent more time together produced less USVs. Interestingly, males who received testosterone injections produced calls that had a smaller bandwidth.

Altogether, this paper provides behavioral evidence that testosterone has an effect on conditioned place preference in a natural, complex setting that is consistent with what has been seen in the laboratory setting. However, the paper is largely descriptive in nature and does not offer any novel mechanistic insights as to how testosterone influences place preference. The data show that having pups has a significant influence on male time at the nest regardless of testosterone. It is unclear from the data if having pups also significantly increases USVs in a manner that is distinct from testosterone pulses. Thus, the specific role of testosterone in driving these behaviors is unclear. For instance, would other rewards or pharmacological agents known to produce CPP, administered at the site of the nest, produce a different behavioral profile than what was observed with testosterone? Thus, while the authors provide evidence in a natural setting that confirms findings seen in the laboratory setting, the mechanism of testosterone in driving the observed behaviors remains unclear.

Reviewer #3 (Public Review):

In this interesting paper, Chen & St. Johnston deliver a detailed description of how newborn enterocytes (ECs) integrate into the gut epithelium of Drosophila. They show that this involves a novel mechanism whereby a new apical plasma membrane domain is formed inside the cell, before it is exposed to the gut lumen, and they provide extensive data on the localizations and movements of many cell adhesion and cytoskeletal proteins involved in the process. Their description of this unusual process is complete, clear, and convincing, even though their analysis used exclusively fixed samples and lacked a real-time analysis (which would be technically very challenging, if not impossible at this time). The description of EC integration is significant not only for the unique cell biology at play, but because it explains how new cells are integrated into the gut epithelium without breaching the gut's barrier function. Aspects of this process may well prove relevant to cell integration in other endodermal barrier epithelia that are renewed by stem cells. Overall the paper is a very high quality work that should be valuable in the field of Drosophila gut homeostasis, and more broadly as a fine example of epithelial cell biology. Moreover, the manuscript is very well written, easy to follow, and the illustrations and data are all very good.

Reviewer #2 (Public Review):

The authors recently showed the polarization of the cells of the adult Drosophila midgut does not require any of the canonical epithelial polarity factors, and instead depend on basal cues from adhesion to the ECM, as well as septate junction proteins (Chen et al, 2018). Here they extend this research to examine in greater detail precisely how midgut epithelial cells integrate in the pre-exisiting epithelium and become polarized. Surprisingly, they show that enteroblasts form an apical membrane initiation site prior to polarizing. Furthermore, they show that this develops into a pre-apical compartment containing fully-formed brush border. This is a very interesting finding - it explains how integrating enteroblasts can integrate into a pre-existing epithelium without disrupting barrier function. The conclusions of this paper are mostly well supported by data, but some aspects could do with being clarified and extended as outlined below.

Model presented in Figure 6:

While the separation of membranes indicated in Figure 6 steps 3-5 can be seen in the image shown in Figure 3B, this is one of the only images which supports the idea that there is a separation of membranes between the enteroblast and overlying enterocytes during PAC formation. Is the model in Figure 6 supported by EM data - can you see a region where there is brush border and separation of cells? Supplementing Figure 3 with corresponding EM images would greatly aid the reader in interpreting the data and strengthen the model.

Coracle is used as a readout for the localization of septate junction components, yet the staining for Cora in Figure S3B looks quite different to Mesh in S3D. If Cora is to be used as a readout for the localization of septate junction components, then staining for Cora/Mesh and/or Cora/SSk or Tsp2a should be shown.

A key step in the model is that the clearance of E-Cadherin from the apical membrane leads to a loss of adhesion between the enteroblast and the overlying enterocytes. This would need to be supported by functional data such as overexpression of E-Cad or E-CadDN in enteroblasts or by generating shg mutant clones. If the model is correct, perturbing E-Cad levels in enteroblasts should lead to defects in PAC formation, such as loss of de-adhesion/early de-adhesion/excessive de-adhesion.

Role for the septate junction proteins:

Septate junction proteins were previously shown by these authors to be required for enteroblast polarization and integration into the midgut epithelium (Chen et al, 2018). Here they extend this by examining enteroblasts mutant for septate junction proteins, and conclude that septate junction proteins are required for normal PAC formation. However, it is not clear what aspect of the polarization of the enteroblasts is disrupted, because a number of mesh mutant cells (albeit a lower proportion than in wildtype) do form PACs. The main phenotype seems to be that cells fail to polarize (as previously reported) or have internalised PACs. It is hard to know what to conclude from this data about the role of the septate junction components in PAC formation.

When discussing the requirement for septate junctions for enteroblast integration - Coracle and Mesh are used interchangeably - but as mentioned before, it is not clear if they colocalize, or if their localization is interdependent (as demonstrated for Mesh, Tsp2a and Ssk in Figure 7). What is the phenotype of enteroblasts mutant for cora?

Following from the previous point - while it is clear that Coracle is apical early during AMIS formation, it is not clear if Mesh, Tsp2a and Ssk also are, yet these are the mutants that are examined for a role in AMIS/PAC formation. It would be good to know whether the loss of cora would lead to defects in AMIS formation.

It is unclear what is happening in Figure 8A,C,E, S7D. Is that a detachment phenotype or an integration phenotype? Are the majority of cells unpolarised due to loss of integrin attachment rather than failure to form an AMIS/PAC?

It is unclear whether enteroblasts really pass through an 'unpolarized stage'. In Figure 6, when they are described as 'unpolarised', they clearly have distinct basal and AJ domains. In septate junction mutants, when cells are classified as unpolarized, do they still have distinct regions of integrin/E-Cad expression?

Reviewer #1 (Public Review):

1. This manuscript presents data to show how an initially unpolarised cell, the intestinal stem cell/enteroblast in the adult Drosophila midgut, acquires an apical pole de-novo during its integration into the existing epithelium. Results show the formation of an actin-rich "Preformed Apical Compartment" (PAC) on the enteroblast, which ultimately leads to the formation of an apical membrane during differentiation of the enteroblast to an enterocyte. During the integration into the epithelium, existing septate junctions between two neighbouring enterocytes are replaced by newly formed septate junctions between the differentiating enteroblast and the enterocyte, thus maintaining a functional barrier throughout this process. Data presented provide further evidence that septate junctions are instrumental to initiate the apical membrane in enteroblasts and ensure their proper integration.

2. This paper is a follow-up of the authors previous paper (2018), in which they carefully described the organisation of the junctions between cells of the adult Drosophila midgut epithelium and their control from the basal side by integrin signalling. Here, the authors used state-of-the art imaging and genetics to unravel step-by-step the events leading from an initially unpolarised cell to an epithelial cell that integrates into the existing epithelium. Many of the images are accompanied by cartoons, which help the reader to better understand the images and follow the conclusions. It would have been helpful yet, in particular with respect to the mutant phenotypes described later, if they would have named each of the steps/stages. In addition, mentioning the timescale would give an idea about the temporal frame in which this process elapses.

The authors convincingly show that septate junctions are instrumental for proper polarisation and integration of the enteroblast. However, while they nicely showed that Canoe in neither required in the enteroblast nor in the enterocytes for this process, it remains unclear whether septate junction proteins are required in enteroblast or in enterocytes or in both and at which particular step the process fails in the mutant.

3. Most of the data allow the reader to follow the conclusions made. The data presented extend our current knowledge by showing a novel mechanism by which a cell can acquire an apical pole de-novo. The adult fly midgut is an ideal system to analyse this process is an organ (rather than in cells in culture).

4. Given the high degree of similarity between the adult Drosophila midgut and the mammalian small intestine, the data presented here will certainly stimulate novel concepts and approaches to unravel mechanisms involved in the maintenance of epithelial homeostasis, not only in flies, but also in mammals. Loss of homeostasis can lead to various diseases, including cancer.

Reviewer #3 (Public Review):

Strengths:

The method is based on sound theoretical footing and clearly explicated.

The method is rigorously tested in model and experiment and is shown to clearly modify the membrane time constant of the soma of a model cell or living rat dentate gyrus granule cells.

CapClamp has predictable effects on spike amplitude and the f/I relationship.

CapClamp is relatively easy and inexpensive to implement (trivially so for current fast Dynamic Clamp rigs.)

Weaknesses:

The method requires accurate measurement of the capacitance of the compartment to be clamped (usually this should be the soma). This can be difficult in neurons with complex dendritic architecture.<br /> The method requires fast clamping feedback; fast compared to the fastest electrical event in a neuron (usually action potentials), and for vertebrate neurons it should be 20KHz or faster and yet faster for fast spiking neurons.

CapClamp might have limited applicability in many invertebrate neurons where the soma does not place a capacitive load on the integrating segment.

Reviewer #1 (Public Review):

This study examined the features and the corresponding temporal dynamics underlying the ability to understand actions from naturalistic visual stimuli. To this aim, the authors applied a combination of a priori feature labels and behavioural and neural measures of representational spaces to a large-scale dataset. Features were selected on the basis of previous studies and were divided into visual, action-related and socio-affective features. The authors determined the features that best explained behavioural data (measured via a multi-arrangement task of the same actions) and the corresponding neural dynamics (measured with EEG). The authors observed that socio-affective features predicted behavioural data better than visual and action-related features, with a temporal progression from visual to action-related to socio-affective features.

Strengths:

The manuscript is well written and addresses an important gap in the literature, namely, the features that contribute to the understanding of visual actions and the underlying neural dynamics. In contrast to most previous studies that used a relatively small range of actions, the current study used a large-scale dataset of visual actions and used a range of a priory feature labels as well as behavioural multi-arrangement data and measures of the neural representational space of these actions using EEG. The authors should be commended for replicating their behavioural data in two separate data sets, and for trying to minimize the correlations between features.

Weaknesses:

The authors wished to distinguish between visual, action-related and socio-affective features, but the assignment of features to these different domains was not always straightforward (as an example, should the number of agents be considered a visual or a socio-affective feature?). Moreover, whereas the authors tried to minimize the correlations between features, some of the correlations were still significant, which may have biased the estimates of the beta weights, which in turn may have impacted the variance partitioning analysis.

Reviewer #2 (Public Review):

The authors use representational similarity analysis on a combination of behavioral similarity ratings and EEG responses to investigate the representation of actions. They specifically explore the role of visual, action-related, and social-affective features in explaining the similarity ratings and brain responses. They find that social-affective features best explain the similarity ratings, and that visual, action-related, and social-affective features each explain some of the variance in the EEG responses in a temporal progression (from visual to action-related to social-affective).

The stimulus set is nicely constructed, broadly sampled from a large set of naturalistic stimuli to minimize correlations between features of interest. I'd like to acknowledge and appreciate the work that went into this in particular.

The analyses of the behavioral similarity judgments are well executed and interesting. The subject exclusion criteria and catch trials for online workers are smart choices, and the authors have tested a good range of models drawn from different categories. I find the case that the authors make for social features as determinants of behavioral similarity ratings to be compelling.

I have a few questions and requests for additional detail about the EEG analyses. I appreciate that the authors have provided the code they used for all the analyses, and I'm sure that the answers to many if not all of my questions are there, but I don't have access to a Matlab license to run the code. Also, since the code requires familiarity with not just Matlab but with specific libraries to understand, I think that more description of the analysis in the paper would be appropriate.

Some more detail is needed in the description of the multivariate classifier analysis. The authors write (line 597-599): "The two pseudotrials were used to train and test the classifier separately at each timepoint, and multivariate noise normalization was performed using the covariance matrix of the training data (Guggenmos et al., 2018). "

I suspect I'm missing something here, because as written this sounds as if there was only one trial on which to train the classifier, which does not seem compatible with SVM classification. If only one trial was used to train the classifier, that sounds more like nearest-neighbor classification (or something else). Alternatively, if all different pseudo-trial averages - each incorporating a different subset of trials - were used for training, then that would seem to mean that some of the training pseudo-trials contained information from trials that were also averaged into the pseudo-trials used for testing. I don't know if this was done (probably not) but if it was it would constitute contamination of the test set. I think this part of the methods needs more detail so we can evaluate it. How many trials were used to train and to test for each iteration?

I think a bit more detail is also necessary to clarify the features used for the classification. My understanding is that each timepoint was classified as one action vs each other action on the basis of all the electrodes in the EEG for a given temporal window. Is this correct? (I'm guessing / inferring more than a little here.)

It would be useful to know how many features constituted each feature space. For example, was motion energy reduced to one summary feature (total optic flow for whole sequence?) For "pixel value", is that luminance? (I suspect so, since hue is quantified separately, but I don't think this was specified).

More broadly, I would appreciate a bit more discussion of the role of time in these analyses. Each clip unfolds over half a second, so what should we make of the temporal progression of RDM correlations? Are the social and affective features correlated with later responses because they take more time to compute (neurally speaking), or because they depend on longer temporal integration of information? These two are not even exactly mutually exclusive, and I realize that it may be difficult to say with certainty based on this data, but I think some discussion of this issue would be appropriate.

Reviewer #1 (Public Review):

We possess a detailed understanding of how the myotome, precursors of the epaxial and hypaxial muscles, differentiates from the somites, the molecular mechanisms underlying subsequent morphogenetic movements are not well understood. It was previously shown that in the Medaka double anal fin mutant the dorsal trunk region is transformed into a ventral one and that this phenotype is caused by reduced zic1/zic2 expression in the dorsal somites. The loss of zic1 also increases proliferation in the dorsal dermamyotome. However, the downstream effectors of zic1/zic4 were not known. Here the authors show take advantage of a zic1 reporter line which they use to perform in vivo imaging of dorsal myotome cells. They show that in contrast to prior belief, the somites of both sides of the embryo fuse dorsally of the neural tube by active cell migration. After crossing the reporter line with zic1/zic4 mutants they observed a reduction in protrusive activity and a decrease in proliferation, that explain the failure of myotome fusion at the dorsal midline. Photoconversion experiments show that specifically the dorsal DM cells and the mesenchymal cells derived from them seem to actively participate in the entire process of dorsal somite extension. To determine the molecular machinery controlling dorsal somite extension the authors performed RNASeq, ATACSeq and ChIP Seq using a transgenic zic1:myc line that they generated that allowed them to identify 3200 direct downstream targets. In this manuscript the authors specifically study the downstream target wnt11r. The findings that zic1 binds to wnt11r is interesting, as wnt11 has been previously shown to be involved in cell migration in other systems. However, the reliance on photomorpholinos to downregulate wnt11r dampens my enthusiasm a bit, as the judgement of its efficacy relies on circumstantial evidence that the phenotype resembles the zic1 phenotype and that exogenously supplied human wnt11 protein partially rescues the phenotype. The strength of the manuscript are the in vivo time lapse analyses and the discovery that dorsal epaxial myotome cells actively migrate, as well as the identification of downstream targets. However, how wnt11r via non-canonical Wnt signaling leads to an increase in polarized protrusion and migration needs to be further investigated in the future.

Reviewer #2 (Public Review):

The Medaka double anal fin mutant provides a unique tool for studying epaxial myogenesis and the processes that expand body wall musculature to enclose the neural tube. In these mutants, the myotome fails to expand over the neural tube in the stages examined. The time lapse imaging provided by the authors reveal the intriguing migratory dynamics of dorsal somitic cells, which bridge the inter-somitic space between opposing myotomes. These data provide evidence of differences in the behavior of Zic1:GFP+ cells between the Da and Wt fish. The authors show that Da fish have a reduced ability to form large protrusions. However, the fate of dorsal somitic migratory cells and their putative role in epaxial myogenesis is not clear.

In addition to documenting cell dynamics, the authors also performed dissections and FACS sorting with Tg(Zic1:GFP) transgenic fish to compare RNA-seq and ATAC-seq data sets between GFP+ (dorsal) and GFP- (ventral) regions of the somites. ChIP-seq experiments were also performed using a Myc-tagged Zic1 in the Da background to identify potential Zic1 target genes. Comparisons of Chip-seq data sets with genes highly expressed in the dorsal somite suggested the involvement of Wnt signaling in epaxial myogenesis. The authors specifically focused on Wnt11r, which they hypothesized to be a direct target of Zic1 and a key regulator of epaxial muscle expansion. In support of this hypothesis, the authors show Wnt11r expression is reduced in Da mutants. While their Chip-seq and ATACseq data sets suggest the position of a putative Wnt11r enhancers, enhancer function was not directly tested. Interestingly, morpholino knockdown of Wnt11r, or pharmacological inhibition of the Wnt/Ca2+ pathway, resulted in partial phenocopy of the Da phenotype, including reduced protrusions from dorsal somitic cells. Exogenous application of human recombinant Wnt11 in Da mutants rescued cell protrusion formation, further supporting a role for Wnt11 in epaxial myogenesis.

Overall, this paper is well written and addresses an interesting and underexplored question in developmental biology. The identification of a migratory population of dorsal somitic cells is an intriguing observation. The fate and function of these cells in epaxial myogenesis, however, is not clear from the current data set and warrants further investigation.

Reviewer #3 (Public Review):

This study is of interest to researchers who study cell migration and or muscle development. It builds upon prior analysis of Double Anal fin (Da) mutants by using detailed bioinformatic and time-lapse analysis to explain dorsal somite extension, and find evidence that dorsal muscle morphogenesis is actively guided, rather than being passively shaped by physical constraints alone. Looking downstream of Da, they show that Wnt signaling is central to to dorsal extension of the epaxial myotome in medaka and propose that similar functions may shape the dorsal musculature across vertebrates.

Strengths:

Previously, the authors found that the medaka Da mutant causes strong loss of zic1 and zic4 expression, loss of epaxial myotome growth, and a 'ventralized' fin phenotype. However, the cellular and molecular mechanisms underpinning these defects remained unclear. It also remained unclear whether cells of the epaxial myotome are actively guided to their destinations or simply forced dorsally by passive constraints.

In this study, using high resolution time-lapse data provides important insights into epaxial myogenesis, particularly by providing evidence of active migration rather than simply constrained growth. The authors demonstrate that the Da mutant has a specific lack of large cell protrusions, which may explain the dorsal growth defect.

The authors establish a dataset of genes with expression enriched in Zic1+ cells, and promoters bound by Zic1 in these cells, which will be a rich resource for further investigation of epaxial myogenesis.

Using this dataset, the authors identify Wnt11r ad a candidate Da-dependent signaling factor that may explain dorsal defects in the mutant. Consistent with this model, they show that wnt11r-MO causes loss of long-protrusions, similar to the Da mutant itself. They chase the signal further downstream by blocking CamKII function and find that this elicits an effect similar to the Da mutant, namely, specific loss of long-protrusions. Critically, they are able to restore formation of long-protrusions by injecting human Wnt11 protein into a dorsal somite, bolstering their argument that activation of Wnt signaling is a central target of Zic1/4. Although one could argue against any one of these findings in isolation, they work together to make a compelling case for wnt11 in actively guiding dorsal myotome extension.

The paper's discussion concludes with a strong argument that these findings are not limited to fish, but are likely in play across vertebrates.

Concerns:

It would be important to clarify in results and methods how somites were isolated prior to FACs sorting. One line in the manuscript implies that somites were dissected cleanly while another suggests that whole tails were included. If it's just the somite, please say a little more in the methods about how this tissue was separated from its surroundings. If the whole tail was used, then the language about dorsal vs. ventral somite sorts should be adjusted.

This manuscript makes use of Wnt11r morpholino data without confirmation using a mutant, which is considered the gold standard. So, a few comments could be softened, such as the claim that Wnt11r is essential. Including a photo-MO helps, because at least the earliest non-specific functions can be ruled out. This concern is also offset by the authors protein injection and CamKII inhibitor experiments, which establish confidence that this pathway is involved.

Reviewer #1 (Public Review):

This paper by Olenic et al focuses on interaction between the intramembrane metalloprotease SpoIVFB, and its inhibitors, SpoIVFA and BofA. A member of a large class of proteases with representatives in mammals as well as bacteria, its status as a multipass membrane protein has made illuminating the molecular basis of SpoIVFB inhibition challenging. Here, Olenic and colleagues combine genetics, cross-linking, and co-evolutionary bioinformatic analysis to develop a structural model of interaction between SpoIVFB and SpoIVFA and BofA. Overall, I found the experiments appropriate and the results compelling. Given the conservation and importance of this family of metalloproteases, I anticipate this work will be of interest to investigators working outside B. subtilis and should be appealing to a broad audience (subject to making the manuscript more accessible).

Reviewer #2 (Public Review):

Interestingly Co-IP experiments suggest that SpoIVFP, SpoIVFA, BofA and Pro-sigmaK are all simultaneously bound in complex.

They use crosslinking studies to show that BofA binds to the active site of SpoIVFB.

The authors provide strong evidence using cross-linking studies that the inhibitory proteins prevent Pro-sigmaK from interacting with the SpoIVFB active site.

The authors also identify mutations in BofA that lose the inhibitory effect of Pro-sigmaK processing. One limitation of this study is the instability of the proteins in the absence of the complex. This makes it difficult to interpret how mutations in one protein affect the stability of that protein.

Reviewer #3 (Public Review):

Olenic et al describe a very comprehensive investigation of the molecular mechanism of the regulation of the intramembrane metallo protease SpoIVFB from Bacillus subtilis. This protease plays essential roles in regulating the transcription of genes involved in spore coat formation by cleaving and thus releasing the transcriptional co-activator Pro-σK. The authors show that the activity of the enzyme is regulated by complex formation with two other proteins, BofA and SpoIVFA. They use a sophisticated plasmid design to make sure that all three components as well as the substrate are expressed at equivalent levels. Through a combination of functional assays and alanine-scanning they identify three residues in BofA that are important for inhibition, they further show that only the full complex is stable and that removal or mutations of one component leads to degradation. By introducing cysteine residues at certain locations and investigating the cross linking between the cysteines they identify an interface between SpoIVFB and BofA and extend the analysis to obtain a model of the inhibitory complex. In this model BofA blocks the access to the active site of the enzyme but without inhibiting the binding of the substrate to a specialized soluble domain of the enzyme.

Overall, the mechanism is an interesting new addition to the field of activity regulation of intramembrane proteolysis and is based on an extensive characterization of the entire system.

Reviewer #1 (Public Review):

Trask et al. first investigated whether males and females develop a conditioned compensatory response to pain-associated contexts: an effect that has been shown previously to discrete stimuli, and predominantly in male mice. In their first two experiments, they found that both males and females can indeed develop such a response, but that females do so more readily, with lower dose acetic acid injections used in the training phases. They then show that these effects are likely mediated by endogenous opioids rather than corticosterone, because they are blocked by systemic injections of the opioid-antagonist naloxone but have no relation to levels of corticosterone. Finally, they attempt to tease apart whether these effects are truly 'conditioned' or a result of some autonomic response to the acetic acid injection (by which I assume they mean some kind of habituation process) by omitting the acetic acid injection prior to test. The results here are somewhat confusing, but appear to demonstrate that in females at least, the effect is truly conditioned - i.e. the compensatory response is present even when the animals do not receive acid injections prior to test.

Overall this is a well-written and well presented manuscript that reports a series of interesting and novel results in an elegant manner. For the most part, the conclusions appear well supported, although I do have some queries as listed in the weaknesses section below. The results are particularly illuminating with regards to how important it is to include both female and male mice in our experiments - a practice that is still not ubiquitous - and illustrate that any conclusions made on the basis of experiments with males only may not generalise well to females. I think the results of this paper will be of interest to many researchers across fields of associative learning, neuroscience, and pain research.

Strengths:

• The manuscript has many strengths. It addresses an important novel topic, presents some exciting results, and presents the results in a systematic way.<br /> • It is well written, the sample sizes and statistics are appropriate for the most part, and the discussion is insightful.<br /> • The conclusions are mostly well supported although I do have some questions regarding whether they are all supported, which I will list in the weaknesses section.

Weaknesses

1. For the most part the logical flow of the manuscript is good, however, there are some sections in which I found the organisation difficult to follow. For example, Figure 1 details two experiments: one in which context-pain associations are formed and tested, and another in which animals are given naloxone. In the text, the first two experiments described involve escalating or consistent dose acetic acid injections, no mention of naloxone. The design is in Figures 2 and 3. Do the authors mean that Figure 1 explains two experimental series, each of which include multiple experiments? In addition, the manuscript jumps from explaining clear sex differences in conditional pain tolerance to reporting naloxone experiments for which results appear to be averaged across sexes, which is not signposted and thus a bit jarring.

2. Figure 3D. The authors suggest that, because male mice had higher withdrawal thresholds in the acid-paired context than in the vehicle context on day 4, that these animals were able to develop context-dependent pain tolerance. However, the fact that there is no difference in responding in this Context on Days 1 and 4 counteracts this claim somewhat - if animals learned tolerance across days then thresholds should be higher on Day 4. I also note that there is a lot of variability in the data, particularly with some animals increasing and some decreasing. I wonder if this works similarly to punishment - whether there is a median split of animals who develop tolerance and those who don't. It is quite the contrast from the females who are all in the same direction over days.

3. The corticosterone data (Lines 303-306, Figure 4C) is correlational but is referred to as causal (e.g. "...tolerance is not mediated by changes in circulating corticosterone...").

4. The null effect in the vehicle group in Figure 4X relies on a very low sample size, n = 4.

5. I found the experiments reported in Figure 5 a little confusing. Males appear to maintain their sensitivity to the context, suggesting the lack of a development of a compensatory mechanism in these mice, which is contradictory to the authors' claims in prior sections. Moreover, I'm not clear on why the data in Figure 5E show that females exhibit conditional recruitment of endogenous opioid systems in the training context? For this to be true, it would seem to me that the authors need to show that this effect (i.e. the naloxone-mediated increase in sensitivity) is not present in the vehicle context also.

Reviewer #2 (Public Review):

As noted by the authors, there has been relatively little research on the basic mechanisms of how context cues influence pain processing, particularly outside the fear learning literature. The current study addresses this gap in knowledge by developing a robust and reliable animal model for this phenomenon.

The experimental design is generally appropriate for the question at hand and has a number of strengths that should make it attractive to researchers in this area. Most notably, it has a short experimental timeline (3 days of conditioning and 1 day of testing) and makes use of well established procedures for inducing visceral pain (acetic acid injection) and assessing sensitivity to mechanical irritation (von Frey filament withdrawal). While these individual preclinical pain models have been extensively characterized in mice, the current study investigates how they interact, specifically how contextual cues paired with visceral pain influence the withdrawal reflex to an anatomically distinct touch stimulus.

Importantly, for most of the experiments in the manuscript (but see below), testing was conducted 45-60 min after an acetic acid injection, which was either coupled with exposure to a context that had already been paired with such injections or with a neutral (vehicle-paired) context. Findings from these experiments therefore reflect the unconditioned effects of visceral pain on mechanical touch sensitivity (apparent on the first day of conditioning following exposure to initial context-acid pairing or on the test day after exposure to the vehicle-paired context) and how these effects are modulated by context conditioning (apparent on the test day after exposure to the acid-paired context). The first experiment found that mice display mechanical allodynia (heightened sensitivity to touch stimuli) after visceral pain in the absence of pain-paired cues. Importantly, this pain-induced allodynia was abolished by a conditioned analgesic response (restoring withdrawal thresholds to baseline values) in females but not males when pre-test pain was signaled by pain-paired contextual cues. Follow-up experiments demonstrated that male mice show a similar albeit less pronounced conditioned analgesic effect at test when a more painful stimulus is used during conditioning, indicating that a sex difference in pain sensitivity may underpin the sex difference in conditioned analgesia described above.

While a within-subjects design was used in most experiments, the authors replicated their basic findings using a between-subjects design, which helps rule out more complex interpretations of the data and establishes the robustness and reliability of the basic findings. The authors also show that, after the test session, circulating levels of the stress-hormone corticosterone were similar for vehicle- and acid-trained mice, suggesting that the conditioned analgesic response described above was not mediated by this response, though it must be noted that there was no investigation of the time course of this effect and that context-dependent effects on corticosterone may have been obscured by nonspecific effects of pre-test acid injection and von Frey testing.

However, the conditioned analgesia induced by the pain-paired context was largely abolished when mice were pretreated with naloxone, indicating that this effect was mediated by an endogenous opioid response. This disruption was observed in both males and females. It was also observed in the final experiment, which contrasted the influence of pain- and vehicle-paired context cues alone, in the absence of visceral pain. Under these conditions, male mice actually showed conditioned allodynia (faster withdrawal) response when tested following exposure to the pain-paired context (relative to the neutral context). Females, on the other hand, showed no difference in withdrawal between contexts. However, this lack of cue-specificity was not due to a failure to learn or discriminate, but instead appears to reflect the engagement of two distinct conditioning processes, one that facilitates withdrawal (displayed by males) and a conditioned analgesic response which opposes this facilitation (not displayed by males). This was demonstrated by pre-treating mice with naloxone prior to testing, which selectively abolished the conditioned analgesic response in females, such that both sexes showed a conditioned allodynia effect.

It is important to note that the current study provides only the first step in establishing this new model, and therefore many important questions remain unanswered. For instance, von Frey testing was conducted after exposure to the pain-paired context. Thus it remains unclear whether a different result would be observed if the cues were actually present when sensitivity to nociceptive touch was actually being assessed. Similarly, it is not clear how long-lasting the conditioned effects persist after cue removal. These are important questions that have both practical and theoretical implications.

With regard to theory, opponent process accounts of pain processing have been advanced to explain conditioned analgesic effects like the one reported here, but do not readily explain the conditioned allodynia displayed by both sexes in the final experiment, when pre-test visceral pain was omitted. The current findings highlight the complexity of conditioned pain processing and raise important questions about the stimulus-specificity of such effects. For instance, it is unclear why male mice showed evidence of conditioned analgesia when given an injection of acid prior to testing but not when the paired-context was presented alone. Presumably it is that the conditioned analgesic effect is somewhat pain-specific, in that it is more effective in opposing the facilitatory influencing of pre-test visceral pain on nociceptive touch perception than it is in dampening nociceptive touch perception, per se.

These questions do not detract from the impressive work laid out here and instead represent goals for future research. There are, however, a few issues with the current study that make data interpretation difficult and weakens the overall impact of the paper in its present form. For instance, there is no description of writhing behavior (unconditioned pain response to acid injection) or how it may have interacted with von Frey testing. Moreover, the question of stimulus-specificity could be more directly addressed by assessing how the pain-paired context influenced writhing to the pre-test acid injection. Moreover, was there any evidence of conditioned effects of the pain-paired context on locomotor behavior and could this impact von Frey testing.

Reviewer #3 (Public Review):

This study used a classical-conditioning design to compare effects of associative learning on expression of pain-related behaviors in male and female mice. The experiments address an important topic, both because learning is an important but understudied contributor to the human pain experience and because there is evidence for sex differences in human pain expression. In this study, IP injection of acetic acid served as the principal unconditioned stimulus (US), and hypersensitivity of hindpaw-withdrawal responses to mechanical stimulation was the unconditioned response (UR). The US or its vehicle control was paired with a test chamber as the conditioned stimulus (CS), and US+CS pairing produced changes in mechanical sensitivity that were interpreted as the conditioned response (CR).

There were three main findings. First, the IP-acid US was more potent to elicit mechanical-hypersensitivity as the UR in females than males. Second, pairing of the CS with US intensities adequate to elicit the UR resulted in a CR, so this study provides strong evidence of conditioning. In the presence of the US (i.e. in the presence of US+CS after US+CS pairing), the CR manifested as a reduction in mechanical-hypersensitivity UR in both sexes. This was interpreted as "conditioned pain tolerance." However, in the absence of the US (i.e. CS alone after US+CS pairing), the CR manifested as conditioned mechanical hypersensitivity only in males. Lastly, studies with naloxone implicated endogenous opioid signaling in conditioned pain tolerance in both sexes and resistance to conditioned mechanical hypersensitivity in females.

This study provides a novel approach to the use of classical conditioning for research on expression of pain-related behaviors. The intent was to identify patterns of learned pain behaviors in mice that both correlate with human patterns of pain expression and provide a basis for follow-up mechanistic studies. It is unclear if the results meet the translational goal, but the study describes novel strategies and outcomes of classical conditioning with noxious stimuli that are of high significance and warrant further study.

STRENGTHS

-The study used an appropriate experimental design to evaluate the degree to which contextual stimuli could be established as a CS to modulate expression of a pain-related behavior in male and female mice as the CR.

-Of particular importance, the study evaluated effects of conditioning on pain behavior not only in the absence of the pain stimulus (i.e. after presentation of the contextual CS alone) but also in the presence of the pain stimulus (i.e. after presentation of the pain stimulus US and contextual CS together).

-Results provide clear evidence of a sex difference in both acute effects of the pain stimulus on the pain behavior (i.e. the UR) and in conditioning produced by repeated presentation of that stimulus (i.e. the CR).

WEAKNESSES

-The pain stimulus used in this study (intraperitoneal acid injection) elicits a wide range of pain behaviors as URs. This study focused on one of these pain behavior URs (mechanical hypersensitivity of hindpaw withdrawal responses), and the sex difference in this UR (females more sensitive than males) appears to be substantially larger than for many other IP acid-induced URs (where sex differences are generally not significant). The basis for this larger sex difference is not considered, and the implications of this sex difference for conditioning of this behavior or for conditioning of other IP acid-induced behaviors are also not fully considered.

-Studies with the opioid antagonist naloxone implicate recruitment of endogenous opioid signaling as contributor to conditioned pain behaviors. However, an important control experiment with naloxone was omitted from one part of the study.

-The authors note that associative learning like that studied here may contribute to the transition from acute to chronic pain, and that chronic pain is more prevalent in women than men. However, conditioning effects observed in this study were protective in females. Consequently, it is not clear how results of this study might provide insight into the basis for higher prevalence of chronic pain in women.

Reviewer #1 (Public Review):

In this study, the authors present a detailed analysis of the T cell receptor repertoire in mice examining how the age, the cell differentiation status, the tissue compartment distinguishing between spleen and bone marrow, and antigen exposure influence its composition. Looking at amino acid motif distributions and sharing patterns of nucleotide sequences within the individual clones, and comparing them between the different cell compartments and groups, they aim at identifying the main axes of influence that shape the T cell receptor repertoire within these mice. They find some interesting differences, with e.g. repertoires from different functional compartments being more separated within young animals compared to older ones. However, given the complexity of the different aspects that are investigated and compared, it is sometimes difficult to follow the main conclusions from each of the presented analyses. In addition, the main conclusion shown in Figure 7 that repertoire evolution is influenced by cell migration, differentiation and age/infection seems to be partly well known, as also acknowledged by the authors. However, it would be really interesting if, based on their analyses, the authors could put a "weight" to each of these features, i.e. if aging has a larger effect on repertoire differences than tissue compartments. This is currently not easily seen from their analyses. If possible this would increase the value of this study going beyond a descriptive presentation of the results and support the mechanistic relationships hypothesized within the discussion.

Reviewer #2 (Public Review):

This is a careful observational study of a rich dataset, quantifying the relationships between naive, regulatory, effector and memory subsets. it is notable for its thorough approach to analysing TCR diversity by multiple levels of granularity, from V-beta usage to nucleotide level. However it is a little lacking in narrative and interpretation. As a result my impression is that it doesn't present any results that expand significantly on our existing understanding of T cell biology. As the authors note, shifts in diversity of T cell subsets with age are already well established and while multiple measures of diversity are explored, the results are broadly in agreement with each other. I wanted to be more enthusiastic about this study but it comes across as a tour de force in data exploration rather than something that sheds light on the forces shaping the structure and overlap of T cell repertoires.

Reviewer #3 (Public Review):

The adaptive immune system employs an incredibly diverse set of non-germline-encoded receptors for specific defense. Despite this diversity the system responds robustly to infections across individuals, and there is even a certain degree of stereotypy in the targets of response. A key question in the field is how diversity and robustness can co-exist and how both are sculpted by the stochastic processes shaping an individual's immune repertoire. Here, Mark et al. address this question in a tour de force combining extensive repertoire sequencing and novel computational analysis techniques. A major strength of the manuscript is the detailed dataset that underlies the findings: The authors have used sequencing to map repertoire organization across multiple phenotypic and spatial compartments in mice, including following an external challenge (LCMV infection) and in two age groups. Among the notable findings are the following: First, a number of high-level statistical observables (V gene/amino acid motif usage) show little variability in the naive compartment of young mice, which increases both with age and in effector/memory repertoires. Second, there are statistical features that discriminate between different compartments, most clearly for the CD4/CD8 subsets but also between phenotypic subsets. Importantly, the paper skillfully connects the somewhat abstact study of repertoire organization to concrete questions about the underlying immunobiology, thus demonstrating the usefulness of the architectural viewpoint. For instance, the analyses show that the Treg compartment transitions from a naive-like to an effector-like composition with age, presumably reflecting the natural vs. induced Treg shift.

Overall the claims are well-supported by the presented analyses, but the evidence could be further strengthened by a more detailed methods section and additional robustness checks with regards to sampling variations.

Reviewer #1 (Public Review):

The study by McHugh et al. uses a combination of in vitro methodologies in an attempt to reconstitute some of the complicated biochemistry that is typically found at the plus end of dynamic microtubules in cells. A myriad of effector molecules play important roles in modulating microtubule dynamics, which is critical to ensure microtubule-mediated processes occur with appropriate spatial and temporal precision (e.g., assembly of the mitotic spindle). Whereas many groups have assessed the role of individual factors in affecting microtubule dynamics (MCAK, Kif18b, etc.), how these molecules function in concert to affect microtubule dynamics is less well understood. This study attempts to do so, with a particular focus on the plus end-directed kinesin, Kif18b, the plus end-binding protein, EB3, and the microtubule-depolymerizing kinesin, MCAK. Although the study yields some interesting insight into the concerted action of these three molecules, the work is confounded by various factors, including findings that conflict with previously published studies, somewhat ambiguous and unconvincing results, and at least one significant unsubstantiated statement/conclusion (see note about MCAK impacting Kif18b processivity). Notably, it seems that the most novel and important contribution of this study is limited to a single finding (that the EB3/Kif18b/MCAK complex is a more potent effector of microtubule dynamics that each protein alone), limiting the overall impact and scope of this study.

The authors demonstrate the following: (1) that Kif18b binds to EB3 (this was shown previously by Stout et al., MBoC 2011); (2) that Kif18b binds to MCAK (this was shown by Tanenbaum et al., Curr Biol 2011), and can use it as cargo via the MCAK N-terminus; (3) that Kif18b may form a tripartite complex with EB3 and MCAK, at least on stabilized MTs; (4) that Kif18b protects the plus ends of stabilized MTs from MCAK-mediated depolymerization (note this contrasts with findings on dynamic MTs; see point #7 below); (5) that the Kif18b tail reduces MCAK depolymerization activity, although the mechanism may simply be due to lattice binding-mediated stabilization (they note the same with CAMSAP); (6) that EB3/MCAK are slightly better at affecting catastrophe frequencies than MCAK alone (note this contrasts with previously published work (Montenegro Gouveia et al, Curr Biol 2010); (7) that Kif18b increases the frequency of MCAK-mediated catastrophe on dynamic MTs (albeit to a modest effect); and, (8) that EB3, MCAK and Kif18b act cooperatively to induce catastrophe on dynamic MTs (this is the most interesting and novel of their observations). My specific concerns are detailed below.

Major points:

1) "Our data indicate that Kif18b promotes EB3 and MCAK plus end targeting and that Kif18b and EB3 proteins function cooperatively to facilitate MCAK microtubule plus end accumulation." To be clear, the authors showed plus end accumulation along GMPCPP-stabilized MTs. This statement should be changed to reflect this important difference. Data presented in Figure 1 suggest that the three proteins interact, but do not indicate how the proteins will interplay along a dynamic microtubule with a native plus end. In fact, given that EB3 exhibits very low affinity for these microtubules, it is unclear how permitting EB-plus end binding would impact these interactions. Moreover, as noted below (point 2), a clear interaction between EB3 and MCAK is not observed by the authors when dynamic MTs are used (Figure 4), thus challenging this statement.

2) The results in Figure 4 seem to contrast with published data describing the combined effects of MCAK and EB3. For one, Montenegro Gouveia et al (Curr Biol 2010) showed that EB3 targets MCAK to the plus ends of dynamic microtubules in vitro, which the authors of this study do not observe (thus challenging their statement noted in point 1 above; also note that MCAK localizes to plus ends in cells). Secondly, the Montenegro Gouveia et al study also showed that EB3/MCAK dramatically increases catastrophe frequency (in fact, they observed no growth at all above 6 nM MCAK). The reasons for these notable discrepancies are unclear; however, the lack of plus end association of MCAK in their example images (kymographs in Figure 4e, right) raise concerns about the functionality of their protein. Alternatively, the buffer conditions may be sufficiently different from those used by the other study, which then raises the question of which buffer is the best to recapitulate in vivo phenomena? I am more likely to believe positive data than negative data, given the latter could be a consequence of functionally impaired protein, inappropriate buffer conditions, or otherwise.

3) The authors postulate that the MCAK N-terminus "impacts the processive behavior of Kif18b on the lattice" (this point is also stated in the conclusion paragraph of the introduction); however, they did not report on motor processivity in any condition (e.g., with or without MCAK/EB3). Rather, they only reported a qualitative description of diffusive motion, and pointed to the effects of this behavior on velocity. The authors should either remove the statement concerning processivity modulation, or directly measure it (I would suggest the latter since it may report on something of import). However, the authors would need to analyze many more particles to report an accurate read-out of processivity.

4) Conceptually speaking, I'm unclear how much information to extract from the interaction studies on stabilized MTs (Figs. 1 and 2). For example, given the weak affinity of EB3 for these (GMPCPP) MTs, how would the Kif18b-EB3 interaction occur when EB3 is near its high affinity-binding site at the plus end? If the authors think that Kif18b can transport EB3 to plus ends, then why didn't they look for this in their dynamic MT experimental scheme (Figs. 4 and 5)?

Reviewer #2 (Public Review):

In this study by McHugh and Welburn, the authors investigate why release of Kif18b into cytoplasm at nuclear envelope breakdown (NEB) results in robust astral MT shortening when the molecule's own MT depolymerizing activity in isolation is comparatively modest. The authors demonstrate, using live reconstitution of EB3, Kif18b and MCAK motors on both GMP-PNP stabilized and live MTs that these proteins interact to form a putative complex in the context of the MT. Kif18b convincingly promoted transport of MCAK and EB3 toward the MT end. Also, accumulation of these proteins at MT tips was enhanced when all three proteins were present. Both MCAK and Kif18b possess consensus sequences (SxIP) for association with EB proteins. Counterintuitively, increased doses of Kif18b protected the MT plus end from depolymerization by MCAK but enhanced catastrophe of live MTs in combination with MCAK. Collectively, these data suggest that in the context of the MT, EB3 and Kif18b synergize with MCAK via weak interactions to promote the targeting of MCAK to MT ends and regulate astral MT length by increasing MT catastrophes in mitosis.

This manuscript confirms and extends, with more extensive data, the previous work of Tanenbaum et al. Curr. Biol. (2011) suggesting that Kif18b complexes with MCAK to facilitate MT depolymerization and MT length regulation. These data also underscore the concept that weak interactions, in the context of MT binding, can refine diffusive behavior, MT dwell time and MT end targeting of MT regulators. The authors define a system in mammalian cells in which weak interactions between a plus-end directed kinesin and EB proteins can influence the extent and distribution of EB proteins at MT ends. This concept has previously been demonstrated in yeast via reconstitution of Mal3, Tip2 and Tea2 by Bieling et al. Nature (2007). Finally, similar to Montenegro Gouveia et al. Curr Biol (2010), these data show how MCAK activity (with respect to catastrophes and MT length regulation) is potentiated by plus end targeting by accessory proteins. Thus, although none of the principles guiding the behavior of Kif18b, MCAK and EB3 are completely novel, I find the data to be of good quality and generally supportive of the authors' conclusions. Also, despite the previously published studies cited above, we still do not fully understand how the many proteins that are recruited to MT ends are coordinated in their activity. This manuscript represents a solid contribution toward understanding how these proteins synergize functionally at MT ends although there are still some unanswered questions regarding the mechanism of coordination between Kif18b's observed inhibition of MCAK-dependent depolymerization rates while facilitating MCAK-dependent catastrophe.

Reviewer #3 (Public Review):

In this manuscript, McHugh and Welburn, address how the collective activity of three mitotic proteins that act at microtubule ends, MCAK, Kif18b and EB, results in potent microtubule depolymerization, at levels greater than either depolymerase (Kif18b or MCAK) in the system individually. In the cell biological context, their findings provide a biochemical basis for the observed cellular phenotypes of Kif18b depletion despite its relatively weak depolymerase activity in vitro. Prior in vitro and cellular studies have suggested interactions between pairs of proteins in this 3-protein module, but their collective activity has not been reconstituted in vitro, and biochemical models for how they act together are not tested. The findings in this manuscript suggest that Kif18b promotes the microtubule tip localization of both EB and MCAK, where they act collectively to promote depolymerization. The work also adds to our understanding of how MCAK can be effectively localized at microtubule ends when length scales are incompatible with the proposed "diffusion and capture" mechanism or EB-MCAK interactions are not sufficient to explain the observations. The findings presented will be of interest to researchers in the fields of mitosis and microtubule organization. There are some questions as detailed below, which need to be addressed.

Reviewer #1 (Public Review):

The manuscript by Zhang et al. describes a new surgical procedure to access the optic nerve in large mammals to provide therapeutic hypothermia. Therapeutic hypothermia is a powerful idea to prevent degeneration of the nervous system following trauma or other insults. The present work offers a very important step forward in the applicability of such technology to hidden areas of the nervous system in large mammals, such as the optic nerve. A large amount of new technology has been employed and a computer approach is provided to guide the surgeons in the application of the technology to large animals and, eventually, to humans. But for a few suggestions, I believe the manuscript is well written and has the potential to reach a large audience.

Reviewer #2 (Public Review):

Zhang et al. describe a new method for inducing traumatic optic neuropathy in larger mammalian models that offers the additional advantage of allowing rapid administration of local therapies to the site of optic nerve injury. Furthermore, the authors build on their prior work which has demonstrated a neuroprotective effect of hypothermia provided that protease inhibitors are employed to protect against cold-induced microtubule damage. In the present manuscript, they show that an endonasal approach to accessing the optic nerve within the optic canal can be performed safely in goat without inducing optic nerve damage. They then demonstrate that experimental crush of the optic nerve within the optic canal results in progressive degeneration of retinal ganglion cell (RGC) neurons and of their axons which form the optic nerve; this occurs over a period of several months, a similar time course to traumatic optic neuropathy in humans. Transcriptional profiling of mRNA obtained from the optic nerve at its site of injury identified changes in gene expression related to molecular pathways involved in inflammation, ischemia, and cellular metabolism. The authors then proceed to apply local hypothermia or protease inhibitor administration (individually or in combination) to the site of optic nerve crush for two minutes and observed a decrease in axonal degeneration in the subsequent months, although without an improvement of conduction of visual information by the affected optic nerve. Finally, the authors describe a computer program which uses computed tomography scans to evaluate thousands of potential endonasal approaches to access the prechiasmal optic nerve in large and medium sized mammals, and they proceed to successfully perform optic nerve exposure and experimental crush in a macaque model.

The authors' interpretation of the data is generally accurate; however, their conclusions about the impact of the work are somewhat overstated.

Strengths:

The prevailing use of rodent models of traumatic optic neuropathy in the field is problematic, and the authors' efforts to use larger mammalian models may be helpful in understanding the pathophysiology of and developing treatments for traumatic optic neuropathy in humans. The computer program that evaluates and recommends detailed surgical approaches and instrumentation is novel and would be quite useful to other investigators attempting to perform similar endonasal procedures. The authors make use of multimodal assessments of the goats and macaques [e.g. quantitative retina and optic nerve histology; optical coherence tomography measurements of retinal layers; pupillary light reflex assessment; and electrophysiology studies including visual evoked potential (VEP) and pattern electroretinography (PERG)] to convincingly demonstrate that the endonasal procedure itself can be performed without inducing progressive optic nerve damage and that experimental optic nerve crush using this procedure induces the expected profound decrease in optic nerve function, associated with progressive degeneration of RGC cell bodies and axons. The histological assessment of goat optic nerves following the local hypothermia/protease inhibitor treatment demonstrates a convincing reduction in the absolute number of RGC axons that are lost at 1 month after optic nerve crush.

Weaknesses:

The premise that optic nerve crush within the optic canal is much more physiologically relevant than other existing animal models is overstated: while the optic canal is believed to be the most common site of injury to the optic nerve, most human cases of traumatic optic neuropathy occur as a result of indirect mechanisms rather than compression/crush-namely, stretching and shearing forces are applied to the optic nerve where it is tethered to the periosteum of the optic canal by its dura. The authors' example of a bony fragment compressing the optic nerve within the optic canal (Figure 1B) is relatively rare and would actually represent one of the few cases where a surgical intervention (to relieve acute optic nerve compression) might be considered clinically justifiable.

The transcriptomic profiling at three locations along the visual pathway in post-trauma goats only showed differences in expression at the location of optic nerve injury, and not within the retina or proximal optic nerve on the affected side. The authors assert that the high rate of expression changes in pathways relevant to ischemia, inflammation and metabolism indicates "that targeting these pathways with local treatment could alleviate secondary damage." This is overstated. While such profiling may be useful for hypothesis generation, it was not followed up by any experiments to determine whether these expression changes are actually detrimental to the optic nerve. Some of them may very well be compensatory, such that inhibiting them may only exacerbate damage. Furthermore, given that these transcriptional changes are not seen in the retina (where RGC nuclei reside) or in the proximal optic nerve, this would suggest that the observed transcriptional changes at the site of injury are actually occurring in non-neuronal cells (e.g. astrocytes, oligodendrocytes, microglia). The authors should convey that the changes they observe are unlikely intrinsic to the optic nerve axons.

The lack of any rescue of the pupillary light reflex or of visual evoked potential responses after local hypothermia/protease inhibitor treatment suggests that the physiological significance of any anatomical rescue by this treatment is minimal. If a number of axons survive but cannot conduct sufficient visual signal to stimulate the pupil response or stimulate the visual cortex, then the local treatment (even when applied immediately after trauma in this model, unlike in human patients in which a delay of a number of hours would be required at the very least) cannot be considered a substantial success. The authors also characterize the goats at 1 month post-injury, so one cannot say whether the statistically significant improvement in axon loss with the combined treatment would be durable at the later 3-month time point.

As the authors acknowledge, the use of larger mammals prevented them from conducting studies with a large n. As a result, their analyses are underpowered.

Because of the dissimilarities between their model and the most common mechanism of human traumatic optic neuropathy and because of the lack of a clinically significant rescue of the optic neuropathy when the local hypothermia/protease inhibitor treatment was applied, the authors' assertion that their model may "trigger a paradigm shift " for traumatic optic neuropathy research should be scaled back.

Reviewer #1 (Public Review):

The authors investigated spindle growth dynamics during anaphase B in S. pombe, a unicellular eukaryote which undergoes closed mitosis. In order to accurately quantify spindle growth speeds, the authors tagged Alp7, a protein that localizes to plus ends of microtubules, with 3xGFP, and tracked its position in the dividing cell during mitosis, resulting in precise measurements of both the duration and velocity of microtubule growth events for the first time. By performing these experiments across a set of different genotypes (e.g. in strains with knock-outs of specific microtubule-associated proteins (MAPs)) the authors conclude that (1) microtubule rescues preferentially occur at the midzone edges, (2) microtubule growth speed decreases throughout anaphase B, independent of several known anaphase MAPs and (3) wrapping of the nuclear membrane around the spindle is responsible for this reduction in MT growth speed.

The data in this study is of very high quality and the conclusions are largely well supported by the data, but some changes could be made in the interest of simplicity and clarity, and some additional experiments should ideally be performed to strengthen the third claim.

Many changes occur in the nuclear bridge in late anaphase, including the disassembly of nuclear pore complexes and the fenestration of the nuclear envelope (Lucena et al. 2015, Exposito-Serrano et al. 2020, Dey et al. 2020). This opens up the possibility for a different interpretation of some of the authors' data - for example, that local alterations in the permeability barrier directly alter microtubule polymerisation dynamics, rather than the wrapping of the nuclear envelope in the bridge per se. This could help explain the ark1-as3 data, for example, in which (non-physiological) membrane tubes wrap around the spindle but local NEB is prevented (Dey et al. 2020).

The authors state that 'transition from fast to slow microtubule growth occurs in the absence of known anaphase MAPs' (heading paragraph 3 (239-240) and Figure 2), yet two paragraphs later, they show that the MAP Ase1 does in fact impact this transition. This distinction might prove confusing for readers, especially those unfamiliar with the S. pombe spindle.<br /> The authors state that Ase1 is required for the decrease in growth speed during anaphase. While the example kymograph in Figure 5B looks convincing, there seem to be too few points at the right side of Figure 5F to properly see the two distributions. Without any statistics to compare wt to ase1∆, it is difficult to tell if the apparent absence of decrease is real. In addition, as the authors also show in Figure 1C-E, the spindle collapses, causing the final spindle length to be shorter than wt. It could be that the spindle collapses before the characteristic drop in growth rate could be observed.<br /> One of Ase1's direct interactors, Cls1, was shown to not have an impact on the transition of fast to slow microtubule growth (Figure 2). In Ase1's case, a full deletion of the gene was necessary to reveal loss of the transition. The ase1off strain with reduced Ase1 expression showed a similar transition to wt, similar to the cls1off strain. cls1 is an essential gene and cannot be deleted, but similar to its interactor, its phenotype might be hidden even at low expression values.

Some observations, such as Figure 2G-L, lack associated statistics. In addition, since Alp7 tagged with 3xGFP is used throughout the paper, it seems important to test whether this tag influences microtubule dynamics.

Reviewer #2 (Public Review):

Lera-Ramirez et al. investigated how interpolar microtubules are regulated during anaphase B to support sustained spindle elongation. This is a perplexing question, since spindle elongation is known to require sliding between anti-parallel microtubules in the spindle midzone, and these microtubules must therefore grow to maintain the midzone as the spindle poles move further and further apart. Whereas previous studies have identified proteins that are necessary for spindle elongation and midzone function, this study focuses on understanding the changes in midzone microtubule dynamics and how those changes impact spindle stability during elongation. They report two major findings. First they use a clever combination of high-resolution imaging of living yeast cells and with genetic manipulation of spindle and nuclear membrane dynamics to show that the decrease in microtubule polymerization rate when the spindle reaches long lengths requires the formation of a compact nuclear membrane bridge that surrounds the midzone microtubules. Second, they combine their live-cell imaging approach with computational simulations to establish that the promotion of microtubule rescues near the midzone edges prevents spindle collapse during elongation. Overall, this is a well-written manuscript that advances our understanding of anaphase spindle elongation and will likely spur future research to extend the findings.

Strengths:

The results supporting the two major conclusions are generally clear and convincing. Although the study does not define the molecular mechanisms that control polymerization decrease and rescue at the midzone edges (more on that below), the major findings are nevertheless important. A key strength of the study is the use of structured illumination microscopy to measure the dynamics of microtubule ends in the midzone during spindle elongation. Whereas previous studies used FRAP experiments to infer microtubule dynamics, the direct approach used here enables a new level of insight. This method, combined with approaches to prevent bridge formation by either inhibiting Aurora B or inhibiting membrane biosynthesis with cerulenin, lead to the proposed model that microtubule polymerization slows when the nuclear membrane bridge surrounds the midzone in late anaphase. The resulting model that the "spatial cue" of the encroaching nuclear membrane drives the slowing of microtubule polymerization is an exciting idea and may connect to recent studies from the Gatlin and Rodinov labs on how cytoplasmic volume impacts microtubules dynamics.

Another strength is the use of computational simulations to complement the experimental measurements and explore the impact of rescue enrichment on spindle stability. This is important, because the authors show that ase1∆ mutants severely alter rescue frequency in the midzone, but the computational approach allows the authors to explore how a range of perturbations to rescue frequency and position impact the larger process of spindle stability. This is a nice integration of experiment and computation.

Weaknesses:

1) The changes in microtubule growth rate and regulation of rescues at microtubule ends are dealt with as separate processes, leaving the reader to wonder how they might be related. For example, the experiments in Figure 2 examine polymerization rate in the context of a variety of mutant or overexpression conditions that alter known microtubule regulators in the midzone. These results are largely negative with respect to polymerization, but what about rescue? Since the mechanism for regulating rescue at the midzone edges is unresolved, this data set seems like a valuable resource for identifying potential regulators.<br /> Similarly, the authors state that "we also observed that in ase1Δ cells microtubule growth velocity no longer decreased during anaphase B (Fig. 5F, Fig. 5-Supplement 1B)." Given the previous figures, and the model invoking the nuclear membrane, it seems important to examine whether Ase1 has a role in the formation or function of the nuclear membrane bridge. An alternative possibility is that ase1∆ spindles do not reach long enough lengths to pull the nuclear membrane into the bridge.

2) Throughout the manuscript, the authors analyze microtubule dynamics by labeling ends with Alp7-3GFP and Sid4-GFP. Since only the ends are labeled, the authors must make some assumptions about which spindle pole each plus end is connected to. This is essential for determining whether a feature in their kymographs represents a growing microtubule from the distal pole or a shrinking microtubule from the proximal pole. Which criteria were used could be more clearly stated.

3) Recent papers from the Kapoor and Moore labs have investigated the role of Ase1/PRC1 in controlling anaphase spindle elongation and the regulation of midzone microtubule dynamics. These papers are relevant to the discussion here and should be included.<br /> The authors state that "... depletion of PRC1/Ase1 does not perturb anaphase spindle elongation either [4], suggesting that if microtubule rescue organisation is required for spindle stability, it may rely on a mechanism other than recruitment of CLASP by PRC1." This statement contradicts the study from the Kapoor lab (PMID: 31248912), which showed that cells depleted for PRC1 do exhibit faster anaphase spindle elongation. Given the contradictory results from the Tolic and Kapoor labs, whether PRC1 depletion perturbs anaphase spindle elongation in mammalian cells may be an open and somewhat complicated question.<br /> The paper from the Moore lab (PMID: 32997572) shows that Ase1 in budding yeast recruits the EB homologue Bim1 to the midzone and this stabilizes microtubule dynamics during spindle elongation. Mutants that disrupt this recruitment show phenotypes that are reminiscent of those reported here for ase1∆ mutants in fission yeast. A preprint from the Surrey lab indicates that a similar recruitment mechanism may exist in mammalian cells (https://doi.org/10.1101/2020.07.09.195347). This model involving Ase1/PRC1 and Bim1/EB seems very relevant for the discussion.

Reviewer #3 (Public Review):

The authors report that during mitosis, the spindle midzone keeps a constant length throughout anaphase by promoting microtubule rescues at midzone edges. Interestingly, they also observed that wrapping of the nuclear membrane around the spindle midzone reduces microtubule growth speed in an Ase1/PRC1 dependent manner.

The strengths of this manuscript lie in the quality of the experiments carried out, not only from the technological point of view, but also from the quality of their interpretation. The mechanisms of coordination of microtubule sliding and growth events at the interdigitated zone are still poorly understood and this study brings us a better understanding of the key actors involved in these processes. The finding that the wrapping of the nuclear membrane around the spindle midzone reduces the rate of microtubule growth is in line with recent studies showing an interplay between the nuclear membrane and the central spindle. The authors suggest that such a cross-talk between the nuclear membrane and the central spindle might affect microtubule dynamics.

The weaknesses of the manuscript are mainly the lack of a clear mechanism to explain how the nuclear membrane around the spindle midzone reduces microtubule growth speed. Furthermore, it is not clear from the manuscript that this reduction in microtubule growth speed at anaphase B is an essential/important event for cell division and not just phenomenological. So, at this stage, the manuscript is very descriptive.

Joint Public Review:

In this manuscript, Freitas and Attwell use a rat model of renal ischemia and reperfusion to investigate the cellular and molecular basis of acute kidney injury that follows renal ischemia/reperfusion, such as occurs in certain clinical settings, including cardiac surgery, renal transplantation and severe hemorrhage. They found that the long-lasting "no-flow" phenomenon that develops under these conditions is attributable to contraction of pericytes in descending vasa recta and peritubular capillaries, without the involvement of glomerular arterioles. Using a pharmacological approach, they further demonstrated that perfusion during the reperfusion phase was normalized in the cortex and increased relative to controls in the medulla by the selective RhoA/Rho kinase (ROCK) inhibitor, hydroxyfasudil (HF). The authors conclude that ROCK-dependent contraction of capillary pericytes is responsible for the observed long-lasting decrease in blood flow in the kidney upon ischemia/reperfusion.

Support for capillary pericyte contraction is largely descriptive - imaging in kidney slices from NG2-DsRed mice perfused with a FITC-albumen/gelatin solution showing reduced capillary diameter near NG2-labeled cells combined with a quantitative analysis of the distribution of blockage-pericyte distances. Data obtained using HF provides additional indirect support for the centrality of pericyte contraction/relaxation, showing that HF increases capillary blood flow, increases capillary diameter in the vicinity of pericytes, and does not affect the diameter of glomerular arterioles.

Reviewer #1 (Public Review):

This work presents a significant amount of data and analyses (openly available via a Github repository) explaining and rigorously assessing how a crowd of citizens can estimate the growth of Mycobacterim tuberculosis (Mtb) strains and therefor measure the Minimum Inhibitory Concentration (MIC) needed to choose which antibiotics can be used to treat patients infected by Mtb. Measuring MIC can rapidly become time consuming and requires highly skilled scientists and/or dedicated software (such as AmyGDA) but the latter is sometime prone to errors such as artifacts classification. Thus, the use of a crowd will definitely help to overcome these limitations.

This manuscript has several undeniable strengths and few minor weaknesses:

Strengths:<br /> - First, Fowler and co-authors have constructed different datasets to then assess the users classifications. Interestingly, they also discussed the potential biases and limitations of each dataset. These datasets would be then useful to develop other programs to measure MIC for Mtb strains or to train ML models.<br /> - Then, Fowler and co-authors performed a careful analysis to validate the consensus, reproducibility, and accuracy of the classifications made by the citizens.<br /> - Overall, the development of the citizen science project BashTheBug is of particular interest to rapidly classify huge amount of MIC images generated by the CRyPTIC project. It may also pave the way of a new approach to quickly assess MIC data for Mtb growth in countries which may not have access to state of the art facilities or highly skilled scientists.

Weaknesses:<br /> - While the authors explained how they try to engage people to "play" this serious game and describe the number of classifications, there is no real discussion about the number of users playing every day. Reaching a minimum number of regular players is essential for the sustainability of such project.<br /> - In the discussion the authors mentioned that this approach may help training laboratory scientists unfortunately this claim was not really explored in this manuscript. It may have been interesting to analyze, for the most engaged volunteers, the improvement in term of accuracy of a user after 10, 100 or 1000 classifications. This may be also interesting to reweight the accuracy results in function of the users experience to see if it can improve the classification scores. It would have been also of interest to know if the way of presenting the data or playing the game may help experts (i.e. laboratory scientists) to improve their skills to quickly assess MIC using the methodology design to assess the citizens (such as time spent on a classification presented in Fig. S5).<br /> - 13 drugs were tested on 19 different strains of Mtb. It would have been of broad interest to see then how to reconstruct each plate from the different classifications and briefly present the practical outputs of these classifications: i.e. the resistance of each strain to the different antibiotics. Furthermore, except H37rV, the other strains are not mentioned; only a vial code is presented in Table S1.

Reviewer #2 (Public Review):

Thank you for the opportunity to review this extremely interesting, transdisciplinary paper, which reports a new method to analyse large scale data about the pathogen M. tuberculosis. The authors have the long-term goal of shifting the paradigm of antibiotic susceptibility testing (AST) from culture-based to genetics-based, where the treatability of a given pathogen is inferred from its genome rather than ascertained from laboratory testing, which can take several weeks and be demanding of expertise and resources. This study aims to establish that a crowd of volunteers with no clinical training can measure the growth rates of microbial samples and thus provide a large dataset suitable to train machine learning models, which would have required a great deal more time and resources if produced by experts. M. tuberculosis is a particularly significant pathogen to study because of its long incubation period, which means that testing for it requires more resources than most pathogens, and its prevalence in the world, having caused the most fatalities of any pathogen in 2019 (only surpassed by SARS-CoV-2 in 2020).

This paper will be of significance in many fields: that of microbiology and other health-related fields, and also of citizen science. I do not have the experience to judge the former in detail, but in the latter, the authors use a well-established platform (the Zooniverse) to carry out their experiment, and thoughtfully consider many sources of bias and and compare similar Zooniverse projects with their own. The process of recruiting and training volunteers is well described and a "wisdom of crowds" approach is used (though not named as such or referenced) to ensure that each data point is examined by at least 17 different people. The data quality obtained from a smaller number of classifications, e.g. 9, is considered, but it is not explained why 17 classifications in particular was chosen as a suitable number. (It is also stated that some samples were classified by far more than 17 people, but not why this was or what effect it had.) The authors also showed themselves to be thoughtful, flexible and empathetic to volunteers in the early stages of the experiment, noting that the M. tuberculosis samples were set out in trays of 96 wells and that classifying all 96 was too lengthy a task, and so they personally watched the process undertaken by a trained expert and noted that this expert worked by comparing each well to a control one in which no antibiotic was used. This effort to understand how participants think and work will have contributed to the quality of the Zooniverse project.

The authors demonstrate clearly the varying appropriateness of the mode, median and mean from these classifications to determine the minimum inhibitory concentration (MIC) of each antibiotic, which essentially determines whether or not it is an effective antibiotic with which to treat that culture - and, in the long term, a pathogen with that genome. There is a very good explanation of the different sources of bias incurred from expert analysis and also from analysis by software known as Automated Mycobacterial Growth Detection Algorithm (AMyGDA) - although the authors point out that this makes comparisons and analysis difficult, they do not state clearly how they addressed this difficulty.

The authors do not seem to have done any tests for even a very small crowd of experts, to see if there is significant difference between this and a crowd of volunteers, although they do compare volunteers' classifications to experts' classifications. Some new metrics are presented for data comparison, which are named the exact agreement and the essential agreement, and which I found difficult to understand. They seem to be derived from a reference method that comes from a set of standards from 2007 that have since been withdrawn, and it is not explained why these are superior to more standard statistical methods. Nonetheless, overall the authors have thoroughly compared their datasets in a great many ways and their approach seems rigorous.

The conclusion - that a crowd of volunteers can indeed analyse the growth rates of microbial samples - is broadly supported by the data presented, though there are a few inconsistencies. In several places the paper highlights a need for 95% reproducibility and 90% accuracy; however, later, when showing reproducibilities of 94.2% and 94.1% (for the mode and median), and 90.2% and 91.0% accuracy (again for the mode and median), although this almost but not quite meets the 95% benchmark, the authors suddenly claim that the 95% is not needed. There is probably a good reason for this, but it was not clearly explained.

The authors provide very few details about the origin of the 20,000 samples of M. tuberculosis collected by one of their organisations - presumably these are clinical samples taken from patients, but it is not stated whether patient consent was required or obtained, or what the geographical distribution was of this collection. Furthermore, it is remarked that vials of samples were sent to seven laboratories but only tested by two members of staff, the logistics of which were rather confusing to picture, and it was hinted that there was a more detailed process which was "described previously", but only in another paper.

There is some very interesting discussion of participation inequality (measured by the Gini coefficient) and the fact that this seemed, on average, greater for this project than other biomedical Zooniverse projects, but few suggestions as to why this might be or the implications for similar projects, of which there are likely to be many in the near future given that health citizen science is a rapidly expanding field. Nevertheless, some exciting recommendations are made for the field, such as their support for efforts to create a set of standards for Mycobacterial antibiotic susceptibility testing, and a remark that the Zooniverse platform does not yet allow images to be withdrawn from classification after enough agreement has been established by volunteer classifications, even if its number of classifications is less than that recommended (in this case 17). This means that, as well as having implications for the testing and treatment of cases of tuberculosis worldwide, this paper has possible implications for microbial citizen science methodology.

Reviewer #3 (Public Review):

In this article the authors present a creative approach to resolve the limited availability of expert mycobacteriologists while providing accurate MIC testing by presenting MIC data to lay interpreters that provide reproducible, accurate results for a large number of samples. While overall the work is compelling, this creative, comprehensive analysis has a few important limitations that should be addressed.

The authors report that the combination of the single expert classification and the AMyGDA classification represents a dataset with two complimentary, and therefore negligible, sources of error. For many similar studies MIC reading would be performed by two independent reviewers, the authors should discuss their previous data supporting the assumption that this combination represents a valid reference against which the user-level comparisons can be compared. The use of this as the reference for lay interpretation may in part explain the high rate of image exclusion (50.3%), which may significantly change the results of the study. An alternative consideration could be that a high error rate for the AMyGDA software (implied in the text) restricts the validity of the crowdsourcing model only to those samples for which AMyGDA is also consistent with expert consensus, and as a result, supporting the use of the crowdsourcing model for MIC reads, but limiting the benefit of crowdsourcing beyond that which AMyGDA supplies on its own.

In addition, the authors refer to an absence of reference standards for Mtb antimicrobial susceptibility testing (Results section, subheading "How to compare?" lines 3-5 and Discussion section 1st paragraph line 3). The 2018 "Technical report on critical concentrations for drug susceptibility testing of medicines used in the treatment of drug-resistant tuberculosis" published by WHO with FIND should be considered to serve this purpose. It is likely that the authors intended to refer to the absence of consensus methods for MIC determination, which would be better supported by their following paragraph. This should be clarified.

Given that MIC testing currently serves primarily as a reference level test performed at sites with a greater availability of mycobacterial expertise, the idea described in the final paragraph of the discussion in which the authors suggest that crowdsourcing could replace the second reviewer may be of less benefit. While it is possible that such an approach could be effective, since the presented analysis represents neither a comparison between the crowdsourcing model and the full dataset, nor between the crowdsourcing model and a two expert reader dataset, such a consideration remains hypothetical. The presented conclusions would be strengthened were the authors to confirm similar benefit among those samples for which AMyGDA was ineffective - indicating that among samples for which automated software could not replace an expert read, crowdsourcing might. Alternatively, if crowdsourcing and AMyGDA were adequate on their own, the expert may not be required at all.

Reviewer #1 (Public Review):

The authors have used a classical behavioral task (learning to press a lever for a food reward in food-restricted mice) to address complementary changes in dopamine (DA) and acetylcholine (ACh). They have used the latest methods to monitor DA and ACh and have chosen a behavioral test that elicits reliable changes in both. The paper adds to existing literature on which behavioral aspects are influenced by these transmitters. A particular strength is examination of how a reward-related drop in ACh levels is altered after conditional knockout of D2 DA receptors in striatal cholinergic interneurons (ChIs). ChIs are the primary source of striatal ACh, and show a decrease in firing rate (a pause) as DA levels rise - an effect that has been linked to D2 activation. Here, the authors show that the duration of the decrease in ACh, as an index of ACh activity, is indeed D2 dependent, although a drop in ACh is still seen, implying other regulators besides DA.

Despite these strengths, there are a few limitations, as well. First, there is no discussion of other regulators that might lead to a decrease in ACh amplitude that is DA-independent, which is somewhat unsatisfying. Second, much of the report examines correlations between ACh and DA levels at different points in the behavior, with a focus on how DA regulates ACh levels. Not addressing the opposite question of DA regulation by ACh, as well, seems a missed opportunity. Lastly, the paper frames the changes in transmitter concentration monitored with genetically encoded probes as though these changes cause the behaviors examined. This seems simplistic, given that there are many steps between the data reported and understanding how DA and ACh influence the circuitry underlying the behaviors. The discussion considers some of these, but the general framing is on the observed changes in transmitter levels, rather than underlying cellular activity, narrowing the implications of the results.

Reviewer #2 (Public Review):

The authors nicely demonstrate a tight correlation between striatal ACh and dopamine release, and its regulation by CIN-D2 receptors. The strong correlation was demonstrated through pharmacological and selective genetic manipulations and extensively verified. Nevertheless, while the authors conclude that their data supports a role of CIN-D2 receptor control of ACh release in motivated behavior, data supporting the role of this signaling mechanisms in motivated behavior is lacking.<br /> This study would benefit from further analyses on the behavioral effects of pharmacological and genetic manipulations. The inclusion of additional behavioral tests would greatly strengthen the study by identifying clear behavioral repercussions of CIN-D2 receptor control of ACh release.

Reviewer #3 (Public Review):

The authors showed that D2R antagonism did not affect the initial dip amplitude but shortened the temporal length of the dip and the rebound ACh levels. In addition, by using both ACh and DA sensors, the authors showed DA levels correlate with ACh dip length and rebound level, not the dip amplitude. Both pieces of evidence support their conclusion that DA does not evoke the dip but controls the overall shape of ACh dip.<br /> Overall the current study provides solid data and interpretation. The combination of D2R antagonist and CIN-specific Drd2 KO further support a causal relationship between DA and ACh dip. Overall, the experiments are well-designed, carefully conducted and the manuscript is well-written.

At the behavioral level, the author found a positive correlation between total AUC (of ACh signal dip) and press latency in Figure 10, indicating cholinergic levels contributes to the motivation. The next logic experiment would be to compare the press latency between control and ChAT-Drd2KO mice, since KO mice have smaller AUC while not affecting DA. However, this piece of information was missing in the manuscript. The author instead showed the correlation between AUC and latency was disrupted, which is indirectly related to the conclusion and hard to interpret. Figure 10 showed that eticlopride elongates the press latency, in a dose-dependent manner. However, it is not clear what this press latency means and how it was measured in this CRF task (Since there is no initial cue in the CRF test, how can we define the press latency?).

Pearson r<0.5 is normally defined as a weak correlation. It is better to state r values and discuss that in the manuscript.

Is there any correlation between ACh AUC and other behavior indexes such as press speed or the time between press and reward licking?

In figure 2B CS+ group, the author was focusing on the responses at CS+, however, the ACh dips at reward delivery seem to persist even after in this particular example. This might be an interesting phenomenon in which ACh got dissociated from DA signals, which needs further analysis from the author.

Reviewer #1 (Public Review):

This report includes the identification and subsequent molecular dynamics analysis of posttranslational modifications of specific residues in beta-MHC in normal hearts and hearts in cardiac failure. The study is prompted by the possible regulatory roles of beta MHC in the generation of mechanical activity and possible reversion to fetal isoforms in cardiac failure. The identifications are followed by molecular dynamics simulations bearing on the stability of thick filament tail interactions and myosin head positioning.

Reviewer #2 (Public Review):

1. The authors were aiming to determine what post-translational modifications were present on beta myosin motor protein and whether these were altered in two forms of heart failure. They then used molecular dynamics simulations to assess their potential effects on function and made some predictions based on the modeling.<br /> 2.. The strengths were that they found acetylations and phosphorylations albeit at very low frequency and they found that some of the PTMs were decreased in the failing heart.<br /> 3. A limitation is that only a relatively small number of samples was examined; with more samples, it might have been possible to make stronger conclusions.

Reviewer #3 (Public Review):

The PTMs on β-myosin heavy chain reported in this study are likely to inspire further work into whether such modifications can produce discernable functional consequences on the sarcomere, cell, and heart scales. Molecular dynamics simulations provide useful context for selecting those PTMs which are most likely to merit further investigation. An interesting implication of these novel phosphorylation and acetylation sites is that they could interact with emerging small molecule therapies targeting myosin that may have been developed in the absence of realistic β-myosin PTMs.

Reviewer #1 (Public Review):

This submission is dealing with the unmet need to generate a machine learning approach for the early and accurate estimation of the risk among COVID-19 submission. The presented data generate confidence on the validity since they have been developed in a vast number of patients and they are validated in cohorts from different geographical regions.

Reviewer #2 (Public Review):

The authors describe the development by machine learning of a score, namely CODOP, to predict in an easy and cheap way in-hospital mortality of patients with COVId-19 pneumonia. The score is developed and validated through large and different (multinational) cohorts suggesting robust results. They provide two versions in case of over- and under-triage.<br /> The manuscript is well written and statistics are adequate. All related data are provided and ethical issues do not rise.