eLife assessment

This is a valuable study that quantifies CD8 T cell movement in different tissue environments and concludes that T cells display more confined movement in the inflamed lung than in lymph nodes or intestinal villi. The evidence supporting conclusions is solid with well-defined measurements and sufficient statistical analysis. The work will stimulate further efforts to understand the mechanisms behind the different behaviour of T cells that are important in host defence against intracellular pathogens and cancer.

Reviewer #1 (Public Review):

The authors set out to analyse the pattern of movement of T cells in different tissues- lymph nodes, villi, and inflamed/infected lungs. The authors are comparing data sets from multiple sites in different studies but acquired using similar instruments, preparations, and imaging conditions.

The more confined movement pattern in the lung that has a turning angle distribution with more incidence of angles near 180 degrees is striking.

T cells in the infected inflamed lung search a smaller volume over time but will explore it more extensively.

The measurements of T cell movement are context-free such that obstacles and tissue boundaries that could account for some of the confined behaviours in the lung parenchyma are not discussed.

Nonetheless, the work will motivate further study of the biological significance of the different T cell movement patterns in the lung, which may also be considered in the context of recent data on changes in B cell motility- a potential interacting cell.

Reviewer #2 (Public Review):

This paper addresses the topic of how T cells migrate in different tissues. The authors provide experimental evidence that T cell migration in the lung is more confined than in lymph nodes and gut villi. While prior studies have started to define the way T cells migrate during normal and pathological conditions, there is still a lot to learn about the factors that control this process. Thus, the topic is significant and timely. The authors use previously acquired data with two-photon microscopy from murine tissues. They compare multiple motility parameters of T cells in lymph nodes, gut villi, and inflamed lungs. Experiments demonstrate that T cells in the lung have a particular mode of migration characterized by low speeds, back-and-forth motions, and confinement.

Strengths:<br /> Overall, this is a very well-performed study. The data presented is of excellent quality and, for the most part, supports the authors' conclusions. The imaging techniques used to track T cells in various organs and the mouse models implemented are very relevant and robust. The functional analysis of the different migration features of T cells is compelling and should be of use to the community. The conclusion that T cells use different migration modes depending on the organ appears novel. This is considered of major significance.

Weaknesses:<br /> The main weakness of the manuscript is that the study remains descriptive and comparative. It is important to analyze and describe different migration modes depending on the organ. Still, it would have been desirable for the authors to provide information on the reason for such differences. One of the striking observations is the back-and-forth motion of T cells in the lung. Searching for mechanisms underlying this unique mode of displacement would strengthen the quality of the study.

Reviewer #3 (Public Review):

The ability of T cells to move through a variety of complex and disparate tissue environments is fundamental to their success in surveying and responding to infectious challenges. A better understanding of the molecular cues that regulate T cell motility in tissues is needed in order to inform therapeutic targeting of T cell migration. Contributions that are intrinsic and extrinsic to the T cells themselves have been shown to shape the pattern of T cell movement. This study uses advanced quantitative image analysis tools to dissect differences in T cell motility in different tissue locations, to better define how the tissue environment shapes the pattern of motility and scope of tissue explored. The combination of different quantitative measures of motion enables the extensive characterization of CD8 T cell motility in the lymph node, lung, and villi of the small intestine. However, there are too many variables with respect to the CD8 T cell populations used for analysis to be able to gain new insight into the impact of the tissue microenvironment itself.

The use of these advanced quantitative imaging analysis tools has the potential to significantly expand our analysis capabilities of T cell movement within and across tissues. The strength of the paper is the comprehensive analysis of multiple motility parameters designed with T cell function in mind. Specifically, with respect to the need for T cells to search a tissue area to identify antigen-bearing cells for T cell activation and identify cellular targets for the delivery of anti-microbial effector functions. The inclusion of an analysis of the "patrolled volume per time" is seen as a particularly useful advance to compare T cell behaviors across tissues.

However, with the current data sets, it is difficult to draw definitive conclusions on the impact of the tissue environment on how T cell move, given the considerable variability in the CD8 T cells themselves. Extended experimentation would be needed to fully support their key claims. In particular:

1) The authors have separated out naïve and activated CD8 T cells for their analysis, but this is a marked over-simplification. There are too many variables within these groups to be able to distinguish between differences in the T cell populations versus differences in the tissue environment. Variables include:<br /> a) T cells pre-activated in vitro before in vivo transfer (LPS-lung) versus transfer of naïve T cells for activation in vivo (Flu-lung, LCMV-villi)<br /> b) Polyclonal CD8 T cells (naïve, LPS-lung, Flu-lung) versus monoclonal (P14) CD8 T cells (LCMV-villi)<br /> c) Presence of cognate-antigen (Flu-lung, LCMV-villi) versus absence of antigen (LPS-lung)<br /> d) Cell numbers, 104 polyclonal naïve for Flu-lung versus 5 x 104 monoclonal (P14 T cells) for LCMV-villi)<br /> e) Intravital imaging (LCMV-villi) versus tissue explants (Flu-lung)

The authors do present data that suggest similarities of motility patterns within the same tissue occur despite variabilities in the CD8 T cell source, for example, the MSD is not significantly different in the two lung groups despite differences in the way the CD8 T cells were activated. However, these similarities are lost when other parameters are analyzed suggesting additional variability independent of the tissue itself.

2) Controlled experiments are needed, where the input CD8 T cell population is kept constant and the target tissue differs, to substantiate any of the current conclusions. This could be done by using a single source and/or specificity of CD8 T cells (e.g., P14 or OT-I TCR transgenics, or polyclonal in vitro activated CD8 T cells) transferred into mice where the tissue providing the antigen or inflammation source is varied (lung with pOVA-flu versus small intestine with pOVA-LCMV for example).

Alternatively, activated polyclonal CD8 T cells could be analyzed in the LPS-lung draining LN as well as in the LPS-lung to make a direct comparison between the tissues (LN versus lung) using CD8 T cells of the same activation status.

3) Differences in the micro-anatomical regions of the tissues studied may also contribute to tissue differences in movement patterns between the lung and the small intestine. The region of the small intestine imaged was specifically focused on the villi, close to the gut epithelium. Details of the location within the lung where images were taken are missing, therefore the motility differences between the lung and small intestine could reflect differences in the micro-anatomical position of the CD8 T cells within the tissue (proximal to epithelium versus parenchymal), rather than differences between the tissues themselves.

Overall, the authors have developed a quantitative multi-parameter approach to the study of T-cell motility in different tissues. Application of these analytical tools to the study of T-cell behavior in different tissue locations has the potential to reveal tissue and/or T-cell-specific patterns of movement that may help to identify molecular requirements for context-specific dynamic T-cell behavior. Their quantitative approach reveals small but statistically significant differences in particular motility parameters, the functional significance of which will require further study. The careful design of experiments to reduce as many variables as possible will be needed to increase the impact of the work and ensure new insights into this important aspect of T-cell function.

eLife assessment

This valuable study reports improvements in methods and tools for curating complex pathogen-host interactions. A compelling framework is described, using rigorous approaches and to considerable extent validated by the biocuration community. The developed ontologies and controlled vocabularies could be extended beyond host pathogens, e.g. ecological contexts with multi-species and multilevel interactions.

Reviewer #1 (Public Review):

This study presents a resource aiming to unify language and rules used in the literature to describe, curate and assess biology experiments, published or not. Focusing on host-pathogen interactions, the work presents a new ontology and controlled vocabulary, as well as rules to describe 'metagenotypes', a term coined for the joint description of interacting host-pathogen genotypes. 'PHI-Canto' extends a previous resource by also enabling using UniProtKB IDs to curate proteins. Among other important by-products, PHI-Canto could contribute to damping proliferating names and acronyms for genes, processes, and interactions; a chronic annoyance in the biosciences.

The tool does give the impression that, with sufficient time and usage, it could become a rich and robust resource. Just addressing the Uniprot IDs issue is a nice move.

Reviewer #2 (Public Review):

In this paper, the authors propose a system for annotating and curating scientific publications in the context of interspecies host-pathogen interactions. This system, called PHI-Canto (the Pathogen-Host Interaction Community Annotation Tool), is an extension of an existing tool (called Canto). In addition, they present the development of new concepts, controlled vocabularies, and an ontology for annotating relevant aspects in this domain, called PHIPO (Pathogen-Host Interaction Phenotype Ontology).

The approach has been empirically validated by annotating ten publications. The application's source code is available, as well as the associated ontologies and vocabularies and an example of the data resulting from the annotation process.

Reviewer #3 (Public Review):

In this work, the authors have built a framework for the annotation of interactions between species. The framework includes ontologies, methodologies, and an annotation tool called PHI-Canto. The framework makes use of multiple existing ontologies that are in wide use in the biocuration community. In addition, the authors have built their own project-specific controlled vocabularies and ontologies for the capture of pathogen-host interaction phenotypes (PHIPO), diseases (PHIDO), and environmental conditions (PHI-ECO). Their work builds on and extends methods that have been developed within the Gene Ontology Consortium and model organism databases. The tool PHI-Canto is an extension of the tool Canto developed by PomBase for curation. The authors used this framework to annotate pathogen-host interactions within the Pathogen-Host Interactions Database.

Strengths: The manuscript is well-written and includes significant detail regarding curation policies/methods and the use of the actual PHI-Canto tool. The appendices are very detailed and provide useful illustrations of the annotation practices and tool interface. The work has built upon and extended well-established standards and methods that have proven their utility over many years of use in the biocuration community. The authors have rigorously tested their framework with the curation of a variety of publications providing a diverse assortment of annotation challenges. The concept of a "metagenotype" is important and providing such a structured system for the capture of this information is useful. All of the materials produced by the work are completely freely available for use by the wider community.

Weaknesses: There are some areas of the manuscript and appendices which are a bit confusing and could be improved. The authors have developed their own set of disease terms (PHIDO) but do not comment on why existing disease terminologies (such as Mondo or DO) were not used or if the PHIDO terms relate to those other vocabularies. There is no discussion of the possible use of a graph representation for the capture of this complex information (which is being done in many settings including the Gene Ontology with GO Causal Activity Models (GO-CAMs)) or why such a structure was not used. Although the abstract talks about the use of the framework within the PHI database as a test case for broader use regarding interspecies interactions, there is no mention of extending the use of the tool to other species interaction communities beyond pathogen-host interactions.

Author Response:

Reviewer #1 (Public Review):

This study presents a resource aiming to unify language and rules used in the literature to describe, curate and assess biology experiments, published or not. Focusing on host-pathogen interactions, the work presents a new ontology and controlled vocabulary, as well as rules to describe 'metagenotypes', a term coined for the joint description of interacting host-pathogen genotypes. 'PHI-Canto' extends a previous resource by also enabling using UniProtKB IDs to curate proteins. Among other important by-products, PHI-Canto could contribute to damping proliferating names and acronyms for genes, processes, and interactions; a chronic annoyance in the biosciences.

The tool does give the impression that, with sufficient time and usage, it could become a rich and robust resource. Just addressing the Uniprot IDs issue is a nice move.

We thank the reviewer for their positive comments and acknowledgement of the importance of using unified language in literature curation. We are pleased to see that our effort to improve interoperability and use existing resources has been recognized. We are also pleased that this reviewer recognizes the additional benefits of choosing to use UniProtKB accession numbers. 

Reviewer #2 (Public Review):

In this paper, the authors propose a system for annotating and curating scientific publications in the context of interspecies host-pathogen interactions. This system, called PHI-Canto (the Pathogen-Host Interaction Community Annotation Tool), is an extension of an existing tool (called Canto). In addition, they present the development of new concepts, controlled vocabularies, and an ontology for annotating relevant aspects in this domain, called PHIPO (Pathogen-Host Interaction Phenotype Ontology).

The approach has been empirically validated by annotating ten publications. The application's source code is available, as well as the associated ontologies and vocabularies and an example of the data resulting from the annotation process.

We thank the reviewer for their positive comments on our framework for curating interspecies interactions literature. We are pleased that the reviewer has recognized that the source code, associated ontologies and curated data are freely available for others to use. We are delighted that the reviewer found the curation of ten trial publications in PHI-Canto informative and benefited from the worked curation examples.

Reviewer #3 (Public Review):

In this work, the authors have built a framework for the annotation of interactions between species. The framework includes ontologies, methodologies, and an annotation tool called PHI-Canto. The framework makes use of multiple existing ontologies that are in wide use in the biocuration community. In addition, the authors have built their own project-specific controlled vocabularies and ontologies for the capture of pathogen-host interaction phenotypes (PHIPO), diseases (PHIDO), and environmental conditions (PHI-ECO). Their work builds on and extends methods that have been developed within the Gene Ontology Consortium and model organism databases. The tool PHI-Canto is an extension of the tool Canto developed by PomBase for curation. The authors used this framework to annotate pathogen-host interactions within the Pathogen-Host Interactions Database.

Strengths: The manuscript is well-written and includes significant detail regarding curation policies/methods and the use of the actual PHI-Canto tool. The appendices are very detailed and provide useful illustrations of the annotation practices and tool interface. The work has built upon and extended well-established standards and methods that have proven their utility over many years of use in the biocuration community. The authors have rigorously tested their framework with the curation of a variety of publications providing a diverse assortment of annotation challenges. The concept of a "metagenotype" is important and providing such a structured system for the capture of this information is useful. All of the materials produced by the work are completely freely available for use by the wider community.

Weaknesses: There are some areas of the manuscript and appendices which are a bit confusing and could be improved. The authors have developed their own set of disease terms (PHIDO) but do not comment on why existing disease terminologies (such as Mondo or DO) were not used or if the PHIDO terms relate to those other vocabularies. There is no discussion of the possible use of a graph representation for the capture of this complex information (which is being done in many settings including the Gene Ontology with GO Causal Activity Models (GO-CAMs)) or why such a structure was not used. Although the abstract talks about the use of the framework within the PHI database as a test case for broader use regarding interspecies interactions, there is no mention of extending the use of the tool to other species interaction communities beyond pathogen-host interactions.

We thank the reviewer for their detailed response. We are pleased that the reviewer found the manuscript to be well-written and informative with useful examples. We thank the reviewer for their helpful suggestions to improve the appendices and manuscript text.

We would like to clarify that PHIDO is not intended to compete with existing disease ontologies: it is instead being used as a placeholder, until the time when its terms can be replaced with terms from existing disease ontologies. PHIDO was an expedient solution, in the sense that it provided the fastest way for us to test the process of curating diseases with PHI-Canto. This is because we only had to convert the existing list of disease names already in PHI-base into a controlled vocabulary, thus removing the need to wait for maintainers of other ontologies to add terms for us (as reported in Urban et al., 2022).

Additionally, we were required to use terms from PHIDO due to the lack of representation for plant and animal diseases in existing ontologies or vocabularies. Plant disease, in particular, is very underrepresented, with the ontologies we surveyed having either inappropriate semantics (e.g. the Plant Trait Ontology focusing on traits related to disease, rather than the diseases themselves) or still being in development (e.g. the Plant Stress Ontology). The majority of source ontologies used by MONDO are human-centric, and DO is exclusively for human disease, yet human disease represents only part of the focus of PHI-base (~35%). Furthermore, our choice of vocabularies is limited by the fact that Canto currently only supports ontologies in OBO format (for historical reasons).

We have begun the process of harmonizing disease names in PHI-base with terms from existing disease ontologies – such as MONDO, DO, and the National Cancer Institute Thesaurus – with the ultimate aim of using terms from those ontologies in curation, instead of terms from PHIDO. As general vocabularies for animal and plant disease emerge or are identified, we will extend this procedure to those diseases.

With regards to a graph representation of the data, we are aware of the examples the reviewer described, and we agree that this type of representation could be preferable. However, our data model is currently constrained by the developers of Canto, who use a relational data model and currently have no plans to implement a graph data model or a graph representation. We acknowledge that query languages like GraphQL can provide a graph-based interface to an existing relational data model, but we believe this would require a significant technological investment. For PHI-base, we plan to enable a graph representation of the data by integrating with existing knowledge graph tools, such as KnetMiner (www.knetminer.com;doi.org/10.1111/pbi.13583), which will provide graph-based queries on PHI-base (albeit only on select species for which knowledge graphs will be provided, i.e. Arabidopsis, rice, wheat, eight plant and human infecting fungal ascomycete pathogens, and two non-pathogenic yeast species). We will also use KnetMiner integration to embed subgraphs of the complete knowledge graph into the gene-centric pages on the PHI-base 5 website.

We acknowledge the lack of discussion about extending the tool for broader interspecies interactions. These examples may have been omitted from a previous draft due to journal word count limits. Possible future uses of the PHI-Canto schema could include insect–plant interactions (both beneficial and detrimental), endosymbiotic relationships such as mycorrhiza–plant rhizosphere interactions, nodulating bacteria–plant rhizosphere interactions, fungi–fungi interactions, plant–plant interactions or bacteria–insect interactions, and non-pathogenic relationships in natural environments, such as bulk soil, rhizosphere, phyllosphere, air, freshwater, estuarine water or seawater, and tissues or organs (e.g. the gut, lungs, and skin of humans, birds, or other animals). The schema could also be extended to situations where phenotype relations to genes or genotypes have been established for predator–prey relationships, or where there is competition in herbivore–herbivore, predator–predator, or prey–prey relationships in the air, on land or in the water. Customizing Canto to use other ontologies and controlled vocabularies is as simple as editing a configuration file within the source code.

eLife assessment

This work presents a multimodal approach to ascertain links between risk and resilience to depression and Alzheimer's disease in a large pediatric sample. The authors find two latent imaging variables that may be associated with resilience to adverse life events and disease risk, which show some spatial overlap with disease relevant gene-expression patterns and neurotransmitter expression. Such findings could be important for understanding mechanisms underlying resilience in neurological disorders, however, the analyses are inadequate for fully supporting the interpretation of the variables involved in these models, or for supporting some of the overall conclusions of the work.

Reviewer #1 (Public Review):

Motivated by the premise that Alzheimer's disease (ADD) and major depressive disorder (MDD) have shared underlying environmental and genetic risk factors, Petrican and Fornito combine non-imaging risk factors and executive task-based functional network change indices into latent variables of resilience to AD and MDD. The authors find two latent variables (LVs): LV1 represents change in network membership over time of distributed nodes during task, which is associated with greater genetic MDD risk, less psychopathology, and more advanced puberty, all while adjusting for age and indices of environmental stressors. LV2 represents occipital lobe nodal flexibility across task and time, decreased AD genetic risk, increased MDD genetic risk and less psychopathology, again adjusted for age and environmental stressors. The authors validate the latent network variables by assessing their overlap with genes for which SNPs have been associated with both depression risk and change in gene expression. Finally, the authors create simple path models in order to break down the relationships between genetic risk, latent variables, and what the authors term "resilience", finding distinct path for MDD and (non-APOE) AD genetic risk. All of these analyses are then re-run using a different brain parcellation. LV2 replicates, while a new LV1 emerges with similar non-imaging variables now being correlated with a different set of distributed network nodes.

The authors conclude from this work that they have identified imaging indices of resilience manifest during adolescent brain development, and that they have found further evidence linking MDD to AD. However, the analyses do not fully support the conclusions. The premise of this work - to examine links between MDD and AD and to try to define indices of resilience during development - is fascinating and will hopefully motivate future work in this direction. However, the impact of this work as currently presented may be limited.

*STUDY STRENGTHS*

There are two premises motivating this study that deserve praise for their innovation and creativity. First, in the introduction the authors present several fairly new papers showing shared environmental and risk factors between AD and MDD. This is a very interesting line of study that certainly deserves more attention. Second, the authors are interested in finding aspects of adolescent brain development that may be helpful to understanding resilience to genetic or environmental risk later in life. The AD resilience community is very interested in contributions of early life experiences and development, but there is still very little research in this domain. I hope the authors continue to conduct research in the direction of these pursuits.

The authors demonstrate great methodological and statistical rigor in some aspects of data preprocessing and analysis. This is particularly salient in null modeling and permutation, graph-based analysis, treatment of motion for functional imaging, using eQTLs to inform disease-relevant genes, statistical considerations in PLS and path modeling, processing of Allen Brain Atlas gene expression data, and validating certain study variables. The methodology of these steps displays great attention to detail and a mastery of certain data types.

The authors reproduce all analyses using a second parcellation and carefully report the results. This type of painstaking analysis is nonetheless important in the context of network-based graph analysis that is reliant on nodal information.

*STUDY LIMITATIONS*

1) The overarching limitation of this study is that the study variables, both independent and dependent, are abstracted to the point where interpretations are challenging. The authors' own interpretations are not sufficiently justified and are often taken at face value rather than supported by analysis. These are further combined into latent variables with weak conceptual foundation, which are then abstracted even further to other analyses with cortical molecular data maps. It is not clear that the conclusions drawn are convincingly supported by this highly abstracted analysis.

2) The other major limitation of this study is that several PLS models are run but, while appropriate null modeling is used to identify "significant" LVs, none of the LVs are cross-validated. Null modeling can help to protect against overfitting to noise in data, but it does not necessarily provide a good index of generalizability nor reliability. Without cross-validation, I question the reliability of the LVs irrespective of how they are interpreted. This is once again partially driven by the fact that changing the atlas resulted in a different imaging LV.

3) The study notes that participants were selected based on "having contributed high-quality data on all measures of interest". This is of course meritorious from a methodological perspective, but the authors should be aware that this may create an important selection bias (10.1007/s11682-022-00665-2, 10.1016/j.ynirp.2022.100085, 10.1016/j.neuroimage.2022.119296)

4) The premise of this paper was interesting, as described in the Strengths section above. However, what was missing was a clear theory or hypothesis as to how resilience to AD and MDD are related, and how the analyses in this study were conducted in order to support that hypothesis. The relevance of the results to AD was not clear; a clear biological model would help put the pieces together.

5) The selection of relevant features involved in LVs was inconsistent. At several points, the authors use an arbitrary threshold of bootstrap ratio (BSR) > 4, which they equated to a p-value. A p-value doesn't make sense in this context, since bootstrap samples are not independent samples. Instead, features should be selected based on 95% CIs that don't cross 0, which the authors do in some places but not in others.

Reviewer #2 (Public Review):

The authors' manuscript has several strengths. First, the authors consider multiple relevant levels of biology including genomics, transcriptomics, structural and functional neuroimaging, cognitive neuroscience, and psychological/environmental factors. Such an approach is often necessary to deconvolute the complexities of psychiatric phenotypes. The authors have taken careful steps to think about potential confounds (e.g., ancestry for PRS) and to try to define their phenotypes (e.g., psychological resilience and biological aging) as best as they can, given the data they have access to from the ABCD study. The manuscript is well written overall.

My main concerns relate to core assumptions and techniques that underlie the premise of the study. First, while there is comorbidity between AD and MDD, a causal relationship between the two (in either direction) is not established. Though MDD often predates AD, this is to be expected given MDD's high lifetime prevalence (15-20% of the general population) and typical age of onset before age 65. Because AD typically presents late in life (>65 years of age), MDD will, by definition, usually predate AD. While new onset, late life MDD is often the first presenting symptom of AD/Parkinson's disease and other neurodegenerative conditions, it is also not clear that this is the same disorder as idiopathic MDD.

To this point, two genetic tools can help us determine the biological relationship between MDD/AD, genetic correlation and Mendelian Randomization. Using the data from the MDD PRS used in this analysis, the Supplementary Table 3 from the Howard et al. 2019 paper (https://doi.org/10.1038/s41593-018-0326-7) reveals a genetic correlation of -0.041 between the two. This indicates essentially no strong relationship between the MDD/AD (perhaps even a slightly inverse relationship). Mendelian Randomization studies in addition to the Howard et al paper (https://doi.org/10.1212/WNL.0000000000010463) find no causal role for MDD towards AD and vice versa. Thus, their comorbidity is likely mediated by additional factors. Additionally, while stress contributes to AD pathophysiology, AD is strongly genetic and, given its late onset, it is unclear how genetic risk for AD would meaningfully impact the psychological resilience of a 9 to 10-year-old.

My second concern is regarding the statement "adolescents at genetic risk for AD/MDD" when describing the sample. Per Howard et al 2019 out-of-sample prediction testing, the MDD PRS used by the authors explains between 1.5-3.2% of the phenotypic variance in MDD when used on a sample such as ABCD. MDD PRS is in its infancy and cannot reliably be used to identify individuals at high risk of MDD given that even individuals in the top 10th percentile of MDD PRS have an odds ratio for depression of only ~2.4. We would expect 90 or so individuals in this cohort to fall into this group leaving significant concerns about statistical power and the potential for false positive discoveries. While the AD PRS is significantly further along compared to MDD because of AD's simpler genetic architecture, the same concerns apply as, outside of APOE, the AD PRS does not capture the majority of phenotypic variance in AD.

The authors state that they wish to examine the effects of perinatal adversity directly/indirectly on biological aging and then assess the potential effects of biological aging on resilience. The authors use of pubertal age as a measure of accelerated aging is understandable given the data available, though not ideal. There are well validated measures of biological age such as Horvath's epigenetic clock. While advanced pubertal age is technically a form of accelerated aging, the majority of pubertal age as a phenotype is not likely to be explained by perinatal adversity. Rather, a combination of unmeasured variables including genetic variation, dietary factors, environmental exposures (endocrine disrupting chemicals), and obesity that play a substantial role in determining pubertal age. Childhood stress has been shown to have relatively small effects on pubertal age (d = -0.1) (10.1037/bul0000270).

Lastly, the authors employ the use of an as of yet unpublished technique to map neurotransmitters density to structural data from neuroimaging studies. While this technique is certainly interesting, its face validity is not clear given that many of the receptor-disease associations reported in the original preprint do not line up with what we know about the biology of these disorders from strong human genetics data or current FDA approved treatments. Moreover, the authors mention "Excitation/Inhibition" imbalance but the technique used appears to only include glutamate data from one receptor type, mGluR5. This may not be an adequate measure of E/I imbalance, despite there being a statistically significant finding.

Measuring both transcriptional output from GWAS loci and gene expression correlates from MRI data is a noisy and challenging prospect. Indeed, recent research has shown poor correlation between gene expression and neurotransmitter receptor density.(https://doi.org/10.1016/j.neuroimage.2022.119671).

Thus, fundamental aspects of this manuscript including the use of MDD PRS to identify "at risk" individuals, the unclear link between AD and adolescent psychological resilience, the use of prepubertal age as a measure of biological age, and the limited conclusions that can be drawn from the gene expression and receptor density technique limits confidence in the results as presented.

Author Response:

We appreciate the Reviewers’ feedback. The manuscript was extensively revised and ultimately accepted for publication (Petrican and Fornito, 2023, Developmental Cognitive Neuroscience). The revisions address the Reviewers’ key concerns, including the theoretical basis of the link between MDD and AD, the rationale for studying this link in adolescence, clear references to significant genetic associations between the two, detailed assessment of CCA and PLS model generalisability and reliability, quantification of resilience, residualization of confounders, and corrections for multiple comparisons. We also note that the details concerning the receptor density maps we use in our analysis have now been published (Hansen et al., 2022, Nature Neuroscience; Markello et al., 2022, Nature Methods).

eLife assessment

The manuscript by Eyraud and colleagues examines the role of interactions between fibrocytes and CD8 cells as drivers of disease progression in COPD (chronic obstructive pulmonary disease). The findings that there exist bidirectional interactions between CD8 cells and fibrocytes are supported by solid evidence that combines histology of clinical lung samples, in vitro studies obtained from circulating blood fibrocytes and CD8 cells, as well as a computational model that predicts how bidirectional interactions could promote disease progression over the course of 20 years. The study, which is based on patient samples, thus provides fundamental insights on COPD progression.

Reviewer #1 (Public Review):

The present study combines quantitative histomorphometry, live cell imaging and tracking, functional analyses, and computational modeling to define potentially pathologic interactions between lung CD8 T cells and fibrocytes in human COPD. The authors use multiple technical approaches to establish the close proximity of CD8 T cells with fibrocytes in peri-bronchial tissue in COPD subjects that notably correlate with functional disease parameters (FEV1/FEV). Their follow-on studies identify specific chemokine pathways and inflammatory consequences of these interactions. Collectively, these seminal data acquired in a unified experimental context, provide support for pathogenic interactions between lung CD8 T cells and fibrocytes and now offer the consideration of mediators and pathways that may be amenable to therapeutic targeting. The strength of the study is the integration of the multi-modality approach, the quality of the quantitative data, and the creation of a tenable model for the interaction role in COPD of CD8 T cells and fibrocytes. While both have been previously implicated in COPD, this new study is more definitive by using this integrated approach.

Reviewer #2 (Public Review):

The authors use a series of elegant methods to describe the nature of the interrelationship among CD8+ T cells and fibrocytes in the airways of COPD patients. They find an increased presence of these interactions in COPD and show that CXCL8-CXCR2 interactions are crucial for this interaction, leading to increased CD8+ T cell proliferation.

Major strengths of the work include the detailed functional experiments used to describe the nature of the CD8+ T cell - fibrocyte interaction. Another key strength is the translational approach of the work, building on clinical data and connecting back to these same clinical data. The conclusions of the authors are supported by the data. The impact of the work is significant and key to our understanding of the interrelationship between inflammation and tissue remodeling in COPD. Understanding this relationship holds strong potential for the identification of new drug targets and for the identification of patients at risk.

The derivation of the CXCL8/CXCR2 dependency is based on a limited number of COPD patients, which could be strengthened. Also, the impact of the interrelationship between CD8 cells and the fibrocytes is not fully described.

Reviewer #3 (Public Review):

Eyraud and colleagues examine how fibrocytes and CD8 cells can interact with each other to promote COPD. The key findings include that CD8 cells and fibrocytes are found to exist in close proximity to each other in COPD lungs using histopathological analysis of patient samples. The authors leverage pre-existing transcriptomic data on CD8 cells to focus on chemokine release by CD8 cells as a potential pathogenic mechanism by which they could affect fibrocyte migration. In vitro studies using peripheral blood-derived CD8 cells and fibrocytes confirm increased fibrocyte migration in the presence of CD8 cells. as drivers of COPD progression. Conversely, in vitro studies show that fibrocytes exert a pro-proliferative effect on CD8 cells. The authors also use a computational model to assess how these interactions could promote the development of fibrocyte-CD8 clusters as COPD progresses over the course of 20 years.

The strengths of the study include:

1) The multi-faceted research approach that integrates histopathology from clinical COPD lung sections, in vitro co-culture studies, and computational modeling.

2) Applying computational modeling to determine how cell-cell interactions of migration and proliferation can result in distribution patterns within the lung that approximate what is found in actual clinical samples

3) Propose a feedback loop of CD8 cells and fibrocytes that could become a potential therapeutic target to interrupt a vicious cycle that promotes COPD.

However, there are also some weaknesses:

1) Specificity of the role of CD8 cells: While much of the focus is on the proximity of and interactions between CD8 cells and fibrocytes, it is not clear whether other cells similarly interact with fibrocytes. For example, CD4 cells, dendritic cells, or interstitial macrophages may similarly interact with fibrocytes as several of these also release chemokines. In the absence of a more comprehensive assessment, it becomes difficult to parse out how specific and relevant the fibrocyte-CD8 cell interactions are for COPD progression when compared to other putative interactions.

2) The transcriptomic analysis which in many ways sets the stage for the chemokine studies uses a pre-existing dataset of COPD and non-COPD samples with only n=2. The robustness of such a sample size is limited and the narrow focus on chemokines or adhesion receptors of CD8 cells in this limited sample size does not provide a more comprehensive analysis that would require larger samples sizes, studying the transcriptomes of other cell types and a broader analysis of which pathways are the most likely to be dysregulated in the cells that surround fibrocytes.

3) Specificity of the findings for COPD: The in vitro studies use circulating cells which are different from lung cells and this is appropriately acknowledged by the authors. However, it appears from the description that the cells are all from COPD patients. It is therefore not clear whether these interactions between fibrocytes and CD8 cells are unique to COPD, whether they also occur between control CD8 and fibrocytes, or only in cells obtained from patients with inflammatory/pulmonary diseases.

eLife assessment

This manuscript will be of interest to scientists who study cardiomyocyte homeostasis and contraction. It assesses the functional consequences of cardiomyocyte-specific knockout of Palladin, leading to the identification of a compensation mechanism when Palladin is deleted in embryogenesis, but not in adulthood. In addition, the authors identified new Palladin interactors, revealing a role for Palladin in the maintenance of intercalated disc structure.

Reviewer #1 (Public Review):

In this manuscript, Mastrototaro et al. perform a series of experiments in transgenic murine models assessing the function of Palladin (PALLD) in the heart. Global PALLD KOs are embryonic lethal, precluding the assessment of the roles of this protein in adulthood. To circumvent this limitation, the authors generated a floxed Palld allele and ablated it with two cardiomyocyte-specific Cres: the constitutively active Myh6-Cre and the tamoxifen-inducible aMHC-MerCreMer. Interestingly, ablation with the constitutive Cre (cKO) did not produce any overt phenotype, but ablation in adulthood (cKOi) resulted in compromised cardiac function. These observations suggest a compensation mechanism that takes place when cardiomyocytes develop in the complete absence of this protein but not when cardiomyocytes develop in a wild-type background and are deprived of this protein after achieving full maturation. These experiments were complemented with yeast two-hybrid techniques to identify novel partners that bind to a region of PALLD for each no interactants had been previously identified. Experiments in human samples revealed an upregulation of PALLD transcripts in the hearts of patients.

This manuscript adds important information to our understanding of sarcomeric proteins. Data are generally of good quality and well presented in figures. The numbers of animals in echocardiographic studies are also adequate for proper conclusions. Authors achieve most of their goals, including the identification of novel partners of PALLD and the identification of a requirement for PALLD in cardiomyocytes for normal heart function. However, given that all experiments performed in this study were focused on the loss-of-function of PALLD, it is not clear what is the relevance of the PALLD upregulation observed in human patients. Authors should clearly state this limitation in their results.

Considering that authors have observed evidence for nuclear PALLD, which could hint at potential major gene expression changes when this protein is ablated, it would be interesting to perform an unbiased assessment of transcriptional alterations (RNA-seq) in cardiomyocytes isolated from control and cKOi hearts. In addition, to test if the compensation observed in the embryonic cKO involves mechanisms of transcriptional adaptation, it would be interesting to compare RNA-seq results from cKOi and cKO (genes encoding proteins similar to PALLD that are upregulated in cKO but not cKOi cardiomyocytes would be very strong candidates). However, these transcriptomic data are not essential to support current findings and can be performed in follow-up studies.

Reviewer #2 (Public Review):

The role of the actin-binding protein palladin (PALLD) in cardiomyocyte development, growth, and function has not been defined. In order to address this question, the authors first identified that CARP and FHOD1 interact with PALLD in cardiomyocytes. They then performed cardiomyocyte selective deletion of PALLD in embryonic and adult mice and discovered that deletion of PALLD in adult mice leads to dilated cardiomyopathy (DCM) and intercalated disc ultrastructural changes. In contrast, embryonic deletion of cardiomyocyte PALLD did not cause a cardiomyopathy phenotype in neonatal or adult animals.

1. The divergent cardiac phenotypes of the embryonic deletion of cardiomyocyte PALLD (no cardiomyopathy) versus the adult deletion of cardiomyocyte PALLD (dilated cardiomyopathy(DCM)) is an interesting result. The authors speculate that embryonic deletion of PALLD induces compensatory pathways that prevent the development of adult cardiomyopathy in these mice. However, these compensatory pathways remain unexplored.<br /> 2. The authors discovered that mice with adult cardiomyocyte deletion of PALLD had significant changes in the cardiomyocyte intercalated disc (ICD) ultrastructure. They suggest these changes in ICD ultrastructure contribute to DCM formation in the adult PALLD deletion mice (line 270). However, it remains unclear if these changes in ICD ultrastructure are specific to mice with adult deletion of PALLD.<br /> 3. The different transgenic Cre mouse lines may be an alternative explanation for the divergent cardiac phenotypes in the embryonic versus adult deletion of cardiomyocyte PALLD. The tamoxifen dose administered for the inducible Myh6:MerCreMer mice was 30mg/kg/day x 5 which has been reported to lead to the induction of cardiomyocyte DNA damage response pathways (Dis Model Mech. 2013 Nov; 6(6): 1459-1469, J Cardiovasc Aging 2022;2:8). The electron micrograph experiments in Figure 5 did not include a group of Myh6:MerCreMer mice administered tamoxifen. The authors only compared PALLD fl/fl and Myh6:MerCreMer/PALLD fl/fl mice.<br /> 4. The apoptosis assessment was performed 24 weeks after administration of tamoxifen to the Myh6:MerCreMer/PALLD fl/fl mice. However, cardiomyocyte apoptosis may have occurred much earlier if it was secondary to Myh6:MerCreMer tamoxifen-induced cardiotoxicity (or related to PALLD deletion).<br /> 5. The animal studies in Fig 3D show a DCM phenotype in mice with adult deletion of cardiomyocyte 200kDa PALLD which suggests a potential loss of function mechanism for DCM formation. However, the authors then report in Fig 6 that human DCM heart tissue samples have a ~2.5fold increase in mRNA expression of the 200kDa PALLD transcript which would suggest a possible gain of function mechanism for DCM formation. How do the authors reconcile these divergent results with regard to palladin's role in cardiomyocyte homeostasis and cardiomyopathy formation?

Reviewer #3 (Public Review):

This study shows for the first time changes in palladin expression under disease conditions and mRNA alterations in human samples. The authors have identified novel binding partners for the protein as a first step toward determining how palladin mediates its effects in the heart. Finally, through the use of mouse models to decrease palladin expression they identify a crucial role for palladin in the cardiac response to pathological stress, with some interesting findings that show the effects of palladin depend on when the protein is altered.

The novel findings of the study are supported by the data presented, but there are several instances where clarification is needed of the conclusions drawn from the data reach beyond what is presented in the Results section.

The focus on only male mice is a significant limitation of the paper, as it is well known that there are profound sex differences in the response to pathological stressors. While the ability to obtain sufficient heart samples from male and female patients may be a reasonable justification for focusing on males, the preclinical mouse model should have been examined in both sexes and the limitation of this choice should be clearly noted in the paper.

The changes in myopalladin expression were not measured in the disease model (TAC), which limits the ability to determine if myopalladin was altered in the disease state. This addition would strengthen the study.

Finally, the myofilament data are presented as evidence that changes in the contractile apparatus are contributors to the observed contractile dysfunction at the organ level. But these studies were conducted using levels of calcium that far exceed what is seen in vivo and, therefore, do not support the conclusion drawn.

Author Response

Reviewer #1 (Public Review):

By performing immunopeptidomics of macrophages infected with virulent M. tuberculosis, the authors were able to appropriately address whether Mtb proteins are able to enter the MHC-I antigen processing pathway. Their interrogation provides convincing evidence that substrates of Mtb's type VII secretion systems (T7SS) are a significant contributor to the Mtb-derived peptides presented on MHC-I. Compelling data are provided to demonstrate that ESX-1 activity is required for the MHC-1 presentation of these newly identified peptides.

Strength

Employing a virulent strain of Mtb for infection of human monocyte-derived macrophages to identify Mtb proteins that access the MHC-I antigen processing pathways and the associated mechanisms.

Weakness

The immunogenicity of at least some of the identified peptides should have been evaluated.

Although obtaining T cells from a cohort of TB-exposed patients was not within the scope of this study, we are also eager to assess the immunogenicity of the epitopes we identified in future work. In addition to the references we made in our initial submission to prior work showing that many of the proteins from which the epitopes we identified derive elicit T cell responses in Mtb-exposed humans, we’ve added references to prior studies that show that a few of the specific epitopes we identified are immunogenic, providing at least a preliminary indication that MHC-I peptides identified by MS can be immunogenic T cell epitopes (lines 420-423): “Individual peptides we identified by MS have also been previously shown to be recognized by human T cells, including EsxJ24-34 (Grotzke et al., 2010; Lewinsohn et al., 2013) and EsxA28-36 (Tully et al., 2005), providing a proof of concept that particular epitopes identified by MS can be immunogenic.”

Author Response

Reviewer #1 (Public Review):

The authors have performed scATACseq on multiple timepoints during mouse male gonadogenesis and germ cell maturation during the fetal to neonatal transition (E18.5 and postnatal days 1,2,5). Clustering of thousands of cells revealed striking cellular diversity and led to the identification of cell populations that were not known before. This work may have far reaching implications, but additional validation is needed.

We would like to start by expressing our appreciation to the reviewer’s valuable comments and feedback on our manuscript. We would also like to express our sincere apologies for the delay in submitting our revised manuscript. The COVID-19 pandemic has had a significant impact on academic research and publication, and we encountered several challenges during this time. Both co-first authors of this manuscript were promoted to new roles, which required additional time and effort to transition into these new positions. Furthermore, we experienced significant delays in obtaining the necessary research materials due to longer shipment times for antibodies and other reagents during the pandemic, which further contributed to the delay. We understand that our delay may have caused inconvenience but we want to assure you that we have carefully addressed all of the reviewer comments and we deeply appreciate your understanding and patience during these challenging times.

The identification of novel transitional spermatogonia population in Figure 4D is intriguing. Independent validation by flow cytometry or in testis cross section to better allow the colocalization of nr5a1 and Oct4 and other germ cell markers would be important. Additional validation is needed to ensure that populations 1 and 2 in figure 4d are not to doublets. Providing violin plots for both soma and germ cell markers will be helpful. Is SF1 the only gene expressed in this unique germ cell population or are many other somatic markers expressed in the population. Do these cells express well recognized SPG markers like Oct4+ , PLZF, GFRA?

We have performed immunostaining of NR5A1 in testicular sections and showed that NR5A1+ germ cells (TRA98+ cells) exist in P5.5 testis (Figure 4D). We appreciate the reviewer's comment and understand the concern regarding potential doublets in figure 4d. We examined the expression of various markers in both scATAC-seq (gene score) and scRNA-seq (mRNA) datasets and provided violin plots. Sertoli cell markers and germ cell markers showed variable levels in unknown 1 and 2 populations while the Leydig cell marker did not (Supplementary figure S6D).

As additional evidence supporting our finding that a subset of somatic markers are expressed in the unique germ cell population we identified, we reference a study where cells in the spermatogonial signature 3 cluster showed high levels of mRNAs characteristic of Sertoli cells, including Nr5a1, Sox9, and Wt1 (PMID: 25568304). This indicates that cells with germ cell identity can express somatic cell genes, which is consistent with our findings. Additionally, another study reported the expression of the somatic cell marker WT1 in some germ cells through immunostaining (Figure 3B, PMID: 34815802). We have included this information in the revised manuscript to further support our conclusion (line 301). In addition, as we have isolated nuclei rather than whole cells, it is less likely that germ cells and sertoli cells are sticking together during single cell capture. We hope that the additional evidence and analysis provided will help to ease the reviewer's concerns and further support the conclusions drawn from our data.

The IF validation in 5F is not as convincing that these cells are potentially Sertoli stem cells. IF in cross-sections will be easier to interpret- especially when co-stained with several germ, somatic, or novel markers of that population. purification of these cells and further characterization is needed. A hallmark of fetal Sertoli cells is to mediate the migration of endothelial cells to the seminiferous tubules during testicular cord formation. Is it possible to purify these cells to determine whether they have functional Sertoli cells properties in vitro using human umbilical vein endothelial cells (HUVECs). Do these cells have immune privilege properties - can they suppress proliferation of Jurkat E6 cells.

Following the reviewer’s suggestions, we conducted further immunostaining of MBD3 and AMH in Sertoli cells (Figure 5F). The observed staining results not only confirm the properties of MBD3+ cells (MBD3-high/AMH-high) but also highlight the heterogeneity of Sertoli cells, as evidenced by the presence of various expression patterns such as MBD3-low/AMH-high (cluster SC3 in Figure 5A) and MBD3-low/AMH-low (cluster SC2/4/5/6 in Figure 5A). This further emphasizes the complexity and diversity within the Sertoli cell population.

However, we understand that it is premature to definitively conclude that MBD3-high cells are Sertoli stem cells without functional studies. We appreciate the suggestion of using additional functional assays such as in vitro co-culture with HUVECs and immune privilege assays to further characterize the potential Sertoli stem cell population. These are valuable experiments to consider for future research in order to gain a deeper understanding of the properties and functions of these cells. To more accurately reflect the scope of our study and avoid potential misinterpretation, we have revised the language to reflect that we have identified subpopulations of Sertoli cells with unique characteristics, rather than using the term "stem cell". We hope that our revised data adequately addresses the reviewer’s concerns.

Reviewer #2 (Public Review):

Liao et at performed single cell ATAC sequencing to reveal chromatin status in various cell types in the perinatal mouse testes. The chromatin status was then used to define cell types and identify potential transcription factors that control the progress of differentiation. This work could provide new insights into how various cell types acquire their fate in early testis development and establish a genomic framework that can be used to correlate with human data for infertility. The strength lies on the novelty of single cell analyses. The weaknesses include a lack of statistical power, the uncertainty on the correlation between chromatin status, gene expression, and transcription factor activity, and insufficient information and confirmation on some of the experiments and results.

We would like to start by expressing our appreciation to the reviewer’s valuable comments and feedback on our manuscript. We would also like to express our sincere apologies for the delay in submitting our revised manuscript. The COVID-19 pandemic has had a significant impact on academic research and publication, and we encountered several challenges during this time. Both co-first authors of this manuscript were promoted to new roles, which required additional time and effort to transition into these new positions. Furthermore, we experienced significant delays in obtaining the necessary research materials due to longer shipment times for antibodies and other reagents during the pandemic, which further contributed to the delay. We understand that our delay may have caused inconvenience but we want to assure you that we have carefully addressed all of the reviewer comments and we deeply appreciate your understanding and patience during these challenging times.

Author Response

Reviewer #1 (Public Review):

The manuscript by Lujan and colleagues describes a series of cellular phenotypes associated with the depletion of TANGO2, a poorly characterized gene product but relevant to neurological and muscular disorders. The authors report that TANGO2 associates with membrane-bound organelles, mainly mitochondria, impacting in lipid metabolism and the accumulation of reactive-oxygen species. Based on these observations the authors speculate that TANGO2 function in Acyl-CoA metabolism.

The observations are generally convincing and most of the conclusions appear logical. While the function of TANGO2 remains unclear, the finding that it interferes with lipid metabolism is novel and important. This observation was not developed to a great extent and based on the data presented, the link between TANGO2 and acyl-CoA, as proposed by the authors, appears rather speculative.

We thank you for your advice and now include additional data that lends support to the role of TANGO2 in lipid metabolism. We have changed the title accordingly.

1) The data with overexpressed TANGO2 looks convincing but I wonder if the authors analyzed the localization of endogenous TANGO2 by immunofluorescence using the antibody described in Figure S2. The idea that TANGO2 localizes to membrane contact sites between mitochondria and the ER and LDs would also be strengthened by experiments including multiple organelle markers.

We agree that most of the data on TANGO2 localization are based on the overexpression of the protein. As suggested by the reviewer and despite the lack of commercial antibodies for immunofluorescence-based evaluation, see the following chart, we tested the commercial antibody described in Figure 2 on HepG2 and U2OS cells. Moreover, we used Förster resonance energy transfer (FRET) technology to analyze the proximity of TANGO2 and Tom20, a specific outer mitochondrial membrane protein. In addition, we visualized cells expressing tagged TANGO2 and tagged VAP-B, an integral ER protein in the mitochondria-associated membranes (doi:10.1093/hmg/ddr559) or tagged TANGO2 and tagged GPAT4-Hairpin, an integral LD protein (doi:10.1016/j.devcel.2013.01.013). These data strengthen our proposal and are presented in the revised manuscript.

As suggested by the reviewer, we have also visualized two additional cell lines (HepG2 and U2OS) with the anti-TANGO2( from Novus Biologicals) that have been used for western blot (see chart above). As shown in the following figure, the commercial antibody shows a lot of staining in addition to mitochondria, especially in U2OS cells, where it also appears to label the nucleus.

2) The changes in LD size in TANGO2-depleted cells are very interesting and consistent with the role of TANGO2 in lipid metabolism. From the lipidomics analysis, it seems that the relative levels of the main neutral lipids in TANGO2-depleted cells remain unaltered (TAG) or even decrease (CE). Therefore, it would be interesting to explore further the increase in LD size for example analyze/display the absolute levels of neutral lipids in the various conditions.

We agree with the reviewer and now present the absolute levels of lipids of interest in the various conditions of the lipidomics analyses (Figure S 3).

3) Most of the lipidomics changes in TANGO2-depleted cells are observed in lipid species present in very low amounts while the relative abundance of major phospholipids (PC, PE PI) remains mostly unchanged. It would be good to also display the absolute levels of the various lipids analyzed. This is an important point to clarify as it would be unlikely that these major phospholipids are unaffected by an overall defect in Acyl-CoA metabolism, as proposed by the authors.

As stated above, we have now included the absolute levels of lipids of interest in the various conditions of the lipidomics analyses (Figure S 3).

eLife assessment

This important manuscript describes a series of cellular phenotypes associated with the depletion of TANGO2, a poorly characterized gene product but relevant to neurological and muscular disorders. The authors present solid data indicating that TANGO2 associates with membrane-bound organelles, mainly mitochondria, impacting lipid metabolism and the accumulation of reactive-oxygen species. A few additional experiments would help to understand the link between the lipid changes reported and the cellular phenotype.

Reviewer #1 (Public Review):

The manuscript by Lujan and colleagues describes a series of cellular phenotypes associated with the depletion of TANGO2, a poorly characterized gene product but relevant to neurological and muscular disorders. The authors report that TANGO2 associates with membrane-bound organelles, mainly mitochondria, impacting in lipid metabolism and the accumulation of reactive-oxygen species. Based on these observations the authors speculate that TANGO2 function in Acyl-CoA metabolism.

The observations are generally convincing and most of the conclusions appear logical. While the function of TANGO2 remains unclear, the finding that it interferes with lipid metabolism is novel and important. This observation was not developed to a great extent and based on the data presented, the link between TANGO2 and acyl-CoA, as proposed by the authors, appears rather speculative.

1. The data with overexpressed TANGO2 looks convincing but I wonder if the authors analyzed the localization of endogenous TANGO2 by immunofluorescence using the antibody described in Figure S2. The idea that TANGO2 localizes to membrane contact sites between mitochondria and the ER and LDs would also be strengthened by experiments including multiple organelle markers.

2. The changes in LD size in TANGO2-depleted cells are very interesting and consistent with the role of TANGO2 in lipid metabolism. From the lipidomics analysis, it seems that the relative levels of the main neutral lipids in TANGO2-depleted cells remain unaltered (TAG) or even decrease (CE). Therefore, it would be interesting to explore further the increase in LD size for example analyze/display the absolute levels of neutral lipids in the various conditions.

3. Most of the lipidomics changes in TANGO2-depleted cells are observed in lipid species present in very low amounts while the relative abundance of major phospholipids (PC, PE PI) remains mostly unchanged. It would be good to also display the absolute levels of the various lipids analyzed. This is an important point to clarify as it would be unlikely that these major phospholipids are unaffected by an overall defect in Acyl-CoA metabolism, as proposed by the authors.

Reviewer #2 (Public Review):

This is an interesting study that seeks to deorphanize Tango2, a protein linked to muscle dysfunction but with no known function. It reveals that Tango2 primarily co-localizes with mitochondria, and its loss impacts mitochondrial homeostasis. Tango2-depleted cells also accumulate LDs. Lipidomic analysis indicated a partial depletion of diacyl lipids including PA in Tango2-depleted cells, and an accumulation of lyso-lipids such as LPA. The proposed model suggests that Tango2 plays a role in lipid metabolism, potentially in acyl-CoA trafficking and or delivery to lyso-lipids to generate diacyl-lipids for mitochondrial homeostasis, which is defective in tango2-deficient diseases like rhabdomyslosis. In general, this is a well-conducted and potentially important study. The first section which deals with Tango2 localization and profiling of cellular changes in Tango2-depleted cells is well conducted. However, the latter half which seeks to understand how Tango2 loss impacts lipid homeostasis is more preliminary. Lyso-lipids like LPA are definitely altered with tango2 loss, but additional work is necessary to understand whether this is due to increased lyso-lipid synthesis, a block in their acylation, or some combination of factors. Delineating these possibilities will significantly enhance this study.

Author Response

Reviewer #1 (Public Review):

This is a well-performed and carefully executed and quantified study. There is however a point that needs clarification:

We thank the reviewer for these motivating comments and appreciate the careful reflection of our work.

The authors state that acute regeneration occurs between 5-10dpt. However, the graphs in Fig 1D, F, and 2F indicate that most PC generation occurs from 20-30 days. What happens in this period? Does proliferation increase? Can the authors perform BrdU incorporation between 6 days and 1 month?

The reviewer is right that PC regeneration seems to be more intense from 20-30 days. Yet during this stage also wildtype larvae add a number of PCs to their PC population pool, thus we would consider only PCs being added in surplus to the number of regularly added PCs as a contribution to regeneration, and here we see in quantified samples the largest increase of regenerating PCs during 8-10 days post-treatment with 20,9 and 23,2 additional (surplus) PCs on average respectively.

This question also relates to the first comment of reviewer 3 who asked for a combined BrdU and EdU labeling approach to address the cell cycle length of PC progenitors. We have therefore performed this experiment with the first pulse of BrdU-labeling at 18 days after PC-ablation to include the request stated here for a BrdU-labeling at later stages of regeneration. Again, no significant difference between BrdU-positive PC progenitors was found at this later stage of PC regeneration, but a small number of PC progenitors underwent additional rounds of proliferation compared to controls, which provide an explanation of how the entire PC population is replenished and why complete PC regeneration requires several months. Please see also our answer to question 1 of reviewer 3. These new findings are now presented in an additional Supplementary Figure (Figure 1-figure supplement 3) and have been added to the last paragraph of the section reporting the findings presented in Figure 1.

Related to this, as the authors indicate in lines 129-131, the regeneration of new PCs overlaps with normal development. Are other neuronal cell types generated in appropriate numbers?

This is an interesting question raised by the reviewer. But it is very general relating to all cerebellar neuronal cell types, which is out of our possibilities to address. We considered eurydendroid cells as the most likely cell population, which could be affected in their numbers by PC ablation and regeneration, because eurydendroid cells share the same ptf1a+-expressing progenitor cells with Purkinje cells. Eurydendroid cells – the zebrafish equivalents to deep nuclei neurons in mammals – can be identified by their expression of olig2. We have therefore quantified the number of eurydendroid cells in the cerebellum of double transgenic PC-ATTAC/olig2:GFP larvae 15 days after PC ablation. No significant difference in olig2:GFP positive cells could be observed between PC-regenerating and control zebrafish suggesting that eurydendroid cells are not affected in their quantity and are generated in appropriate numbers in PC regenerating larvae. These findings are presented in a new Supplementary Figure (Figure 3-figure supplement 3) and are described together with findings about eurydendroid cells presented in the main Figure 3.

eLife assessment

The present manuscript addresses the controversial issue of the regeneration potential of cerebellar Purkinje cells in zebrafish and their integration into functional circuits. The authors use interesting genetic models to induce Purkinje cell-specific ablation to demonstrate regeneration of Purkinje cells can occur until adulthood and is accomplished by ptf1a+ progenitors. They further show that regenerated neurons reestablish electrophysiological properties and support appropriate behavior. These are important results that may help understand why mammalian neurons do not have similar properties and fail to regenerate. The conclusions on the source of regenerated neurons will however need additional experimental support.

Reviewer #1 (Public Review):

According to current knowledge, zebrafish neurons maintain the capacity of regenerating with the exception of adult cerebellar Purkinje cells (PC), which are thought to have lost this property. Regeneration instead occurs at larval stages but whether newly generated PC form fully functional circuits is still unclear. This elegant and well-performed study takes advantage of a transgenic zebrafish line that enables inducing apoptosis under a tamoxifen-inducible system and at the same time visualizes PCs morphology through a membrane tagged RFP. Using this line (and other lines that tag radial glial and ventricular progenitors) in combination with morphological and functional analysis, the authors show that ventricular progenitors retain the lifelong ability to regenerate PCs. At larval stages, the newly regenerated PCs form fully functional circuits that lead to normal behavior. In adults, PC regeneration is less efficient (and PCs are also less prone to undergo apoptosis) but sufficient to support exploratory behavior. This study resolves the controversial issue of whether adult PC regeneration is possible and demonstrates that newly formed PCs at larval and adult stages can form functional circuits that support normal behavior.

This is a well-performed and carefully executed and quantified study. There is however a point that needs clarification:

The authors state that acute regeneration occurs between 5-10dpt. However, the graphs in Fig 1D, F, and 2F indicate that most PC generation occurs from 20-30 days. What happens in this period? Does proliferation increase? Can the authors perform BrdU incorporation between 6 days and 1 month? Related to this, as the authors indicate in lines 129-131, the regeneration of new PCs overlaps with normal development. Are other neuronal cell types generated in appropriate numbers?

Reviewer #2 (Public Review):

In this paper, Pose-Méndez and colleagues have investigated the lifelong ability of zebrafish for functional Purkinje cell regeneration after selective ablation. Previous studies have determined that the adult zebrafish cerebellum lacks the capacity to regenerate Purkinje cells after traumatic injury. The authors use an elegant approach to determine whether selective ablation of Purkinje cells, a scenario closer to neurodegenerative disease, would allow for regeneration. The overall message is, that Purkinje cell regeneration is accomplished at every age after targeted ablation. The authors find in a series of well-executed functional and behavioral experiments that selective loss of Purkinje cells leads to a change in neuronal circuit activity and behaviors. During the regeneration process and interestingly before the full recovery of Purkinje cell numbers compared to controls neuronal activity as well as behaviors are recovered.

Reviewer #3 (Public Review):

In "Lifelong regeneration of cerebellar Purkinje neurons after induced cell ablation in zebrafish" by Pose-Mendez and colleagues, the authors followed the regenerative properties that Purkinje cells have in larvae and adult Zebrafish. These properties common in teleostean and other animals are rare in mammals and, therefore, their study is of great interest to the neurodevelopmental community.

In this work, the authors use an already established animal model (PC-ATTACTM) to selectively ablate Purkinje cells in the larvae and adult Zebrafish, in a temporal control manner, that is by administering 4-OHT at defined stages. In doing so, the authors show that a full recovery of an ablated Purkinje cell population can be achieved when the ablation is induced in the larval stage, but this recovery is more modest when the ablation is induced in the adult stage, albeit very significant. The authors also show that regenerated Purkinje cells quickly elaborate their native electrical properties and integrate into functional circuits, which allow for the recuperation of motor behaviors produced by the loss of ablated Purkinje cells.

Overall, the work by Pose-Mendez and colleagues contributes to our understanding of neuronal regeneration in non-mammals. Technically, this study is well conducted and the provided data support most of the conclusions made by the authors.

Author Response

Reviewer #1 (Public Review):

In this manuscript, Gonzalez et al investigated the dynamics of dopamine signals, measured with optophysiological methods in the lateral shell of the nucleus accumbens (LNAc), in response to different types of visual stimuli. Contrary to most current theories of dopamine signaling, the authors found that LNAc dopamine transients tracked sensory transitions in visual stimulation rather than any immediately apparent motivational variable. This unorthodox finding is of potential interest to the field, as it suggests that dopamine in this particular area of the striatum supports a very different, albeit unclear behavioral function than what has been previously attributed to this neuromodulator. Many of the approaches used by the authors were very elegant, like the careful selection of visual stimuli parameters and the use of Gnat1/2 KO mice to demonstrate that the dopamine responses were directly dependent on the visual stimulation of rods and cones. That said, the authors did not discuss how their findings relate to much previously published work, many of which offer potential alternative explanations for their results. It is also not clear from the manuscript text which mice were used for which experiments, and how testing history might affect the results.

We would like to thank the reviewer for their careful review of our manuscript. In our revised manuscript, we reworked our Materials and Methods to better detail the experimental workflow, which is highlighted in yellow. We have also added new data in stimulus-naïve animals to better examine the effect of exposure history on the dopaminergic response to light. To provide validation of our recording sites, we have included a new figure (Figure 1-Figure Supplement 1) that contains a representative histological image showing the location of the optical fiber/virus expression, as well as a schematic demonstrating optical fiber placements. Finally, the reviewer’s point about discussing the current results in the context of previous literature is well taken, and we have added three new paragraphs of text in the Discussion to highlight these findings.

Reviewer #2 (Public Review):

In this elegant work, the authors investigated dopamine release (measured by dLight sensor fiber photometry) in the nucleus accumbens shell, in response to salient luminance change. They show that abrupt visual stimuli - including stimuli not detectable by the human eye - can evoke robust dopamine release in the accumbens shell.

The fact that dopamine signals can be evoked by salient sensory stimuli is not itself novel, but the paper manages to make several important and new findings:

1) The authors show that the dopamine signal is not related to the level of threat evoked by the visual stimuli.

2) They provide important detail about the stimuli parameters relevant to dopamine release. For instance, they show that the rate of luminance change (or abruptness) is a key factor in evoking dopamine responses.

3) They show that robust dopamine responses can be evoked by visual stimuli of low intensity, including stimuli not perceptible by the human eye.

4) They show that these dopamine responses can be evoked by all wavelengths in the visible spectrum (with some higher sensitivity at certain wavelengths).

5) Finally, by recording dopamine responses in two knockout mice strains, the authors show that the light-evoked dopamine release critically relies on rod and cone photoreceptors, but not melanopsin phototransduction.

These results add to a series of recent findings showing that dopamine signals are not restricted to the encoding of reward prediction error, but instead contribute to signaling environmental changes more broadly. The study has been skillfully executed, the results are clear and appropriately analyzed, and the manuscript is very well written. Although the work did not include control mice lacking the dLight sensor, the fact that light-evoked dopamine responses were not observed in mice lacking cone + rod phototransduction is strong evidence that the fiberphotometry signals were not due to direct light artifacts.

We would like to thank the reviewer for taking their valuable time over the holidays to review our manuscript. We appreciate their feedback and have responded to their concerns below.

Comment/concerns are minor:

1) The authors show that the dopamine response evoked by a brief visual stimulus is drastically reduced when the visual stimulus is repeated in rapid succession (stimulus train). The authors interpret this as evidence for the HABITUATION of this light-evoked dopamine release. An alternative explanation is that it is the prediction of the stimulus that is responsible for canceling the dopamine response (i.e. sensory prediction error). The authors should discuss this alternative explanation for this finding.

This is a valid point, which we have now addressed in the revised Discussion section (Paragraph 3).

2) Although the study largely focuses on dopamine responses to visual stimuli, the results are largely consistent with previous studies showing dopamine signals encoding value-neutral changes in sensory inputs (i.e. sensory prediction errors) in different modalities (taste or odors; cf. Takahashi et al., 2017, Neuron; Howard & Kahnt, 2018, Nat. Comm.). The authors might want to cite those papers (note that I am not affiliated with those papers).

This is similar to the point brought up by Reviewer 1, namely that several key pieces of literature were not discussed in the original manuscript. We agree that this was an oversight and hope we have remedied it in the revised Discussion, as detailed in the response to Reviewer 1. We have included both citations in the new text.

eLife assessment

In this manuscript, Gonzalez et al investigated the dynamics of dopamine signals in the lateral shell of the nucleus accumbens (LNAc) in response to different types of carefully defined visual stimuli. Contrary to reigning theories of dopamine signaling, the authors presented convincing evidence that LNAcc dopamine transients tracked visual sensory transitions rather than any immediately apparent motivational variable. These important findings based on compelling evidence point to a potentially new role for dopamine signaling in the ventral striatum.

Reviewer #1 (Public Review):

In this manuscript, Gonzalez et al investigated the dynamics of dopamine signals, measured with optophysiological methods in the lateral shell of the nucleus accumbens (LNAc), in response to different types of visual stimuli. Contrary to most current theories of dopamine signaling, the authors found that LNAcc dopamine transients tracked sensory transitions in visual stimulation rather than any immediately apparent motivational variable. This unorthodox finding is of potential interest to the field, as it suggests that dopamine in this particular area of the striatum supports a very different, albeit unclear behavioral function than what has been previously attributed to this neuromodulator. Many of the approaches used by the authors were very elegant, like the careful selection of visual stimuli parameters and the use of Gnat1/2 KO mice to demonstrate that the dopamine responses were directly dependent on the visual stimulation of rods and cones. That said, the authors did not discuss how their findings relate to much previously published work, many of which offer potential alternative explanations for their results. It is also not clear from the manuscript text which mice were used for which experiments, and how testing history might affect the results.

Reviewer #2 (Public Review):

In this elegant work,  the authors investigated dopamine release (measured by dLight sensor fiber photometry) in the nucleus accumbens shell, in response to salient luminance change. They show that abrupt visual stimuli - including stimuli not detectable by the human eye - can evoke robust dopamine release in the accumbens shell.

The fact that dopamine signals can be evoked by salient sensory stimuli is not itself novel, but the paper manages to make several important and new findings:

1. The authors show that the dopamine signal is not related to the level of threat evoked by the visual stimuli. <br /> 2. They provide important detail about the stimuli parameters relevant to dopamine release. For instance, they show that the rate of luminance change (or abruptness) is a key factor in evoking dopamine responses.<br /> 3. They show that robust dopamine responses can be evoked by visual stimuli of low intensity,  including stimuli not perceptible by the human eye.<br /> 4. They show that these dopamine responses can be evoked by all wavelengths in the visible spectrum (with some higher sensitivity at certain wavelengths).<br /> 5. Finally, by recording dopamine responses in two knockout mice strains, the authors show that the light-evoked dopamine release critically relies on rod and cone photoreceptors, but not melanopsin phototransduction. 

These results add to a series of recent findings showing that dopamine signals are not restricted to the encoding of reward prediction error, but instead contribute to signaling environmental changes more broadly. The study has been skillfully executed, the results are clear and appropriately analyzed, and the manuscript is very well written. Although the work did not include control mice lacking the dLight sensor, the fact that light-evoked dopamine responses were not observed in mice lacking cone + rod phototransduction is strong evidence that the fiberphotometry signals were not due to direct light artifacts.

Comment/concerns are minor:

1. The authors show that the dopamine response evoked by a brief visual stimulus is drastically reduced when the visual stimulus is repeated in rapid succession (stimulus train). The authors interpret this as evidence for the HABITUATION of this light-evoked dopamine release. An alternative explanation is that it is the prediction of the stimulus that is responsible for canceling the dopamine response (i.e. sensory prediction error). The authors should discuss this alternative explanation for this finding.

2. Although the study largely focuses on dopamine responses to visual stimuli, the results are largely consistent with previous studies showing dopamine signals encoding value-neutral changes in sensory inputs (i.e. sensory prediction errors) in different modalities (taste or odors; cf. Takahashi et al., 2017, Neuron; Howard & Kahnt, 2018, Nat. Comm.). The authors might want to cite those papers (note that I am not affiliated with those papers).

Reviewer #3 (Public Review):<br /> <br /> Gonzalez and colleagues investigate dopamine signals in response to visual stimuli. This work builds on the longstanding notion that dopamine neurons respond to unexpected sensory stimuli, including visual cues. Using fiber photometry measurements of a fluorescent dopamine sensor, they find that in the lateral ventral striatum, dopamine signals reliably report salient transitions in illuminance. Dopamine signals scale with light intensity and the speed of illuminance changes. They further find that the frequency of illuminance transitions, rather than the number, dictates the extent that dopamine signals habituate. In a number of studies, they characterize dopamine signals to light of different wavelengths, durations, and intensities. These results shed new "light" on the role of dopamine in signaling salience, independent of reward or threat learning. This work is elegantly done and compelling. While the results are potentially specific to this region of the striatum, rather than a broad dopaminergic profile of visual stimulus encoding, this work offers valuable insight into dopamine function, as well as a practical guide and considerations for the implementation of visual stimuli in behavioral tasks that assay dopamine systems.

Author Response

Reviewer #1 (Public Review):

This manuscript describes efforts to understand how independence from ribonucleotide reduction might evolve in obligate intracellular bacterial pathogens using E. coli as a model for this process. The authors successfully deleted the three ribonucleotide reductase (RNR) operons present in E. coli and showed that growth of this knockout strain can be achieved with deoxyribonucleotide supplementation. They also performed evolutionary experiments and analysis of cell growth and morphology under conditions of low nucleotide availability. In this work, they established that certain genes are consistently mutated to compensate for the loss of RNR activity and the low availability of deoxynucleotides. Comparison to genomes of intracellular pathogens that lack RNR genes shows that these patterns are largely conserved.

While the experimental results support the conclusions of the study, the authors do report changes in cell morphology upon the growth of the RNR knockout strains with low concentrations of nucleotides. It would be ideal to note this complication earlier in the manuscript. And to clarify how the possibility of cell elongation might affect the OD measurements in Figure 3 describing the experiments to establish that dC is necessary for growth in the knockout strain. It would also be ideal to provide a more detailed explanation for that observation in the discussion.

Thank you for the feedback. We have now added mention of cell morphology in the final paragraph of the introduction, where we summarise key findings.

For establishing if there is either growth or no growth under various conditions, as we have done, a qualitative assessment such as the one presented in Figure 3 is sufficient. The issue of whether OD is impacted by cell elongation has been documented by Stevenson et al. (https://www.nature.com/articles/srep38828), and becomes a problem if trying to quantify parameters such as doubling time or when trying to estimate cell counts. We do not do either of these, as calculation of both requires an assumption of normal cell morphology in E. coli. We have added a note to clarify this in the first paragraph of the Discussion section, as per the suggestion from Reviewer #1.

Reviewer #2 (Public Review):

Ribonucleotide reductase (RNR) is crucial for de novo synthesis of the dNTP building blocks needed for DNA synthesis and is essential in nearly all organisms. In the current study, all three E. coli RNRs have been removed and the essential function of the enzyme is bypassed by the introduction of an exogenous deoxyribonucleoside kinase that enables dNTP production via salvage synthesis. This leads to a complete dependency on exogenously supplied deoxyribonucleosides (dNs), loss of control of dNTP regulation, and a highly increased mutation rate. The bacteria could also grow with only supplied deoxycytidine (and no other dNs), indicating that all dNTPs could be synthesized from deoxycytidine. An evolutionary analysis of the recombinant E. coli strain grown in multiple generations showed that mutations accumulated in genes involved in the catabolism of deoxycytidine and deoxyribose-1-P, supporting a model that all the other deoxyribonucleosides can be produced by a phosphorylase using nucleobases and deoxyribose-1-P as substrates and that the deoxycytidine (besides being a precursor of dCTP) could be a substrate to produce the deoxyribose-1-P needed by the phosphorylase working in the opposite direction.

The story is very interesting with novel findings, and the experiments are well performed. There are a few missing pieces of information, but on the other hand, it is many steps to cover if everything is going to be shown in a single paper and I came to the conclusion that the data is enough at this stage. One of the missing points for future research is to check what happens with the dNTP pools. RNR is a very important enzyme to control the dNTP levels and it is likely that it is unbalanced dNTP pools that lead to the increased mutation rates. However, it would be interesting to really measure the dNTP pools and connect them to the mutations reported. Another missing piece is to identify which nucleoside phosphorylase is involved and investigate its substrate specificity to better understand why the cells can live on deoxycytidine but not other dNs.

We thank the reviewer for these comments. It is certainly possible that the mutational biases we observe across the genomes of our evolved lines are related to skewed pools. We hope to examine this in a follow-up study. Likewise, it will be interesting to investigate the biochemical basis for our lines being able to grow solely on deoxycytidine, and to ascertain how this might also impact mutation.

Reviewer #3 (Public Review):

The study focuses on a compelling question focusing on a largely indispensable mechanism, ribonucleotide reduction. The authors generate a unique specific bacterial strain where the ribonucleotide reducatase operon, entirely, is deleted. They grow the mutant strain in environments that have various amounts of the necessary deoxyribonucleoside levels, further, they perform evolution experiments to see whether and how the evolved lines would be able to adapt to the limited deoxyribonucleosides. Finally, researchers identify key mutations and generate key isogenic genetic constructs where target mutants are deleted. A summary postulation based on the evolutionary trajectory of ribonucleotide reduction by bacteria is presented. Overall, the study is well presented, well-justified, and builds on fairly classic genetic and evolution experiments. The select question and hypotheses and the overall framing of the story are fairly novel for the respective communities. The results should be interesting to evolutionary biology researchers, especially those interested in RNA>DNA directional evolution, as well as molecular microbiologists interested in the ribonucleotide reception dependence and selection by the environment. A discussion on the limitations of the laboratory study for the broader understanding of the host dependence during endosymbiosis and parasitism would be a good addition given the emphasis on this phenomenon as a part of the broader impacts of the study.

We thank the reviewer for suggestion that we consider the broader implications of our work. We have now added a final paragraph which addresses the question of why loss of ribonucleotide reduction appears so rare.

eLife assessment

Nearly all organisms require a ribonucleotide reductase (RNR) to convert ribonucleotides to their deoxyribonucleotide counterparts. In this important study, the reader learns how the model organism Escherichia coli can adapt to survive without any of its three RNRs. Compelling microbiology experiments to develop this model and analysis of compensatory mutations reveals patterns that are conserved in the few known pathogens that have also eliminated their dependence on an RNR. The manuscript will be of interest to microbiologists, biochemists, and those who work on the evolution of microbial metabolism.

Reviewer #1 (Public Review):

This manuscript describes efforts to understand how independence from ribonucleotide reduction might evolve in obligate intracellular bacterial pathogens using E. coli as a model for this process. The authors successfully deleted the three ribonucleotide reductase (RNR) operons present in E. coli and showed that growth of this knockout strain can be achieved with deoxyribonucleotide supplementation. They also performed evolutionary experiments and analysis of cell growth and morphology under conditions of low nucleotide availability. In this work, they established that certain genes are consistently mutated to compensate for the loss of RNR activity and the low availability of deoxynucleotides. Comparison to genomes of intracellular pathogens that lack RNR genes shows that these patterns are largely conserved.

While the experimental results support the conclusions of the study, the authors do report changes in cell morphology upon the growth of the RNR knockout strains with low concentrations of nucleotides. It would be ideal to note this complication earlier in the manuscript. And to clarify how the possibility of cell elongation might affect the OD measurements in Figure 3 describing the experiments to establish that dC is necessary for growth in the knockout strain. It would also be ideal to provide a more detailed explanation for that observation in the discussion.

Reviewer #2 (Public Review):

Ribonucleotide reductase (RNR) is crucial for de novo synthesis of the dNTP building blocks needed for DNA synthesis and is essential in nearly all organisms. In the current study, all three E. coli RNRs have been removed and the essential function of the enzyme is bypassed by the introduction of an exogenous deoxyribonucleoside kinase that enables dNTP production via salvage synthesis. This leads to a complete dependency on exogenously supplied deoxyribonucleosides (dNs), loss of control of dNTP regulation, and a highly increased mutation rate. The bacteria could also grow with only supplied deoxycytidine (and no other dNs), indicating that all dNTPs could be synthesized from deoxycytidine. An evolutionary analysis of the recombinant E. coli strain grown in multiple generations showed that mutations accumulated in genes involved in the catabolism of deoxycytidine and deoxyribose-1-P, supporting a model that all the other deoxyribonucleosides can be produced by a phosphorylase using nucleobases and deoxyribose-1-P as substrates and that the deoxycytidine (besides being a precursor of dCTP) could be a substrate to produce the deoxyribose-1-P needed by the phosphorylase working in the opposite direction.

The story is very interesting with novel findings, and the experiments are well performed. There are a few missing pieces of information, but on the other hand, it is many steps to cover if everything is going to be shown in a single paper and I came to the conclusion that the data is enough at this stage. One of the missing points for future research is to check what happens with the dNTP pools. RNR is a very important enzyme to control the dNTP levels and it is likely that it is unbalanced dNTP pools that lead to the increased mutation rates. However, it would be interesting to really measure the dNTP pools and connect them to the mutations reported. Another missing piece is to identify which nucleoside phosphorylase is involved and investigate its substrate specificity to better understand why the cells can live on deoxycytidine but not other dNs.

Reviewer #3 (Public Review):

The study focuses on a compelling question focusing on a largely indispensable mechanism, ribonucleotide reduction. The authors generate a unique specific bacterial strain where the ribonucleotide reducatase operon, entirely, is deleted. They grow the mutant strain in environments that have various amounts of the necessary deoxyribonucleoside levels, further, they perform evolution experiments to see whether and how the evolved lines would be able to adapt to the limited deoxyribonucleosides. Finally, researchers identify key mutations and generate key isogenic genetic constructs where target mutants are deleted. A summary postulation based on the evolutionary trajectory of ribonucleotide reduction by bacteria is presented. Overall, the study is well presented, well-justified, and builds on fairly classic genetic and evolution experiments. The select question and hypotheses and the overall framing of the story are fairly novel for the respective communities. The results should be interesting to evolutionary biology researchers, especially those interested in RNA>DNA directional evolution, as well as molecular microbiologists interested in the ribonucleotide reception dependence and selection by the environment. A discussion on the limitations of the laboratory study for the broader understanding of the host dependence during endosymbiosis and parasitism would be a good addition given the emphasis on this phenomenon as a part of the broader impacts of the study.

Author Response:

What is novel here is that we calculated the time-varying retinal motion patterns generated during the gait cycle using a 3D reconstruction of the terrain. This allows calculation of the actual statistics of retinal motion experienced by walkers over a broad range of normal experience. We certainly do not mean to claim that stabilizing gaze is novel, and agree that the general patterns follow directly from the geometry as worked out very elegantly by Koenderink and others.  We spend time describing the terrain-linked gaze behavior because it is essential for understanding the paper. We do not claim that the basic saccade/stabilize/saccade behavior is novel and now make this clearer.

The other novel aspect is that the motion patterns vary with gaze location which in turn varies with terrain in a way that depends on behavioral goals. So while some aspects of the general patterns are not unexpected, the quantitative values depend on the statistics of the behavior.  The actual statistics require these in situ measurements, and this has not previously been done, as stated in the abstract.

The measured statistics provide a well-defined set of hypotheses about the pattern of direction and speed tuning across the visual field in humans. Points of comparison in the existing literature are hard to find because the stimuli have not been closely matched to actual retinal flow patterns, and the statistics will vary with the species in question. However, recent advances allow for neurophysiological measurements and eye tracking during experiments with head-fixed running, head-free, and freely moving animals. These emerging paradigms will allow the study of retinal optic flow processing in contexts that do not require simulated locomotion. While the exact the relation between the retinal motion statistics we have measured and the response properties of motion-sensitive cells remains unresolved, the emerging tools in neurophysiology and computation make similar approaches with different species more feasible.

A more detailed description of the methods including the photogrammetry and the reference frames for the measurements has been added primarily to the Methods section.

Reviewer #1 (Public Review):

Much experimental work on understanding how the visual system processes optic flow during navigation has involved the use of artificial visual stimuli that do not recapitulate the complexity of optic flow patterns generated by actual walking through a natural environment. The paper by Muller and colleagues aims to carefully document "retinal" optic flow patterns generated by human participants walking a straight path in real terrains that differ in "smoothness". By doing so, they gain unique insights into an aspect of natural behavior that should move the field forward and allow for the development of new, more principled, computational models that may better explain the visual processing taking place during walking in humans.

Strengths:

Appropriate, state-of-the-art technology was used to obtain a simultaneous assessment of eye movements, head movements, and gait, together with an analysis of the scene, so as to estimate retinal motion maps across the central 90 deg of the visual field. This allowed the team to show that walkers stabilize gaze, causing low velocities to be concentrated around the fovea and faster velocities at the visual periphery (albeit more the periphery of the camera used than the actual visual field). The study concluded that the pattern of optic flow observed around the visual field was most likely related to the translation of the eye and body in space, and the rotations and counter-rotations this entailed to maintain stability. The authors were able to specify what aspects of the retinal motion flow pattern were impacted by terrain roughness, and why (concentration of gaze closer to the body, to control foot placement), and to differentiate this from the impact of lateral eye movements. They were also able to identify generalizable aspects of the pattern of retinal flow across terrains by subsampling identical behaviors in different conditions.

Weaknesses:

While the study has much to commend, it could benefit from additional methodological information about the computations performed to generate the data shown. In addition, an estimation of inter-individual variability, and the role of sex, age, and optical correction would increase our understanding of factors that could impact these results, thus providing a clearer estimate of how generalizable they are outside the confines of the present experiments.

Properties of gait depend on the passive dynamics of the body and factors such as leg length and subject specific cost functions which are influenced by image quality and therefore by optical correction. In this experiment all subjects were normal acuity or corrected to normal (with no information regarding their uncorrected vision). This is now noted in the Methods. The goal of the present work was to calculate average statistics over a range of observers and conditions in order to constrain the experience-dependent properties one might see in neurophysiology. We have added between-subjects error bars to Figure 2 and added gaze angle distributions as a function of terrain for individual observers in the Supplementary materials. Figure 4 b and d now show standard errors across subjects. Individual subject plots are shown in the Supplementary materials. For Figure 2, most variability between subjects occurs in the Flat and Bark terrains where one might expect individual choices of energetic costs versus speed and stability etc might come into play. This is supported by our subsequent unpublished work on factors influencing foothold choice. We have also found that leg length determines path choices and thus will influence the retinal motion. Differences between observers are now noted in the text. These individual subject differences should indicate the range of variability that might be expected in the underlying neural properties and perhaps in behavioral sensitivity. Because of the size of our dataset (n=11) it is not feasible to make comparisons of sex or age. There were equal numbers of males and females and age ranged from 24 to 54. Now noted in the Methods section.

Reviewer #2 (Public Review):

The goal of this study was to provide in situ measurements of how combined eye and body movements interact with real 3D environments to shape the statistics of retinal motion signals. To achieve this, they had human walkers navigate different natural terrains while they measured information about eyes, body, and the 3D environment. They found average flow fields that resemble the Gibsonian view of optic flow, an asymmetry between upper and lower visual fields, low velocities at the fovea, a compression of directions near the horizontal meridian, and a preponderance of vertical directions modulated by lateral gaze positions.

Strengths of the work include the methodological rigor with which the measurements were obtained. The 3D capture and motion capture systems, which have been tested and published before, are state-of-the-art. In addition, the authors used computer vision to reconstruct the 3D terrain structure from the recorded video.

Together this setup makes for an exciting rig that should enable state-of-the-art measurements of eye and body movements during locomotion. The results are presented clearly and convincingly and reveal a number of interesting statistical properties (summarized above) that are a direct result of human walking behavior.

A weakness of the article concerns tying the behavioral results and statistical descriptions to insights about neural organization. Although the authors relate their findings about the statistics of retinal motion to previous literature, the implications of their findings for neural organization remain somewhat speculative and inconclusive. An efficient coding theory of visual motion would indeed suggest that some of the statistics of retinal motion patterns should be reflected in the tuning of neural populations in the visual cortex, but as is the present findings could not be convincingly tied to known findings about the neural code of vision. Thus, the behavioral results remain strong, but the link to neural organization principles appears somewhat weak.

We agree, but we think that strengthening the neural links requires future studies. As mentioned above, it is very difficult to relate the measured statistics to existing neurophysiological literature and we have tried to make this clearer in the Discussion (p14, 15, 16). This is because the stimuli chosen are typically arbitrary and not chosen to be realistic examples of patterns consistent with natural motion across a ground plane. Other stimuli are simply inconsistent with self-motion together with gaze stabilization (eg not zero velocity at the fovea). It has also been technically difficult to map cell properties across the visual field. We have made the comparisons we thought were useful. The point of the paper is to provide a hypothesis about the pattern of direction and speed tuning across the visual field. So the challenge for neurophysiology is to show how the observed cell properties vary across the visual field. Note also that the motion patterns will be influenced by the body motion of the animal in question, and because of this we are now collaborating with a group who are attempting to record from monkey MT/MST during locomotion while tracking eyes and body. Similarly we are training neural networks to learn the patterns generated by human gait to develop more specific hypotheses about receptive field properties.

Reviewer #3 (Public Review):

Gaze-stabilizing motor coordination and the resulting patterns of retinal image flow are computed from empirically recorded eye movement and motion capture data. These patterns are assessed in terms of the information that would be potentially useful for guiding locomotion that the retinal signals actually yield. (As opposed to the "ecological" information in the optic array, defined as independent of a particular sensor and sampling strategy).

While the question posed is fundamental, and the concept of the methodology shows promise, there are some methodological details to resolve. Also, some terminological ambiguities remain, which are the legacy of the field not having settled on a standardized meaning for several technical terms that would be consistent across laboratory setups and field experiments.

Technical limits and potential error sources should be discussed more. Additional ideas about how to extend/scale up the approach to tasks with more complex scenes, higher speed or other additional task demands and what that might reveal beyond the present results could be discussed.

This issue is addressed in more detail in the Discussion, second paragraph, and also the second last paragraph.

eLife assessment

This important study should be of interest to vision scientists and those seeking to model naturalistic image processing for humans in simulated or real navigational [walking] situations. The experiments aim to provide information about the statistics of "retinal" motion patterns generated by human participants physically walking a straight path in real terrains that differ in "smoothness". State-of-the-art eye, head, and body tracking allowed simultaneous assessment of eye movements, head movements, and gait, with convincing evidence for an asymmetrical gradient of flow speeds during walking, tied predominantly to vertical gaze angle, together with a radial motion direction distribution tied most critically on horizontal gaze angle. While not a major weakness per se, additional details on analytical methods used and estimations of variance across observers would strengthen these results and clarify the basis of the global claims made about visual motion information across the visual field in walking humans.

Reviewer #1 (Public Review):

Much experimental work on understanding how the visual system processes optic flow during navigation has involved the use of artificial visual stimuli that do not recapitulate the complexity of optic flow patterns generated by actual walking through a natural environment. The paper by Muller and colleagues aims to carefully document "retinal" optic flow patterns generated by human participants walking a straight path in real terrains that differ in "smoothness". By doing so, they gain unique insights into an aspect of natural behavior that should move the field forward and allow for the development of new, more principled, computational models that may better explain the visual processing taking place during walking in humans.

Strengths:<br /> Appropriate, state-of-the-art technology was used to obtain a simultaneous assessment of eye movements, head movements, and gait, together with an analysis of the scene, so as to estimate retinal motion maps across the central 90 deg of the visual field. This allowed the team to show that walkers stabilize gaze, causing low velocities to be concentrated around the fovea and faster velocities at the visual periphery (albeit more the periphery of the camera used than the actual visual field). The study concluded that the pattern of optic flow observed around the visual field was most likely related to the translation of the eye and body in space, and the rotations and counter-rotations this entailed to maintain stability. The authors were able to specify what aspects of the retinal motion flow pattern were impacted by terrain roughness, and why (concentration of gaze closer to the body, to control foot placement), and to differentiate this from the impact of lateral eye movements. They were also able to identify generalizable aspects of the pattern of retinal flow across terrains by subsampling identical behaviors in different conditions.

Weaknesses:<br /> While the study has much to commend, it could benefit from additional methodological information about the computations performed to generate the data shown. In addition, an estimation of inter-individual variability, and the role of sex, age, and optical correction would increase our understanding of factors that could impact these results, thus providing a clearer estimate of how generalizable they are outside the confines of the present experiments.

Reviewer #2 (Public Review):

The goal of this study was to provide in situ measurements of how combined eye and body movements interact with real 3D environments to shape the statistics of retinal motion signals. To achieve this, they had human walkers navigate different natural terrains while they measured information about eyes, body, and the 3D environment. They found average flow fields that resemble the Gibsonian view of optic flow, an asymmetry between upper and lower visual fields, low velocities at the fovea, a compression of directions near the horizontal meridian, and a preponderance of vertical directions modulated by lateral gaze positions.

Strengths of the work include the methodological rigor with which the measurements were obtained. The 3D capture and motion capture systems, which have been tested and published before, are state-of-the-art. In addition, the authors used computer vision to reconstruct the 3D terrain structure from the recorded video. Together this setup makes for an exciting rig that should enable state-of-the-art measurements of eye and body movements during locomotion. The results are presented clearly and convincingly and reveal a number of interesting statistical properties (summarized above) that are a direct result of human walking behavior.

A weakness of the article concerns tying the behavioral results and statistical descriptions to insights about neural organization. Although the authors relate their findings about the statistics of retinal motion to previous literature, the implications of their findings for neural organization remain somewhat speculative and inconclusive. An efficient coding theory of visual motion would indeed suggest that some of the statistics of retinal motion patterns should be reflected in the tuning of neural populations in the visual cortex, but as is the present findings could not be convincingly tied to known findings about the neural code of vision. Thus, the behavioral results remain strong, but the link to neural organization principles appears somewhat weak.

Reviewer #3 (Public Review):

Gaze-stabilizing motor coordination and the resulting patterns of retinal image flow are computed from empirically recorded eye movement and motion capture data. These patterns are assessed in terms of the information that would be potentially useful for guiding locomotion that the retinal signals actually yield. (As opposed to the "ecological" information in the optic array, defined as independent of a particular sensor and sampling strategy).

While the question posed is fundamental, and the concept of the methodology shows promise, there are some methodological details to resolve. Also, some terminological ambiguities remain, which are the legacy of the field not having settled on a standardized meaning for several technical terms that would be consistent across laboratory setups and field experiments.

Technical limits and potential error sources should be discussed more. Additional ideas about how to extend/scale up the approach to tasks with more complex scenes, higher speed, or other additional task demands and what that might reveal beyond the present results could be discussed.

Author Response

Reviewer #1 (Public Review):

This work presents a unification model (of sorts) for explaining how the flow of evidence through networks can be controlled during decision-making. The authors combine two general frameworks previously used as neural models of cortical decision-making, dynamic normalization (that implement value encoding via firing activity) and recurrent network models (which capture winner-take-all selection processes) into a unified model called the local disinhibition-based decision model (LDDM). The simple motif of the LDDM allows for the disinhibition of excitatory cells that represent the engagement of individual actions that happens through a recurrent inhibitory loop (i.e., a leaky competing accumulator). The authors show how the LDDM works effectively well at explaining both decision dynamics and the properties of cortical cells during perceptual decision-making tasks.

All in all, I thought this was an interesting study with an ambitious goal. But like any good study, there are some open issues worth noting and correcting.

MAJOR CONCERNS

1. Big picture

This was a comprehensive and extremely well-vetted set of theoretical experiments. However, the scope and complexity also made the take-home message hard to discern. The abstract and most of the introduction focus on the framing of LDDM as a hybrid of dynamic normalization models (DNM) and recurrent network models (RNMs). This is sold as a unification of value normalization and selection into a novel unified framework. Then the focus shifts to the role of disinhibition in decision-making. Then in the Discussion, the goal is stated as to determine whether the LDDM generates persistent activity and does this activity differ from RNMs. As a reader, it seems like the paper jumps between two high- level goals: 1) the unification of DNM and RNM architectures, and 2) the role of disinhibition. This constant changing makes it hard to focus as the reader goes on. So what is the big picture goal specifically?

Also, the framing of value normalization and WTA as a novel computational goal is a bit odd as this is a major focus of the field of reinforcement learning (both abstractly at the computational level and more concretely in models of the circuits that regulate it). I know that the authors do not think they are the first to unify value judgements with selection criteria. The writing just comes across that way and should be clarified.

We thank the Reviewer for their thoughtful consideration of the overall framing of the big picture goals of the paper. Upon reflection, we agree that the paper really centers on the importance of incorporating disinhibition into computational circuit-based models of decision-making. Thus, we have significantly revised the Introduction and Discussion to focus on the theoretical and empirical importance of incorporating disinhibition into computational models of decision-making, and use the integration of value normalization and WTA selection as an example of how disinhibition increases the richness of circuit decision models. Please see the response to recommendations below for more detail on the changes.

1. Link to other models

The LDDM is described as a novel unification of value normalization and winner-take-all (WTA) selection, combining value processing and selection. While the authors do an excellent job of referencing a significant chunk of the decision neuroscience literature (160 references!) the motif they end up designing has a highly similar structure to a well-known neural circuit linked to decision-making: the cortico-basal ganglia pathways. Extensive work over the past 20+ years has highlighted how cortical-basal ganglia loops work via disinhibition of cortical decision units in a similar way as the LDDM (see the work by Michael Frank, Wei Wei, Jonathan Rubin, Fred Hamker, Rafal Bogacz, and many others). It was surprising to not see this link brought up in the paper as most of the framing was on the possibility of the LDDM representing cortical motifs, yet as far as I know, there does not exist evidence for such architectures in the cortex, but there is in these cortical-basal ganglia systems.

We thank the Reviewer for the suggestion to link the LDDM to disinhibition in CBG models; this is indeed an important body of empirical and computational work that we overlooked in the original manuscript. We have now added text to the Discussion to highlight the link between LDDM and these CBL disinhibition models, focusing on how they are conceptually similar and how they differ. Please see our response to recommendations below for a more detailed discussion of the revisions.

1. Model evaluations

The authors do a great job of extensively probing the LDDM under different conditions and against some empirical data. However, most of the time there is no "control" model or current state-of-the-art model that the LDDM is being compared against. In a few of the simulation experiments, the LDDM is compared against the DNM and RNM alone, so as to show how the two components of the LDDM motif compare against the holistic model itself. But this component model comparison is inconsistently used across simulation experiments.

Also, it is worth asking whether the DNM and RNM are appropriate comparison models to vet the LDDM against for two reasons. First, these are the components of the full LDDM. So these tests show us how the two underlying architectural systems that go into LDDM perform independently, but not necessarily how the LDDM compares against other architectures without these features. Second, as pointed out in my previous comment, the LDDM is a more complex model, with more parameters, than either the DNM or RNM. The field of decision neuroscience is awash in competing decision models (including probabilistic attractor models, non-recurrent integrators, etc.). If we really want to understand the utility of the LDDM, it would be good to know how it performs against similarly complex models, as opposed to its two underlying component models.

We greatly appreciate the Reviewer’s comments on the point of model comparison, which points out that our original manuscript failed to clearly convey a very important difference between the LDDM and the existing RNM(s). In the revision, we now make it clearer that the fundamental difference between the LDDM and the RNMs is the architecture of disinhibition (see the revised Introduction, especially p. 8 lines 164-168). The LDDM is not simply a combination of the DNM model with RNM architecture (a point we may have mistakenly conveyed in the original manuscript): the introduction of disinhibition separates LDDM inhibition into option-selective subpopulations, as opposed to the single pooled inhibition of RNM models. Given this fact, the LDDM predicts unique selectiveinhibition dynamics shown in recent optogenetic and calcium imaging results, a finding inconsistent with the common-pooled and non-selective inhibition assumed in the existing RNMs and many of its variants. Thus, we believe that a comparison between the LDDM and the RNM, which share similar level of complexity and numbers of parameters, is important.

We also appreciated the Reviewer’s concern about testing the LDDM against alternative models. In order to better connect to the existing literature, we now compare the LDDM to another standard circuit model of decision-making - the leaky competing accumulator (LCA) model. The LCA is a circuit model that captures many of the aspects of perceptual decision-making seen in the mathematical drift diffusion model (DDM), but with a construction that allows for fitting to behavioral data and comparison of underlying unit activities. Please see our response to recommendations below for further detail.

1. Comparison to physiological data

I quite enjoyed the comparisons of the excitatory cell activity to empirical data from the Shadlen lab experiments. However, these were largely qualitative in nature. In conjunction with my prior point on the models that the LDDM is being compared against, it would be ideal to have a direct measure of model fits that can be used to compare the performance of different competing "control" models. These measures would have to account for differences in model complexity (e.g., AIC or BIC), but such an analysis would help the reader understand the utility of the LDDM in connecting with empirical data much better.

We agree with the Reviewer that a quantitative comparison of the match between model neural predictions and empirical neurophysiological data is important. First, we wish to clarify that the model neural predictions are simulated from models fit to the behavioral (choice and RT data), not from fits to the neural activity traces – a point we now clarify in the text. While directly fitting dynamic models (LDDM, RNM, or LCA) to the neurophysiological data is appealing, there are currently several obstacles to this approach. The first problem is the complexity of the dynamic neural traces. Despite the long history of the random-dot motion paradigm, detailed features of the dynamics are still not understood. For example, the stereotyped initial dip after stimulus onset may reflect a reset of the network state to improve signal to noise ratio (Conen and Padoa-Schioppa, 2015) or simply reflect a surround suppression-like lateral inhibition in visual processing. A second problem is that the primary difference between the models is the activity of inhibitory (and disinhibitory) neurons, which are typically not recorded in neurophysiological experiments; thus, there is a lack of empirical data to which to fit the models. In the revision, we clarified that the model fitting to the Roitman & Shadlen data is for behavioral data only, and model unit activity traces are derived from models fit to behavioral data.

That being said, we agree that a quantitative comparison of model activity predictions is helpful. Because the models are fit not to the neural data but to the behavioral data, rather than using likelihood-based measures like AIC and BIC we used a simple RMSE measure to compare the match between predicted and neural activity patterns (revised Fig. 6E, Fig 6-S4E, Fig 6-S5E). Please see response to recommendations below for details.

Reviewer #2 (Public Review):

The aim of this article was to create a biologically plausible model of decision-making that can both represent a choice's value and reproduce winner-take-all ramping behavior that determines the choice, two fundamental components of value- based decision-making. Both of these aspects have been studied and modeled independently but empirical studies have found that single neurons can switch between both of the aspects (i.e., from representing value to winner-take-all ramping behavior) in ways that are not well described by current biological plausible models of decision making.

The current article provides a thorough investigation of a new model (the local disinhibition decision model; LDDM) that has the goal of combining value representations and winner-takes-all ramping dynamics related to choice. Their model uses biologically plausible disinhibition to control the levels of inhibition in a local network of simulated neurons. Through a careful series of simulation experiments, they demonstrate that their network can first represent the value of different options, then switch to winner-takes-all ramping dynamics when a choice needs to be made. They further demonstrate that their single model reproduces key components of value-based and winner-takes-all dynamics found in both neural and behavioral data. They additionally conduct simulation studies to demonstrate that recurrent excitatory properties in their network produce value-persistence behavior that could be related to memory. They end by conducting a careful simulation study of the influence of GABA agonists that provide clear and testable predictions of their proposed role of inhibition in the neural processes that underlie decision-making. This last piece is especially important as it provides a clear set of predictions and experiments to help support or falsify their model.

There are overall many strengths to this paper. As the authors note, current network models do not explain both value- based and ramping-like decision-making properties. Their thorough simulation studies and their validation against empirical neural and behavioral data will be of strong interest to neuroscientists and psychologists interested in value- based decision-making. The simulations related to persistence and the GABA-agonist experiments they propose also provide very clear guidelines for future research that would help advance the field of decision-making research.

Although the methods and model were generally clear, there was a fair amount of emphasis on the role of recurrence in the LDDM, but very little evidence that recurrence was important or necessary for any of the empirical data examined. The authors do demonstrate the importance of recurrence in some of their simulation studies (particularly in their studies of persistence), but these would need to be compared against empirical data to be validated. Nevertheless, the model and thorough simulation investigations will likely help develop more precise theories of value-based decision-making.

We appreciate the Reviewer’s thoughtful comments. These comments - especially about anatomic recurrence and its relationship to the parameter 𝛼 - inspired us to think more about the uniqueness of the current circuit to others, especially the implications related to the parameters 𝛼 (i.e., self-excitation) and 𝛽 (i.e., local disinhibition). Recurrence is required to drive winner-take-all competition in the standard RNM of decision-making. However, we show here with both analytical and numerical approaches that recurrence helps WTA competition but is not necessary in our model. Instead, the key feature of the LDDM is to utilize disinhibition in conjunction with lateral inhibition to realize winner-take-all competition. That leads to many different predictions of the current model from the existing models, such as selective inhibition and flexible control of dynamics.

In response to the Reviewer’s points and after careful consideration of the differential equations, we realized that in our model fitting, the 𝛼 parameter fitting to zero does not necessarily mean recurrence should be zero. The 𝛼 parameter shares a lot of similarity to the baseline gain control (parameter BG in our revision), and thus is unidentifiable in the current dataset. In the interest of parsimony, we did not include the parameter BG in the original manuscript, but now include it because it reveals the difficulty of interpreting fit 𝛼 values as simply the level of recurrence.

Overall, disinhibition (𝛽) in the LDDM is required for WTA activity while recurrence (𝛼) can contribute but is not necessary; however, 𝛼 is theoretically important for generating persistent activity, with the caveat that in the current framework there is an unclear relationship between fit 𝛼 and recurrence. Regardless, we agree that the contribution of 𝛼 to the LDDM framework is worth further testing and examining with future empirical data.

Reviewer #3 (Public Review):

Shen et al. attempt to reconcile two distinct features of neural responses in frontoparietal areas during perceptual and value-guided decision-making into a single biologically realistic circuit model. First, previous work has demonstrated that value coding in the parietal cortex is relative (dependent on the value of all available choice options) and that this feature can be explained by divisive normalization, implemented using adaptive gain control in a recurrently connected circuit model (Louie et al, 2011). Second, a wealth of previous studies on perceptual decision-making (Gold & Shadlen 2007) have provided strong evidence that competitive winner-take-all dynamics implemented through recurrent dynamics characterized by mutual inhibition (Wang 2008) can account for categorical choice coding. The authors propose a circuit model whose key feature is the flexible gating of 'disinhibition', which captures both types of computation - divisive normalization and winner-take-all competition. The model is qualitatively able to explain the 'early' transients in parietal neural responses, which show signatures of divisive normalization indicating a relative value code, persistent activity during delay periods, and 'late' accumulation-to-bound type categorical responses prior to the report of choice/action onset.

The attempt to integrate these two sets of findings by a unified circuit model is certainly interesting and would be useful to those who seek a tighter link between biologically realistic recurrent neural network models and neural recordings. I also appreciate the effort undertaken by the authors in using analytical tools to gain an understanding of the underlying dynamical mechanism of the proposed model. However, I have two major concerns. First, the manuscript in its current form lacks sufficient clarity, specifically in how some of the key parameters of the model are supposed to be interpreted (see point 1 below). Second, the authors overlook important previous work that is closely related to the ideas that are being presented in this paper (see point 2 below).

1) The behavior of the proposed model is critically dependent on a single parameter 'beta' whose value, the authors claim, controls the switch from value-coding to choice-coding. However, the precise definition/interpretation of 'beta' seems inconsistent in different parts of the text. I elaborate on this issue in sub-points (1a-b) below:

1a). For instance, in the equations of the main text (Equations 1-3), 'beta' is used to denote the coupling from the excitatory units (R) to the disinhibitory units (D) in Equations 1-3. However, in the main figures (Fig 2) and in the methods (Equation 5-8), 'beta' is instead used to refer to the coupling between the disinhibitory (D) and the inhibitory gain control units (G). Based on my reading of the text (and the predominant definition used by the authors themselves in the main figures and the methods), it seems that 'beta' should be the coupling between the D and G units.

1b). A more general and critical issue is the failure to clearly specify whether this coupling of D-G units (parameterized by 'beta') should be interpreted as a 'functional' one, or an 'anatomical' one. A straightforward interpretation of the model equations (Equations 5-8) suggests that 'beta' is the synaptic weight (anatomical coupling) between the D and G units/populations. However, significant portions of the text seem to indicate otherwise (i.e a 'functional' coupling). I elaborate on this in subpoints (i-iii) below:

(1b-i). One of the main claims of the paper is that the value of 'beta' is under 'external' top-down control (Figure 2 caption, lines 124-126). When 'beta' equals zero, the model is consistent with the previous DNM model (dynamic normalization, Louie et al 2011), but for moderate/large non-zero values of 'beta', the network exhibits WTA dynamics. If 'beta' is indeed the anatomical coupling between D and G (as suggested by the equations of the model), then, are we to interpret that the synaptic weight between D-G is changed by the top-down control signal within a trial? My understanding of the text suggests that this is not in fact the case. Instead, the authors seem to want to convey that top-down input "functionally" gates the activity of D units. When the top-down control signal is "off", the disinhibitory units (D) are "effectively absent" (i.e their activity is clamped at zero as in the schematic in Fig 2B), and therefore do not drive the G units. This would in- turn be equivalent to there being no "anatomical coupling" between D and G. However when the top-down signal is "on", D units have non-zero activity (schematic in Fig 2B), and therefore drive the G units, ultimately resulting in WTA-like dynamics.

(1b-ii). Therefore, it seems like when the authors say that beta equals zero during the value coding phase they are almost certainly referring to a functional coupling from D to G, or else it would be inconsistent with their other claim that the proposed model flexibly reconfigures dynamics only through a single topdown input but without a change to the circuit architecture (reiterated in lines 398-399, 442-444, 544-546, 557-558, 579-590). However, such a 'functional' definition of 'beta' would seem inconsistent with how it should actually be interpreted based on the model equations, and also somewhat misleading considering the claim that the proposed network is a biologically realistic circuit model.

(1b-iii). The only way to reconcile the results with an 'anatomical' interpretation of 'beta' is if there is a way to clamp the values of the 'D' units to zero when the top-down control signal is 'off'. Considering that the D units also integrate feed- forward inputs from the excitatory R units (Fig 2, Equations 1-3 or 5-8), this can be achieved either via a non-linearity, or if the top-down control input multiplicatively gates the synapse (consistent with the argument made in lines 115-116 and 585-586 that this top-down control signal is 'neuromodulatory' in nature). Neither of these two scenarios seems to be consistent with the basic definition of the model (Equations 1-3), which therefore confirms my suspicion that the interpretation of 'beta' being used in the text is more consistent with a 'functional' coupling from D to G.

We thank the reviewer for pointing out this confusion. We apologize that the original illustrations (Fig. 2A) and the differential equations in Methods (Eqs. 5-8) did not convey very well our ideas. 𝛽 is intended to reference the coupling from R to D, not a change in the weights between D and G units. We realize there was some confusion on this part due to inconsistency between our original figures, text, and supplementary material.

Given the lack of clarity in the previous version as well as the Reviewer’s questions, we now emphasize that 𝛽 represents a functional coupling between the R and D neurons. The biological assumption of the disinhibitory architecture is built based on recent findings that VIP neurons in the cortex always inhibit other neighboring inhibitory cells, such as SST and PV neurons, and consequently disinhibit the neighboring primary neurons (e.g., Fu et al., 2014; Karnani et al., 2014, 2016). We did not see evidence in the literature of fast-changing (anatomic) connections between VIP and SST/PV. However, there is evidence that the responsiveness of VIP neurons to excitatory neurons can be modulated by changing the concentrations of neuromodulators, such as acetylcholine and serotonin (Prönneke et al., 2020). While the stereotype of neuromodulator action is slow dynamics, recent findings show that for example basal forebrain cholinergic neurons respond to reward and punishment with surprising speed and precision (18 ± 3ms) (Hangya et al., 2015) to modulate arousal, attention, and learning in the neocortex. Given the large number of studies that identify long-term projections and neuromodulatory inputs to VIP neurons (e.g., Pfeffer et al., 2013; Pi et al., 2013; Alitto & Dan, 2013; Tremblay et al., 2016), we believe that it will be more plausible to assume the connection weights between R and D in our case is quickly modulated within a trial.

To clarify this issue in the revised manuscript, we made the following corrections:

1. We repositioned the 𝛽 parameter in Fig. 2A between the connection from R to D, to align the description of 𝛽 modulating R to D in the main text.

2. We modified the differential equations 5-8 (now numbered as Eqs. 28-32) in Methods (pp. 61) to include the disinhibitory unit D as an independent control from the inhibitory unit I, in order to be consistent with the disinhibitory D units in LDDM. Such a change makes tiny differences in the model predictions (please see dynamics simulated after the change in Fig. 2-figure supplement 1B).

3. We updated the neural circuit motif in Fig. 2 -figure supplement 1A accordingly.

2) The main contribution of the manuscript is to integrate the characteristics of the dynamic normalization model (Louie et al, 2011) and the winner-take-all behavior of recurrent circuit models that employ mutual inhibition (Wang, 2008), into a circuit motif that can flexibly switch between these two computations. The main ingredient for achieving this seems to be the dynamical 'gating' of the disinhibition, which produces a switch in the dynamics, from point-attractor-like 'stable' dynamics during value coding to saddle-point-like 'unstable' dynamics during categorical choice coding. While the specific use of disinhibition to switch between these two computations is new, the authors fail to cite previous work that has explored similar ideas that are closely related to the results being presented in their study. It would be very useful if the authors can elaborate on the relationship between their work and some of these previous studies. I elaborate on this point in (a-b) below:

2a) While the authors may be correct in claiming that RNM models based on mutual inhibition are incapable of relative value coding, it has already been shown previously that RNM models characterized by mutual inhibition can be flexibly reconfigured to produce dynamical regimes other than those that just support WTA competition (Machens, Romo & Brody, 2005). Similar to the behavior of the proposed model (Fig 9), the model by Machens and colleagues can flexibly switch between point-attractor dynamics (during stimulus encoding), line-attractor dynamics (during working memory), and saddle-point dynamics (during categorical choice) depending on the task epoch. It achieves this via a flexible reconfiguration of the external inputs to the RNM. Therefore, the authors should acknowledge that the mechanism they propose may just be one of many potential ways in which a single circuit motif is reconfigured to produce different task dynamics. This also brings into question their claim that the type of persistent activity produced by the model is "novel", which I don't believe it is (see Machens et al 2005 for the same line-attractor-based mechanism for working memory)

We thank the Reviewer for pointing out the conceptual similarities between the LDDM and the Machens Romo Brody model, and now include a discussion of the link between the two early in the revised Discussion (p. 38, lines 826-837). Please see response to recommendations below for a more detailed discussion of this point.

2b) The authors also fail to cite or describe their work in relation to previous work that has used disinhibition-based circuit motifs to achieve all 3 proposed functions of their model - (i) divisive normalization (Litwin-Kumar et al, 2016), (ii) flexible gating/decision making (Yang et al, 2016), and working memory maintenance (Kim & Sejnowski,2021)

The Reviewer notes several relevant papers, and we have now discussed them and their relationship to the LDDM in a revised Discussion section (pp. 35-36). Please see response to recommendations below for a more details.

eLife assessment

This work provides a promising first pass at providing an integrative model for how decisions arise from neural circuits. The approach is novel but lacks a more rigorous vetting against alternative model formulations to be able to determine its true significance. More stringent evaluations of the model in the context of existing work, as well as a clearer description of the goals and implementation of the approach, would help to address these concerns.

Reviewer #1 (Public Review):

This work presents a unification model (of sorts) for explaining how the flow of evidence through networks can be controlled during decision-making. The authors combine two general frameworks previously used as neural models of cortical decision-making, dynamic normalization (that implement value encoding via firing activity) and recurrent network models (which capture winner-take-all selection processes) into a unified model called the local disinhibition-based decision model (LDDM). The simple motif of the LDDM allows for the disinhibition of excitatory cells that represent the engagement of individual actions that happens through a recurrent inhibitory loop (i.e., a leaky competing accumulator). The authors show how the LDDM works effectively well at explaining both decision dynamics and the properties of cortical cells during perceptual decision-making tasks.

All in all, I thought this was an interesting study with an ambitious goal. But like any good study, there are some open issues worth noting and correcting.

MAJOR CONCERNS

1. Big picture

This was a comprehensive and extremely well-vetted set of theoretical experiments. However, the scope and complexity also made the take-home message hard to discern. The abstract and most of the introduction focus on the framing of LDDM as a hybrid of dynamic normalization models (DNM) and recurrent network models (RNMs). This is sold as a unification of value normalization and selection into a novel unified framework. Then the focus shifts to the role of disinhibition in decision-making. Then in the Discussion, the goal is stated as to determine whether the LDDM generates persistent activity and does this activity differ from RNMs. As a reader, it seems like the paper jumps between two high-level goals: 1) the unification of DNM and RNM architectures, and 2) the role of disinhibition. This constant changing makes it hard to focus as the reader goes on. So what is the big picture goal specifically?

Also, the framing of value normalization and WTA as a novel computational goal is a bit odd as this is a major focus of the field of reinforcement learning (both abstractly at the computational level and more concretely in models of the circuits that regulate it). I know that the authors do not think they are the first to unify value judgements with selection criteria. The writing just comes across that way and should be clarified.

2. Link to other models

The LDDM is described as a novel unification of value normalization and winner-take-all (WTA) selection, combining value processing and selection. While the authors do an excellent job of referencing a significant chunk of the decision neuroscience literature (160 references!) the motif they end up designing has a highly similar structure to a well-known neural circuit linked to decision-making: the cortico-basal ganglia pathways. Extensive work over the past 20+ years has highlighted how cortical-basal ganglia loops work via disinhibition of cortical decision units in a similar way as the LDDM (see the work by Michael Frank, Wei Wei, Jonathan Rubin, Fred Hamker, Rafal Bogacz, and many others). It was surprising to not see this link brought up in the paper as most of the framing was on the possibility of the LDDM representing cortical motifs, yet as far as I know, there does not exist evidence for such architectures in the cortex, but there is in these cortical-basal ganglia systems.

3. Model evaluations

The authors do a great job of extensively probing the LDDM under different conditions and against some empirical data. However, most of the time there is no "control" model or current state-of-the-art model that the LDDM is being compared against. In a few of the simulation experiments, the LDDM is compared against the DNM and RNM alone, so as to show how the two components of the LDDM motif compare against the holistic model itself. But this component model comparison is inconsistently used across simulation experiments.

Also, it is worth asking whether the DNM and RNM are appropriate comparison models to vet the LDDM against for two reasons. First, these are the components of the full LDDM. So these tests show us how the two underlying architectural systems that go into LDDM perform independently, but not necessarily how the LDDM compares against other architectures without these features. Second, as pointed out in my previous comment, the LDDM is a more complex model, with more parameters, than either the DNM or RNM. The field of decision neuroscience is awash in competing decision models (including probabilistic attractor models, non-recurrent integrators, etc.). If we really want to understand the utility of the LDDM, it would be good to know how it performs against similarly complex models, as opposed to its two underlying component models.

4. Comparison to physiological data

I quite enjoyed the comparisons of the excitatory cell activity to empirical data from the Shadlen lab experiments. However, these were largely qualitative in nature. In conjunction with my prior point on the models that the LDDM is being compared against, it would be ideal to have a direct measure of model fits that can be used to compare the performance of different competing "control" models. These measures would have to account for differences in model complexity (e.g., AIC or BIC), but such an analysis would help the reader understand the utility of the LDDM in connecting with empirical data much better.

Reviewer #2 (Public Review):

The aim of this article was to create a biologically plausible model of decision-making that can both represent a choice's value and reproduce winner-take-all ramping behavior that determines the choice, two fundamental components of value-based decision-making. Both of these aspects have been studied and modeled independently but empirical studies have found that single neurons can switch between both of the aspects (i.e., from representing value to winner-take-all ramping behavior) in ways that are not well described by current biological plausible models of decision making.

The current article provides a thorough investigation of a new model (the local disinhibition decision model; LDDM) that has the goal of combining value representations and winner-takes-all ramping dynamics related to choice. Their model uses biologically plausible disinhibition to control the levels of inhibition in a local network of simulated neurons. Through a careful series of simulation experiments, they demonstrate that their network can first represent the value of different options, then switch to winner-takes-all ramping dynamics when a choice needs to be made. They further demonstrate that their single model reproduces key components of value-based and winner-takes-all dynamics found in both neural and behavioral data. They additionally conduct simulation studies to demonstrate that recurrent excitatory properties in their network produce value-persistence behavior that could be related to memory. They end by conducting a careful simulation study of the influence of GABA agonists that provide clear and testable predictions of their proposed role of inhibition in the neural processes that underlie decision-making. This last piece is especially important as it provides a clear set of predictions and experiments to help support or falsify their model.

There are overall many strengths to this paper. As the authors note, current network models do not explain both value-based and ramping-like decision-making properties. Their thorough simulation studies and their validation against empirical neural and behavioral data will be of strong interest to neuroscientists and psychologists interested in value-based decision-making. The simulations related to persistence and the GABA-agonist experiments they propose also provide very clear guidelines for future research that would help advance the field of decision-making research.

Although the methods and model were generally clear, there was a fair amount of emphasis on the role of recurrence in the LDDM, but very little evidence that recurrence was important or necessary for any of the empirical data examined. The authors do demonstrate the importance of recurrence in some of their simulation studies (particularly in their studies of persistence), but these would need to be compared against empirical data to be validated. Nevertheless, the model and thorough simulation investigations will likely help develop more precise theories of value-based decision-making.

Reviewer #3 (Public Review):

Shen et al. attempt to reconcile two distinct features of neural responses in frontoparietal areas during perceptual and value-guided decision-making into a single biologically realistic circuit model. First, previous work has demonstrated that value coding in the parietal cortex is relative (dependent on the value of all available choice options) and that this feature can be explained by divisive normalization, implemented using adaptive gain control in a recurrently connected circuit model (Louie et al, 2011). Second, a wealth of previous studies on perceptual decision-making (Gold & Shadlen 2007) have provided strong evidence that competitive winner-take-all dynamics implemented through recurrent dynamics characterized by mutual inhibition (Wang 2008) can account for categorical choice coding. The authors propose a circuit model whose key feature is the flexible gating of 'disinhibition', which captures both types of computation - divisive normalization and winner-take-all competition. The model is qualitatively able to explain the 'early' transients in parietal neural responses, which show signatures of divisive normalization indicating a relative value code, persistent activity during delay periods, and 'late' accumulation-to-bound type categorical responses prior to the report of choice/action onset.

The attempt to integrate these two sets of findings by a unified circuit model is certainly interesting and would be useful to those who seek a tighter link between biologically realistic recurrent neural network models and neural recordings. I also appreciate the effort undertaken by the authors in using analytical tools to gain an understanding of the underlying dynamical mechanism of the proposed model. However, I have two major concerns. First, the manuscript in its current form lacks sufficient clarity, specifically in how some of the key parameters of the model are supposed to be interpreted (see point 1 below). Second, the authors overlook important previous work that is closely related to the ideas that are being presented in this paper (see point 2 below).

1) The behavior of the proposed model is critically dependent on a single parameter 'beta' whose value, the authors claim, controls the switch from value-coding to choice-coding. However, the precise definition/interpretation of 'beta' seems inconsistent in different parts of the text. I elaborate on this issue in sub-points (1a-b) below:

1a). For instance, in the equations of the main text (Equations 1-3), 'beta' is used to denote the coupling from the excitatory units (R) to the disinhibitory units (D) in Equations 1-3. However, in the main figures (Fig 2) and in the methods (Equation 5-8), 'beta' is instead used to refer to the coupling between the disinhibitory (D) and the inhibitory gain control units (G). Based on my reading of the text (and the predominant definition used by the authors themselves in the main figures and the methods), it seems that 'beta' should be the coupling between the D and G units.

1b). A more general and critical issue is the failure to clearly specify whether this coupling of D-G units (parameterized by 'beta') should be interpreted as a 'functional' one, or an 'anatomical' one. A straightforward interpretation of the model equations (Equations 5-8) suggests that 'beta' is the synaptic weight (anatomical coupling) between the D and G units/populations. However, significant portions of the text seem to indicate otherwise (i.e a 'functional' coupling). I elaborate on this in subpoints (i-iii) below:

(1b-i). One of the main claims of the paper is that the value of 'beta' is under 'external' top-down control (Figure 2 caption, lines 124-126). When 'beta' equals zero, the model is consistent with the previous DNM model (dynamic normalization, Louie et al 2011), but for moderate/large non-zero values of 'beta', the network exhibits WTA dynamics. If 'beta' is indeed the anatomical coupling between D and G (as suggested by the equations of the model), then, are we to interpret that the synaptic weight between D-G is changed by the top-down control signal within a trial? My understanding of the text suggests that this is not in fact the case. Instead, the authors seem to want to convey that top-down input "functionally" gates the activity of D units. When the top-down control signal is "off", the disinhibitory units (D) are "effectively absent" (i.e their activity is clamped at zero as in the schematic in Fig 2B), and therefore do not drive the G units. This would in-turn be equivalent to there being no "anatomical coupling" between D and G. However when the top-down signal is "on", D units have non-zero activity (schematic in Fig 2B), and therefore drive the G units, ultimately resulting in WTA-like dynamics.

(1b-ii). Therefore, it seems like when the authors say that beta equals zero during the value coding phase they are almost certainly referring to a functional coupling from D to G, or else it would be inconsistent with their other claim that the proposed model flexibly reconfigures dynamics only through a single top-down input but without a change to the circuit architecture (reiterated in lines 398-399, 442-444, 544-546, 557-558, 579-590). However, such a 'functional' definition of 'beta' would seem inconsistent with how it should actually be interpreted based on the model equations, and also somewhat misleading considering the claim that the proposed network is a biologically realistic circuit model.

(1b-iii). The only way to reconcile the results with an 'anatomical' interpretation of 'beta' is if there is a way to clamp the values of the 'D' units to zero when the top-down control signal is 'off'. Considering that the D units also integrate feed-forward inputs from the excitatory R units (Fig 2, Equations 1-3 or 5-8), this can be achieved either via a non-linearity, or if the top-down control input multiplicatively gates the synapse (consistent with the argument made in lines 115-116 and 585-586 that this top-down control signal is 'neuromodulatory' in nature). Neither of these two scenarios seems to be consistent with the basic definition of the model (Equations 1-3), which therefore confirms my suspicion that the interpretation of 'beta' being used in the text is more consistent with a 'functional' coupling from D to G.

2) The main contribution of the manuscript is to integrate the characteristics of the dynamic normalization model (Louie et al, 2011) and the winner-take-all behavior of recurrent circuit models that employ mutual inhibition (Wang, 2008), into a circuit motif that can flexibly switch between these two computations. The main ingredient for achieving this seems to be the dynamical 'gating' of the disinhibition, which produces a switch in the dynamics, from point-attractor-like 'stable' dynamics during value coding to saddle-point-like 'unstable' dynamics during categorical choice coding. While the specific use of disinhibition to switch between these two computations is new, the authors fail to cite previous work that has explored similar ideas that are closely related to the results being presented in their study. It would be very useful if the authors can elaborate on the relationship between their work and some of these previous studies. I elaborate on this point in (a-b) below:

2a) While the authors may be correct in claiming that RNM models based on mutual inhibition are incapable of relative value coding, it has already been shown previously that RNM models characterized by mutual inhibition can be flexibly reconfigured to produce dynamical regimes other than those that just support WTA competition (Machens, Romo & Brody, 2005). Similar to the behavior of the proposed model (Fig 9), the model by Machens and colleagues can flexibly switch between point-attractor dynamics (during stimulus encoding), line-attractor dynamics (during working memory), and saddle-point dynamics (during categorical choice) depending on the task epoch. It achieves this via a flexible reconfiguration of the external inputs to the RNM. Therefore, the authors should acknowledge that the mechanism they propose may just be one of many potential ways in which a single circuit motif is reconfigured to produce different task dynamics. This also brings into question their claim that the type of persistent activity produced by the model is "novel", which I don't believe it is (see Machens et al 2005 for the same line-attractor-based mechanism for working memory)

2b) The authors also fail to cite or describe their work in relation to previous work that has used disinhibition-based circuit motifs to achieve all 3 proposed functions of their model - (i) divisive normalization (Litwin-Kumar et al, 2016), (ii) flexible gating/decision making (Yang et al, 2016), and working memory maintenance (Kim & Sejnowski,2021)

Author Response

Reviewer #2 (Public Review):

The two new micropeptides are well characterized in the manuscript and appear to be functionally important with some chromatin-level consequences of their loss (which can be either direct or indirect), but the finding that lincRNA sequences encode micropeptides is not novel, and the two described in the paper appear to be zebrafish-specific and their function was tested only in zebrafish, which limits the interest in these genes. The use of ribosome profile data along behavioral screening to identify micropeptides is interesting and important, but the scope of the screen, the candidates selected for testing, etc. are not clear enough as presented. The ChIP-seq analysis of the new proteins is very interesting but is not described in any detail. Overall, the experimental part is well designed and the phenotypes reported by the authors appear to be strong and convincing, but the mechanistic understanding of what the two new proteins do and how, and the general interest in the results given the current scope of understanding of micropeptide is limited.

We apologize for the misunderstanding that these genes are zebrafish-specific. In this revision, we have clarified throughout the text and with additional data that these genes are not zebrafish-specific, but that linc-mipep and linc-wrb are homologous to human Hmgn1.

eLife assessment

This paper will be of interest to scientists involved in understanding the function of long non-coding RNAs. The authors found two genes previously reported as lincRNAs in early studies encode micropeptides in zebrafish. Zebrafish mutants lacking these micro-peptides show altered gene regulatory networks that preferentially affect oligodendrocytes and cerebellar cells in the embryonic brain. The data presented in the study are solid and present convincing additional evidence for the versatile functions of micro-peptides.

Reviewer #1 (Public Review):

Tornini et al. investigate the function of long non-coding RNAs in vivo. In the manuscript, the authors show that two of these molecules linc-mipep and linc-wrb encode for a micropeptide that regulates zebrafish behavior. In the absence of this peptide, zebrafish larvae show dysregulation of NMDA receptor and glucocorticoid receptor-mediated signaling and immediate early gene induction. Given the homology of linc-mipep and linc-wrb encoded peptides with homology to chromosome binding and chromatin unwinding domain of HMGN1 the authors explore the altered chromatin accessibility in the mutant animals. This analysis revealed a broad dysregulation of 3D chromatin structure with some enrichment at loci regulating the expression of immediate early response genes. Finally, single cell analysis revealed that oligodendrocyte progenitor cells and cerebellar granule cells are more affected in the mutants.

This work represents a technical tour-de-force with extensive genomics data to characterize the molecular phenotype of linc-mipep and linc-wrb loss of function. This data show interesting findings in part consistent with the behavioral phenotype observed.

The manuscript provides compelling evidence that micropeptides encoded by what were previously identified as long non-coding RNAs have a precise biological function.

Reviewer #2 (Public Review):

The two new micropeptides are well characterized in the manuscript and appear to be functionally important with some chromatin-level consequences of their loss (which can be either direct or indirect), but the finding that lincRNA sequences encode micropeptides is not novel, and the two described in the paper appear to be zebrafish-specific and their function was tested only in zebrafish, which limits the interest in these genes. The use of ribosome profile data along behavioral screening to identify micropeptides is interesting and important, but the scope of the screen, the candidates selected for testing, etc. are not clear enough as presented. The ChIP-seq analysis of the new proteins is very interesting but is not described in any detail. Overall, the experimental part is well designed and the phenotypes reported by the authors appear to be strong and convincing, but the mechanistic understanding of what the two new proteins do and how, and the general interest in the results given the current scope of understanding of micropeptide is limited.

Reviewer #3 (Public Review):

The study aimed at the identification of functional micro-peptides encoded by transcripts previously annotated as long noncoding RNAs (lncRNAs). The authors pre-selected 10 candidates out of the ~500 zebrafish lncRNA data set based on their engagement with the ribosome (by ribosome profiling data) and their expression in the embryonic brain. By performing an F0 CRISPR/Cas9 screen coupled with embryonic behavioral assays, two transcripts encoding sequence-related micro-peptides were identified. Using a set of stable mutant alleles, the authors showed that mutations specifically affecting the open reading frame (ORF) of the putative micro-peptides cause changes in embryonic behavior when compared to wild-type embryos or embryos with mutations in the non-coding regions of the tested transcripts. The locomotor hyperactivity phenotype was even stronger in double homozygous mutants suggesting a redundant function of both micro-peptides. The authors demonstrated that the behavioral phenotype of one of the mutants was rescued by the transgene expression of the coding sequence (CDS). Sequence analyses of both peptides revealed their conservation and homology to the human non-histone chromosomal proteins (HMGN1 proteins). The authors demonstrated that the micro-peptide mutants exhibit changes in chromatin accessibility for transcription factors modifying neural activation, dysregulation of gene expression programs, and changes in oligodendrocyte and cerebellar cell states during development.

The study presents an important discovery of two sequence-related micro-peptides with important and potentially conserved functions during development. While it is still unclear how the micro-peptides act in the cell, it is evident that they are key regulators of cellular states. Whereas the study is well done, the data presentation should be improved as several important details were omitted.

Reviewer #4 (Public Review):

In this manuscript, Tornini and colleagues identify two previously un-characterized micropeptides encoded by linc-mipep and linc-wrb as important modulators of day-time activity in zebrafish larvae. The authors demonstrate that each single mutant shows an increase in day-time activity and that double mutants show a more pronounced effect. Of interest, ubiquitous overexpression of the ORF encoding the linc-mipep-derived peptide can rescue the day-time over-activity phenotype of linc-mipep mutant larvae, establishing that linc-mipep acts indeed as a protein and not at the level of RNA. Using a series of experimental approaches, including ATAC-Seq from double mutant brains and scRNA-Seq and scATAC-seq analyses from linc-mipep mutants as well as linc-mipep and linc-wrb CHIP analyses, the authors furthermore identify differences in chromatin accessibility and gene expression in specific cell types of the larval brain in the absence of linc-mipep (and in case of globale ATAC-Seq, in the absence of both peptides). They conclude that the micropeptides regulate behavior and neuronal states by modulating chromatin accessibility, revealing functional similarities to their known vertebrate homolog HMGN1.

Overall, the key finding of this paper, namely the identification of two functional microproteins that had previously been misannotated as lincRNAs but have homology to HMGN1 both based on their sequence and function is an exciting discovery since relatively few newly predicted micropeptides have been functionally characterized to date, and because it advances our understanding of the molecular mechanisms underlying vertebrate-specific neuronal function and diversity. The F0 screen leading to the identification of 2 functional micropeptides provides a major advance to the field since so far screens in the F0 generation have not been typically done (rather germline-transmission). Thus, this work provides a major step forward in this regard. In addition, it includes a series of scRNA- and scATAC analyses that are technologically at the forefront and not easy to conduct and analyse.

The weakest part of the paper in its current form is on the one hand missing the link between the behavioral phenotype in mutants and the molecular phenotypes in the larval brain. It remains unclear how one can reconcile the broad neuronal expression (in the case of linc-mipep preferentially in Purkinje cells) and linc-wrb with the cell-specific effects. Moreover, it is not clear whether both peptides act redundantly or in parallel but distinct pathways since the rescue is only shown for the single linc-mipep mutant by linc-mipep overexpression (and no rescue is shown for linc-wrb or the double mutant). While the authors suggest throughout the manuscript that both peptides have similar functions (act redundantly), no clear data is provided for this, and the use of either single linc-mipep mutants (all single-cell analyses in the last Figure) or double linc-mipep/linc-wrb mutants (global brain ATAC-Seq analyses) for different brain analyses makes the molecular analyses inconsistent and not easy to interpret. While the overall finding(s) of the paper is really interesting, to make this paper really solid, additional controls and analyses will be needed.

Author Response

Reviewer #1 (Public Review):

Francou et al. examine the dynamics of cell ingression at the primitive streak during mouse gastrulation and correlate this with the localization of elements of the apical Crumbs complex and the actomyosin cytoskeleton. Using time-lapse live imaging, they show that cells at the primitive streak ingress in a stochastic manner, by constricting their apical surface through a ratcheting shrinkage of individual junctions. Meticulous evaluation of immunofluorescent staining for many elements of the actomyosin contractile process as well as junctional and apical domain elements reveals anisotropic localization of Crumbs2, ZO1, and ppMLC. In addition, the localization of two groups of proteins showed a close correlation - actomyosin regulators and apical and junctional components - but there was a lack of correlation of localization of these two groups of proteins to each other. The localization of actomyosin and its activity, was altered and more homogeneous in Crumbs2-/- embryos, and there was a significant decrease in aPKC and Rock1. The authors conclude from these observations that Crumbs2 regulates anisotropic actomyosin contractility to promote apical constriction and cell ingression.

The strengths of this manuscript are the very detailed observations on the process of apical constriction and the meticulous evaluation of the localization of the many proteins likely to be involved in the process. While many of the general observations are not new, Francou et al. provide a much richer understanding of this process, as well as a paradigm with which to evaluate the effects of mutations on the gastrulation process. The figures are beautiful, clear, and informative, and support the conclusions made by the authors. The data provide a very compelling picture of both the dynamics of cell behavior and the anisotropies in protein localization associated with it.

However, much of the Crumbs2 mutant phenotype is not sufficiently explained by the authors' data or conclusions. First, the loss of Crumbs2 does not prevent ingression, as there are mesoderm cells evident between the epiblast and endoderm (Ramkumar et al., 2016, Xiao et al., 2011). There are certainly fewer, and the biggest effect appears to be during the elongation of the axis from E7.75 onward and not during the earlier migratory period (E6.5-E7.75) according to data from both previously published work (Xiao et al., 2011; Ramkumar et al., 2015, 2016) and the data presented here.

• The reviewer makes a good point regarding the defects observed in Crumbs2 mutant embryos. It is true that in this mutant, a first wave of gastrulation EMT, taking place around E6.5, does not appear to be affected. We interpret this to mean that the gastrulation EMT is a sequential process under differential regulation, and that Crumbs2 is not required for the first wave of cells ingression through the primitive streak, at the onset of gastrulation. Consequently, a small number of early mesodermal cells are produced in Crumbs2 mutants. However, within 24hours of the onset of gastrulation, corresponding to around E7.75, ingression defects are evident in Crumbs2 mutant embryos.

• For simplicity, these distinct sequential phases of gastrulation regulation, initially independent of Crumbs2, but subsequently dependent, were not initially discussed in our manuscript. We have now elaborated these details in the revised manuscript.

Nor does the loss of Crumbs2 prevent apical constriction. Ramkumar et al. in their 2016 paper show by live imaging that the major effect of the Crumbs2 mutation is to prevent the cells from detaching from the epithelium, but that the apical domain does undergo constriction, leading to many elongated flask-shaped cells still attached at the apical end. These observations do not fit well with the model proposed by the authors of Crumbs2 regulating anisotropic actomyosin contractility to promote apical constriction and suggest a more complicated story.

• We thank the reviewer for bringing this up, as it is an important point that we now discuss in greater detail and clarify in the revised manuscript.

• Importantly, we do not believe our data are in disagreement with the previous study of Ramkumar et al. The precise details of the defect observed in Crumbs2 mutants are still not totally clear. However, we would like to point out that in Ramkumar et al., the timelapse imaging data did not depict cells constricting their surfaces, but rather these data revealed that cells having small apical surfaces failed to detach and delaminate out of the epiblast layer. Thus, this previous study focused on the subsequent step in the process of ingression (delamination), to that being addressed in the present work.

• Furthermore, epiblast cells outside the domain occupied by the primitive streak, and even some cells positioned on the lateral sides of the embryo, were reported by Ramkumar and colleagues to exhibit abnormally small apical surfaces in Crumbs2 mutants. These cells, at a distance from the primitive streak, will not normally constrict their apical surfaces, since they are not going to undergo the gastrulation EMT, a behavior restricted to the region of the primitive streak. Thus, these previous data do not directly address nor demonstrate that epiblast cells in Crumbs2 mutants undergo apical constriction.

• Moreover, in Crumbs2 mutants a large number of cells were reported to fail to ingress at the primitive streak, and consequently they were seen to accumulate within the epiblast epithelial layer. Indeed, we believe that the small apical surfaces first reported in Crumbs2 mutants by Ramkumar and colleagues, most likely result from the crowding/jamming of cells within the epiblast layer, and that this causes changes in the shape and volume of cells due to them being spatially constrained. Thus, increased crowding of epithelial cells within a spatially constrained tissue, likely drives a reduction in apical surface area and extensive apico-basal elongation, as observed in Crumbs2 mutants.

However, the complications of the Crumbs2 mutant do not detract from the value of the basic observations presented in this manuscript, which are solid and well-documented, and will be a valuable resource for the field.

Reviewer #2 (Public Review):

In their manuscript, Francou and colleagues study the delamination of epiblast cells into the mesodermal layers using live imaging of mouse embryos cultured ex vivo. By segmenting the apical area of delaminating cells, they quantify extensively the dynamic behavior of delaminating cells. Using immunostaining and crumbs2 mutants, they propose that apical constriction of cells results from pulsed contractions, which could be guided by crumbs2 signals.

The manuscript is interesting and provides extremely valuable data for our understanding of mouse gastrulation. Occasionally, the manuscript can be a bit confusing and contains a few inaccuracies.

However, the main issues I have are with some of the interpretations from the authors, which may be incorrect due to limited time resolution (with a 5 min time resolution that was used, it might be difficult to distinguish pulses from measurement noise) and the analysis of immunostaining data, which would require more rigorous quantification.

• We acknowledge the reviewer’s comments and agree that a shorter time resolution would be ideal to facilitate the detection of constriction pulses of apical surfaces. However, we need to consider that imaging the apical surface of cells within the epiblast layer, which constitutes the most internal surface inside the embryo, is technically challenging in a gastrulating mouse embryo.

• As suggested by the reviewer, we attempted to image with a shorter time interval than 5min on several different microscope systems and modalities available at our institution (including two different laser point scanning confocals, a spinning disc system, as well as light-sheet microscopes with both upright and inverted configurations) and were not successful in acquiring usable images (having a shorted time-resolution) with the ZO1GFP knock-in reporter. We also need to consider that single-copy GFP knock-in reporters are often dim, thereby exacerbating the issue. In our hands, a high-speed resonant scanning confocal (Nikon A1RHD25) was the system that gave us the best signal-to-noise ratio, spatial resolution and temporal resolution, and was the set-up we used for our most recent live imaging experiments. Using this system, we were able to acquire a limited number of time-lapses with a time resolution of 2min, but none with a shorter time interval, and from our analyses, we determined that movies with a 2min time interval did not yield increased detail over movies with 5min time intervals to warrant a detailed reanalysis. We have provided additional detail relating to these technical issues within the revised manuscript and edited some of the conclusions.

• We acknowledge that immunostaining is not the most quantitative method, but we were unable to come up with alternative methods that can be used with our samples. We believe the junctional reduction of Myosin, aPKC and Rock1 is generally due to a nonrecruitment or activation of these proteins at junctions, and do not reflect their reduced expression at the gene or protein level. We do not believe that methods such as RTqPCR or Western blotting would be informative in the context in which we are looking, especially since they do not yield spatial resolution. Furthermore, we would need to isolate primitive streak cells to consider applying these methods, and we do not believe they would provide a sufficient improvement over immunostaining.

• By contrast to the live imaging, which was performed by placing the objective at the posterior side of the embryo in closest proximity to the outer visceral endoderm layer, for fixed tissue imaging, embryos were microdissected to recover the posterior side containing the primitive streak. Microdissected posterior regions were imaged on the side of the cavity by placing the objective in closest proximity to the inner epiblast layer, which permitted direct access to the apical surface of epiblast cells at the primitive streak. In this fixed tissue imaging configuration, the apical surfaces of cells in WT and Crumbs2 mutants were in closest proximity to the imaging objective and thus directly accessible. Thus, any difference in tissue thickness on the other side of the epithelium did not interfere with light penetration. We have edited the figures and include schematics to clarify how the objective positions are flipped with respect to the primitive streak regions at the embryo’s posterior for live vs. fixed tissue imaging.

• We have now measured the signal intensity in the cytoplasmic region of WT and Crumbs2 mutant embryos, and junctional intensity measurements have been normalized to cytoplasmic intensities.

Reviewer #3 (Public Review):

The manuscript by Francou et al investigated cellular mechanisms of epiblast ingression during mouse gastrulation. The authors wanted to know whether/how epiblast cell-cell junctional dynamics correlate with apical constriction and subsequent ingression. Because mouse gastrula adopts an inverted-cup morphology (as a result of differential invasive behavior of polar and mural trophoblast cells), epiblast cells are located in the innermost position and are difficult to image. This is more so when one wants to perform live imaging of epiblast cells' apical surface. The authors tackled such problems/limitations by using a combination of ZO-1 GFP line, confocal time-lapse microscopy, fixed embryo immunostaining, and Crumbs2 mutant embryos. The authors observed that apical constriction was associated with cell ingression, that this constriction occurred in a pulsed fashion (i.e., 2-4 cycles with phases of contraction and expansion, eventually leading to reduction of apical surface and ingression), that this constriction took place asynchronously (i.e., neighboring epiblast cells did not exhibit coordinated behavior) and that junctional shrinkage during apical constriction also occurred in a pulsed and asynchronous manner. The authors also investigated localization/co-localization of several apical proteins (Crumbs2, Myosin2B, pMLC, ppMLC, Rock1, F-actin, PatJ, and aPKC) in fixed samples, uncovering somewhat reciprocal distribution of two groups of proteins (represented by Myosin2B in one group, and Crumbs2 in the other). Finally, the authors showed that Crumbs2 -/- embryos had disturbed actomyosin distribution/levels without affecting junctional integrity (partially explaining the ingression defect reported in Crumbs2 -/- mutant embryos). Overall, this manuscript offers high-quality live imaging data on the dynamic remodeling of epiblast apical junctions during mouse gastrulation.

It would be interesting to see whether phenomena reported in this manuscript can be extended to the entire primitive streak (or are they specific only to a subset of mesoderm precursors) and to the entire period of mesendoderm formation. More importantly, it would be interesting to see whether the ingression behavior seen here is representative of all eutherian mammals regardless of their gastrular topography.

• The reviewer raises a very interesting and important point. We focused our data analysis on a middle region in the proximo-distal axis of the embryo, because this is the most optically accessible and the flattest region of the posterior of the embryo to analyze. We also focused on the E7.5 stage of development when the primitive streak is fully elongated, so as to capture as many ingression events within a single time-lapse experiment as possible. Due to the difficulties associated with live imaging the apical epiblast layer of embryos at these stages, we chose to focus our analysis on a defined region of the embryo and a defined period of time. We acknowledge that it will be important to analyze different regions of the primitive streak and at different stages of gastrulation to glean any general versus more distinct modes of epiblast cell ingression, but given the technical difficulties discussed we believe that any extended analysis is beyond the scope of the current study.

• We also agree that it would be interesting to know if the ingression behavior we observe in the mouse embryo is representative of all mammals, and even more generally of amniotes, but this is beyond the scope of our study.

eLife assessment

This study employs live imaging to investigate the movement of mesodermal cells in early mouse embryos. By examining the dynamics of cell behavior in normal and mutant embryos, the authors propose that apical constriction of cells results from pulsed contraction guided by crumbs2 signals. The paper presents beautiful images and adds to the molecular understanding of cell migration during early development.

Reviewer #1 (Public Review):

Francou et al. examine the dynamics of cell ingression at the primitive streak during mouse gastrulation and correlate this with the localization of elements of the apical Crumbs complex and the actomyosin cytoskeleton. Using time-lapse live imaging, they show that cells at the primitive streak ingress in a stochastic manner, by constricting their apical surface through a ratcheting shrinkage of individual junctions. Meticulous evaluation of immunofluorescent staining for many elements of the actomyosin contractile process as well as junctional and apical domain elements reveals anisotropic localization of Crumbs2, ZO1, and ppMLC. In addition, the localization of two groups of proteins showed a close correlation - actomyosin regulators and apical and junctional components - but there was a lack of correlation of localization of these two groups of proteins to each other. The localization of actomyosin and its activity, was altered and more homogeneous in Crumbs2-/- embryos, and there was a significant decrease in aPKC and Rock1. The authors conclude from these observations that Crumbs2 regulates anisotropic actomyosin contractility to promote apical constriction and cell ingression.

The strengths of this manuscript are the very detailed observations on the process of apical constriction and the meticulous evaluation of the localization of the many proteins likely to be involved in the process. While many of the general observations are not new, Francou et al. provide a much richer understanding of this process, as well as a paradigm with which to evaluate the effects of mutations on the gastrulation process. The figures are beautiful, clear, and informative, and support the conclusions made by the authors. The data provide a very compelling picture of both the dynamics of cell behavior and the anisotropies in protein localization associated with it.

However, much of the Crumbs2 mutant phenotype is not sufficiently explained by the authors' data or conclusions. First, the loss of Crumbs2 does not prevent ingression, as there are mesoderm cells evident between the epiblast and endoderm (Ramkumar et al., 2016, Xiao et al., 2011). There are certainly fewer, and the biggest effect appears to be during the elongation of the axis from E7.75 onward and not during the earlier migratory period (E6.5-E7.75) according to data from both previously published work (Xiao et al., 2011; Ramkumar et al., 2015, 2016) and the data presented here. Nor does the loss of Crumbs2 prevent apical constriction. Ramkumar et al. in their 2016 paper show by live imaging that the major effect of the Crumbs2 mutation is to prevent the cells from detaching from the epithelium, but that the apical domain does undergo constriction, leading to many elongated flask-shaped cells still attached at the apical end. These observations do not fit well with the model proposed by the authors of Crumbs2 regulating anisotropic actomyosin contractility to promote apical constriction and suggest a more complicated story. However, the complications of the Crumbs2 mutant do not detract from the value of the basic observations presented in this manuscript, which are solid and well-documented, and will be a valuable resource for the field.

Reviewer #2 (Public Review):

In their manuscript, Francou and colleagues study the delamination of epiblast cells into the mesodermal layers using live imaging of mouse embryos cultured ex vivo. By segmenting the apical area of delaminating cells, they quantify extensively the dynamic behavior of delaminating cells. Using immunostaining and crumbs2 mutants, they propose that apical constriction of cells results from pulsed contractions, which could be guided by crumbs2 signals.

The manuscript is interesting and provides extremely valuable data for our understanding of mouse gastrulation. Occasionally, the manuscript can be a bit confusing and contains a few inaccuracies. However, the main issues I have are with some of the interpretations from the authors, which may be incorrect due to limited time resolution (with a 5 min time resolution that was used, it might be difficult to distinguish pulses from measurement noise) and the analysis of immunostaining data, which would require more rigorous quantification.

Reviewer #3 (Public Review):<br /> <br /> The manuscript by Francou et al investigated cellular mechanisms of epiblast ingression during mouse gastrulation. The authors wanted to know whether/how epiblast cell-cell junctional dynamics correlate with apical constriction and subsequent ingression. Because mouse gastrula adopts an inverted-cup morphology (as a result of differential invasive behavior of polar and mural trophoblast cells), epiblast cells are located in the innermost position and are difficult to image. This is more so when one wants to perform live imaging of epiblast cells' apical surface. The authors tackled such problems/limitations by using a combination of ZO-1 GFP line, confocal time-lapse microscopy, fixed embryo immunostaining, and Crumbs2 mutant embryos. The authors observed that apical constriction was associated with cell ingression, that this constriction occurred in a pulsed fashion (i.e., 2-4 cycles with phases of contraction and expansion, eventually leading to reduction of apical surface and ingression), that this constriction took place asynchronously (i.e., neighboring epiblast cells did not exhibit coordinated behavior) and that junctional shrinkage during apical constriction also occurred in a pulsed and asynchronous manner. The authors also investigated localization/co-localization of several apical proteins (Crumbs2, Myosin2B, pMLC, ppMLC, Rock1, F-actin, PatJ, and aPKC) in fixed samples, uncovering somewhat reciprocal distribution of two groups of proteins (represented by Myosin2B in one group, and Crumbs2 in the other). Finally, the authors showed that Crumbs2 -/- embryos had disturbed actomyosin distribution/levels without affecting junctional integrity (partially explaining the ingression defect reported in Crumbs2 -/- mutant embryos). Overall, this manuscript offers high-quality live imaging data on the dynamic remodeling of epiblast apical junctions during mouse gastrulation. It would be interesting to see whether phenomena reported in this manuscript can be extended to the entire primitive streak (or are they specific only to a subset of mesoderm precursors) and to the entire period of mesendoderm formation. More importantly, it would be interesting to see whether the ingression behavior seen here is representative of all eutherian mammals regardless of their gastrular topography.

Author Response

Reviewer #2 (Public Review):

Throughout the manuscript, the authors aim to distinguish signal from the lack of it. All conclusions depend on the success of this process. In such an endeavor, the sensitivity of the applied methods is critical. Thus, the authors must use the most sensitive tools to draw meaningful conclusions. The latest iGluSnFR has amazing sensitivity allowing the detection of single AP-evoked responses. This is not the case for vGpH, which requires hundred APs to get a meaningful signal. Similar, synthetic Ca2+ dyes have much better dynamic range, linearity and sensitivity compared to GCaMP6f.

The rate of silent boutons at 2 mM [Ca2+]e is lower for a single AP compared to 20 or 200 APs. The overall failure rate cannot be increased with increasing the number of APs. This clearly indicates a technical issue (e.g. insufficient sensitivity of vGpH and GCaMP6f).

We thank the reviewer for raising this concern. We attribute the relatively lower rate of silencing with 1 AP in [Ca2+]e 2.0 mM in neurons expressing iGluSnFr to its sensitivity to detect glutamate exocytosed from neighboring, possibly non-transfected terminals. This limitation is described in the manuscript (page 7, line 26 – page 8, line 5). The overall agreement in the proportion of silencing with iGluSnFr compared to physin-GCaMP or vGpH at lower [Ca2+]e, where the contributions from neighboring terminals is likely greatly diminished, supports this interpretation.

The authors used three different measuring tools and used three different stimulation protocols, making the interpretation of the data challenging. It is impossible to tell how the failure rate changes from 1 to 20 APs without knowing the release probability, the pool size, depletion, recovery of SVs, and facilitation. These are all unknown.

In an ideal world, a measure of release probability during a train of stimuli at varied [Ca2+]e would provide the most insight, but this is difficult to achieve with any of the existing methods, including the remarkable new iGluSnFR. The challenge we face is, for our approach, it is impossible to exclude signals from neighboring axons that are closely packed near the axon harboring the indicator. This limitation is described in the manuscript (page 7, line 26 – page 8, line 5). Given this, we felt that showing that silencing can be revealed with all the different techniques was the most conservative approach to address the issue. Because we have focused on this phenomenon, the number of APs is experimentally important only to ensure an adequate response could be detected. We have also included, in the discussion, an acknowledgement of the possibility that we are failing to detect minimal Ca2+ entry (see response to #8 from the synthesized review).

The last experiment with the GABAB agonist has little novelty in its present form. The authors demonstrate that GABAB agonism increases the rate of silent terminals. The interesting issue would be to reveal how the effect of GABAB activation depends on the [Ca2+]e. This information is essential to see whether there is indeed a shoulder in its effectiveness curve.

We are grateful to the reviewer for this recommendation and we have performed additional experiments (see response to #7 from the synthesized review).

The authors refer to a theoretical set-point in [Ca2+]e below which the function of the terminals is fundamentally different. From the presented experiments, the reviewer does not see any data that is inconsistent with a continuum. 'Thus, as with Ca2+ influx, SV recycling is modulated in an all-or-none manner by modest changes in [Ca2+]e around the physiological set point.' This statement is not supported by the data. The reviewer cannot see a set point.

We appreciate the reviewer’s criticism and wish to clarify that we mean the normal physiologic [Ca2+]e in the CSF. We have changed the text to clarify this point (page 7, line 20).

eLife assessment

The authors revisit fundamentals of synaptic transmission using a combination of advanced optical methods capable of visualizing calcium influx and neurotransmitter release at single release sites. By doing so, the authors present evidence for silencing of neurotransmitter release at single release sites as a function of external calcium. The data have relevance to a wide range of phenomena including neural plasticity and inhibitory modulation of synaptic communication.

Reviewer #1 (Public Review):

This is a fascinating effort from the Ryan laboratory, revisiting fundamental issues of calcium-dependent release probability at cultured synapses. The authors point out that our basic understanding of mammalian synapses rests on a foundation of older research that was not acquired at physiological temperature, and represented a statistical interpretation of data acquired electrophysiologically without direct knowledge of release at individual active zones. The authors employ techniques of calcium imaging and glutamate sensing and argue that single synapses can be 'silenced' by a moderate drop in extracellular calcium, a drop that is within the range of calcium channel inhibition following activation of GABAergic signaling. While fascinating, the conclusions are most powerful when the data can be distilled to direct observation of single release sites and this is not uniformly the case.

Reviewer #2 (Public Review):

Throughout the manuscript, the authors aim to distinguish signal from the lack of it. All conclusions depend on the success of this process. In such an endeavor, the sensitivity of the applied methods is critical. Thus, the authors must use the most sensitive tools to draw meaningful conclusions. The latest iGluSnFR has amazing sensitivity allowing the detection of single AP-evoked responses. This is not the case for vGpH, which requires hundred APs to get a meaningful signal. Similar, synthetic Ca2+ dyes have much better dynamic range, linearity and sensitivity compared to GCaMP6f.

The rate of silent boutons at 2 mM [Ca2+]e is lower for a single AP compared to 20 or 200 APs. The overall failure rate cannot be increased with increasing the number of APs. This clearly indicates a technical issue (e.g. insufficient sensitivity of vGpH and GCaMP6f).

The authors used three different measuring tools and used three different stimulation protocols, making the interpretation of the data challenging. It is impossible to tell how the failure rate changes from 1 to 20 APs without knowing the release probability, the pool size, depletion, recovery of SVs, and facilitation. These are all unknown.

The last experiment with the GABAB agonist has little novelty in its present form. The authors demonstrate that GABAB agonism increases the rate of silent terminals. The interesting issue would be to reveal how the effect of GABAB activation depends on the [Ca2+]e. This information is essential to see whether there is indeed a shoulder in its effectiveness curve.

The authors refer to a theoretical set-point in [Ca2+]e below which the function of the terminals is fundamentally different. From the presented experiments, the reviewer does not see any data that is inconsistent with a continuum. 'Thus, as with Ca2+ influx, SV recycling is modulated in an all-or-none manner by modest changes in [Ca2+]e around the physiological set point.' This statement is not supported by the data. The reviewer cannot see a set point.

Reviewer #3 (Public Review):

In this study Cook and Ryan examine, at physiological temperatures, the sensitivity of neurotransmitter release to external calcium concentrations close to physiological ones. Using hippocampal neurons in culture, field potential-based stimulation, a spatially confined genetically encoded calcium indicator (GCaMP6f) as well as fluorescent reporters of exocytosis and extracellular glutamate, the authors show that as extracellular calcium concentrations are reduced from 2.0, to 1.2 and finally to 0.8 mM, a disproportional fraction of presynaptic terminals cease to respond, as evidenced by no elevations in intracellular calcium concentrations, no detectable exocytosis or changes in extracellular glutamate. The phenomenon is quantitively modulated by blocking particular types of calcium channels, but is qualitatively conserved across all tested conditions. Finally, the authors show that effects of lower extracellular calcium concentrations can be mimicked by applying Baclofen, an agonist of type B GABA receptors. The authors reveal the sensitivity of all-or none calcium influx and exocytosis near extracellular calcium physiological set points and highlight the potential importance of this sensitivity as an effective control point for neural circuit modulation.

The findings described in the manuscript are potentially important as they seem to uncover a new, yet undescribed, all-or none (binary) phenomenon in the field of synaptic neuroscience, that is, of individual presynaptic terminals moving between two 'states' - 'active' and 'silenced'- which are set somehow by levels of extracellular calcium concentrations. Moreover, this dependency is observed at extracellular calcium concentrations that are quite close to the physiological concentration set point. The use of multiple reporters (intracellular calcium concentrations, synaptic vesicle fusion and extracellular glutamate) strengthens the validity of the observations.

On the other hand, there are two major points that need to be addressed.

The first is that alternative explanations should be ruled out more convincingly, first and foremost the matter of membrane excitability. Two observations are relevant here: The qualitative preservation of the phenomenon when two types of voltage gated calcium channels are blocked separately, and the large heterogeneity of the % of silenced boutons among neurons at a given extracellular calcium concentrations, which is at least as great as the range of modulation of the % of silenced synapses by extracellular calcium concentrations at single neurons. One then wonders if the findings might be attributed to a) the fidelity of the field potential-based stimulation system, that is, the degree to which neurons track the stimuli trains; b) the heterogeneity of neurons in this regard, c) this fidelity at different extracellular calcium concentrations for different neurons, and d) the identity of presynaptic sites analyzed in one run (are they all part of the same axon?). Along these lines, there is an assumption that the field potential-based stimulation system is the sole driver of excitation in these networks, which is reasonable given that excitatory synaptic transmission is mostly blocked pharmacologically (by CNQX and APV). Inhibitory transmission, however, was not blocked and thus, there is no guarantee that the inhibitory input neurons receive and its modulation by extracellular calcium does affect the degree to which neurons fire precisely and reliably at 20 Hz at all conditions. If it could be shown, at least for a substantial subset of the data, that all terminals analyzed for a particular neuron are part of an unambiguously identified axon stretch, with no branches (potential conduction failure points) and still demonstrate the claimed heterogeneity, this potential confound would be less of an issue.

The second issue relates to the ties made to neuromodulation. In spite of the title, introduction and discussion, not a single neuromodulator (such as dopamine, acetylcholine, noradrenaline, serotonin) was tested, only baclofen, which as a derivative of GABA, activates GABAB receptors, not receptors of canonical neuromodulators. The title of this manuscript is therefore not appropriate.

Author Response

Reviewer #1 (Public Review):

While the mechanism about arm-races between plant and specialist herbivores has been studied, such as detoxification of specific secondary metabolites, the mechanism of the wider diet breadth, so-called generalist herbivores have been less studied. Since the heterogeneity of host plant species, the experimental validation of phylogenetic generalism of herbivores seemed as hard to be conducted. The authors declared the two major hypotheses about the large diet breadth ("metabolic generalism" and "multi-host metabolic specialism"), and carefully designed the experiment using Drosophila suzukii as a model herbivore species.

By an untargeted metabolomics approach using UHPLC-MS, authors attempted to falsify the hypotheses both in qualitative- and quantitative metabolomic profiles. Intersections of four fruit (puree) samples and each diet-based fly individual samples from the qualitative data revealed that there were few ions that occur as the specific metabolite in each diet-based fly group, which could reject the "multi-host metabolic specialism" hypothesis. Quantitative data also showed results that could support the "metabolic generalism" hypothesis. Therefore, the wide diet breadth of D. suzukii seemed to be derived from the general metabolism rather than the adaptive traits of the diverse host plant species. On the other hand, the reduction of the metabolites (ions) set using GLM seemed logical and 2-D clustering from the reduced ions set showed that quantitative aspects of diet-associated ions could classify "what the flies ate". These interesting results could enhance the understanding of the diet breadth (niche) of herbivorous insects.

The authors' approach seemed clear to falsify the hypotheses based on the appropriate data processing. The intersection of shared ions from the qualitative dataset could distinguish the diet-specific metabolites in flies and commonly occurring metabolites among flies and/or fruits. Also, filtering on the diet-specific ions seemed to be a logical and appropriate way. Meanwhile, the discussion about the results seemed to be focused on different points regarding the research hypotheses which were raised in the introduction part. Discussion about the results mainly focused on the metabolism of D. suzukii itself, rather than the research hypotheses and questions that were raised from the evolution of the wide diet breadth of generalist herbivores. In particular, the conclusion seems to be far from the main context of the authors' research; e.g. frugivory. It makes the implication of the study weaker.

We wish to thank Reviewer #1 for their appreciation of our study. As recommended, we now focus our discussion more on the general aspect of our findings (relevant to insects, herbivores, or frugivores), and less on the peculiarities of the metabolism of D. suzukii itself. Specifically, we now only mention D. suzukii in one section (two sentences) of our Discussion, to serve as an example (l.387-396). Thanks to this comment, the Discussion may interest a broader readership, on the evolution of diet breadth in generalist herbivorous species and offers a better understanding of the general implications of our findings.

Reviewer #2 (Public Review):

The manuscript: "Metabolic consequences of various fruit-based diets in a generalist insect species" by Olazcuaga et al., addresses an interesting question. Using an untargeted metabolomics approach, the authors study how diet generalism may have evolved versus diet specialization which is generally more commonly observed, at least in drosophila species. Using the phytophagous species Drosophila suzukii, and by directly comparing the metabolomes of fruit purees and the flies that fed on them, the authors found evidence for "metabolic generalism". Metabolic generalism means that individuals of a generalist species process all types of diet in a similar way, which is in contrast to "multi-host metabolic specialism" which entails the use of specific pathways to metabolize unique compounds of different diets. The authors find strong evidence for the first hypothesis, as they could easily detect the signature of each fruit diet in the flies. The authors then go on to speculate on the evolutionary ramifications of this for how potentially diet specializations may have evolved from diet generalism. Overall, the paper is well written, the experiments well documented, and the conclusions convincing.

We thank Reviewer #2 for their comments and appreciation of our work.

Reviewer #3 (Public Review):

Laure Olazcuaga et al. investigated the metabolomes of four fruit-based diets and corresponding individuals of Drosophila suzukii that reared on them using comparative metabolomics analysis. They observed that the four fruit-based diets are metabolically dissimilar. On the contrary, flies that fed on them are mostly similar in their metabolic response. From a quantitative point of view, they find that part of the fly metabolomes correlates well with that of the corresponding diet metabolomes, which is indicative of insect ingestive history. By further focusing on 71 metabolites derived from diet-specific fly ions and highly abundant fruit ions, the authors show that D. suzukii differentially accumulates diet metabolism in a compound-specific manner. The authors claim that the data support the metabolic generalism hypothesis while rejecting the multi-host metabolic specialism hypothesis. This study provides a valuable global chemical comparison of how diverse diet metabolites are processed by a generalist insect species.

Strengths:

The rapid advances in high-resolution mass spectrometry have recently accelerated the discovery of many novel post-ingestive compounds through comparative metabolomics analysis of insect/frass and plant samples. Untargeted metabolomics is thus a very powerful approach for the systematic comparison of global chemical shifts when diverse plant-derived specialized metabolites are further modified or quantitatively metabolized after ingestion by insects. The technique can be readily extended to a larger micro- or macro-evolutionary context for both generalist and specialist insects to systematically investigate how plant chemical diversity contributes to dietary generalism and specialism.

We would like to thank Reviewer #3 for their insightful comments on the power of untargeted metabolomics to evaluate the fate of plant metabolites and their use by herbivores. We also agree that these techniques can be used to tackle eco-evolutionary issues, such as the origin and maintenance of dietary generalism and specialism here. We hope that our study will inspire other researchers to explore such techniques and experiments to gain a global overview of biochemistry fluxes and their evolution. We now mention it in the conclusion (L454-459).

Weaknesses:

The authors claim that their data support the hypothesis of metabolic generalism, however, a total analysis of insect metabolism may not generate a clean dataset for direct comparison of fruit-derived metabolites with those metabolized by D. suzukii, given that much of these metabolites would be "diluted" proportionally by insect-derived metabolites. If the insect-derived metabolites predominate, then, as the authors observed, a tight clustering of D. suzukii metabolomes in the PCA plot would be expected. It is therefore very difficult to interpret these patterns.

We agree with Reviewer #3 that a careful examination of the different possible origins of metabolites should take place to distinguish between our two competing hypotheses.

The only source of metabolites for insects in our experimental setup is a mixture of (i) a large proportion of fruit purees and (ii) a minor proportion of artificial medium consisting mainly of yeast. Our goal is thus to understand the fate of (i) “fruit-derived” metabolites (transformed and untransformed), while controlling for (ii) “artificial media-derived” metabolites, that constitute a nuisance signal but are necessary for a complete development in our system.

By “fruit-derived” and “insect-derived” metabolites, it is our understanding that Reviewer #3 means “fruit” metabolites (when in insects, untransformed “fruit-derived” metabolites) and “artificial medium-derived” metabolites. It is true that we do wish to avoid a predominance of “artificial medium-derived” metabolites and focus on “fruit-derived” metabolites in insects. We also want to note that it is of primary importance in our study to distinguish between “fruit” metabolites that are carried as is (“fruit” metabolites present in insects, ie untransformed “fruit-derived” metabolites), and “fruit” metabolites that are used after transformation by the insect (i.e., transformed “fruit-derived” metabolites).

We agree with Reviewer #3 that the presence of “artificial medium-derived” metabolites could be problematic in direct comparisons of fruits and insects (and not among fruits or among insects’ comparisons).

However, we took some steps to avoid such problems:

1. We included control fly samples in our experiment: at each experimental generation, flies developed only on artificial medium (without fruit puree) were collected and processed simultaneously with flies that developed on fruit media. Results using these artificial medium-reared flies as controls (by subtracting their ions levels and removing ions that were similar, respective of their generation) were similar to results using raw data and conclusions were identical (see below).

2. We lowered the proportion of artificial medium in our fruit media so that it was kept to a minimum, compatible with larval development and adult survival.

Consistent with the low impact of this “artificial medium” component on our conclusions, we also wish to point out the presence pattern of metabolites found only in flies and never in fruits when using raw data (Figure 3, yellow stack). Even in the most conservative hypothesis of 100% of these metabolites originating from our artificial medium (which is probably not the case), we observe that it constitutes only a minor proportion of metabolites common to all flies (15.7%).

For your consideration, we include below the main Figures, using both raw data and artificial medium-controlled:

Figure 2, left = raw data; right = artificial-media controlled:

Figure 3, left = raw data; right = artificial-media controlled:

Figure 3S1, left = raw data; right = artificial-media controlled:

Figure 4, above = raw data; below = artificial-media controlled:

We hope that we convinced the Editor/Reviewers that raw data and artificial-medium controlled data provide a single and same answer to all our analyses. We chose to present only raw data, to simplify the Materials & Methods section.

We however modified the current version of the manuscript to inform the reader that proper controls were done and that their inclusion do not modify any of our conclusions (l.110-113 and l.583-589).

We also wish to point out two additional comments:

• As Reviewer #1 also recommended, we modified the expectations drawn in Fig1G to better consider the general comment of “insect derived” metabolites being fundamentally different from plant metabolites (even if we do show in our study that only approx. 9% of metabolites are private to flies).

• The main part of our care in the use of this global PCA analysis is that it follows two other analyses (global intersection and comparison of intersections among fruits and among flies) and precedes another one (fly-focused PCA). We hope that all these analyses help the readers get a comprehensive overview of the dataset and associated results, avoiding reliance on a single analysis.

• We also help readers to explore and visualize all analyses presented in our manuscript by setting up a shiny application (in addition to our available dataset and R code), at https://fruitfliesmetabo.shinyapps.io/shiny/. This is now mentioned in the main text (l.588-589).

We thank the Reviewer for their comment that greatly improved the manuscript.

The authors generated a qualitative dataset using the peak list produced by XCMS which contains quantitative peak areas, it is unclear how the threshold was selected to determine if a peak is present or absent in a given sample. The qualitative dataset would influence the output of their data analysis.

The referee is right in pointing out that the threshold used to determine if a peak is present or absent in a given sample was not clearly specified. This has now been corrected in the “Host use” section of the Materials & Methods (l.513-516). Briefly, a given replicate of a compound was considered present if the corresponding peak area following XCMS quantification was > 1000. This threshold was selected to be close to the practical quantification threshold of the Thermo Exactive mass spectrometer used in this study. This threshold was selected in order to allow the quantification of low-abundance compounds, as many plant-derived diet compounds were expected to be present in trace amounts in flies. We additionally applied a stringent rule for presence of any given compound (presence in at least 3 biological replicates).

The authors reply on in-source fragmentation for peak annotation when authentic standards are not available. The accuracy of the annotation thus requires further validation.

The Supplementary Table 1 was unfortunately omitted in the first submission of the manuscript. This oversight has been now corrected and the Supplementary Table 1 details all information used for metabolite annotation. In particular, MS/MS data comparison with mass spectral databases as well as with published literature have been added to substantiate metabolite identifications. This MS/MS data was produced thanks to the comment of the Reviewer. We also provide four more annotations from standards to attain 30 / 71 identifications validated through chemical standards.

eLife assessment

This useful study uses untargeted metabolomics to help us understand how some herbivores are able to be generalists, rather than specializing in the metabolism of specific plant species. This is an important area, since little is known about how generalist insect species metabolize their food. In its current form, the study lacks ecological relevance due to the exclusive use of refined sampling procedures, and the metabolomic analysis is incomplete.

Reviewer #1 (Public Review):

While the mechanism about arm-races between plant and specialist herbivores has been studied, such as detoxification of specific secondary metabolites, the mechanism of the wider diet breadth, so-called generalist herbivores have been less studied. Since the heterogeneity of host plant species, the experimental validation of phylogenetic generalism of herbivores seemed as hard to be conducted. The authors declared the two major hypotheses about the large diet breadth ("metabolic generalism" and "multi-host metabolic specialism"), and carefully designed the experiment using Drosophila suzukii as a model herbivore species.

By an untargeted metabolomics approach using UHPLC-MS, authors attempted to falsify the hypotheses both in qualitative- and quantitative metabolomic profiles. Intersections of four fruit (puree) samples and each diet-based fly individual samples from the qualitative data revealed that there were few ions that occur as the specific metabolite in each diet-based fly group, which could reject the "multi-host metabolic specialism" hypothesis. Quantitative data also showed results that could support the "metabolic generalism" hypothesis. Therefore, the wide diet breadth of D. suzukii seemed to be derived from the general metabolism rather than the adaptive traits of the diverse host plant species. On the other hand, the reduction of the metabolites (ions) set using GLM seemed logical and 2-D clustering from the reduced ions set showed that quantitative aspects of diet-associated ions could classify "what the flies ate". These interesting results could enhance the understanding of the diet breadth (niche) of herbivorous insects.

The authors' approach seemed clear to falsify the hypotheses based on the appropriate data processing. The intersection of shared ions from the qualitative dataset could distinguish the diet-specific metabolites in flies and commonly occurring metabolites among flies and/or fruits. Also, filtering on the diet-specific ions seemed to be a logical and appropriate way. Meanwhile, the discussion about the results seemed to be focused on different points regarding the research hypotheses which were raised in the introduction part. Discussion about the results mainly focused on the metabolism of D. suzukii itself, rather than the research hypotheses and questions that were raised from the evolution of the wide diet breadth of generalist herbivores. In particular, the conclusion seems to be far from the main context of the authors' research; e.g. frugivory. It makes the implication of the study weaker.

Reviewer #2 (Public Review):

The manuscript: "Metabolic consequences of various fruit-based diets in a generalist insect species" by Olazcuaga et al., addresses an interesting question. Using an untargeted metabolomics approach, the authors study how diet generalism may have evolved versus diet specialization which is generally more commonly observed, at least in drosophila species. Using the phytophagous species Drosophila suzukii, and by directly comparing the metabolomes of fruit purees and the flies that fed on them, the authors found evidence for "metabolic generalism". Metabolic generalism means that individuals of a generalist species process all types of diet in a similar way, which is in contrast to "multi-host metabolic specialism" which entails the use of specific pathways to metabolize unique compounds of different diets. The authors find strong evidence for the first hypothesis, as they could easily detect the signature of each fruit diet in the flies. The authors then go on to speculate on the evolutionary ramifications of this for how potentially diet specializations may have evolved from diet generalism. Overall, the paper is well written, the experiments well documented, and the conclusions convincing.

Reviewer #3 (Public Review):

Laure Olazcuaga et al. investigated the metabolomes of four fruit-based diets and corresponding individuals of Drosophila suzukii that reared on them using comparative metabolomics analysis. They observed that the four fruit-based diets are metabolically dissimilar. On the contrary, flies that fed on them are mostly similar in their metabolic response. From a quantitative point of view, they find that part of the fly metabolomes correlates well with that of the corresponding diet metabolomes, which is indicative of insect ingestive history. By further focusing on 71 metabolites derived from diet-specific fly ions and highly abundant fruit ions, the authors show that D. suzukii differentially accumulates diet metabolism in a compound-specific manner. The authors claim that the data support the metabolic generalism hypothesis while rejecting the multi-host metabolic specialism hypothesis. This study provides a valuable global chemical comparison of how diverse diet metabolites are processed by a generalist insect species.

Strengths:<br /> The rapid advances in high-resolution mass spectrometry have recently accelerated the discovery of many novel post-ingestive compounds through comparative metabolomics analysis of insect/frass and plant samples. Untargeted metabolomics is thus a very powerful approach for the systematic comparison of global chemical shifts when diverse plant-derived specialized metabolites are further modified or quantitatively metabolized after ingestion by insects. The technique can be readily extended to a larger micro- or macro-evolutionary context for both generalist and specialist insects to systematically investigate how plant chemical diversity contributes to dietary generalism and specialism.

Weaknesses:<br /> The authors claim that their data support the hypothesis of metabolic generalism, however, a total analysis of insect metabolism may not generate a clean dataset for direct comparison of fruit-derived metabolites with those metabolized by D. suzukii, given that much of these metabolites would be "diluted" proportionally by insect-derived metabolites. If the insect-derived metabolites predominate, then, as the authors observed, a tight clustering of D. suzukii metabolomes in the PCA plot would be expected. It is therefore very difficult to interpret these patterns.

The authors generated a qualitative dataset using the peak list produced by XCMS which contains quantitative peak areas, it is unclear how the threshold was selected to determine if a peak is present or absent in a given sample. The qualitative dataset would influence the output of their data analysis.

The authors reply on in-source fragmentation for peak annotation when authentic standards are not available. The accuracy of the annotation thus requires further validation.

eLife assessment

This valuable study provides solid results on the molecular signaling mechanisms of CaM kinase kinase-1 (CKK-1) in the context of the nociceptive behaviors of C. elegans. The authors report previously undescribed elements that control the nuclear/cytoplasmic shuttling of CKK-1, suggesting a complex interplay of multiple nuclear localization and export sequences. Therefore, the work will be of broad interest to scientists studying behavior, neuronal signaling, and signal transduction in general.

Reviewer #1 (Public Review):

Habituation to noxious insults is a conserved mechanism that may act through varying pain-sensitivity thresholds based on previous sensory experience. Impaired regulation of nociceptive habituation may lead to a chronic pain condition. In the current manuscript, the authors identified additional structural elements of the CaM kinase-1 that regulate the protein shuttling between the cytosol and nucleus during nociceptive habituation. Based on the presented findings, we get a more complex regulatory model and a better understanding of the CMK-1 protein redistribution during stimulation-dependent nociceptive plasticity.

The data is carefully planned and results conclusively support the claims of the authors. The performed experiments are easy to follow and the results obtained are robust and statistically well-powered. The complex regulatory model presented in the manuscript is well supported by the reported data. Finally, the presented data presents a complex and dynamic mechanism of nuclear import and export rates of the CMK-1 protein to control nociceptive plasticity.

Reviewer #2 (Public Review):

In this study, Ippolito and colleagues elucidated the molecular mechanism of CMK-1 shuttling between the nucleus and cytoplasm and its function in the context of regulated thermosensation in C. elegans. This study is built on their previous work that identified a specific Nuclear Export Sequence (NES) required for CMK-1 cytoplasmic localization at 20{degree sign}C, and a specific Nuclear Localization Signal (NLS) to promote prolonged heat (28{degree sign}C)-induced CMK-1 nuclear entry. Here they show additional functional NES and NLS which counteract previously identified elements: the NLS297-307-dependent nuclear entry pathway and the S325-dependent cytoplasmic accumulation. Combined with their previous study, their work suggests a model: upon prolonged FLP neuron stimulation by noxious heat, CaM binding to CMK-1 causes CKK-1-dependent phosphorylation of T179, which in turn has a context-dependent dual effect: it is sufficient for nuclear translocation at 20{degree sign}C in an NLS71-78-dependent manner, and it promotes NES288-294-dependent nuclear export at 28{degree sign}C.

The authors thereby established a direct link between the state of a signal transduction pathway and FLP neuronal activity in response to heat stimulation. They used multiple approaches, including transgenics and reporter quantification analysis to characterize CMK-1 nucleo-cytoplasmic dynamic equilibrium. The experiments are well-designed with appropriate controls and appropriate sample sizes. The data analysis is comprehensive and revealing. The findings expand the functionally relevant intrinsic CMK-1 subcellular localization determinants. The new understanding generated in this study will appeal to readers in the fields of cell biology, signal transduction, and physiology.

eLife assessment

This important study proposes a phenomenologically motivated theoretical framework to explain observed patterns of the temperature dependence of microbial diversity. The methodology is overall convincing, but the explanations of approximations and assumptions, and of their regime of validity, are incomplete. The manuscript should be of interest to microbial ecologists.

Reviewer #1 (Public Review):

In this work, the authors propose a phenomenological grounded theoretical framework to explain why microbial taxonomic richness can show positive, unimodal, as well as negative diversity-temperature gradients. They thus propose to introduce a temperature dependence in the form of the Boltzmann-Arrhenius equation in both species' competitive interaction and growth rates. By means of a mean-field-like approximation, they estimate the probability of having N feasible coexisting species as a function of the normalized growth rate, and average competition strength, which in turn depends on temperature. They find that the shape of the microbial community temperature-richness relationship depends on how rapidly the strength of competition between species pairs increases with temperature relative to an increase in the variance of their growth rates. Furthermore, the mean-field result predicts that the position of richness peak depends on the sign of the covariance between the two main parameters of the Boltzmann-Arrhenius law. Finally, they show that the real-world community-level temperature-richness responses observed are qualitatively reproduced by their model.

I found the work interesting and stimulating, surely tackling a relevant research question such as the effect of thermal physiology on biodiversity patterns through a simple, but quantitative model. Overall, I like the proposed approach.

At the same time, the central mathematical results are not clear in my view, some strong approximations are not discussed, but they hold only in very specific conditions. A lot of important details are missing or scattered here and there, the notation is a little sloppy, and in general, it has been difficult for me to reproduce their finding.

The overall structure and flow of the manuscript can be remarkably improved.

Reviewer #2 (Public Review):

In their paper Variation in thermal physiology can drive the temperature dependence of microbial community richness, Clegg and Parwar present a relatively simple phenomenological model for explaining the wide variety of empirically observed relationships between temperature and diversity in the microbial world. Previous theories such as the Metabolic theory of biodiversity (MTB) and the metabolic niche hypothesis have emphasized the role of energy through either more efficient cellular kinetics or temperature-dependent niches. This paper builds on these works by showing that if one accounts for the variation of temperature sensitivity across species, one can get a much richer set of behaviors consistent with empirical observations.

Overall, I find the manuscript quite compelling and the model presented as a very nice summary of how variability in temperature dependence, simple Arrhenius scaling, and arguments based on modern coexistence theory can be combined to explain empirical observations of species abundance distributions and temperature.

Reviewer #3 (Public Review):

In empirical data, the dependence of microbial diversity on environmental temperature can take multiple different functional forms, while the previous theory has not established a clear understanding of when the temperature-dependence of diversity should take a particular form, and why. The authors seek to understand what forms are possible, and when they will occur, via analysis of the feasibility (i.e. positivity) of Lotka-Volterra equation solutions. This is combined with an assumption for the way that species' growth rates depend on temperature, along with an assumption for the way species interaction rates depend on temperature. Together, this completely specifies the form of the Lotka-Volterra equations, and whether all species in the model can coexist indefinitely at a given temperature, or whether only a lower-diversity subset can persist.

The overall goal is valuable, and the overall approach of using this classic model of species interactions is justifiable. My main question marks relate to the way the conditions on feasibility (i.e. when all species will have positive equilibria), whether and when we need to consider the stability of these feasible solutions, and finally how general the way in which model parameters are specified to depend on temperature. I will expand on these three issues below. A more minor issue is that the authors set up this problem with extensive reference to the interaction of consumers and resources, referencing previous approaches that explicitly model these. Since resources are not explicitly present in the Lotka-Volterra formalism, it would be helpful to have a clearer justification for the authors' rationale in choosing this kind of model.

(1) Conditions on growth and interaction rates for feasibility and stability. The authors approach this using a mean field approximation, and it is important to note that there is no particular temperature dependence assumed here: as far as it goes, this analysis is completely general for arbitrary Lotka-Volterra interactions.

However, the starting point for the authors' mean field analysis is the statement that "it is not possible to meaningfully link the structure of species interactions to the exact closed-form analytical solution for [equilibria] 𝑥^*_𝑖 in the Lotka-Volterra model.

I may be misunderstanding, but I don't agree with this statement. The time-independent equilibrium solution with all species present (i.e. at non-zero abundances) takes the form

x^* = A^{-1}r

where A is the inverse of the community matrix, and r is the vector of growth rates. The exceptions to this would be when one or more species has abundance = 0, or A is not invertible. I don't think the authors intended to tackle either of these cases, but maybe I am misunderstanding that.

So to me, the difficulty here is not in writing a closed-form solution for the equilibrium x^*, it is in writing the inverse matrix as a nice function of the entries of the matrix A itself, which is where the authors want to get to. In this light, it looks to me like the condition for feasibility (i.e. that all x^* are positive, which is necessary for an ecologically-interpretable solution) is maybe an approximation for the inverse of A---perhaps valid when off-diagonal entries are small. A weakness then for me was in understanding the range of validity of this approximation, and whether it still holds when off-diagonal entries of A (i.e. inter-specific interactions) are arbitrarily large. I could not tell from the simulation runs whether this full range of off-diagonal values was tested.

As a secondary issue here, it would have been helpful to understand whether the authors' feasible solutions are always stable to small perturbations. In general, I would expect this to be an additional criterion needed to understand diversity, though as the authors point out there are certain broad classes of solutions where feasibility implies stability.

(2) I did not follow the precise rationale for selecting the temperature dependence of growth rate and interaction rates, or how the latter could be tested with empirical data, though I do think that in principle this could be a valuable way to understand the role of temperature dependence in the Lotka-Volterra equations.

First, as the authors note, "the temperature dependence of resource supply will undoubtedly be an important factor in microbial communities"

Even though resources aren't explicitly modeled here, this suggests to me that at some temperatures, resource supply will be sufficiently low for some species that their growth rates will become negative. For example, if temperature dependence is such that the limiting resource for a given species becomes too low to balance its maintenance costs (and hence mortality rate), it seems that the net growth rate will be negative. The alternative would be that temperature affects resource availability, but never such that a limiting resource leads to a negative growth rate when a taxon is rare.

On the other hand, the functional form for the distribution of growth rates (eq 3) seems to imply that growth rates are always positive. I could imagine that this is a good description of microbial populations in a setting where the resource supply rate is controlled independently of temperature, but it wasn't clear how generally this would hold.

Secondly, while I understand that the growth rate in the exponential phase for a single population can be measured to high precision in the lab as a function of temperature, the assumption for the form of the interaction rates' dependence on temperature seems very hard to test using empirical data. In the section starting L193, the authors seem to fit the model parameters using growth rate dependence on temperature, but then assume that it is reasonable to "use the same thermal response for growth rates and interactions". I did not follow this, and I think a weakness here is in not providing clear evidence that the functional form assumed in Equation (4) actually holds.

eLife assessment

In this study, the authors made important progress in understanding bone metabolic defects of T2D. They have established a valuable model that could mimic some aspects of T2D in mice. Particularly, the study provided important evidence showing bone turnover and metabolism were in defects, and changes in glycolysis would rescue bone defects in T2D. Overall, the authors provide compelling evidence from dynamic histomorphometry, C13 isotype labeling in vivo, scRNA-seq, and metabolic assays to demonstrate that the defective glucose metabolism causes osteopenia associated with T2D.

Reviewer #1 (Public Review):<br /> <br /> T2D in youth has been reported to reduce bone mass due to impaired bone anabolism, but the underlying mechanisms are not fully understood. The authors study the relationship between T2DM (Type 2 Diabetes Mellitus) and "skeletal fragility." Specifically, they look at glucose metabolism defects in osteoblasts during T2DM and their impacts on osteoblast activity. The results are novel as they elucidate the effects of low-dose STZ models of T2DM on osteoblast function and the function of osteoblasts from those mice in terms of glycolysis, glucose uptake, and function. Additionally, it covers recovery of glucose metabolic effects through overexpression of Hif1a or Pfkfb3 (targeted to osteoblasts) and metformin treatment. The role of Hif1a and Pfkfb3 in osteoblasts with regard to the rescue of T2DM bone effects is critical to the novelty of the paper and may benefit from being included and emphasized in the title and/or abstract. The study of osteoblasts and their glucose metabolism has been studied but not extensively at the mechanism level. The approach of using a mouse model is good for youth-onset T2D. It would be helpful if the author could include a bit more in the abstract about the critical role of Hif1a and Pfkfb3 in osteoblasts in recovery from T2DM treatment's bone effects in vivo.

Reviewer #2 (Public Review):

Despite high bone mineral density, increased fracture risk has been associated with T2D in humans. In this study, the authors established a model that could mimic some aspects of T2D in mice and then study bone turnover and metabolism in detail.

Strengths<br /> This is an exciting study, the methods are detailed and well done, and the results are presented coherently and support the conclusions.<br /> Previous work from Dr. Long's group over this last decade has established a requirement for glycolysis in osteoblast differentiation. They showed the requirement for glycolysis not only for the anabolic action of PTH but also as an effector downstream of Wnt signaling. Using the T2D mouse model they have generated, they test if manipulating glycolysis and oxidative phosphorylation can rescue some of the detrimental effects on bone in this model.<br /> They use several novel approaches, they use glucose-labeling studies that are relatively underutilized, and it provides some insights into defective TCA cycle. They also utilize BMSCs that have been sorted for performing single-cell sequencing studies to identify specific populations modified with T2D. Unfortunately, the results are modest and need some clarification on what these populations add to the story.<br /> The authors use two approaches: a drug (Metformin) and a number of mouse genetic models to over-express genes involved in the glycolytic pathway using Dox inducible models. The results with overexpressing HIF1 and PFKFB3 show a potential rescue of bone defects with T2D, and Glut1 overexpression does not rescue T2D-induced bone loss.

Concerns<br /> The authors have generated several overexpression models to manipulate the glycolytic pathway to recuse T2D-induced bone loss. The use of DOX in drinking water has been shown to affect mitochondrial metabolism. Did the authors control for these effects? Since both the groups of mice got the DOX in drinking water, there is internal control.<br /> Only one of the rescue experiments had control with the Chow diet. There are some studies that have shown a high-fat diet to be protective of bone loss in TID models.<br /> The use of metformin to correct metabolic dysfunction and, thereby, bone mass is an exciting result. Did the authors test to see if they had in any way rescued this phenotype because of reducing ROS levels? The decrease in OxsPhos seen with the seahorse experiments suggests there could be mitochondrial dysfunction often associated with ROS generation.<br /> All of the experiments used male mice (because STZ use and ease of T2D establishment in males). It would be better if this were made clear in the title.<br /> Is the T2D model presented really represent what is observed in humans? Some experiments to test the other factors implicated in T2D and whether those are modulated in the rescue experiments might help address this.

Reviewer #3 (Public Review):

The manuscript entitled "Osteoblast-intrinsic defect in glucose metabolism impairs bone formation in type II diabetic mice" by Song et al. showed that osteoblast activity was compromised due to impaired glucose metabolism using a youth-onset T2D mouse model. The investigators induced youth-onset T2D in 22-week-old C57BL/6J male mice by a high-fat diet (HFD) starting at 6 weeks of age and injection of low-dose streptozotocin three times at 12-week-old. Then they demonstrated that metformin promoted glycolysis and osteoblast differentiation in vitro and increased bone mass in the diabetic mice. It was also demonstrated that targeted overexpression of Hif1a or Pfkfb3, but not Glut1, in osteoblasts reduced bone loss in T2D mice. Overall, the investigators made a great effort to characterize the changes in metabolism in the bone of the B6/C57 mice by HFD and metformin with microCT, dynamic histomorphometry, C13 isotype labeling in vivo, scRNA-seq and metabolic assays with bone marrow mesenchymal cells in vitro.

eLife assessment

The current study provides important, mechanistic insight into the potential contribution of antisense C4G2 expanded RNA to disease in C9orf72-associated ALS/FTD. The authors convincingly demonstrate that expression of this RNA species activates the PKR/eIF2α-dependent integrated stress response. They further provide evidence that this can contribute to disease phenotypes using multiple models and post-mortem patient samples.

Reviewer #1 (Public Review):

The most common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) is a G4C2 repeat expansion within the first intron of the C9ORF72 gene. However, how this repeat contributes to disease pathology is still an active area of research. This study takes a targeted approach to analyzing specifically how the C9ORF72 antisense transcript (C4G2) may be contributing to FTD/ALS.

Using an artificial (C4G2)75 antisense cassette, the authors show in both HEK293T cells and cultured neurons that the C4G2 antisense transcript leads to elevated levels of activated PKR and increased phosphorylated eIF2alpha. This then leads to a decreased level of translation, the formation of stress granules, and decreased survival, phenotypes that can be suppressed through the knockdown of PKR. The authors nicely demonstrate that PKR activation upon transfection with their antisense cassette is independent of toxic dipeptide repeat proteins by using reporter constructs that do not create these dipeptides but are still able to activate PKR. Furthermore, using a construct that expresses both sense and antisense transcripts, the authors show that knockdown of the antisense, but not the sense transcript, abrogates the PKR response (demonstrating the specificity of this stress pathway for the antisense RNA). The authors additionally show the relevance of PKR activation in FTD/ALS through the presence of activated PKR and elevated eIF2alpha in ALS postmortem brain tissue.

This paper shows that, at least in model systems, the C4G2 transcript can have cytotoxic effects through the stimulation of PKR. The experiments are well-controlled and fairly comprehensive. The claim that PKR activation occurs via the antisense RNA, and not the sense, is well supported by the data. However, some limitations exist, some of which the authors explicitly recognize. They are as follows:<br /> 1. It is not clear how the results from these reporter constructs inform on the repeat expansion RNAs produced in disease, which can be significantly longer, and might be expressed at different levels. Perhaps if the C4G2 repeat used in this work were expressed at levels comparable to what the antisense transcript is expressed in an actual disease, or in a similar RNA context, PKR would not be activated. This is important to keep in mind.<br /> 2. It is still unclear how PKR is being activated in the presence of C4G2 (it could be direct or indirect). The authors list a variety of explanations in the discussion. A prior study has shown that a similar repeat expansion leads to the accumulation of cytoplasmic dsRNA inclusions marked by TDP-43 (Rodriguez et al., 2021). It would be interesting to see if these inclusions are present upon expression of the antisense construct.<br /> 3. In the context of C9ORF72 FTD/ALS disease, it is still difficult to say how much of the disease pathology is on account of antisense triggered stress responses as opposed to dipeptide repeat, RBP titration, etc. This study nevertheless provides a new perspective to consider for how the C9ORF72 repeat expansion contributes to the diseased state.

Reviewer #2 (Public Review):

The underlying toxic species in C9ORF72 FTD/ALS is debated, with evidence for the contribution of both loss of function and gain of function of sense G4C2 repeat-expanded mRNAs and DRPS has been shown. The authors ask what the role - if any - of the antisense C4G2 repeat expanded mRNAs, which are equally abundant in patient brains, in producing toxicity. They convincingly show a role for these, independent of DRP expression, and distinct from sense G4C2repeat-expanded in toxicity in cell lines, neurons, and zebrafish, mediated via PKR activation. The latter is shown through increased p-eIF2alpha and reduced protein synthesis rates, associated with toxic phenotypes, rescued by PKR knockdown. The authors have achieved their aims, where the excellent data strongly support their conclusions.

The mechanism for PKR activation by antisense but sense repeat-expanded mRNAs is not examined, but the authors reasonably propose secondary structure differences in PKR activation. This could be tested in future work.

The work adds to our understanding of mechanisms of toxicity in repeat disorders, and this particular mechanism has implications for therapy via ISR modulation to reverse the effects of PKR activation.

The human data adds to the spectrum of protein-misfolding neurodegenerative diseases that show UPR/ISR activation, again with implications for therapy via ISR modulation.

Interestingly, PKR knockdown only partially rescues cell toxicity in neuronal cells, possibly reflecting other toxic mechanisms at play.

eLife assessment

This important study reports a unique N-terminal motif of Staphylococcus aureus GpsB and the co-crystal structure of GpsB with the C-terminus of PBP4. It provides convincing evidence demonstrating the interactions of GpsB with PBP4 and FtsZ, shedding light on the role of GpsB in the pathogen's cell division. However, the functional characterization of GpsB's new motif caused and the structural characterization of GpsB and FtsZ's interaction is incomplete.

Reviewer #1 (Public Review):

In the manuscript "Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB", Sacco et. al. solved the crystal structure of S. aureus GpsB, an essential cell growth and division protein. The authors also identified its interactions with the master regulator of cell division FtsZ and a penicillin-binding protein PBP4 that is implicated in B-lactam insensitivity. Although GpsB is essential for growth in S. aureus the reason for its essentiality is poorly understood. The authors used biochemical, biophysical, and crystallographic methods to determine the structure of GpsB and characterized its binding with FtsZ and PBP4. The authors also solved the co-crystal structure of GpsB with the C-terminal peptide of PBP4. These results are significant because it details the interactions of an essential growth protein in S. aureus with known cell division proteins. However, the impact of the work could be further enhanced if the authors had more functional studies to demonstrate the importance of the new hinge motif, the binding with FtsZ C-terminal tail, and PBP4.

Reviewer #2 (Public Review):

This work continues the exploration of the GspB protein as a cytosolic hub for different cell wall enzymes. In particular, this manuscript presents evidence for the direct interaction of GspB with both FtsZ and PBP4 in Staphylococcus aureus. Structural determination is provided for the N-term region of GspB alone and in complex with the small cytosolic region of PBP4 recognized by GspB.

After previously published works from the same group identifying the connection between GspB and FtsZ, and from another group providing the structural basis for the interaction between GspB and PBPs in different bacterial species; the present work provides incremental information for the S. aureus case. The work is sound, and the experimental evidence supports the presented conclusions.

The main strength of the manuscript is providing pieces of evidence of the protein-protein interaction between GspB and FtsZ and between GspB and PBP4.

However, no structural information is provided for the GspB:FtsZ complex, and the 3D structure of the N-term domain of GspB is very similar to previous ones solved for other bacteria, but with the presence of a three-residues insertion that provides flexibility to the domain, a fact that seems to be important in vivo.<br /> The complex of N-term GspB with the cytosolic micro-domain of PBP4, reveals the interactions involved in the recognition; an interaction network that is similar to the previously reported for GspB and PBPs in bacillus subtilis and in Streptococcus pneumonia.

eLife assessment

This fundamental work shows the absence of links between striatal dopamine synthesis capacity and working memory capacity, spontaneous eye-blink rate, and trait impulsivity. The evidence supporting the conclusions is compelling, with rigorous PET investigations and state-of-the-art cognitive assessments in a large sample. Given the high interest in the role of dopamine, the work will be of very broad interest to basic neuroscientists, clinical neuroscientists, and clinicians including neurologists and psychiatrists.

Reviewer #1 (Public Review):

The authors present a study to test the relationships between a measured dopamine marker in the brain - so-called, dopamine synthesis capacity - and various other measures purported to index dopamine function. These measures include questionnaire answers about behaviour, and measured behaviour. Various studies have used these other measures as indices or proxies of dopamine function with some evidence to support this. However, some of the evidence is in small groups or indirect.

The major strength of this study is the size of the sample (n=66-94) compared to other studies and the three different analytical strategies employed - frequentist, Bayesian, and predictive modelling.

Areas, where the study is more limited, are the use of only one marker of dopamine neurochemistry ([18F]FDOPA) and this does not discount relationships with other markers such as pre-synaptic receptors, post-synaptic receptors, and dynamic release. The authors acknowledge that this study does not speak to the general principle of dopamine relationships with other measures. While the numbers are impressive for this type of study the use of correlation means their power is for correlations of 0.32-0.37 and higher (G*power). It is possible genuine relationships between markers do exist but all studies to date, including this one, are underpowered. The Bayesian analysis conducted speaks to this and is a welcome addition. It is also possible that the conclusions are restricted by the participants recruited as they are limited to the ages of 18-43 and it is not clear how representative they are of the general community from the information provided.

The dopamine system is not one entity in terms of system components (pre-synaptic, post-synaptic, etc), but also in terms of subcortical area with a gradient of input from the brainstem and a distinct connectionist anatomy between the striatum and the cortex (via other structures). Here the authors use a segmentation of the striatum to test the relationships. While this is embedded in the methods and results the introduction's treatment of the subcortical dopamine system is as a single entity. This could be improved.

The results of this work have an important impact in that they strongly suggest one cannot use proxies to estimate endogenous neurochemistry (at least in the dopamine system). However, this implies that any other proxy for any other system needs to be (re-)assessed using similar methods. This is not to say that the proxies are not sensitive to dopamine manipulations, but that they cannot by themselves be used instead of direct measurement. Given the number of studies which suggest that a measure of baseline state may predict the effects of dopaminergic drugs, one must question what the baseline state is being measured.

Despite these limitations, the authors have provided the largest assessment of the relationships between [18F] FDOPA-assessed dopamine synthesis capacity and various markers previously linked to dopamine function. In this respect, it is an important negative. This does mean that the assessments used cannot be used to assess 'baseline' states in relation to dopaminergic drug effects, but the mechanism through which this baseline dependency operates is not well understood.

Reviewer #2 (Public Review):

This study examined the relationship between dopamine synthesis capacity, working memory, impulsivity, and spontaneous eye blink rate. The rationale for the study is sound and well-articulated given the results of prior studies suggesting relations between dopaminergic measures and these behavioral measures. Understanding these relationships is important both for understanding the neural and neurochemical correlates of behavioral traits, but also because it has been proposed that these measures might be used as a proxy for dopamine synthesis capacity, which is extremely expensive to collect and requires exposure to radiation. The study used appropriate methods and a major strength is that it was performed in a larger sample than is typical for PET studies, which are typically underpowered due to the expense of using radioligands. Critically, the study did not find evidence for associations. Although the results can be seen as disappointing in that they failed to confirm hypotheses, the findings nevertheless have substantial implications for the field. Specifically, the results argue against the use of these behavioral constructs as a proxy for dopamine synthesis activity. As such, the findings provide a critical corrective for prior conclusions that were derived from past smaller studies.

eLife assessment

The paper is of interest to neuroscientists, developmental biologists, and those interested in mechanisms that underlie intellectual disability. The study is well executed and brings new insight into the role of WDR62 and its role in causing microcephaly. The key claims of the manuscript require additional data.

Reviewer #1 (Public Review):

The manuscript provides a comprehensive analysis of the consequences of a mutation in WDR62 in human pluripotent stem cell-derived progenitor cells and neurons. The experiments are logical and presented well. The data support the conclusion that WDR62 dysfunction causes impaired cell cycle progression and defective neuronal differentiation. The data corroborate previous findings in mouse and human cells and cell lines and extend knowledge to cells that are relevant to the microcephaly characteristic of individuals with WDR62 mutations. The major shortcoming of the data is that it relies on cells from a single donor and so requires additional validation to support the generalization of the conclusions. In addition, limited mechanistic insight is provided.

Reviewer #2 (Public Review):

Dell'Amico and colleagues examine a C-terminal truncating mutation of WDR62, a gene identified as the 2nd most frequent cause of primary microcephaly. The authors generate neural progenitor cells and neurons from patient-derived IPSCs to examine the cell biological phenotypes of the truncation. This reveals the localization of WDR62 in the Golgi apparatus during interphase and suggests that shuttling from the GA to the spindle poles could be a potential mechanism underlying the effects of WDR62 truncation on cortical development.

Whereas these model systems are useful to study certain cell biological aspects of mutated cells, they do not fully recapitulate all features of the cortical development that the authors study. This model system lacks polarity of the tissue, which is important for a correct cell division of radial glia, which in turn is the key process impaired in microcephaly. Together with the inherent heterogeneity of the differentiation protocols, this poses a major weakness to the authors' approaches. On the other hand, the authors' system is well-suited for the analysis of co-localization and they show compelling evidence of the localization of WDR62 to the GA in interphase, which is the main strength of the study. These data are corroborated by immunostainings in fetal human tissue. Minor experiments are still needed to show a direct interaction of WDR62 with GA proteins and to further assess by immunofluorescence the GA-WDR62 co-localization in the radial glia of fetal human samples. Further, the author's interpretation that premature neurogenesis is not occurring in their system should be better supported by additional immunostaining. Finally, the manuscript is well written and the methods are adequately explained.

Reviewer #3 (Public Review):

WDR62 is a spindle pole-associated scaffold protein. Recessive mutations in WDR62 account for the second most common cause of autosomal recessive primary microcephaly (MCPH). This paper investigates how a C-terminal truncating mutation D955AfsX112 in WDR62 causes MCPH using iPSCs from a patient. The authors generated neuroepithelial (NES) cells, cortical progenitors, and neurons from the patient-derived and isogenic retro-mutated iPSC lines. They found that: (1) the mutant WDR62 fails to localize to the spindle poles during mitosis; (2) patient-derived iPS-NES cells exhibit shorter primary cilia and significantly smaller spindle angles; (3) the mutation leads to differentiation defects in iPSC-derived cortical neurons; (4) during the interphase-to-mitosis transition, WDR62 translocates from the Golgi apparatus to the spindle poles in a microtubule-dependent manner; and (5) the mutation prevents WDR62 shuttling from the Golgi to the spindle poles. Using the isogenic retro-mutated iPSC lines as the control increased the rigor of the current study. In general, this is a very carefully designed study, the data support the authors' conclusions, and confirm previous findings of WDR62 functions.

eLife assessment<br /> <br /> This work provides a valuable allele-specific gene editing therapeutic approach to selectively target the human RHO-T17M mutation, one of the most frequent genetic causes of autosomal dominant retinitis pigmentosa. However, the current data are incomplete. Further validation of gene editing efficiency in rods at cellular level in vivo and use of Rho-T17M mice will strengthen the conclusion.

Reviewer #1 (Public Review):

The authors attempted to delete a rhodopsin allele with single-nucleotide mutation seen in a Chinese subpopulation of autosomal dominant retinitis pigmentosa patients, (Rho-T17M). This was done in vitro and in vivo, while keeping the Rho wild type allele intact in vitro and in vivo using CRISPR-SaCAS9 guide RNA-specific approach, a previously established technique. In this study, solid in vitro data was presented showing that one of the tested guide RNAs was effective to specifically delete targeted the Rho-T17M sequence of synthetic DNA as well as in iPSCs from RP patients. However, the in vivo part of this study is incomplete. The issues are: 1. confusing choice of disease animal model (Rho-5m mice that carry 4 additional rhodopsin mutations other than the targeted T17M); 2. no proof of gene editing efficiency at the cellular level of the targeted cell type (i.e. what percentage of rod photoreceptors lose the T17M disease mutation?); and 3) lack of evidence of therapeutic potential (i.e. is there any rescue of vision in the mouse disease model or any toxicity due to the vector itself?).

Reviewer #2 (Public Review):

The authors attempt to develop an allele-specific editing approach targeting RHO-T17M mutation for potential therapeutic use to treat the mutation associated with autosomal dominant retinitis pigmentosa.

1) The authors reported three sgRNAs for the RHO T17M allele for verification. It would be helpful to describe details of the discovery phase of these sgRNAs, including design, in silico predictions, inclusion criteria, off-target analysis, etc.

2) The authors claim that the targeted gene-editing efficiencies are dose-dependent. However, data were presented from only one mouse for the 5ｘ108 dose group (line 231-237), which might need more explanation.

3) With respect to Fig. 4C, the flat-mount retina is not representative. A better image of flat-mount of retina is preferred.

4) With respect to Fig. 6B & 6C, it seems that T17M protein and RHO-5m protein are likely detected in both cytoplasm and plasma membrane rather than being limited to the cytoplasm alone.

5) The therapeutic efficacy benefit should be supported by data of photoreceptor function and cell preservation after treatment. It is be better to include two more control groups, namely wild-type mice and untreated mutant mice, which may help evaluate improved response after treatment.

6) The mouse lines are confusing. Did the authors generate three lines of mice, including RHOwt/hum, Mut-RHOwt/hum, RHOhum/m-hum mice? Did the authors use the Rhohum/m-hum mice for verification of cutting efficiencies, whereas they use the other two lines of mice for rescue experiments? The authors should clarify.

7) Mut-RHOwt/hum mice have previously been reported to have fundus pigment abnormalities, so the fundus should be examined after rescue. The expression of Rho-5M mRNA was reduced in vitro. Was the expression of RHO mRNA also down regulated after rescue as well as in vitro? Did the subretinal injection of GFP spread to the whole retina? This can be determined with retinal flat mount or panretinal staining using GFP labeling. The authors showed that the cell numbers in the ONL were increased in the treatment group compared with the control group at 9 mpi. Were the other nuclear layers or plexiform layer also affected? Did the other retinal cells develop normally? Figure 8 showed retinal functions with AAV-based SaCas9/17-Sg2 in Mut-Rhowt/hum mice. ERG of Mut-Rhowt/hum mice without treatment are also needed.

The efficiency and safety of RHO T17M allele-specific editing in this paper are well supported by in vitro and in vivo experiments.

The fundamental basis of the study design should be clearly stated, ie which truncation variants in RHO cause disease or not. It is reported that truncation variants occurring before K296 are likely benign, which should be mentioned. This is the key starting point for this kind of study and is not limited to RHO. but as an allele-specific gene editing approach as a potential therapy for dominant mutations in any gene for which heterozygous loss-of-function is tolerated in the whole gene or in part of the gene (mostly at N-terminals). Apart from RHO, in fact, N-terminal truncating variants in several other IRD associated genes have been reported to be benign in heterozygotes, including CRX, TOPORS, RP1, etc. This study verified the efficiency and safety of this approach based on both patient derived iPSC and humanized animal models which are unique compared with other studies on RHO.

eLife assessment

Based on the Cryo-EM structure of human ETB in complex with the vasoconstricting peptide ET-1 and the inhibitory G-protein (Gi), this valuable study presents convincing data on how agonist binding is coupled to Gi-protein binding. The complex structure is solid and will appeal to the GPCR and pharmacology communities.

Reviewer #1 (Public Review):

The endothelin ETB receptor is a G-protein coupled receptor activated by vasoactive peptide endothelins, causing vaslorelaxtion in smooth muscle. By determining the Cryo EM structure of human ETB in complex with the vasoconstricting peptide ET-1 and the inhibitory G-protein (Gi), the study represents a convincing insight into agonist-induced receptor activation and transducer-coupling. The complex structure is solid and will appeal to the GPCR and pharmacology communities.

Strengthens: The authors have managed to obtain the first G-protein complex structure of an ETB receptor by working with a receptor that still retains G-protein coupling (i.e. not a thermostabilized mutant) and by developing new methodologies into how the G-protein is remotely tethered to the GPCR. The Cryo EM structural details highlight clear differences into how the G-protein binds that also includes the more downward movement of TM7.

Weaknesses: While it is technically challenging to obtain an endothelin-1-ETB-Gi complex, the fusion approach means that there is equilibrium is already pushed towards a complex that may otherwise require lipids, such as PIP2. Whilst I don't know what may alter how alpha 5 interacts with ETB, this cannot be ruled out either.

Reviewer #2 (Public Review):

This study adds value in the relatively new field, specifically in the topic of ET-B receptor. In this study the authors provide a new structure in ET-B receptor that might be beneficial to the development of ET-B agonist. However, from the clinical and physiological point of view, the manuscript did not provide sufficient evidence in its current form.

Reviewer #3 (Public Review):

This manuscript by Sano et al., presents cryo-EM structure of endothelin-1-bound endothelin B receptor (ETbR) in complex with heterotrimeric G-proteins. The structural snapshot provides important information about agonist-induced receptor activation and transducer-coupling. This manuscript also designs and present a successful case example for a variation of previously used NanoBiT-fusion-based strategy to stabilize GPCR-G-protein complexes. This strategy may be broadly applicable to other GPCR-G-protein complexes as well, and therefore, also provides an important methodological advance. Overall, the experimental design and interpretation of the structure are excellent, and the manuscript present an easy-to-follow coherent story. Considering the importance of ETbR signaling in multiple physiological and disease conditions, this structural snapshot, taken together with earlier structural studies by the same laboratory, advances the ETbR biology significantly with potential for novel ligand discovery. This manuscript is also available as a preprint in bioRxiv as well as another manuscript from Xu and Jiang group. Considering the structural information presented in these manuscripts, I would strongly suggest that even if the other manuscript is published somewhere before this one, it should not be viewed as a compromise on novelty, and rather considered as complementary information from independent studies that further strengthen the impact.

eLife assessment

The study represents an impressive effort to use atomistic simulations to probe cryptic binding sites in the envelope of six flaviviruses. Moreover, using constant pH simulations, the authors suggest that a cluster of ionizable residues contribute to the pH dependent conformational rearrangements required in the infection process. Therefore, the study provides new mechanistic insights that can be helpful in future efforts to develop drugs that target flaviviruses.

Reviewer #1 (Public Review):<br /> <br /> The pH-dependent conformational change of the envelope protein in flaviviruses is required for the infection process, thus it represents an attractive target for drug development. In this study, the authors conducted extensive atomistic simulations for models for the envelope in six flaviviruses. Using a benzene-mapping approach, they were able to identify several cryptic binding sites that can be targeted for drug development. One of the cryptic binding site was observed in a previous study to be occupied by a detergent molecule, while the other cryptic binding site is located at domain interface. The second binding site involves a cluster of ionizable residues. Using constant pH simulations, the authors suggested that the cluster of ionizable residues contribute to the pH dependent conformational rearrangements. This cluster model helps to explain the inconsistencies reported in the literature regarding the role of several key histidine residues as pH sensors. Overall, the study has provided new mechanistic insights that can be taken advantage of in future drug developments that target flaviviruses. The work also highlights the importance of constant pH simulations to the analysis of pH sensitive biological processes.

Reviewer #2 (Public Review):

The authors made an applaudable attempt to identify druggable cryptic pockets and address a controversy regarding a pH switch of a very large system of significant biological and Pharmaceutical interest. Due to the size of the system and uncertainty in the membrane interactions/curvature the draft produces etc, it is a nontrivial task. By using a previously validated mixed solvent (i.e., benzene mapping) protocol, the authors were able to analyze the potential pockets in the entire system. This is big technical advance and the protocol can be used by other works in the field for studying cryptic pockets.

Reviewer #3 (Public Review):

This work dives into the inner molecular workings of viruses such as yellow fever, Zika, and tick borne encephalitis. Due to their pathogenic nature, these are active targets for drug development, and motivated by this, the authors set out to search for so-called "cryptic" binding pockets, concealed from the protein surface and therefore often missed. Using atomistic computer simulations of viral rafts embedded in lipid membranes, the authors present new methodology to detect and characterise structural and electrostatic features of viral envelope proteins. By mixing in a small organic co-solvent (benzene) that acts as a drug proxy, structural fluctuations are enhanced, which reveal hitherto hidden binding pockets. The authors convincingly show that this perturbation has only a minute effect on protein secondary structure. The technique revealed a new cryptic binding pocket that is well conserved across multiple flaviviruses.

The cryptic site involves four potentially charged residues and to understand their interplay, constant pH molecular dynamics simulations are combined with a detailed structural and electrostatic analysis of the binding pocket.<br /> Due it's multi-dimensional nature, the response to a possible pH change is a complex process and the authors present a compelling analysis involving charge states, inter-residue distances (reduced using PCA), and structural features of the pocket. An important conclusion is that the role of histidine is less important than previously thought: the pH dependent behaviour is a collective property of the pocket.

This study is an important contribution to computer aided drug-design. In particular, using co-solutes to induce structural fluctuations seems very helpful for uncovering new binding sites. Of equal importance are methodology to analyse complex trajectories. This work is a good example of how multiple dimensions can be reduced and rationalised using e.g. solvent accessibly surface area (SASA), radius of gyration, net-charge, and principal component analysis. There are likely several other properties that could aid in this rationalising and the present work is a solid platform for exploring these.

eLife assessment

This is an important study that investigates the impact of tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia. Through a combination of pre-clinical in vivo measurements, clinical data, and computational modeling, the authors present solid evidence regarding the heterogeneous effects of TKIs in patients and how the response to treatment may be improved. With the assumptions about differences between normal and leukemic cells addressed, this study would be of interest to those working in the fields of mathematical oncology and cancer biology.

Reviewer #1 (Public Review):

This work introduces a new computational model of healthy blood cell formation and chronic myeloid leukemia (CML). By combining data from the literature, animal experiments and patients the authors aim to develop a detailed description of the regulatory mechanisms governing healthy blood cell formation and CML therapy response. The model is used to derive hypotheses explaining why some patients respond to tyrosine kinase inhibitors (TKI) better than others. Based on the model simulations the authors seek predictors of TKI efficacy and for concepts to improve CML therapy.

Strengths:

(1) The authors start from all possible ordinary differential equation models which describe positive and negative regulations of proliferation rates and self-renewal/differentiation probabilities. The models account for hematopoietic stem cells, multipotent progenitors, terminally differentiated myeloid cells, and terminally differentiated lymphoid cells. Using an automated approach referred to as design space analysis (DSA) the authors exclude models with unfeasible qualitative dynamics. Using data from mouse experiments the authors exclude all regulatory configurations except one. This systematic approach combining model analysis and data from various sources is clearly a strength of the work.

(2) The authors consider a large number of parameter sets that are in line with physiological steady-state cell counts and realistic responses to system perturbations. Thus the authors can potentially account for inter-patient differences.

(3) The model predictions are compared to experimental and published data. The proposed predictors of TKI efficacy are tested on retrospective patient data.

Weaknesses:

(1) In my opinion the sub-model of leukemic cells requires a more solid justification. The authors assume that the configuration of regulatory loops and most key parameters are identical for normal and leukemic cells. The only difference the proposed model accounts for is that leukemic cells exhibit a weaker response to the feedback signal acting on stem cell self-renewal. The weaker response of leukemic stem cells is justified by data from the literature supporting differential responses to CCL3. However, the authors propose no justification for the assumption that all other parameters, such as proliferation rates or maximal self-renewal probabilities, are identical or have minor impacts.

(2) The authors come to the conclusion that "a key predictor of refractory response to TKI treatment is an increased probability of self-renewal of normal hematopoietic stem cells" (Abstract). This conclusion is, in my opinion, not fully supported by the model as it is. In the model, it is assumed that normal and leukemic stem cells have the same maximal self-renewal probability. Only the regulation of self-renewal by feedback signals is different. The parameter which is a predictor in the presented analysis (p_{0,max}) is the maximal self-renewal probability of both normal AND leukemic stem cells. Therefore, the conclusion that normal stem cell self-renewal is a predictor of TKI response is, in my opinion, questionable. If I understand the analysis correctly, the authors show the following: Under the assumptions that the maximal self-renewal probability of normal and leukemic stem cells is identical and that the feedback inhibition of self-renewal is weaker in leukemic stem cells compared to normal stem cells, the maximal self-renewal probability of the two stem cell populations is a predictor of TKI response. Notably, if the value of maximal self-renewal probability is increased, the self-renewal probability of leukemic and normal stem cells increases simultaneously at all time points. Therefore, I find it difficult to argue that normal stem cell self-renewal [as opposed to leukemic stem cell self-renewal] is the relevant quantity.

(3) The simulation of differentiation therapy is interesting, however, due to a lack of knowledge in the field, the specific impacts of such therapy on normal versus leukemic cell differentiation have to be rather hypothetical.

(4) The used patient cohort is very small (n = 21).

The proposed model of the regulations governing blood cell formation is a valuable contribution to the fields of computational modeling and experimental hematology. The derived predictors of TKI efficacy are potentially useful.

Reviewer #2 (Public Review):

The authors want to capture the dynamics of CML therapy with TKI and understand why some patients fail to respond to therapy (primary resistance). They develop a mathematical model of hematopoiesis that includes stem cells, progenitor cells, and mature cells linked through feedback mechanisms. They explore parameter space using sophisticated algorithms to reduce this parameter space and the potential models to one final model and then apply it to chronic myeloid leukemia in the chronic phase under therapy with a tyrosine kinase inhibitor. The novelty in the model is the feedback mechanism introduced and the concomitant animal model data to understand the parameters.

The model is tractable and yet captures important physiologic aspects of hematopoiesis that have not been explored previously in CML. The animal data to validate it is also quite important. Finally, the application of the model to clinical data illustrates its applicability to real clinical scenarios and provides interesting insights.

One concern is whether the short-term transplantation experiments truly reflect the steady state of hematopoiesis and how CML develops in humans.

It is possible that the model can be applied to other hematologic conditions such as myeloproliferative disorders since one would expect the dynamics and interactions to be similar.

Reviewer #3 (Public Review):

Rodriguez et al. develop a nonlinear ordinary differential equation model of hematopoiesis under normal and chronic myeloid leukaemia (CML) conditions, incorporating feedback control, lineage branching, and signaling between normal and CML cells. Design space analysis is used to identify viable models of cell-cell signalling interaction. Data from mouse models are used to refine the set of cell-cell interactions considered viable, resulting in a novel feedback-feedforward model. Through this framework, the response to tyrosine kinase inhibitor (TKI) therapy is analysed. Model behaviour is qualitatively consistent with experimental data from mouse models, and clinical data. In particular, the model demonstrates varying responses to tyrosine kinase inhibitor therapy across a range of parameter sets consistent with "normal" hematopoietic cell counts; and predicts that a relatively high proportion of leukemic hematopoietic stem cells is a contributor to (though does not guarantee) primary tyrosine kinase inhibitor resistance, consistent with experimental and clinical data.

Strengths:<br /> Mathematical modelling in the work is validated using both experimental and clinical data.

The approach to model selection and identification of reasonable parameter regions is interesting and appealing, particularly in the context of modelling processes such as CML which can exhibit significant heterogeneity between patients.

I expect that this work will be useful to the community, as the approach employed in this work could be readily adapted to study other similar problems (for example, different conditions or treatments), provided that suitable experimental and/or clinical data are collected or available.

The work is supported by extensive supplementary material, clearly documenting in detail the techniques involved and assumptions made.

Weaknesses:<br /> Clinical data from CML patients treated with TKI therapy is limited (n=21).

As acknowledged by the authors, there are some physiological aspects that may be important that are not modelled; including stem cell-niche interactions in the bone marrow microenvironment, and interactions with immune cells.

eLife assessment

This important study presents a machine learning-based classifier that can accurately determine the geographic origin of a Salmonella enterica sample from its whole-genome sequencing data in under five minutes leading to actionable public health insights. Applying the method to 2,313 whole genome sequences collected in the United Kingdom and several external validation datasets, the authors provide convincing evidence that Salmonella genomic data can be used to identify the likely geographic source of a food-borne outbreak and, in most cases, correctly identify the country of origin of an infection acquired overseas. The work presents an excellent case for the potential utility of routine genomics coupled with machine learning for public health microbiology and the methods are likely to be applicable to other pathogens besides Salmonella enterica.

Reviewer #1 (Public Review):

In this manuscript the authors describe the development and application of hierarchical machine learning model to identify the likely source of S. Enteritidis using whole genome sequence data. The application makes use of a collection of 2,313 genomes from 4 continents, 11 sub-regions and 38 countries. The approach is, to the best of my knowledge, novel and represents a substantial advance over previous approaches. The model is demonstrated to have good performance at the continental level and - where sufficient training data were available - also at the country level.

Strengths of the work include the clear exposition of the methods, application to a large and detailed genomic database of clinical S. Enteritidis isolates, and the use of five independent validation data-sets.

Limitations include lack of validation using post-pandemic data (as the authors state, the model may need retraining in light of changes to the global food network). Also, claimed novelties of the work include greater geographic granularity and faster turnaround time compared to alternative methods, but no explicit comparison to other methods is made.

Overall, the authors achieve their aims in describing a hierarchical machine learning model for source attribution using pathogen whole genome sequences. The approach is likely to be of broad relevance and considerable public health utility.

Reviewer #2 (Public Review):

In this study, Bayliss et al. built a machine learning algorithm that predicts which country an isolate of Salmonella Enteritidis has come from based on its genome sequence. The study used S. Enteritidis isolates taken from clinical infections in the UK with recently reported travel, with the recent travel location being assumed as the source of infection.

The reason for developing this type of algorithm is to use it for source attribution in the case of gastroenteritis cases caused by imported food or cases of gastroenteritis picked up during travel overseas. S. Enteritidis is a major cause of gastroenteritis worldwide. Its transmission is tied in with the food chain, and understanding where it travels and how is key to reducing the burden of these infections. While a country's efforts to reduce the burden of these bacteria within its own borders can have tremendous benefits, imported food can still introduce contaminated meat and produce, and these have indeed become larger proportional risks following control efforts in the UK.

S. Enteritidis shows strong geographical substructuring across its phylogenetic tree. Traditional phylogenetic analysis is time-consuming (particularly to perform repeatedly on a routine basis) and required highly skilled staff to perform. Machine learning should be able to identify genetic markers linked to clades typically found in a single location, without the need to build and interpret a phylogenetic tree.

There is some nice methods development work in this paper, with the employment of a hierarchical structure to the ML modelling pipeline and the use of an array of classifier, resampler, feature selection and parameter optimisation techniques to increase accuracy.

However, the main strength of this paper is how well tailored the model is to a real world use case. Many groups are applying machine learning to genomic data, but often not with a clearly defined use case or realistic training and testing conditions. The results begin by giving the reader an understanding of the current state of this work in a UK context, where all clinically reported cases of Salmonella are sequenced and when appropriate, travel history is recorded. The algorithm is designed to fit into this existing practise and thought has been put into how this would be operationalised. For example, the authors have shown that this work can truly be done in real-time, by developing an algorithm that works directly on raw reads and takes <4 mins to run. A great touch in this work was determining the time horizon over which the model should be retrained to keep up with contemporary geographic distributions of this pathogen. The time horizon itself may not be highly generalizable in genomic epidemiology, but the methods provided make it easier for others to make the same assessment for their pathogen and use case.

A weakness of the work is the areas where predictions are not as accurate, but this relates to the extent of pathogen sequencing today rather than the method itself. Countries with less accurate predictions are ones which few people return from with an infection and if they do, it tends to be a different strain each time, making building an accurate algorithm for these cases impossible without denser sampling outside of clinical infections or more sequencing of infections occurring in other countries. Without proofs of concept like this, there is less of a strong economic argument to justify these investments. Therefore this work represents an important step in demonstrating the feasibility of the method itself and the value in gathering more data. In contrast, a major strength of this work is that it uses data collected routinely from existing practice in the UK, rather than a bespoke sampling strategy that may not be realistic for routine public health. A comparison of the collection to NCBI also found this sampling to be less biased by specific outbreaks of interest, which is encouraging.

The training dataset appears to be only based on infections acquired overseas, while I suspect the model would be more useful in investigating infections due to imported contaminated food. An unresolved question from this work is therefore whether the source of travel-acquired infections and infections caused by food imported from the same places is the same, or whether exported vs domestically consumed food around the world is treated differently in important ways that would affect the relative prevalence and success of strains in causing infections. Looking at clinical infections also may bias Salmonella to those that cause more severe forms of infection, as many people don't report to a doctor when they have food poisoning. The large egg-related outbreak that did not feature much at all in the UKHSA dataset is potentially a nice example of this.

The low accuracy on countries with low infection numbers and high genetic diversity indicates that these algorithms would likely become less accurate over time if food safety is improved, and that individual countries could avoid being confidently attributed as a source of infection by eliminating or controlling major circulating foodborne clones. More clearly communicating when a prediction is uncertain could be helpful in dealing with isolates from countries where it is hard to make a determination.

One final limitation I see is the exclusion of UK Salmonella isolates - in cases where it is uncertain whether a Salmonella infection is due to import or not, it does not seem possible to make this assessment using the ML tool. This also limits the utility of the tool for other countries that might also benefit.

The authors have done an excellent job of demonstrating the feasibility of this approach and honing their machine learning workflow to the specific demands of the task. The work presents a clear and well thought out use case with the overall performance of the algorithm broken down into test cases where the algorithm is successful and unsuccessful which provide useful insight into what we can expect from the performance of these approaches.

Finding a way to better communicate when the source of an outbreak is unclear due to poor representation of a clade or a clade that is found in many countries would be a valuable extension of this work in the future, but as it is the results represent a promising starting point for initiating investigations into the source of Salmonella infections.

Diarrheal disease is a huge health burden worldwide. Previous work to lower the burden of these infections has shown that targeted interventions can make a substantial difference to the burden of disease and success of clonal outbreaks. The availability of a tool that can be used routinely to assess the most likely overseas origin of an infection could potentially highlight previously unrecognised outbreaks or areas of suddenly increased importation rate. In turn, this could lead to better investigations and targeted improvement of food security.

This paper provides an excellent case for the value of collecting recent travel history and including it in metadata for pathogen genomic data. If this were done in more countries with different patterns of travel and the data could be shared, this would provide a valuable global resource and start to capture the flow of strains internationally.

I am curious about the implications of being better able to attribute clinical gastroenteritis cases in the UK (and elsewhere) to food imported or travel to specific countries with respect to trade and regulation. This is well outside the scope of the paper, however the ability to capture isolates commonly picked up from food around the world without the cooperation of these countries raises interesting issues, particularly when factoring in the authors' scenarios of the true country of origin being obscured by uneven travel patterns and complex food supply networks.

Reviewer #3 (Public Review):

The authors describe a machine learning method for classifying the geographic origin of a Salmonella enterica isolate based on its whole-genome sequencing data. This is done at a continent, region, and country level, and the method is shown to be robust to phylogenetic diversity, temporal trends, and possibly some amount of mislabelling (but please see the first concern below). The authors demonstrate that their pipeline produces results in 5 minutes or less, which makes it applicable to many public health microbiology settings.

Some clear strengths of the paper include:<br /> - the use of a hierarchical classification method, which ensures that only those samples that can be unambiguously classified as belonging to a specific region can get assigned to a sub-region within that region (e.g. continent to country)<br /> - leveraging the UKHSA dataset going back nearly a decade, and containing a comprehensive record of all clinically detected Salmonella enterica infections, which mitigates potential biases and ensures a maximal geographic coverage<br /> - making all the data (microreact) and the source code (GitHub) public, which facilitates replication as well as enables other researchers and public health microbiologists to use the trained models directly on their own data<br /> - the use of unitigs as the basis for prediction, which are more informative than K-mers yet more straightforward to identify than SNPs or gene alleles.

There are several methodological concerns that should ideally be addressed:<br /> - in addition to the more complex situation of a tourist visiting country A and consuming food from country B, it would be good to rule out a simpler one of the tourist visiting both countries on the same trip (including via a stopover at an airport); the authors should elaborate on the plausibility of missing data on such multi-country trips and their frequency based on the available travel data<br /> - similarly, there appears to be an underlying assumption that the UK is never at the origin of a Salmonella enterica infection in the dataset selected; the authors should explain why that is a reasonable assumption for this dataset<br /> - the increase of infection incidence during the summer months might be at least partly attributable to a greater number of trips abroad during that period - if the authors have corrected their data for this, they should explicitly say so<br /> - lastly, in discussing the outbreak due to Polish eggs, it should be possible to check explicitly what fraction of the training data may have originated from this outbreak to see if this is sufficient to explain the observed poor prediction

Overall, this is a paper representing a substantial body of work and combining algorithmic advances with practical utility given the rapid turnaround time. It is likely to be generalisable to other pathogens of public health importance and to become integrated into standard protocols for outbreak origin tracing.

eLife assessment

The findings in this study are important as they establish a rat model of a classic form of early-onset osteoporosis and demonstrate that osteoporosis medications are effective in the model. The evidence supporting the authors' claims is compelling.

Reviewer #1 (Public Review):

The author constructed a novel rat model with a clinically relevant PLS3 hemizygous E10-16del mutation (PLS3E10-16del/0), which presents a classic form of early-onset osteoporosis, which recapitulate the osteoporotic phenotypes. Treatment with alendronate and teriparatide significantly improved bone mass and bone microarchitecture. Their results showed alendronate and teriparatide treatment could be a potential treatment for early-onset osteoporosis induced by PLS3 mutation.

This experiment is very interesting and has clinical relevance. The authors used common clinical drugs to treat osteoporosis caused by PLS3 mutation and achieved certain results. This result will give a way to the treatment of osteoporosis induced by PLS3 mutation.

Reviewer #2 (Public Review):

The mechanism for early-onset osteoporosis (EOOP) is not well understood. The authors performed PLS3 knockout and characterized its bone phenotype in a rat model. This provides a very useful tool for studying EOOP and the potential treatment for EOOP. The authors did a very nice job of characterizing the phenotype including the assessments of bone turnover markers, bone histomorphometric analyses, and bone biomechanical tests. The results from these assessments led to the conclusion that this PLS3 knockout rat model mimics the human EOOP. In addition, treatment with currently available drugs for osteoporosis is effective in this EOOP model. These results support further clinical investigation of anti-osteoporosis drugs for EOOP management.

eLife assessment

This important landmark paper identifies three distinct stellate ganglion nerve cell subtypes stratifiable in terms of their neuropeptide Y expression correlating these with gene expression and electrophysiological properties. Their innovative use of viral tracing techniques compellingly established their conclusions. This major contribution to cardiac sympathetic excitation is relevant to a wide scientific and clinical audience.

Reviewer #1 (Public Review):

The authors have achieved a demonstration of different stellate ganglion nerve cell functions and transmitter subtypes, of potential cardiac importance. They employ viral tracing techniques. These convincingly make this demonstration. The work will be key to our understanding of sympathetic function at the transmitter and physiological levels.

Reviewer #2 (Public Review):

The manuscript at hand by Sharma et al. presents new data on neurons of the stellate ganglia that are relevant for autonomic control of the heart. The authors identify stellate ganglionic neurons (SGN) that innervate the heart by retrograde tracing techniques and differentiate them from SGN neurons innervating other organs and tissues (mostly paw is used as a control). They subsequently employ single-cell RNAseq and morphological and functional (electrophysiological) studies. Their main finding is the identification of 3 SGN subtypes that they were further able to stratify into high and low neuropeptide Y cells. These subpopulations differ with regard to gene expression and action potential generation indicating different electrophysiological properties and different roles in the sympathoexcitation of the heart. They validate these findings by in vivo experiments where electrical stimulation of stellate ganglia after NPY-expressing neurons was depleted and find that heart rate change was lower under stimulation with high frequencies for NPY-depleted mice. The research question is very relevant and might have important therapeutic consequences for patients with cardiac diseases. The paper is written clearly. The methods applied are elegant and appropriate and the data support the conclusion.

The authors do report on some experiments in which stellate ganglion was used. Viral administration and physiological studies were performed on the right, while RNA sequencing was done from the right and left stellate ganglion. As there are physiological lateral differences between the effects of the left and right stellate ganglion, it would be useful to thoroughly report which side was used for which experiment throughout the manuscript and to discuss whether any lateral differences are relevant for the obtained results and conclusions.

Reviewer #3 (Public Review):

Using viral tracing and single-cell transcriptome profiling the authors investigated the electrophysiologic, morphologic, and physiologic roles for subsets of cardiac-specific neurons and found evidence that three adrenergic stellate ganglionic neuron subtypes innervate the heart.

The presented findings provide relevant insights into the properties of neurons modulating cardiac sympathetic control. The findings might open up new avenues to targeted modulation of cardiac sympathetic control. Additional insights from various models addressing for example ischemic and non-ischemic cardiomyopathy might allow to development of targeted therapies for various patient populations in the future.

eLife assessment

This important work demonstrates a significant asymmetry between the connectivity statistics of the left and right hemispheres of the Drosophila larva brain. The evidence supporting the conclusions is compelling and represents a first step toward the development of statistical tests for comparing pairs of connectomes more generally. This work will therefore be of interest to the broad neuroscience community.

Reviewer #1 (Public Review):

Pedigo et al, apply statistical modeling to a complete brain nanoscale network - a synaptic connectome of an insect brain: the Drosophila larva. They use a series of approaches to explore the symmetry of the right and left hemispheres. First, they compare network densities and find significant differences between the two hemispheres, with the right hemisphere having a higher density. They further grouped neurons by cell type to determine whether the differences were distributed across the entire brain or to specific connections and find the differences involving neurons in the learning and memory center, the mushroom body. Finally, they explored different definitions of an edge by using different thresholds either based on synaptic counts or proportions of synaptic inputs to a downstream neuron and found that when using the proportion of synaptic inputs, removing fewer edges (compared to when using synaptic count) was necessary to achieve left and right symmetry. The presentation of the methodology and writing is very clear and effective and is accessible to scientists from various backgrounds: both biologists and theoreticians. The methodology and approach used in this paper on the assessment of the degree of bilateral symmetry will serve as a basis for comparing networks and connectomes in general by providing a clear framework for statistical network modeling. This work is particularly timely as an increasing number of synaptic connectomes is being generated giving opportunities for various connectome comparisons. It will be of interest to neuroscientists in order to address various biological questions: to evaluate the degree of inter-individual variability/stereotypy of connectivity in the brain and how it relates to behavioral variability/stereotypy, to characterize changes in network connectivity due to different diseases, etc.

Reviewer #2 (Public Review):

The authors develop statistical tests for assessing whether two hemispheres of the Drosophila larval brain are bilaterally symmetric, and more generally to develop a framework for comparisons of connectomes. The study is organized in order of increasing complexity of the statistical test, beginning with a simple test of whether or not the two sides of the brain have equal connection density. A more sophisticated approach is applied to a model in which neurons are partitioned into groups defined by preexisting known cell types on the left and right hemispheres and densities are allowed to vary between groups (a stochastic block model). A correction is included for an overall difference in density between hemispheres. Finally, analyses are applied to assess which cell types contribute to differences in the larval connectome. This identifies Kenyon cells as particularly distinct - a density-corrected stochastic block model with Kenyon cells removed results in no significant bilateral asymmetry. Results are also compared across different choices for thresholding of connection weights.

This manuscript tackles an interesting and timely problem. The analyses are largely straightforward applications of standard hypothesis tests for binomially distributed random variables. However, the observation that a density correction is needed to account for the two hemispheres' connection probabilities, and that a stochastic block model is sufficient to describe these probabilities, with the exception of the Kenyon cells, is interesting and makes more precise the notion of bilateral symmetry, at least at the level of connection probabilities, than previous approaches.

There are still several questions that remain about the generality of the results. The first concerns assumptions about the generative model for the graph. As the authors acknowledge, an Erdos-Renyi random network is a strong simplifying assumption. In particular, independent edge weights may be a restrictive model of connectome data given the broad degree distribution, spatial dependencies, and other features that characterize biological connectivity. A second question concerns the issue of statistical power. After partitioning neurons into groups, the most significant difference in connection probabilities comes from Kenyon cells, with the smallest p-value in the density-corrected comparison coming from KC-to-KC connections (Fig. 4B). However, KCs represent a large group of neurons, and the KC-to-KC connection probability is among the highest in the larval brain (Fig. 3B), raising the question of whether the observation of a significant difference specifically for these neurons is simply due to increased power. Third, connection density is only one of the many graph features that may be relevant for evaluating connectome similarity.

In total, although the analyses are straightforward, the study represents a first step toward the evaluation of connectome similarity and should spur further work in this important direction.

eLife assessment

This study is an important contribution to the understanding of Buruli ulcer transmission in Australia. The authors provide compelling evidence that the carriage of Mycobacterium ulcerans by possums, within their small home range, can predict cases of Buruli ulcer disease in individuals who visit those areas. While not directly relevant to the transmission of Buruli ulcer in West and Central Africa, the work will be of great interest to those studying the transmission of opportunistic environmental pathogens.

Reviewer #1 (Public Review):

This study presents a useful study, proposing the modelling of Buruli ulcer occurrence in humans based on detection of M. ulcerans in Australia. The data were collected and analyzed using solid and validated methodology and can be used as a starting point for the elucidation of M. ulcerans transmission in Australia.

Reviewer #2 (Public Review):

In this work, the authors have carried out an extensive and highly granular survey of Mycobacterium ulcerans carriage by possums who are living on the outskirts of Melbourne Australia, in areas that are known hot spots for cases of Buruli ulcer (BU). The work is the culmination of many years of endeavour by this team, who first identified that the faeces of possums can be highly positive for M. ulcerans DNA, genetically linked to the strains found in BU patients who live in, or have visited, the area.

Surveys across two seasons were performed. Based on qPCR data to identify M. ulcerans carriage, spatial mapping of this, and BU case data, a statistical model was generated using data from the Mornington Peninsula that was better predicted than a null model. This statistical model was then validated using a second independent site at Geelong. As a result of this data, there can now be little doubt that possums play a vital role in the transmission cycles of BU in the region, and will allow mitigation strategies to be designed and tested. As BU is a necrotising skin disease that can cause disability and permanent disfiguration even in a high-resource setting such as Australia, such approaches are urgently needed.

Strengths:

The scale (both in terms of geographic reach/granularity and time) of the surveillance effort to understand the distribution of M. ulcerans DNA in the local possum population is unprecedented.

Since BU is a notifiable disease in Australia, the researchers have access to comprehensive clinical information across the study period.

The statistical model developed had a strongly positive influence over the ability to predict where BU cases will arise, over areas with a small radius (several km) which is the first time this has been achieved. The process by which this model was developed and validated seems robust.

Weaknesses:

In their model, the authors have used an assumed "exposure window" for when patients were infected with M. ulcerans in the Mornington Peninsula. Correctly defining, and assigning, this is absolutely critical to the accuracy of the statistical model, as is "blinding" of researchers assigning mesh boxes to patients to the results of surveillance data (and vice versa). These aspects are not fully clear in the current version. Furthermore, the effects on the model of changing these assumptions are not discussed.

The presence of M. ulcerans DNA in possum excreta and in patient samples is defined by qPCR for IS2404, a multicopy insertion sequence. Greater justification for using this as the sole marker is required, as this insertion sequence is also present in other mycolactone-producing mycobacteria. Moreover, some samples were claimed to be 'positive' with Ct values of 40 without justification for using this value (such as standard curves).

Comparing the summer and winter surveys at the Mornington Peninsula, the distribution of M. ulcerans positive excreta appears to have changed quite substantially, especially given that the possums are reported to be highly territorial with a range of only 100m. This version of the manuscript does not formally compare these spatial distributions, only the averages. Such an analysis would help understand if it is the possums that are moving, whether the possums undergo 'waves' of carriage (or indeed any other explanation), or if these apparent differences are down to chance.

Reviewer #3 (Public Review):

K. Vandelannoote and collaborators report on using spatially-localized possum feces investigated for Mycobacterium ulcerans, as a proxy for cases of Buruli ulcer, South Australia. The report is a contributive, enforcing survey of animal excreta and is based on strong pieces of evidence.

eLife assessment

In this Tools and Resources article, Sapiro et al. overcome the technical burden of low Borrelia burgdorferi numbers during infection by physically enriching for spirochetes prior to RNA-sequencing/mass spectrometry. This work is important as it provides technical advances for the study of global transcriptomic changes of B. burgdorferi during tick feeding and builds on the knowledge already collected by the field. The evidence presented is compelling, and the strategy described here could benefit researchers in the field and possibly support broader applications.

Reviewer #1 (Public Review):

In this study, Sapiro et al sought to develop technology for a transcriptomic analysis of B. burgdorferi directly from infected ticks. The methodology has exciting implications to better understand pathogen RNA profiles during specific infection timepoints, even beyond the Lyme spirochete. The authors demonstrate successful sequencing of the B. burgdorferi transcriptome from ticks and perform mass spectrometry to identify possible tick proteins that interact with B. burgdorferi. This technology and first dataset will be useful for the field. The study is limited in that no transcripts/proteins are followed-up by additional experiments and no biological interactions/infectious-processes are investigated.

Critiques and Questions:

This study largely develops a method and is a resource article. This should be more directly stated in the abstract/introduction.

Details of the infection experiment are currently unclear and more information in the results section is warranted. State the species of tick and life-stage (larval vs nymphal ticks) used for experiments. For RNA-seq, are mice are infected and ticks are naïve or are ticks infected and transmitting Borrelia to uninfected mice?

What is the limit of detection for this protocol? Experimental data should be provided about the number of B. burgdorferi required to perform this approach.

More information regarding RNA-seq coverage is required. Line 147-148 "read coverage was sufficient"; what defines sufficient? Browser images of RNA-seq data across different genes would be useful to visualize the read coverage per gene. What is the distribution of reads among tRNAs, mRNAs, UTRs, and sRNAs?

My lab group was excited about the data generated from this paper. Therefore, we downloaded the raw RNA-seq data from GEO and ran it through our RNA-seq computational pipeline. Our QC analysis revealed that day 4 samples have a different GC% pattern and that a high percentage of E. coli sequences were detected. This should be further investigated and addressed in the paper: Are other bacteria being enriched by this method? Why would this be unique to day 4 samples? Does this affect data interpretation?

Comprehensive data comparisons of this study and others are warranted. While the authors note examples of known differentially expressed genes (like lines 235-241), how does this global study compare to other global approaches? Are new expression patterns emerging with this RNA-seq approach compared to other methods? What differences emerged from day 1 to day 4 ticks compared to differences observed in unfed to fed ticks or fed ticks to DMC experiments? Directly compare to the following studies (PMID: 11830671; PMID: 25425211; PMID: 36649080).

Details about the categorization of gene functions should be further described. The authors use functional analysis from Drechtrah et al., 2015, but that study also lacks details of how that annotation file was generated. Here, the authors have seemed to supplement the Drechtrah et al., 2015 list with bacteriophage and lipoprotein predictions - which are the same categories they focus their findings. Have they introduced a bias to these functional groups? While it can be noted that many lipoproteins are upregulated (or comment on specific genes classes), there are even more "unknown" proteins upregulated. I argue that not much can be inferred from functional analysis given the current annotation of the B. burgdorferi genome.

Reviewer #2 (Public Review):

This manuscript documents the study of the transcriptome of Borrelia burgdorferi at 1, 2, 3 and 4 days post-feeding in nymphs of Ixodes scapularis. The authors use antibody-based pull-downs to separate bacteria from tick and mouse cells to perform an enrichment. The data presented support that the transcriptome of B. burgdorferi changes over time in the tick. This work is important as until now, only limited information on specific genes had been collected. This is the first study of its kind and is valuable for the field.

The manuscript is overall well written and easy to follow. The data are compelling and support the conclusions.

eLife assessment

This important work reports the identification of a list of proteins that may participate in the clearance of paternal mitochondria during fertilization, which is known as essential for normal fertilization and embryonic and fetal development. While the main method used is state of the art and the supporting data are solid, the vigor of the biochemical assays and function validation is inadequate. This work will be of interest to developmental and reproductive biologists working on fertilization.

Reviewer #1 (Public Review):

In this manuscript, the authors used an unbiased method to identify proteins from porcine oocyte extracts associated with permeabilised boar spermatozoa in vitro. The identification of the proteins is done by mass spectrometry. A previous publication of this lab validated the cell-free extract purification methods as recapitulating early events after sperm entry in the oocyte. This novel method with mammalian gametes has the advantage that it can be done with many spermatozoa at the time and allows the identification of proteins associated with many permeabilised boar spermatozoa at the time. This allowed the authors to establish a list of proteins either enriched or depleted after incubation with the oocytes extract or even only associated with spermatozoa after incubation for 4h or 24h. The total number of proteins identified in their test is around 2 hundred and with very few present in the sample only when spermatozoa were incubated with the extracts.

The list of proteins identified using this approach and these criteria provide a list of proteins likely associated with spermatozoa remnants after their entry and either removed or recruited for the transformation of spermatozoa-derived structures.

Using WB and histochemistry labelling of spermatozoa and early embryos using specific antibodies the authors confirmed the association/dissociation of 6 proteins suspected to be involved in autophagy.

While this unique approach provides a list of potential proteins involved in sperm mitochondria clearance it's (only) a starting point for many future studies and does not provide the demonstration that any of these proteins has indeed a role in the processes leading to sperm mitochondria clearance since the protein identified may also be involved in other processes going-on in the oocyte at this time of early development.

Concerning the localisation of the 6 proteins further analysed, the authors must add how much the presented picture represents the observed patterns. They must include the details on the fraction of spermatozoa and embryos displaying the presented pattern.

Reviewer #2 (Public Review):

Mitochondria are essential cellular organelles that generate ATPs as the energy source for maintaining regular cellular functions. However, the degradation of sperm-borne mitochondria after fertilization is a conserved event known as mitophagy to ensure the exclusively maternal inheritance of the mitochondrial DNA genome. Defects on post-fertilization sperm mitophagy will lead to fatal consequences in patients. Therefore, understanding the cellular and molecular regulation of the post-fertilization sperm mitophagy process is critically important. In this study, Zuidema et. al applied mass spectrometry in conjunction with a porcine cell-free system to identify potential autophagic cofactors involved in post-fertilization sperm mitophagy. They identified a list of 185 proteins that might be candidates for mitophagy determinants (or their co-factors). Despite the fact that 6 (out of 185) proteins were further studied, based on their known functions, using a porcine cell-free system in conjunction with immunocytochemistry and Western blotting, to characterize the localization and modification changes these proteins, no further functional validation experiments were performed. Nevertheless, the data presented in the current study is of great interest and could be important for future studies in this field.

Reviewer #3 (Public Review):

In this manuscript, a cytosolic extract of porcine oocytes is prepared. To this end, the authors have aspirated follicles from ovaries obtained from by first maturing oocytes to meiose 2 metaphase stage (one polar body) from the slaughterhouse. Cumulus cells (hyaluronidase treatment) and the zona pellucida (pronase treatment) were removed and the resulting naked mature oocytes (1000 per portion) were extracted in a buffer containing divalent cation chelator, beta-mercaptoethanol, protease inhibitors, and a creatine kinase phosphocreatine cocktail for energy regeneration which was subsequently triple frozen/thawed in liquid nitrogen and crushed by 16 kG centrifugation. The supernatant (1.5 mL) was harvested and 10 microliters of it (used for interaction with 10,000 permeabilized boar sperm per 10 microliter extract (which thus represents the cytosol fraction of 6.67 oocytes).

The sperm were in this assay treated with DTT and lysoPC to prime the sperm's mitochondrial sheath.

After incubation and washing these preps were used for Western blot (see point 2) for Fluorescence microscopy and for proteomic identification of proteins.

Points for consideration:

1) The treatment of sperm cells with DTT and lysoPC will permeabilize sperm cells but will also cause the liberation of soluble proteins as well as proteins that may interact with sperm structures via oxidized cysteine groups (disulfide bridges between proteins that will be reduced by DTT).

2) Figure 3: Did the authors really make Western blots with the amount of sperm cells and oocyte extracts as the description in the figures is not clear? This point relates to point 1. The proteins should also be detected in the following preparations (1) for the oocyte extract only (done) (2) for unextracted nude oocytes to see what is lost by the extraction procedure in proteins that may be relevant (not done) (3) for the permeabilized (LPC and DTT treated and washed) sperm only (not done) (4) For sperm that were intact (done) (5) After the assay was 10,000 permeabilized sperm and the equivalent of 6.67 oocyte extracts were incubated and were washed 3 times (or higher amounts after this incubation; not done). Note that the amount of sperm from one assay (10,000) likely will give insufficient protein for proper Western blotting and or Coomassie staining. In the materials and methods, I cannot find how after incubation material was subjected to western blotting the permeabilized sperm. I only see how 50 oocyte extracts and 100 million sperm were processed separately for Western blot.

3) Figures 4, 5, 6, 7, and 8 see point 2. I do miss beyond these conditions also condition 1 despite the fact that the imaged ooplasm does show positive staining.

4) These points 1-3 are all required for understanding what is lost in the sperm and oocyte treatments prior to the incubation step as well as the putative origin of proteins that were shown to interact with the mitochondrial sheath of the oocyte extract incubated permeabilized sperm cells after triple washing. Is the origin from sperm only (Figs 5-8) or also from the oocyte? Is the sperm treatment prior to incubation losing factors of interest (denaturation by DTT or dissolving of interacting proteins pre-incubation Figs 3-8)?

5) Mass spectrometry of the permeabilized sperm incubated with oocyte extracts and subsequent washing has been chosen to identify proteins involved in the autophagy (or cofactors thereof). The interaction of a number of such factors with the mitochondrial sheath of sperm has been shown in some cases from sperm and others for an oocyte origin. Therefore, it is surprising that the authors have not sub-fractionated the sperm after this incubation to work with a mitochondrial-enriched subfraction.

I am very positive about the porcine cell-free assay approach and the results presented here. However, I feel that the shortcomings of the assay are not well discussed (see points 1-5) and some of these points could easily be experimentally implemented in a revised version of this manuscript while others should at least be discussed.

eLife assessment

This study provides valuable insights into the role of two under-researched sperm-specific proteins (Cylicin 1 and Cylicin 2). The authors provide convincing evidence that they have an essential role in sperm head structure during spermatogenesis, and that their loss leads to subfertility or infertility, with a dose-dependent phenotype. The authors identify infertile males with mutations in both Cylicin1 and Cylicin2: thus the findings from the mouse models might be applicable to understanding human male infertility with similar structural defects.

Reviewer #1 (Public Review):

Mice and humans have two Cylicin genes (X-linked Cylicin 1 and the autosomal Cylicin 2) that encode cytoskeletal proteins. Cylicins are localized in the acrosomal region of round spermatids, yet they resemble a calyx component within the perinuclear theca of mature sperm nuclei. The function of Cylicins during this developmental stage of spermiogenesis (tail formation and head elongation/shaping) was not known. In this study, using CRISPR/Cas genome editing, the authors generated Cylc1-and Cylc2-knockout mouse lines to study the loss-of-function of each Cylicin or all together.

The major strengths of the study are the rigorous and comparative phenotypic analyses of all the combinatorial genotypes from the cross between the two mouse lines (Cylc1-/y, Cylc2-/-, Cylc1-/y Cylc2+/- and Cylc1-/y Cylc2-/-) at the levels of male fertility, cellular, and subcellular levels to support the conclusion of the study. While spermatogenesis appeared undisturbed, with germ cells of all types detected in the testis, low sperm counts in epididymis were observed. Mice were subfertile or infertile in a dose-dependent manner where fewer functional alleles had more severe phenotypes; the loss of Cylc2 was less tolerated than the loss of Cylc1. Thus, loss of Cylc1, and to an even greater extent, loss of Cylc2, leads to sperm structure anomalies and decrease sperm motility. Particularly, the sperm head and sperm head-neck region are affected, with calyx not forming in the absence of Cylicins, the acrosomal region being attached more loosely, and the sperm head itself appearing structurally rounder and shorter. Furthermore, manchette, which disassembles during spermiogenesis, persists in mature sperm of mice missing Cylc2. It is interesting that the study identifies a human male that has mutations in both CYLC1 and CYLC2 genes, and suffers from infertility, with similar motility and sperm structure defects compared to the mouse models. CYLC1 in the sperm from the infertile patient sperm is absent, providing evidence that in both rodents and primates, Cylicins are essential for male fertility.

The major weakness of the study is the less robust or absent of statistical analyses determining the statistical significance of some of the morphological phenotypes observed (e.g., the roundness/shortening of sperm head). Evolutionary analysis of two genes-while interesting- is less congruent with the other parts of the study and disrupts the overall flow of the functional studies. The authors show that the reason for the loss of Cylc2 being more severe is due to the higher conservation of Cylc2 compared to Cylc1 in rodents and primates, however, the conservation of these genes in other species is not discussed.

Overall, the work highlights the relevance and importance of Cylicins in male infertility and advances our understanding of perinuclear theca formation during spermiogenesis.

Reviewer #2 (Public Review):

The work presented in this manuscript focuses on the role of Cylicins in spermiogenesis and the consequences of their absence on infertility. The manuscript is presented in two parts: the first part studies the absence of Cylicins from KO mouse models and shows in mice that both isoforms of Cylicins are necessary for normal spermiogenesis. The evaluation of double heterozygotes is particularly useful for the second part which looks at the presence of mutations in these genes in a cohort of infertile men. A patient with two hemizygous/heterozygous mutations in the CYLC1 and 2 genes, respectively, was identified for the first time and the results obtained with the KO models support the hypothesis of the pathogenicity of the mutations.

In general, the experiments are perfectly performed and the results are clear. Numerous techniques in the state of the art in male reproduction are used to obtain high-quality phenotyping of the mouse models.

The discovery of two concomitant mutations in an infertile patient is very interesting and the work carried out on mice allows supporting that an absence of CYLC1 and a heterozygous mutation of CYLC2 could lead to a phenotype of complete infertility. However, as the mutation on CYLC2 is not identified as pathogenic, the pathogenicity of this mutation remains in question (the authors note this point in the discussion). It would be interesting to see if the mutated amino acid is conserved between different species. In mice, the authors have shown the importance of these proteins on the morphology of the acrosome. What about in humans?

Reviewer #3 (Public Review):

The authors tried to study the role of the cylicin gene in sperm formation and male fertility. They used the Crispr/cas 9 to knockout two mouse cylicin genes, cylicin 1 and cylicin 2. They used comprehensive methods to phenotype the mouse models and discovered that the two genes, particularly cylicin 2 are essential for sperm calyx formation. They further compared the evolution of the two genes. Finally, they identified mutations of the genes in a patient. The major strengths are the high quality of data presented, and the conclusion is supported by their findings from the animal models and patients. The major weakness is that the study is descriptive: no molecular mechanism studies were conducted or proposed, limiting its impact on the field.

Author Response

Reviewer #1 (Public Review):

Part 1: Type 2 deiodinase

Table I is supposed to clarify and summarize the results but brings confusion. The text says that table I supports the claim that "in the cerebellum, Luc-mRNA was lower in the Ala92-Dio2 mice" whereas figure 1G does not show any difference. It is unclear whether Table I and figure 1 report the same data, and what the statistical tests are actually addressing (effect of genotype vs effect of treatment, whereas what matters here is only the interaction between genotype and treatment). Overall, it is not acceptable to present quantitative data without giving numbers, standard deviation, p-value, etc. as in Table I.

Thank you. We agree with the reviewer. We intended to minimize the amount of data presented, which was already very large, and therefore only presented the ratios of thr/alaDio2 and which created confusion. This part was removed from the new version of the MS.

Also, evaluating T3 signaling by only looking at the luc reporter and the Hprt housekeeping gene is not always sufficient (many T3 responsive genes can be found in the literature and more than one housekeeping gene should be used as a reference).

Thank you. The advantage of using the THAI mouse is that the Luciferase reporter gene is driven by a promoter that is only sensitive to T3, which is not the case for any other T3-responsive responsive gene. The Hprt housekeeping signal was stable among the samples, and the differences observed were not caused by differences in the housekeeping gene expression. This part was removed from the new version of the MS.

Another important weakness is that the wild-type mice have a proline at position 92. Why not include them? In absence of structural prediction, one wonders whether the mouse models are relevant to the human situation and whether the absence of the proline reduces the enzymatic activity when substituted for an Ala or Thr. This might have been addressed in previous work, but the authors should explain.

The position 92 in DIO2 is occupied by Thr in humans. Its Km(T4) is indistinguishable from mouse Dio2 which has a Pro in the position 92 (4nM vs. 3.1nM) [PMID 8754756; PMID: 10655523]. Humans also carry an Ala in position 92. Comparing the two human alleles is the purpose of the study.

Experiment 2: Ala92-Dio2 Astrocytes Have Limited Ability to Activate T4 to T3

Here, the authors use primary cell cultures from different areas of the brain to measure the in vitro conversion of T4 to T3 by Dio2. They find that hippocampus astrocytes are less active, notably if they come from Ala92-Dio2 mice.

This part has the following weaknesses:

• This result correlates with the results from Fig 1F however the difference between Ala92-Dio2 and Thr92-Dio2 is significant in vitro, but not in vivo.

From a deiodinase perspective, TH signaling in vivo depends on the presence of D2 (expressed in glial cells) and D3 (expressed in neurons), whereas in vitro it only depends on D2. In fact, D2 and D3 are known for a reciprocal regulation to preserve TH signaling [PMID: 33123655]. Thus, it is conceivable that the differences observed between the two models are explained by the intrinsic differences in the models.

What matters is not the activity/astrocytes, but the total activity of the brain area, which depends on the number of astrocytes x individual activity. This is not measured.

We respectfully disagree with the reviewer. The total D2 activity in a brain area depends fundamentally on the number of astrocytes in that area and on the intrinsic activity of the enzyme. The reviewer is suggesting that having an area denser in astrocytes expressing a catalytically less active D2 preserves a normal local T3 production. This is unlikely to be the case because we have no evidence that the density of astrocytes is different in Ala-DIo2 mice. Please keep in mind that the intimate relationship between astrocytes and neurons is what defines the microenvironment that surrounds the neuron. By separating astrocytes from neurons we are able to measure T3 production that is occurring in the neuronal microenvironment and show that cells obtained from AlaDio2 mouse produce less T3.

• What the authors called 'primary astrocytes' is an undefined mixed population of glial cells, (including radial glial cells, stem cells, ependymal cells, progenitor cells, etc...) that proliferated differentially for more than a week in culture, among which an unknown ratio expresses Dio2. The cellular model is thus poorly characterized, and the interpretation must be prudent.

• Again, wild-type mice are not included.

Thank you. We now include a reference to illustrate the types and percentages of cells present in our cultures. Given that the study is to compare the Thr92 and the Ala92 alleles, which are both present in humans, we did not believe it was necessary to include them here. Please note (as explained above) the Km(T4) for Thr92 and Pro92-Dio2 is indistinguishable.

Part 2: Neuronal response to T3 Involves MCT8 and Retrograde TH transport

The authors next move to primary neuronal cultures, prepared from the fetal cortex which they grow in the microfluidic chamber to study axonal transport. This is a surprising move: the focus is not on Dio2 anymore, but on the MCT8 transporter, which is known in humans to play an important role to transfer TH into the brain. It is expressed mainly in glia, but also in neurons. They study the influence of endosomes and type 3 deiodinase on the trafficking and metabolism of TH.

Thank you.

It would be useful to perform an experiment, in which radioactive T3 is introduced in the "wrong" side of the chamber, in an attempt to detect a possible anterograde transport. This would address the possibility that Mct8 also promotes efflux and control so that the chamber is not leaking.

Thank you. To satisfy the reviewer, we have conducted three new experiments adding 125IT3 in the MC-CS. The first experiment verified that the T3 transport in the cortical neurons also occurs anterogradely. The second experiment showed that the anterograde transport depends on mct8. The third experiment shows that D3 activity in the neuronal soma is limiting the amount of T3 transported along axons. We have included a new paragraph in the results section describing these experiments (Line 154 to 167), and a new supplementary figure (Figure 3—figure supplement 3). We have also discussed these new findings. Line 383 to 386. In every experiment, we have controlled for the possibility of leaking using one device without neurons that received radioactive T3. After 24 and 72h samples from the opposite side were obtained but did not contain any radioactive T3. We refer the reviewer to figure 1, where this is explained.

The authors use sylichristin as an inhibitor of Mct8, to demonstrate that transport is Mct8 dependent. They do not provide indications or references that would clearly indicate that this drug is a fully selective antagonist of Mct8 (but not of Oatp1c1, Mct10, Lat1, Lat2, etc., the other TH transporters). A good alternative would be to use Mct8 KO mice as controls.

Thank you. We refer the reviewer to reference 27 [J. Johannes et al., Silychristin, a Flavonolignan Derived from the Milk Thistle, Is a Potent Inhibitor of the Thyroid Hormone Transporter MCT8. Endocrinology 157, 1694-1701 (2016)] clearly indicating that Silychristin has a remarkable specificity toward MCT8. While using mct8 KO is interesting, it would have prevented us from testing some of our hypotheses. Being able to selectively inhibit Mct8 either in the MC-CS or in the MC-AS was a clear advantage. For example, pls see the experiment in which we add T3 in the MC-AS and the silychristin in the MC-CS (Fig. 3F). Here, we discovered new roles of mct8, such as its involvement in the release of T3 from the endosomes (line 228 to 231).

The B27 used in primary neuronal culture might contain TH. This is not easy to know, but at least some batches do.

Thank you. While the neurons were cultured in B27, all experiments were performed in cells incubated with neurobasal only (B27 was removed 24 earlier). This was not clear in the initial version, where there was only a vague reference in the legend of figure 3F. Now, this has been explained in the footnote of figure 3 and in line 207.

The presence of astrocytes, probably expressing Mct8 and Dio2 is inevitable in primary neuronal cultures, and is not mentioned, but might interfere with TH metabolism.

Thank you. We were aware that, under normal conditions, primary neuronal culture contains 25% of astrocytes. This was however minimized/eliminated by 2-day culture with the anti-mitotic cytosine arabinoside, which restricts astrocytes and microglia to <0.01 in this type of culture. This was explained in the initial version of the manuscript in the material and methods section (lines x to x) and supported with reference 53 (reference 57 in the previous version).

Part 3: T3 Transport Triggers Localized TH Signaling in the Mouse Brain

The authors return to in vivo experiments, implanting T3 crystals, labeled or not with radioactive iodine. They do so in the hypothalamus, where they address the retrograde transport of TH in TRH neurons, and in the cortex, looking for contralateral transport. These data are the most difficult to interpret. - First, T3 is hydrosoluble and would probably migrate without active transport.

Thank you. Please note that at no point we characterized the T3 transport “active transport”, which by definition is an ATP-dependent process. Please note that to address the issue raised by the reviewer “migrate without active transport”, in both experimental approaches, we included controls to assess the random diffusion of T3.

In hypothalamic studies, we used the (i) cerebral cortex and (ii) the lateral hypothalamus, a region that is immediately adjacent to the PVN. Neither region exhibit an axonal connection to the median emminence. The results, in both cases, show that the presence of radioactive T3 in the control areas was minimal when compared to the PVN (Fig. 5C).

In the cerebral cortical studies, we included ipsi- and contra-lateral hypothalamic measurements that served as controls given the absence of a connection between the cortex and the hypothalamus. Accordingly, T3 signaling was not detected in any of the control regions (Fig. 6C previous version; now figure 5). Thus, these controls indicate that it is unlikely that the results could be explained by “migrate without active transport” of T3.

• The authors do not demonstrate that these specific neuronal populations contain Mct8, and that these observations are connected to the previous in vitro observation (which used cortical neurons prepared from the fetus).

Thank you. In the previous version, we did not make it abundantly clear that the EM pictures in Fig. 3D-G (previous version; now figure 2 D-G) were from neurons in the mouse motor cortex (this information is now explained in lines 149 to 151), which is where we inserted the T3 crystals. In addition, we have done more histological work on the brain M1 (cortex) of adult mice and found that many neurons in the M1 express D3 and Mct8—lines 433-434 and Figure 5 G-K (along with histological studies showing the specificity of the ab against D3 Fig S6).

The possibility that astrocytes are involved, as reported in the literature, is not considered.

• Here again, using Mct8KO mice would greatly help to interpret the data. In particular, the experiments with cold T3 involve a 48h delay which is very long in comparison to the 30 minutes required for long-distance transfer of radioactive T3.

Thank you. We are unsure about the question posed by the reviewer. We are wondering how would astrocytes play a role in inter-hemispheric transport of T3? Given that astrocytes are not known to project across long distances, we have not considered this possibility. We agree that using the Mct8KO mouse could have provided supporting evidence of the role played by Mct8 in this process, but please keep in mind that the Mct8KO mouse does not have or exhibits a very mild brain phenotype, indicating that during development compensatory mechanisms have occurred that obviate the function of the transporter. This compensatory mechanism most likely involved Oatp1c1, given that only the double Mct8 and Oatp1c1 KO mouse develops a significant phenotype. This consideration directed us to the utilization of sylycristin, the highly selective Mct8 inhibitor, which disrupts the Mct8 pathway in a mouse that developed normally.

The two approaches used to demonstrate neuronal T3 transport in vivo are fundamentally different. The hypothalamus experiments employed radioactive T3, whereas T3 crystals were used in the cerebral cortex. The first approach studied T3 transport whereas the second studied downstream T3 effects, logically requiring more time. The solid T3 implant requires time to release T3 and activate gene expression. In the original paper that utilized T3 implants in the rodent brain, samples were processed after 4 days. (Dyess et al. 1988 Endo; PMID 3139393)

Discussion

Considering the diversity of questions that are addressed in the study, it is not surprising that the discussion is not covering all aspects. The authors implicitly consider that their conclusions can be extended to all neurons, while they use in their experiments a variety of different populations coming from either the fetal cortex, hippocampus, adult cortex, or hypothalamus. The claim that they discovered a mechanism applying to all neurons is not supported by the data.

Thank you. We agree with the reviewer: the high number of neuronal subtypes might include different mechanisms in T3 transport. Our studies involved cortical (central) and dorsal root ganglia (peripheral) neurons in vitro and cortical and hypothalamic neurons in vivo. Thus we think that the described mechanism is not confined to specific neuronal subtypes. The discussion has been modified accordingly (lines 402 to 411).

Moreover, we have done immunofluorescence studies to characterize the neurons present in the MC-CS better. We have found that all the neurons residing in the MC-CS are excitatory, expressing the vesicular glutamate transporter 1 (Vglut1). But no neurons were expressing GAD67, a marker for inhibitory neurons Figure 5—figure supplement 5). This is supported by the fact that during the mouse's brain development, the embryonic days 14.5 to 17.5 is the birth date of layer 4 and 2/3 excitatory neurons (PMID: 34163074). These neurons are migrating and have not extended their cellular processes, making them more likely to survive the isolation protocol from the cortex. On the other hand, the neurons (mostly excitatory) already residing in the cortex may have expanded their processes and changed their morphology, making them less capable of surviving the isolation process.

Some highly relevant literature is not cited. In particular:

• Mct8 KO mice do not have marked brain hypothyroidism (PMID: 24691440) which at least suggests that the pathway discovered by the authors can be efficiently compensated by alternative pathways.

We agree with the reviewer. As mentioned above, a compensatory mechanism triggered during development “compensates” for the inactivation of Mct8. That, however, does not mean that mct8 is not critically important. We have added that limitation to the discussion (lines 342); ref 46.

• Dio3 KO only increases T3 signaling in a few brain areas and only in the long term (PMID: 20719855).

Thank you. That is now included in the ms; ref 25.

• Anterograde transport of T3 has been reported for some brainstem neurons (PMID: 10473259).

Thank you. This was our mistake, indeed. We had worked on several versions of the manuscript that included references to her seminal work but unfortunately deleted it from the final version. This is now included in refs 48 and 49.

Reviewer #2 (Public Review):

Salas-Lucia et al. investigated two main questions: whether the Thr92Ala-DIO2 mutation impairs brain responsiveness to T4 therapy under hypothyroidism induction and the mechanisms of neuronal retrograde transport of T3. They find that the Thr92Ala-DIO2 mutation reduces T4-initiated T3 signaling in the hippocampus, but not in other brain regions. Using neurons cultured in microfluidic chambers, they further describe a novel mechanism for retrograde transport of T3 that depends on MCT8 and endosomal loading (possibly protecting T3 from D3-mediated cytosolic degradation) and microtubule retrotransport. Finally, they present evidence of retrograde transport of T3 through hypothalamic projections and interhemispheric connections in vivo. The main novelty of this study is the delineation of the mechanism of T3 retrograde transport in neurons. This is interesting from the cell biology perspective. The notion of impaired hippocampal T3 signaling is relevant for the cognitive outcomes of hypothyroidism and its associated therapy.

Thank you.

Although the data are exciting and relevant for the community, some issues need to be addressed so that conclusions are more clearly justified by data:

1) The title and the abstract mean that dissecting this novel mechanism of T3 retrograde transport may help improve cognition or brain responsiveness in patients taking T4 or L-T3 therapy. However, how initial results (Figs 1 and 2) connect to later data is not essentially clear. For example, do Thr92Ala-DIO2 mice present altered retrograde transport of T3? Would stimulation of retrograde transport in Thr92Ala-DIO2 mice rescue neurological phenotypes? Can the authors address this experimentally?

Thank you. These are all interesting points raised by the reviewer. However, the three reviewers felt that a connection between the studies in astrocytes and the studies in neurons was missing, and complained about the disjoint nature of the manuscript. To satisfy the reviewers we removed from the MS the experiments with astrocytes and DIO2 polymorphism, and focused on the neuronal transport of T3.

2) Although the authors present in vivo evidence of retrograde T3 transport in the hypothalamus and motor cortex, given the select susceptibility of the hippocampus to hypothyroidism, it would be especially interesting to test whether this mechanism also happens in a hippocampal circuit (CA3-CA1 Schaffer collaterals, mossy fibers or perforant pathway).

Thank you. We agree that this would be interesting, but technically challenging. Nonetheless, we intend to study this in the future.

3) Table 1 should present the raw values for Ala92-DIO2 mice and treatments instead of only displaying the direction of change and statistical significance. From Panels 1E-J, it is unclear if Thr92Ala-DIO2 mice or treatments caused any real change in brain regions other than the hippocampus.

Thank you. These experiments were removed from the new version of the MS.

4) The authors put forward the notion that a rapid nondegradative endosome/lysosome incorporation protects T3 from D3 degradation in the cytosol. Their experiments with pharmacological modulation of MCT8, lysosomes, and microtubules are in this direction. However, they do not represent an unequivocal demonstration of this mechanism. Therefore, the authors should be more cautious in their interpretation and discuss the limitations of their approaches.

Thank you. The manuscript was edited to reflect these important points.

Reviewer #3 (Public Review):

Initially, Salas-Lucia et al examined the effect of deiodinase polymorphism on thyroid hormone-medicated transcription using a transgenic animal model and found that the hippocampus may be the region responsible for altered behavior. Then, by changing to topic completely, they examined T3 transport through the axon using a compartmentalized microfluid device. By using various techniques including an electron microscope, they identified that T3 is uptaken into clathrin-dependent, endosomal/non-degradative lysosomes (NDLs), transported in the axon to reach the nucleus and activate thyroid hormone receptor-mediated transcription.

Although both topics are interesting, it may not be appropriate to deal with two completely different topics in one paper. By deleting the topic shown in Table 1, Figure 1, and Figure 2, the scope of the manuscript can be more clear.

Thank you. We did as suggested by the reviewer. These studies were removed from the present version of the ms.

Their finding showing that triiodothyronine is retrogradely transported through axon without degradation by type 3 deiodinase provides a novel pathway of thyroid hormone transport to the cell nucleus and thus can contribute greatly to increasing our understanding of the mechanisms of thyroid hormone action in the brain.

Thank you.

Author Response

Reviewer #2 (Public Review):

In their study the authors aimed to investigate the dissemination of Enterobacterales plasmids between geographically and temporally restricted isolates recovered from different niches, such as human blood stream infections, livestock, and wastewater treatment works. By using a very strict similarity threshold (Mash distance < 0.0001) the authors identified so-called groups of near-identical plasmids in which plasmids from different genera, species, and clonal background co-clustered. Also, 8% of these groups contained plasmids from different niches (e.g., human BSI and livestock) while in 35% of these cross-niche groups plasmids carried antimicrobial resistance (AMR) genes suggesting recent transfer of AMR plasmids between these ecological niches.

Next, the authors set-out to examine the wider plasmid population structure by clustering plasmids based on 21-mer distributions capturing both coding and non-coding plasmid regions and using a data-driven threshold to build plasmid networks and the Louvain algorithm to detect the plasmid clusters. This yielded 247 clusters of which almost half of the clusters contained BSI plasmids and plasmids from at least one other niche, while 21% contained plasmids carrying AMR genes. To further assess cross-niche plasmids similarities, the authors performed an additional plasmid pangenome-like analysis. This highlighted patterns of gain and loss of accessory plasmid functions in the background of a conserved plasmid backbone.

By comparing plasmid core gene or plasmid backbone phylogenies with chromosome core gene phylogenies, the authors assessed in more detail the dissemination of plasmids between humans and livestock. This indicated that, at least for E. coli, AMR dissemination between human and livestock-associated niches is most likely not the result of clonal spread but that plasmid movement plays an important role in cross-niche dissemination of AMR.

Based on these data the authors conclude that in Enterobacterales plasmid spread between different ecological niches could be relatively common, even might be occurring at greater rates than estimated, as signatures of near-identity could be transient once plasmids occupy and adept to a different niche. After such a host jump, subsequent acquisition, and loss of parts of the accessory plasmid gene content, as a result of plasmid evolution after inter-host transfer, may obscure this near-identity signature. As stated by the authors, this will raise challenges for future One Health-based genomic studies.

Strengths

The article is well written with a clear structure. The authors have used for their analysis a comprehensive collection of more than 1500 whole genome sequenced and fully assembled isolates, yielding a dataset of more than 3600 fully assembled plasmids across different bacterial genera, species, clonal backgrounds, and ecological niches. A strong asset of the collection, especially when analyzing dissemination of AMR contained on plasmids, is that isolates were geographically and temporally restricted. Bioinformatic analyses used to discern plasmid similarity are beyond state-of-the-art. The conclusions about dissemination of plasmids between genera, species, clonal background and across ecological niches are well supported by the data. Although conclusions about inter-host plasmid dissemination patterns may have been drawn before, this is to my knowledge the first time that patterns of dissemination of plasmids have been studied at such a high-level of detail in such a well selected dataset using so many fully assembled genomes.

Weaknesses

One conclusion that is not entirely supported by the data is the general statement in the discussion that "cross-niche plasmid in not driven by clonal lineages". From the tanglegram, displaying the low congruence between the plasmid and chromosome core gene phylogeny in E. coli, this conclusion is probably valid for E. coli, but this not necessarily means that this is also the case for the other Enterobacterales genera and species included in this study. For these other genera, the data supporting this conclusion are not given, probably because total number of isolates for certain genera were low, or because certain niches were clearly underrepresented in certain genera.

Thank you for reviewing our manuscript.

We agree that this statement in the conclusion was too general, and have adapted it (lines 407-409):

“By examining plasmid relatedness compared to bacterial host relatedness in E. coli, we demonstrated that plasmids seen across different niches are not necessarily associated with clonal lineages”

In the limitations section of the Discussion, we have also referenced this specifically as a limitation (lines 422-424):

“Although we evaluated four bacterial genera, 72% (1,044/1,458) of our sequenced isolates were E. coli, and so our analyses and findings are particularly focused on this species.”

Furthermore, the BSI as well as the livestock niches were analyzed as single niches while the BSI niche included both nosocomial and community-derived BSI isolates and the Livestock niche included samples from different livestock-related hosts. Given the fact that a substantial number of plasmids were available from cattle, sheep, pigs, and poultry, it would be interesting to see whether particular livestock hosts were more frequently found in the cross-niche plasmid clusters than other livestock hosts and whether the BSI plasmids in these cross-niche clusters were predominantly of community or nosocomial origin.

We agree that analyses which distinguish between nosocomial/community acquired BSI isolates would be interesting further work, but are beyond the scope of this study. Our analysis of the BSI/livestock cross-niche near-identical plasmid groups details the livestock hosts involved (lines 144-154). Briefly, of the n=8 BSI/livestock cross-niche groups, these involved

• pig/poultry (1/8)

• poultry (1/8)

• pig (2/8)

• sheep (3/8)

• cattle/pig/poultry (1/8)

We have added a note of explanation in the methods to explain how the distance threshold we use for near-identical clustering is maximally conservative at small plasmid sizes (a single SNP produces a new plasmid cluster) but remains highly conservative (tens of SNPs) at large plasmid sizes.

We have carefully considered the point about whether particular hosts were more frequently found in cross-niche plasmid clusters. However, we do not think it is easy to infer whether a particular livestock host is represented more frequently in these cross-niche events than would be expected from chance, given the low density of the sampling.

We have reorganised the paragraph in lines 144-154 to provide more clarity on the groups’ niches.

“Sharing between BSI and livestock-associated isolates was supported by 8/17 cross-niche groups (n=45 plasmids). Of these, n=3/8 groups contained BSI/sheep plasmids: one group contained mobilisable Col-type plasmids, the remaining two groups contained conjugative FIB-type plasmids. Of these, one group contained plasmids carrying the AMR genes aph(3'')-Ib, aph(6)-Id, blaTEM-1, dfrA5, sul2, and the other group contained plasmids carrying the MDR efflux pump protein robA (see Materials and Methods). A further n=2/8 groups contained BSI/pig mobilisable Col-type plasmids, of which one group other carried the AMR genes aph(3'')-Ib, aph(6)-Id, dfrA14, and sul2. Lastly, n=1/8 groups contained BSI/poultry non-mobilisable Col-type plasmids, n=1/8 contained BSI/pig/poultry/influent non-mobilisable Col-type plasmids, and n=1/8 contained BSI/cattle/pig/poultry/influent mobilisable Col-type plasmids.”

We have also added this as a limitation in the discussion (lines 424-426):

“Additionally, we did not sample livestock-associated niches densely enough to explore individual livestock types (cattle/pigs/poultry/sheep) sharing plasmids with BSI isolates (see Appendix 1 Fig. 9).”

We have already recognised that our culture methods may have affected our sensitivity to detect Klebsiella spp. isolates in the livestock/environmental samples – we have expanded on this to explicitly highlight that this may have affected our capacity to evaluate Klebsiella-associated plasmids (lines 443-444):

“This limited our ability to study the epidemiology of livestock Klebsiella plasmids.”

Author Response

Reviewer #1 (Public Review):

Although the authors have identified some properties/molecular markers of canine H3N2 influenza viruses that highlight the potential for infecting humans, it needs to be cautious to emphasize the threat of these viruses to public health. One fact is that despite the increasing prevalence of these viruses in dogs and the close proximity between dogs and humans, there is so far no report of human infection with canine H3N2 influenza viruses. The authors are wished to discuss this in their manuscript so that the readers can have a more comprehensive understanding of their findings and the public health importance of canine influenza viruses.

We agree with the reviewer. We added the related discussion and revised some words to not emphasize the threat of these viruses to public health (lines 342-346).

Reviewer #3 ( Public Review):

1) The investigators should run neuraminidase inhibition assays to established the level of cross reactivity of human sera to the canine origin NA (one of reasons proposed as to the lower impact of the H3N2 pandemic was the presence of anti0N2 antibodies in the human population).

We performed neuraminidase inhibition assays as suggested for both ferret sera against human H3N2 virus and human sera. The results showed that the NI titers of ferret sera against human H3N2 virus to canine H3N2 viruses were <10 (lines 147- 148, Supplementary file 2). Additionally, 2.0%–3.0% of the children's serum samples, 1.0%–2.0% of the adult's serum samples, and 1.0%–2.0% of the elderly adult's serum samples had NI antibody titers of ≥10 to canine origin NA (lines 158-161, Table 1, and lines 435-445).

2) Please tone down the significance of ferret-to-ferret transmission as a predictor of human-to-human transmission. Although flu viruses that transmit among humans do show the same capacity in ferrets, the opposite is NOT always true.

We agree with the reviewer. To tone down the significance of ferret-to-ferret transmission as a predictor of human-to-human transmission, we added the related discussion and deleted or revised some words (lines 342-346, line 37, line 302, line 308, line 322, and line 341).

Author Response

Reviewer #2 (Public Review):

In this manuscript, Vias and co-authors develop HGSOC PDOs and characterized their genomes, transcriptomes, drug sensitivity, and intra-tumoural heterogeneity. They show that PDOs represent the high variability in copy number genotypes observed in HGSOC patients. Drug sensitivity was reproducible compared to parental tissues and the ability of these models to grow in vivo.

Overall, the manuscript lacks sufficient novelty. Several pieces of information and a number of conclusions that are presented here have been previously published by other groups (Nina Maenhoudt, Stem cell reports, 2020; Shuang Zhang, Cancer Discov, 2021).

We agree that several important papers on HGSOC organoids have been published. However, we disagree about your assessment of “lacks sufficient novelty”. Our MS addresses critical questions about conservation of mechanisms of chromosomal instability, how PDOs can be selected as clinical relevant models based on patterns of CIN and their comparative drug response. These questions are vital to using PDOs for therapeutic development and have not been explored before. By contrast, Maenhoudt et al. performed many analyses on several organoids (whole-genome sequencing, whole exome sequencing) but did not analyse the relationships between copy number profiles, mutational signatures or drug sensitivity between donor tissues and derived organoids and did not perform transcriptomic or scDNA analyses. A major novelty of our approach is to provide robust clinical validation of individual HGSOC PDOs by analysing how our PDOs are statistically representative of the various CN subclasses of HGSOC. Maenhoudt et al and Zhang et al classify their models only using infrequent recurrent mutations in driver genes. We do not understand how the Zhang MS overlaps with our MS as it describes the CRISPR-engineering of mouse cells to model HGSOC and investigates drivers of the mouse tumour microenvironment.

Reviewer #3 (Public Review):

1) The manuscript adequately demonstrates that genomic instability is maintained in HGSOC tumourspheres. The use of 3-dimensional HGSOC models to more greatly resemble the in vivo environment has been used for more than a decade, but this is the first demonstration using a variety of genomic assessment tools to show genomic instability in the HGSOC tumoursphere model. It is clearly demonstrated that these HGSOC tumourspheres represent copy number variations similar to information in public datasets (TCGA, PAWG, BriTROC-1) and that cellular heterogeneity is present in these tumourspheres. The simple steps outlined to establish and passage tumourspheres will benefit the field to further study mechanisms of genomic instability in HGSOC.

Thank you for these positive comments.

2) A weakness of the manuscript is the lack of operational definitions for what constitutes an organoid and an appropriate definition to distinguish genomic instability from chromosomal instability (a distinct type of genomic instability). Line 147 states "As PDOs consist of 100% tumour cells...", although this does not appear to have been established by any assessment. This limited characterization of the 3D model is a weakness since no data is provided on whether the tumourspheres constitute only a single cell type (as indicated on line 147) or multiple cell types (e.g., HGSOC cell, mesothelial cells) using markers beyond p53 expression. Based on this information, this model cannot be called a PDO, rather it should be referred to as a tumoursphere.

We define continuous PDO models on page 3 stating our criteria based on passage > 5 and successful reculture after thawing (previous publications have not defined whether their models are continuous or finite). As shown in our targeted-gene mutation analysis, all our PDOs contain a TP53 mutation allele fraction between 80–95%. Moreover, in our single cell DNA-Seq data we do not observe any normal copy number profiles that would indicate normal cells. This information is now included in the text for clarification. Our reasons not to use the term spheroids or tumourspheres are:

1. The word spheroid comes from the in vitro spheroid formation assay which was originally designed to overcome the difficulties found in functional in vivo serial transplantations. This method generates colony-forming units in suspension. Our patient-derived cells are not growing in suspension but within an extra-cellular matrix.

2. Spheroids are clonally expanded from a single-cell as part of the colony-forming assay; our patient-derived organoids were not clonally expanded in any way.

3. Organoids derived from patient-tumours have been named PDOs in multiple publications where pure tumour cellularity was stated for the PDOs [Vlachofiannis et al. Science (2018) 359, 920; Li et al. Nat. Comm.(2018) 9, 2983; Lee et al. Cell (2018)173, 515; Kopper et al. Nat Med (2019) 25, 838]. Use of other terms will cause confusion for readers and prevent important comparisons between PDO from different researchers.

3) Chromosome instability (CIN) is a type of genomic instability that is broadly defined as an increased rate of chromosome gains or losses and is best identified through analysis of single cells (e.g., karyotype analysis), something that bulk whole genome sequencing cannot determine since it is a reflection of cell populations and not individual cells. While the data demonstrate genomic instability is retained in the tumourspheres, and chromosome losses or copy-number amplifications were observed using single-cell whole genome sequencing, evaluation of samples from the same patient over time was not evaluated. While there is evidence to support CIN in these samples, in agreement with other published work that has demonstrated CIN in >95% of HGSOC samples analyzed at the single-cell level, this work is not conclusive. The title of the manuscript should be modified to more accurately represent what the evidence supports.

We have discussed the ambiguity of CIN in our recent publication “A pan-cancer compendium of chromosomal instability” Drews et al Nature 2022.

“CIN has complex consequences, including loss or amplification of driver genes, focal rearrangements, extrachromosomal DNA, micronuclei formation and activation of innate immune signalling. This leads to associations with disease stage, metastasis, poor prognosis and therapeutic resistance. The causes of CIN are also diverse and include mitotic errors, replication stress, homologous recombination deficiency (HRD), telomere crisis and breakage fusion bridge cycles, among others.

Because of the diversity of these causes and consequences, CIN is generally used as an umbrella term. Measures of CIN either divide tumours into broad categories of high or low CIN, are restricted to a single aetiology such as HRD, are limited to a particular genomic feature such as whole-chromosome-arm changes, or can only be quantified in specific cancer types. As a result, there is no systematic framework to comprehensively characterize the diversity, extent and origins of CIN pan-cancer, or to define how different types of CIN within a tumour relate to clinical phenotypes. Here we present a robust analysis framework to quantitatively measure different types of CIN across cancer types.”

Many authors use CIN to include the consequences of CIN and other specifically use CIN to indicate ongoing numerical and structural change. We do not think our usage of CIN in the title and text is controversial and is consistent with previous peer reviewed publications, including our own.

4) An additional weakness is missing information (e.g., Figure 1d, Supplementary Figure 3b, and Supplementary Table 4 were not included in the manuscript; the 13 anticancer compounds used to test drug sensitivity are not indicated) making an assessment of the data impossible, and assessment of some conclusions difficult.

We apologise for this misunderstanding as a typo suggested that there was a Figure 1d (it should have referred to Figure 1c) or Figure 1-Figure supplement 3B (the label of which was missing); we also apologise for the omission of Supplementary Table 4. These errors have been corrected and the list of compounds is now included in the Methods section.

Author Response

Reviewer #1 (Public Review):

We would like to thank reviewer #1 for her helpful comments and would like to respond to these as follows:

1) “Editing efficiencies were variable (99% to 0%) depending on the species, being worst for L. major.”

It is true that the editing efficiency was different in each species and worst for L. major. However, it is important to note that these efficiencies varied not only for each species but also amongst genes and especially chosen sgRNA sequences. Variations in efficiency across sgRNAs targeting the same gene and locus is a common problem in any CRISPR approach. We made this clearer in our revised manuscript (line 670 – 673).

2) “The use of premature termination codons also clearly raises issues for false positives and negatives, especially as there is no evidence for nonsense-mediated mRNA decay in Leishmania.”

We have now included in our revised manuscript that it is currently unclear whether a classical nonsense-mediated decay pathway is present in Leishmania or not. If such a pathway would be present, mutant mRNAs in which a termination codon is present within the normal open reading frame would be removed (Clayton, Open Biology 2019; Delhi et al., PLoS One 2011). But if not, remaining N-terminal protein parts could be functional and may lead to false positive and negative results. However, as reviewer #2 pointed out, this may also provide extra information about functional domains of the targeted protein and highlights that our tool can not only be used to create functional null mutants by inserting premature STOP codons but also to pursue targeted mutagenesis screens (line 674 - 683).

3) “There are already two genome-wide screening options for Leishmania, so the advantages and disadvantages of the method proposed here need to be discussed in a much more detailed and balanced way.”

We have revised our manuscript to include in our introduction (line 36 - 73) and discussion (line 658 - 697) a better comparison of all potential tools for genome-wide screening in Leishmania, including RNAi, bar-seq and base editing screening. We highlight why we think that base editing has unique advantages.

4) “In the "LeishGEM" project (http://www.leishgem.org) all Leishmania mexicana genes will be knocked out and each KO will be bar-coded. At the end, 170 pooled populations of 48 bar-coded mutants will be publicly available. The only real reason the authors of the current paper give for not using this approach is that it is labour-intensive. However, LeishGEM is funded and underway, with several centres involved, so that argument is weak.”

In our original manuscript we gave multiple reasons why we think that the LeishGEdit method, which is being used for the LeishGEM screen and has been developed by the lead author of our here presented study, has clear disadvantages compared to base editing.

As written in our original manuscript (line 709 – 716): “However, for a bar-seq screen, each barcoded mutant needs to be created individually by replacing target genes with drug selectable marker cassettes (20,21), making them extremely labour intensive and most likely “one-offs” on a genome-wide scale. Furthermore, aneuploidy in some Leishmania species can be a major challenge for gene replacement strategies as multiple rounds of transfection or isolation of clones may be required to target genes on multi-copy chromosomes. Using gene replacement approaches it is also not feasible to study multi-copy genes that have copies on multiple chromosomes. These are major disadvantages of bar-seq screening.”

Therefore, we still think that the main disadvantage of bar-seq screening is that it is labour-intensive as each mutant needs to be created individually. The fact that LeishGEM requires five years and several research centres to knockout all genes in just one Leishmania species is proof for this argument.

However, to clarify our position about this further, we have listed other disadvantages of the LeishGEM screen, including difficulties of sharing mutant pools between labs, possible problems in expanding mutant pools without losing uniformity, no ability to change the composition of generated pools and limited ability to distinguish between technical failures and essentiality. If any of these problems would occur, it would require a de novo generation of barcoded mutants and therefore this is an extremely labour-intensive method for large-scale screening. We also added that bar-seq screens are not feasible in Leishmania species that display extreme cases of aneuploidy, such as L. donovani (line 59 – 73).

Despite all these disadvantages of the LeishGEdit approach for the LeishGEM project, there are of course also clear advantages, which we also point out in our introduction (line 52 – 55).

5) “There is also a preprint describing RNAi for functional analysis in Leishmania braziliensis.”

Although our original manuscript included the pre-print about RNAi screening in Leishmania braziliensis already (line 706-709), we understand that this deserves a stronger discussion. We have therefore highlighted now RNAi as a possible tool for genome-wide screening in selected Leishmania species in our revised introduction (line 36 - 43). However, we also argue that RNAi approaches are at the moment only available to Leishmania of the Viannia subgenus and that RNAi activity greatly varies between the species (line 36 – 43 and 665 - 669). In addition, we discuss that the use of RNAi genome-wide screens is much less specific, as usually randomly sheared genomic DNA is used to generate RNAi libraries (line 687 - 689). Since the pre-print is now published, we have replaced the pre-print publication with the peer-reviewed one.

Reviewer #2 (Public Review):

We would like to thank reviewer #2 for helpful comments and would like to respond to those as follows:

1) “Line 482 - the authors wrote 'As expected, the proportion of cells showing a motility phenotype in the IFT88 targeted L. infantum population decreased further' Why is this result expected? Presumably, this is due to the fact that cells without a functional IFT system lack flagella and grow slower so can be outcompeted by faster-growing mutants. This speaks to the major caveat highlighted by the authors in the discussion and the final small-scale screen. In a population of cells, those with deleterious mutations in an essential gene or one whose disruption results in slower growth will be outcompeted by cells in which a non-deleterious mutation has occurred, which feeds into the issue of timing.”

As the reviewer highlighted himself, deleterious mutations that result in slower growth will be outcompeted by cells in which a non-deleterious mutation has occurred. We have stated that the complete deletion of IFT88 in Leishmania mexicana has been shown to have reduced doubling time (Beneke et al., PLoS Pathogens 2019) and are therefore most likely outcompeted from the pool (line 529 – 532 and 767 - 769).

2) “The authors show with CRK3 this process of non-deleterious mutants outcompeting deleterious mutants does result in a detectable drop in the number of parasites with specific CRK3 guides but not in those with IFT88. Is this due to the fact that the outgrowth of the non-deleterious IFT88 mutants occurs rapidly or that the mutation of the targets in IFT88 was ineffective? The data presented in Figure 5 shows that for some species at least a mutation of the IFT88 gene was possible. This might mean that for certain genes the outgrowth occurs within the first 12 days after transfections so will not be seen using this approach, without a wider study, which is beyond the scope of this manuscript it will be difficult to know.”

As we stated in our discussion, we did not test IFT88 guides individually in L. mexicana. Therefore, the editing rate observed for the IFT88 guides in L. major and L. infantum (Fig. 5) may differ from the editing rate in L. mexicana, which is the species we used for the pooled transfection screen. It is therefore difficult to conclude why IFT88 was not depleted from the pool. This may be due to lower guide activity in L. mexicana or rapid selection of non-deleterious mutations (line 769 - 774). We are therefore planning to further optimize our system by streamlining the editing efficiency and eliminating species-specifics effects (line 735 - 745). As the reviewer highlighted, this is beyond the scope of this study.

However, the reviewer raises a fair point about the exact timing of isolating DNA from pools, which might influence when exactly parasites with a deleterious mutation are depleted from the pool. This may differ between guides and may even be gene specific. We have added this point to our discussion (776 - 780).

3) “The authors highlight that this base editing approach will leave potentially functional regions of the NT of proteins, which is true and may mean genes are missed. However, this may also provide extra information about the protein's function/domain structure if STOP codons in certain positions showed an effect on function whereas those in others don't.”

We thank reviewer #2 for pointing out that functional parts of truncated proteins following base editing may actually allow to draw additional conclusions. We have included this in the manuscript (681 - 683).

Author Response

Reviewer #1 (Public Review):

This umbrella review aims to synthesize the results of systematic reviews of the impact of the COVID-19 pandemic on various dimensions of cancer care from prevention to treatment. This is a challenging endeavor given the diversity of outcomes that can be assessed in cancer care.

Search and review methods are good and are in line with recommendations for umbrella reviews. Perhaps one weakness of the search strategy was that only one database (Pubmed) was searched. The search strategy appears adequate, though perhaps some more search terms related to reviews and cancer could have been included. It is therefore possible that some reviews may have been missed by the search strategy.

It is challenging to perform a good umbrella review that yields novel insights, as it is difficult to combine results from different reviews which themselves combine results from different studies with different methodologies. However, I think perhaps one of the main weaknesses of this study is that it is not clear to me what is the core objective of the umbrella review, and how analyses relate to that core objective. In other words, I do not understand based on the introduction what new information the authors are hoping to learn from their umbrella review that could not be learned from reading the individual systematic reviews, beyond a vague objective of "synthesizing" the literature. Because of this, it is not very clear to me how the data extracted and the analysis fits into the larger objectives, and what the new knowledge generated by this review is. Based on the reported results, it would appear that one of the main goals is to assess the quality of systematic reviews and of the underlying studies in the reviews, but it is hard to tell. I think there are potentially important insights this review could tell us, but the message and implications of current evidence remain for me a little confused in the current manuscript.

We thank the reviewer for the encouraging remarks on our work, and for the useful feedback. We have now addressed all concerns as outline below.

Reviewer #2 (Public Review):

This umbrella review summarizes the results of systematic reviews about the impact of the COVID-19 pandemic on cancer care. PRISMA checklist is used for reporting. The literature search was performed in PubMed and systematic reviews published until November 29th, 2022 were included. The quality of included systematic reviews was appraised using the AMSTAR-2 tool and data were reported descriptively due to the high heterogeneity of 45 included studies. Based on the results of this paper, regardless of the low quality of included evidence, COVID-19 affected cancer care in many ways including delay and postponement of cancer screening, diagnosis, and treatment. Also, patients with cancer had been affected psychologically, socially, and financially during the COVID-19 pandemic.

The main limitation of the current study is that the authors have searched only one database, which might have missed some relevant systematic reviews. Also, most of the included reviews in this paper had low and medium methodological quality.

We thank the reviewer for this excellent remark. Guideline on umbrella reviews suggest PubMed, reference screening and an additional bibliographic database for an optimal database combination for searching systematic reviews (Goossen K et al. 2020). To follow the guidelines, and considering the specialized focused on COVID-19, in addition to Pubmed and reference screening, we also performed a search in the WHO COVID-19 Database. Furthermore, we revised the search strategy in Pubmed to include mesh terms. The search was performed by a specialized librarian with experiences in systematic review searches. Overall, we retrieve 485 new references, and found 6 new studies that met out inclusion criteria to be included in final analysis. We have now revised the manuscript to reflect the above changes, and also highlighted this as a strength of our work. In addition, we added the new detailed search strategy in the supplemental material.

Author Response

Reviewer #2 (Public Review):

The authors describe in the nematode C. elegans the effects of perturbed organization of Intermediate filaments (IFs), which form the cytoskeleton of animal cells together with actin filaments. They focus on a previously identified mutant of the kinase SMA-5, which when mutated leads to disorganized IF structure in intestinal cells of C. elegans. The authors found that the phenotypes caused by the mutated SMA-5 kinase concerning gut morphology and animal health can be reversed by removing IF network components such as the protein IFB-2. This finding is extended to other components of the IF network, which also display a certain degree of sma-5 phenotype alleviation when depleted.

Strength:

The finding that suppressing the intestinal phenotypes caused in sma-5 mutants can be suppressed by removing functional IF components is an interesting observation. It confirms a previous study showing that bbln-1 mutation-caused IF phenotypes can be suppressed by depleting IFB-2.

Weakness:

1) The finding of suppressing the intestinal phenotypes caused in sma-5 mutants can be considered a minor conceptual advancement. However, the study comes short of providing insight into the molecular processes of how deranged IF networks and its consequence can be rescued/suppressed by removing e.g. the IFB-2 filaments. Many statements concerning the relationship between SMA-5 and the IFs are based on assumptions. The study requires protein biochemical analysis to show whether SMA